L A N D M A N A G E M E N T H A N D B O O K

40

Field Studies of Seed Biology

1997

Ministry of Forests Research Program Field Studies of Seed Biology

Carole L. Leadem, Sharon L. Gillies, H. Karen Yearsley, Vera Sit, David L. Spittlehouse, and Philip J. Burton

Ministry of Forests Research Program Canadian Cataloguing in Publication Data Main entry under title: Field studies of seed biology

(Land management handbook ; )

“Tree seed biology.”--Cover.  ---

. Trees – British Columbia – Seeds – Experiments. . Trees – Seeds – Experiments. . Reforestation – British Columbia – Experiments. . Reforestation – British Columbia – Experiments. I. Leadem, Carole Louise Scheuplein, – II. British Columbia. Ministry of Forests. Research Branch. III. Series

..  .’’ --

©  Province of British Columbia Published by the Research Branch B.C. Ministry of Forests  Bastion Square Victoria, BC  

Copies of this and other Ministry of Forests titles are available from Crown Publications Inc.  Fort Street Victoria, BC  

Please address any comments or suggestions to the senior author: Carole L. Leadem Glyn Road Research Station B.C. Ministry of Forests PO Box  Stn Prov Govt Victoria, BC  

ii CREDITS

Carole L. Leadem B.C. Ministry of Forests, Research Branch, Glyn Road Research Station, PO Box  Stn Prov Govt, Victoria, BC  

Sharon L. Gillies University College Fraser Valley,  King Road, Abbotsford, BC  

H. Karen Yearsley B.C. Ministry of Forests, Research Branch, PO Box  Stn Prov Govt, Victoria, BC  

Vera Sit B.C. Ministry of Forests, Research Branch, PO Box  Stn Prov Govt, Victoria, BC vw c

David L. Spittlehouse B.C. Ministry of Forests, Research Branch, PO Box  Stn Prov Govt, Victoria, BC vw c

Philip J. Burton Symbios Research and Restoration, PO Box , Smithers, BC  

Editor, indexer: Fran Aitkens Typesetting: Dynamic Typesetting Graphic production: Lyle Ottenbreit Proofreading: Rosalind C. Penty Steve Smith Publication design: Anna Gamble

Original photos and illustrations: Figures ., ., . Dr. David Spittlehouse Figure . Dr. John Owens, Dep. Biol., Univ., Victoria, B.C. Figures . and . Paul Nystedt, B.C. Min. For. Figures ., ., . H. Karen Yearsley Figures . and . Dr. D.G.W. Edwards, Can. For. Serv., (retired) Pac. For. Cent., Victoria, B.C.

iii INTRODUCTION

I like trees because they seem more resigned to the way they have to live than other things do. (Willa Cather “O Pioneers!”)

Except in limited areas where there is enough methods for conducting field studies of tree seeds. A advance regeneration, establishment of forest cover recent assessment of ecosystem management needs on harvested lands continues to depend on seedling stressed the importance of standardized sampling planting programs or on natural regeneration by and monitoring techniques, and the lack of consist- seeds. Whereas successful plantation programs ent methods for archiving, accessing, and updating depend primarily on plant competition and site databases (U.S. Dep. Agric. For. Serv. a). Tech- variables at the time of planting, successful natural niques gleaned from agriculture literature are generally regeneration depends not only on the availability not applicable, and traditional ecological studies of seeds, but on favourable environmental condi- (e.g., of seed banks) tend to be primarily descriptive tions throughout the processes of seed production, with little emphasis on experimental approaches. dispersal, germination, and seedling establishment. The primary objective of this manual is to detail Site preparation and other silvicultural treat- methods that have been gleaned from the literature ments can improve the suitability of the seedbed and from personal experience of the authors. It is a and its micro-environment, but there is still much manual of methods with some general guidelines we do not understand about how various factors and interpretation. Relevant background papers are contribute to successful forest establishment. We cited where appropriate, but it is not a literature have gained some insights, under controlled condi- review. The manual is intended for use by researchers tions, about the influence of major factors such as in public and private forest resource management light and temperature, but we have limited experi- agencies, universities, and colleges. Although specifi- ence with biological responses under actual cally directed to tree seed research in forested conditions in the field. ecosystems, many of the methods described can Anyone who has conducted research in the field be used to study seeds of graminoid, herb, and quickly comes to realize the complexity of the sys- shrub species in both forest and non-forest plant tems chosen for study. An immense number of communities. The extensive background informa- external and internal factors that affect living tion included in the text also provides valuable organisms must be taken into account—with lim- reference material for many who have an interest ited possibilities to control these factors. A major in tree seeds, but who are not directly involved in constraint, particularly in a forest environment, is research activities. The detailed examples from the difficulty inherent in conducting field studies previous studies are included, not to prescribe how involving seeds. Infrequent seed production, preda- such studies should be done, but to assist in plan- tion by animals, difficulty locating small seeds, ning by providing reference values on which to estimating the numbers of buried seeds, measuring base measurements, sample sizes, and other germination, and monitoring survival pose myriad experimental details. challenges for the field researcher. Added to these Since the manual is directed primarily to re- difficulties is the lack of information about effective searchers working in the province of British

v Columbia (B.C.), Canada, many examples (forest types, species, research topics), procedures (the biogeoclimatic ecosystem classification system), and regulatory policies are specific to this geographic and political jurisdiction. Nevertheless, it is hoped that the underlying principles are self-evident and will be generally applicable to the conduct of field research elsewhere.

vi ORGANIZATION OF THE HANDBOOK

Following a discussion of planning and organizing a H. Karen Yearsley, M.Sc., R.P.Bio., earned her field study (Section ) and setting up an environ- graduate degree from the Faculty of Forestry, Uni- mental monitoring program for the experimental versity of British Columbia, and is a member of the site (Section ), the manual is arranged by subject Association of Professional Biologists of British areas most often associated with field studies of tree Columbia. Her  years of research experience in seeds: natural seed production (Section ), seed dis- B.C. include work on ecosystem classification, persal (Section ), seed predation (Section ), seed forest succession, and forest soil seed banks. Karen banks (Section ), assessing seed quality and viabil- Yearsley wrote the sections on seed predation ity (Section ), and effects of silvicultural practices (Section ) and soil seed banks (Section ), and on emergence (Section ). Each section was written contributed to the sections on planning field by one or more experts as follows: studies (Table .) and seed dispersal (Section ). Carole Leadem, Ph.D., R.P.Bio., earned her Vera Sit, M.Sc., earned her graduate degree from degree in plant physiology from the Botany Depart- the Statistics Department, Dalhousie University, and ment, University of British Columbia, and is a is a member of the Statistical Society of Canada. She member of the Association of Professional Biolo- has been with Biometrics Section, Research Branch, gists of British Columbia. She has been in charge of B.C. Ministry of Forests, since . Vera Sit wrote the tree seed biology research program with the B.C. the sections on experimental design and data analy- Ministry of Forests in Victoria since . Carole sis (Sections ., ., ., ., ., ., .) and the Leadem wrote the sections on planning and case studies (Section .), and reviewed and contrib- organizing field studies (Section ), natural seed uted to all the statistical sections. production (Section ), seed responses to the envi- David Spittlehouse, Ph.D., P.Ag., earned his ronment (Section .), seed testing in the laboratory graduate degree in forest climatology from the De- (Section .), seedbed preferences (Section ..), partment of Soil Science, University of British and contributed to the sections on seed dispersal Columbia. His research includes modifying site and silvicultural practices. microclimate to improve seedling regeneration, and Sharon Gillies, Ph.D., earned her degree in plant determining how forest harvesting and regrowth of physiology from the Department of Biological Sci- the forest affects forest hydrology. He has worked ences, Simon Fraser University. She has been a for the B.C. Ministry of Forests in Victoria since biology instructor at the University College Fraser . Dave Spittlehouse wrote most of the section Valley since . Sharon Gillies coordinated compi- on designing an environmental monitoring program lation of the original manuscript, was responsible (Section ). for creating the handbook structure and adhering Philip Burton, Ph.D., R.P.Bio., earned his degree to Ministry of Forests style manual, edited author in plant biology from the University of Illinois at submissions for the first complete draft, wrote the Urbana-Champaign. An independent researcher and section on seed dispersal (Section ), and provided consultant, he has been investigating seed biology, environmental monitoring material for Section , forest regeneration, and vegetation dynamics since and Table . on seedbed suitability. . Phil Burton contributed material for the

vii sections on seed dispersal (Section ), field germina- contemplating new research projects to avoid some tion studies (Section .), and effects of silvicultural of the pitfalls associated with studies in the field. We practices (Section ). anticipate other benefits: that this handbook will help Each section contains background material on standardize field methods and enable comparisons the subject and descriptions of some of the methods between studies, will increase cooperation between and approaches that have been used. There is also investigators, and will promote more efficient use of advice on experimental design and analysis of the resources (equipment, finances, personnel). All of data. Some laboratory procedures have been in- these efforts will help broaden the forest resource cluded to serve as controls for experiments database and increase our understanding of the conducted in the field. Laboratory experiments can multiplicity of factors involved in forest provide valuable data to supplement field measure- regeneration. ments because the results are generally reproducible We anticipate that methods documented in this and environmental variables can be controlled. handbook will be improved once they undergo Many terms are discussed in a comprehensive glos- more extensive field testing, and we invite com- sary, and the main subject areas have been indexed. ments about the information and methods The logistics of field research are difficult enough suggested here, and about your own field experi- in their own right. We hope the information con- ences. Please direct your suggestions to the senior tained in this handbook will help those author at the address inside the front cover.

viii ACKNOWLEDGEMENTS

Very special thanks are due to Dr. John Zasada, Edith Camm, Ph.D., University College Fraser USDA Forest Service, North Central Experiment Valley, Abbotsford, B.C. (Glossary terms). Station, Rhinelander, Wisconsin, who reviewed the Andrea Eastham, M.Sc., Industrial Forest Service, entire handbook twice. From the time John reviewed Regeneration and Research Specialist, Industrial the first draft, his interest, enthusiasm, and encour- Forestry Service Ltd.,  Fifth Ave., Prince George, agement have helped immeasurably to sustain our B.C. (Section : Silvicultural Practices and Tree Seed own commitment to the project. His deep under- Biology). standing of the subject matter emanating from his D. George W. Edwards, Ph.D., Canadian Forest years of experience in the field has substantially Service, Pacific Forestry Centre, Victoria, B.C. broadened the context and increased the value of (Section : Seed Quality and Viability). the field manual. We thank him, too, for insisting David F. Greene, Ph.D., Departments of Geogra- that we include more coverage on hardwood species, phy and Biology, Concordia University, Montreal, forcing us to go beyond the traditional tendency to Quebec (Section : Seed Dispersal). regard conifers as the only trees in the forest. Robert (Bob) Karrfalt, Ph.D., USDA Forest Serv- Next, we want to thank Fran Aitkens, who has ice, National Tree Seed Laboratory, Dry Branch, given us an understanding of the importance of an Georgia (Section : Natural Seed Production and editor. It’s not an easy task to try to meld all the Section : Seed Quality and Viability). styles and approaches of a group of authors with Gina Mohammed, Ph.D., Ontario Ministry of very different backgrounds. Fran’s thoroughness and Natural Resources, Ontario Forest Research Insti- attention to detail, understanding of the technical tute, Sault Ste. Marie, Ontario (Section : Seed aspects of the text, and ability to craft disparate text Quality and Viability). into a cohesive manual have vastly improved the Peter Ott, M.Sc., B.C. Ministry of Forests, material she was given by the authors. Readers will Research Branch, Victoria, B.C. (Biometrics in all also appreciate the clarity and organizational struc- sections). ture she has introduced into the manual. George Powell, M.Sc., Agriculture Canada Performing a technical review is not an especially Research Station (Range), Kamloops, B.C. rewarding task, but it is essential to the review (Section : Seed Banks). process and to gain the benefits of a range of Michael Stoehr, Ph.D., B.C. Ministry of Forests, perspectives. Thus, we extend our sincere apprecia- Glyn Road Research Station, Victoria, B.C. tion to the reviewers of the various drafts of the (Section : Natural Seed Production and Section : manuscript: Silvicultural Practices and Tree Seed Biology). William Archibold, Ph.D., Department of Geog- Tom Sullivan, Ph.D., Applied Mammal Research, raphy, University of Saskatchewan, Saskatoon, Sask. Summerland, B.C. (Section : Seed Predation). (Section : Seed Banks). The following, all of the B.C. Ministry of Forests, Wendy Bergerud, M.Sc., B.C. Ministry of Forests, reviewed and commented on administrative details Research Branch, Victoria, B.C. (Biometrics in all associated with Section  Planning Tree Seed Research sections). in the Field: Brian Barber, Seed Policy Officer, Forest

ix Practices Branch, Victoria; Ken Bowen, Special Pro- information on site index; Dr. John Owens, Univer- jects and Boundaries Supervisor, Resource Tenures sity of Victoria, for the pollen micrographs (Figure and Engineering Branch, Victoria; Dave Cooper- .); and Heather Rooke, Tree Seed Centre, Surrey, smith, Research Silviculturist, Prince George Forest for valuable information on cone and seed charac- Region, Prince George; Ann Cummings, Records teristics of B.C. conifers. Management Analyst, Technical and Administration Branch, Victoria; Brian D’Anjou, Research Silvi- Carole L. Leadem culturist, Vancouver Forest Region, Nanaimo; Sharon L. Gillies Dr. Suzanne Simard, Research Silviculturist, H. Karen Yearsley Kamloops Forest Region, Kamloops; and Alan Vyse, Vera Sit Research Group Leader, Kamloops Forest Region, David L. Spittlehouse Kamloops. Philip J. Burton In addition, we thank Dave Kolotelo, Tree Seed Centre, Surrey, for the germination value data Victoria, B.C. (Table .); Gordon Nigh, Research Branch, for September 

x CONTENTS

credits ...... iii introduction ...... v organization of the handbook ...... vii acknowledgements ...... ix section 1 planning tree seed research in the field ......  . Overview ......  . General Structure of Successful Field Studies ......  . Designing a Field Study ......  .. Formulating the hypothesis ......  .. Stating the objectives ......  .. Selecting the factors to study ......  .. Selecting the methods ......  .. Setting the time frame and determining a schedule ......  .. Choosing the test conditions ......  . Experimental Design ......  .. Basic concepts ......  .. Determining the sample size ......  . Data Management ......  .. Establishing a coding scheme ......  .. Creating a permanent file ......  .. Preparing to collect data and samples ......  .. Collecting the samples and recording the data ......  .. Reporting ......  . Selecting and Describing the Study Site ......  .. Selecting the study site ......  .. Deciding on temporary or permanent plots ......  .. Determining size and shape of the plots ......  .. Installing, marking, and relocating the plots ......  .. Describing the site ......  .. Site index ......  . Analyzing and Interpreting the Data ......  . Administration of the Research Site ......  .. Obtaining site approvals ......  .. Registering field installations ......  .. Security ......  .. Safety ......  .. Using registered seeds ......  .. Making seed collections ...... 

xi . Ecosystem Management ......  . Summary ...... 

section 2 designing an environmental monitoring program ......  . Background ......  . Designing an Environmental Monitoring Program ......  . Methods for Measuring Environmental Factors ......  .. Soil temperature ......  .. Soil moisture ......  .. Solar radiation (light) ......  .. Wind speed and wind direction ......  .. Precipitation ......  .. Air temperature and humidity ......  .. Plant temperature ......  .. Canopy cover ......  .. Soil variables ...... 

section 3 natural seed production ......  . Background ......  .. Collecting stand and study plot information ......  .. Determining sample size ......  . Predicting Natural Seed Yields ......  .. Correlation with weather variables ......  .. Correlation with aspect and slope ......  .. Correlation with crown size and crown class ......  .. Sampling methods using bud counts ......  .. Scales for rating cone crops ......  .. Monitoring the seed crop ......  . Determining Fruit and Seed Maturity and Quality ......  .. Description of conifer and hardwood fruits ......  .. Assessing embryo development ......  .. Assessing seed colour ......  .. Measuring cone and seed dimensions ......  .. Estimating seed weight and volume ......  . Collecting and Processing Seeds ......  .. Conifer seeds ......  .. Hardwood seeds ......  . Assessing Factors that Reduce Seed Yields ......  .. Assessing serotiny ......  .. Assessing predation ......  .. Using X-ray analysis to determine causes of loss ......  . Experimental Design ......  .. Estimation studies ......  .. Modelling studies ......  .. Comparative studies ......  . Data Analysis ......  .. Estimation studies ......  .. Modelling studies ......  .. Comparative studies ......  . Seed Production Case Studies ...... 

xii section 4 seed dispersal ......  . Background ......  .. Why study seed dispersal? ......  .. Mechanisms of seed dispersal ......  .. Timing of seed release ......  .. Dispersal distance ......  .. Quantity and quality of dispersed seeds ......  .. Climatic conditions ......  .. Dispersal patterns ......  .. Dynamics of seedfall ......  .. Approaches to Studying Seed Dispersal ......  . Measurements and Methods ......  .. Basic considerations ......  .. Seed trap design ......  . Experimental and Sampling Design ......  .. Estimating seed rain density ......  . Data Analysis ......  .. Descriptive analysis ......  .. Comparative analysis ......  .. Regression analysis ......  .. Spatial analysis ......  .. Mechanistic modelling ......  section 5 seed predation ......  . Background ......  . Seed Predators ......  . Approaches to Studying Seed Predation ......  .. Natural seed crops versus artificially introduced seeds ......  .. Predation on natural seed crops ......  .. Predation on artificially introduced seeds ......  .. Quantifying seed predation ......  . Methods, Techniques, and Equipment ......  .. Distributing seeds ......  .. Excluding seed predators ......  .. Marking and recovering seeds ......  . Data Analysis ......  section 6 seed banks ......  . Background ......  . Approaches to Studying Soil Seed Banks ......  .. Seed separation versus direct counts ......  .. Assessing vertical distribution ......  .. Monitoring germination in the field ......  .. Seed burial experiments ......  . Methods, Techniques, and Equipment ......  .. Collecting and preparing soil samples ......  .. Seed separation and direct counts ......  .. Germinating sseds in samples ......  .. Monitoring germination in the field ......  .. Seed burial experiments ...... 

xiii . Experimental and Sampling Designs ......  .. Seed bank inventory studies ......  .. Comparison studies ......  . Data Analysis ...... 

section 7 seed quality and viability ......  .. Factors Affecting Seed Biology ......  .. Factors affecting dormancy and emergence ......  .. Factors affecting germination ......  . Seed Testing in the Laboratory ......  .. Sampling methods ......  .. Seed purity, seed weight, and moisture content ......  .. Preparing seeds for testing ......  .. Dormancy-breaking procedures ......  .. Laboratory germination tests ......  ... Quick tests and other viability tests ......  . Field Tests of Tree Seed Germination ......  .. Experimental design and analysis ......  .. Delimiting the site ......  .. Excluding other seeds ......  .. Preparing the seeds ......  .. Excluding predators ......  .. Monitoring germinants ......  . Experimental Design for Germination Studies ......  .. Experimental factors ......  .. Experimental designs ......  .. Replication and randomization ......  . Data Analysis in Germination Studies ......  .. anova ......  .. Categorical data analysis ......  .. Regression ...... 

section 8 silvicultural practices and tree seed biology ......  . Background ......  .. Principles of forest stand manipulation ......  .. Standard silvicultural practices ......  . Effects of Canopy Manipulation ......  .. Light ......  .. Temperature ......  .. Moisture ......  .. Suggested questions and approaches ......  . Effects of Seedbed Manipulation ......  .. Seedbed preferences ......  .. Site preparation ......  .. Suggested questions for seedbed studies ......  .. Methods for seedbed research ......  . Combined Studies ......  . Summary ...... 

index ...... 

xiv appendices

a Tree Species Occurring in British Columbia ...... 

b Conversion Factors ...... 

c Resources for Tree Seed Studies ......  glossary ......  references cited ......  figures

. Framework for evaluating the seed reproduction process in boreal forest trees ...... 

. Maps giving details of the research site should be included in the permanent file ......  . Sustainability can only be achieved when the needs of society and the potential capacity of the earth we live in overlap ...... 

. Climate station with wind direction and wind speed sensor, a rain gauge, and tower with solar radiation, air temperature, and humidity sensors ......  . Electronic datalogger used to monitor and capture data from a series of environmental sensors ......  . Automatic tram system that moves back and forth over a  m span to determine the variation in short- and longwave radiation, and surface and air temperature under a forest canopy ......  . Influence of forest canopy on the intensity and spectral distribution of solar radiation reaching the forest floor ......  . A fine wire thermocouple is used to measure the temperature inside the leader of a young spruce tree ...... 

. Different spatial arrangements comprising % canopy cover ...... 

. Typical development and maturation cycles of British Columbia conifer seeds ...... 

. Climatic conditions required for cone crop production in Douglas-fir ......  . Percentages of black spruce trees (concentric circles) – years old from seed, growing on slight (–%) slopes and on various aspects ......  . Position of measurement for trunk diameters, the diameter of the base of a branch, and main axes for estimating of the number of cones ...... 

. Scanning electron micrographs showing whole pollen and details of the exine ......  . The oval, raised cone scars of Pinus albicaulis can be counted and aged by the nearby annual bud scars on twigs ...... 

. Longitudinal and transverse sectioning of cones ...... 

. Anatomy of a mature Douglas-fir seed ...... 

. Tree seed anatomy (longitudinal sections) ...... 

. Outline drawing of a typical seed of Thuja occidentalis ...... 

. Salix capsules at various stages of opening and the dispersal unit at various stages ...... 

. Partial life table for  jack pine conelet crop, Oneida County, Wisconsin ...... 

xv . X-rays of tree seeds ...... 

. Correlation coefficients for hypothetical relationships ...... 

. A descriptive model of eastern redcedar (Juniperus virginiana L.) cone-crop dispersal from June through May of the following year ...... 

. Seed dispersal curves for nine conifers of the Inland Mountain West ...... 

. Examples of dispersal mechanisms of winged seeds ...... 

. Seed trap designs ...... 

. Schematic of the distribution of seed-traps placed around a point-source ...... 

. Recommended seed-trap layouts at a forest edge for an area source ...... 

. Small mammal exclosures ...... 

. Using a soil auger to remove a soil core for seed bank studies ...... 

. Method for cutting a square forest floor sample ...... 

. Preparing square soil samples for greenhouse germination ...... 

. Dividing a soil core into layers ...... 

. Soil samples in the greenhouse ...... 

  . Absorption of far-red light converts the pigment phytochromefar-red (usually the  active form) back to phytochromered (the inactive form) ......

. Sampling seeds by hand (a) and with a grid (b) ......  . Germination of (a) lodgepole pine, (b) Sitka spruce, and (c) Douglas-fir at different temperatures and after stratification for , , , and  weeks ...... 

. Stages of germinant development in hypogeal and epigeal germination ......  . Stages of germination for Populus seeds, showing time period in which each stage usually occurs ...... 

. Cutting diagram for the tetrazolium test ...... 

. A recommended frame design for delimiting field germination plots ...... 

. Layouts for one factor with two levels ...... 

. The two stages of a split-plot design ...... 

. Effective natural regeneration depends on an adequate seed supply, a suitable seedbed, and an appropriate environment ......  . Illustration of stand structure resulting from five different silvicultural systems used in the Lucille Mountain Project in the Engelmann Spruce–Subalpine Fir () biogeoclimatic zone, Prince George Forest Region, British Columbia ......  . Measured levels of photosynthetic active radiation (par) available to seedlings above and below the shrub layer in various partial cut systems at the Lucille Mountain Project, Prince George Forest Region, British Columbia ...... 

xvi . Growing-season soil temperatures (at  cm depth, -year means on a north-facing slope) in clearcut, small patch cut, and group selection treatments ......  . Number of subalpine fir and Engelmann spruce germinants per hectare within three silvicultural treatments at the Lucille Mountain Project, Prince George Forest Region, British Columbia ......  tables

. Installing and marking the research plots ...... 

. Seed production characteristics of hardwoods native to British Columbia ...... 

. Seed production characteristics of conifers native to British Columbia ...... 

. Cone crop rating based on the relative number of cones on the trees ...... 

. Rating of seed crops by number of filled seeds per hectare ...... 

. Seed-bearing structures of trees occurring in British Columbia ...... 

. Seed sizes of tree species occurring in British Columbia ...... 

. Seed dispersal mechanisms of winged seeds ......  . Mean terminal velocities reported for seeds (with seed wings attached) of some British Columbia tree species ......  . Split-plot-in-time analysis of variance (anova) table for a hierarchical sampling design ...... 

. Summary of exclosure choices for seed predators ...... 

. Two-dimensional contingency table for analyzing seed losses to two predators ......  . Comparison of methods for calculating proportion of seeds lost to predation over time ...... 

. Moisture content guidelines for orthodox tree seeds ...... 

. Classification of mould infestation in seeds ...... 

. Stratification and incubation conditions for British Columbia conifer seeds ...... 

. Stratification and incubation conditions for British Columbia hardwood seeds ...... 

. Summary of stratification methods ...... 

. Dormancy release treatments for tree seeds ...... 

. Germination values for British Columbia conifers ...... 

. Comparative seedbed suitability of some northwestern tree species ......  . (a) The relative abundance of seedbed substrates in an interior Douglas-fir stand (b) Expected and observed seedling association with four forest floor substrates in an interior Douglas-fir stand ...... 

xvii SECTION 1 PLANNING TREE SEED RESEARCH IN THE FIELD

The road to chaos is paved with good assumptions. (Anon.)

It is much less expensive to learn from other people’s mistakes than your own. (McRae and Ryan )

. Overview . General Structure of Successful Field Studies

Forests cover only about % of the earth’s surface, A survey of long-term forest research programs con- yet they account for nearly half of its net primary ducted at many locations throughout the world by productivity, and about % of the net productivity Powers and Van Cleve () stressed the importance occurring on land (Whittaker and Likens ). For- of planning, commitment, and focus. They con- est ecosystems are complex and diverse, and develop cluded that successful long-term experiments shared relatively slowly. Thus, forest ecosystem research eight essential components. Not all field studies are projects may require years to produce meaningful conducted over long periods, nonetheless, consid- findings that can be widely applied. eration of the following principles is instructive to The duration of a study depends entirely on what anyone contemplating field research, regardless of you want to find out. Many of the biological, physical, duration. and chemical phenomena associated with forest eco- systems can be studied over relatively brief periods . Sustained commitment on temporary field plots or in the laboratory. To Fluctuations in philosophy, politics, and funding are document and compare natural processes, short-term the surest way to dampen scientific spirit and inspira- descriptive and baseline studies are essential. Short- tion. Field studies, once established, must have a fair term studies also are important to establish the certainty of continued support, at least to the level immediate impact of processes on a system, even required to maintain research sites and to collect though they are prone to being confounded by core data. This support should be free from political environmental fluctuations such as climate. interference. To enlist this level of commitment, On the other hand, many biological phenomena, researchers should present their arguments based such as plant succession, occur on time scales of primarily on the benefits that can be derived from decades or centuries. Long-term studies allow us investigating socially relevant issues (e.g., sustaining to evaluate interactions among the various factors wood production, providing clean water, protecting controlling ecosystem function that, on a short time soils). Proposals that are couched in terms of “under- scale, might seem inconsequential. Forest ecosystems standing how forest ecosystems work” are far less usually require many years for the effects of per- likely to be granted support by funding administrators. turbations to subside and for long-term trends to appear. This is especially true for communities not . Long-term dedication of a site in equilibrium, such as those recovering from fire Plots maintained after the original questions have or harvesting. been answered can continue to have demonstration

section 1 planning tree seed research in the field 1 value for professionals and the public, and can pay in continuity and maintaining the research site, substantial dividends well beyond the life of the interdisciplinary field studies inherently promote the original study. Again, the chances of having land stability of long-term projects. However, interdiscipli- dedicated for the site will be enhanced if the research nary studies only work if there is strong central has a central, timeless theme. Support is more likely planning and coordination. to continue if research results are disseminated rap- idly to administrators and land managers. . Extension of results Research must be designed to make data as portable . A guiding paradigm as possible so that results can be generalized to a A central focus is necessary to provide structure and variety of species, soils, and forest types. Research will maintain research objectives. As long-term objectives have the highest value if results can be incorporated may grow hazy with time and personnel changes, into a network of coordinated, but geographically periodic reference to the guiding paradigm will help separated, studies. Experiments should be sufficiently to refocus the research. comparable so that databases can be shared, and each research site should be instrumented so that a . A central hypothesis baseline of climatological data can be established. A clear statement of the principal scientific question that the research is designed to answer helps to clarify . Low red tape the research direction and stimulate development of Maintain the least amount of bureaucratic structure the experimental approaches. The central hypothesis needed to prevent chaos. Initially, a board of senior is tested through a number of individual studies with scientists from a variety of disciplines should review definite life spans that terminate once a particular all research proposals. Later, a research coordinator question has been addressed. can review projects to ensure that one study does not interfere with another, and that all collaborators are . Large plots and replication kept abreast of the overall research program. Depen- Plots should be large enough to simulate natural eco- ding on the size of the research site, a site manager system conditions as closely as possible. Large plots may be needed to facilitate day-to-day (or seasonal) not only minimize edge effects, but also increase the scheduling. flexibility of future studies on research sites. Options might include retaining extra control plots that could . Designing a Field Study later be converted to secondary treatments, or creat- ing split-plots for treatments supplemental to the Careful initial planning and organization are critical original design. Large plots facilitate replication of to the success of any field study. Considering the com- treatments, which is essential for statistical analysis plexity, the expense, and the duration of many field and setting confidence intervals. studies, the consequences of poor planning can be great. Most studies consist of three stages—planning . Interdisciplinary approach to research (Stage I), data gathering (Stage II), and data analysis Field installations should be made available to all and interpretation (Stage III). However, the frame- research collaborators, regardless of affiliation or work for all three stages is constructed during the specialty. This will attract excellent scientists and planning stage. The planning process can be articu- promote openness and synergy. Studies that attract lated as a series of steps that provide answers to the a broad array of scientific interests result in much questions: why, what, how, when, where, how much, greater understanding than can be achieved through and so what. isolated, independent efforts. In addition, program scientists benefit from exchanging ideas, cooperating .. Formulating the hypothesis on experimental work, and collaborating on profes- The first step before undertaking any field study is to sional papers. Because collaborators have an interest formulate a clear statement of the principal scientific

2 field studies of seed biology question or central hypothesis that the research is germination, the most suitable variables to study designed to answer—the why of the experiment. A would be (micro)climate, substrate, and species. research plan with a clear statement of the problem Treatments should be chosen to reflect major helps to identify the research direction and provide changes in ecosystem function. Viewing ecosystems valuable guidance if the project should run into under extreme conditions is most likely to reveal difficulty (such as loss of support, changes in per- how various ecosystem components function and sonnel, or environmental disaster). to demonstrate the capacity of these components to recover from change. Studies will have greater value .. Stating the objectives if the treatments have a generally continuous pattern Once the principal scientific problem has been (i.e., increasing or decreasing in size). Data obtained elucidated, research objectives provide the necessary from such treatments lend themselves to predictive structure for planning and executing the project. Ob- regression analysis. Changes in responses can then be jectives are succinct summary statements of what the correlated with changes in the magnitude of specific research is trying to achieve. Keeping research objec- factors, and results can be more readily extrapolated tives in focus during all stages of planning will stimu- to similar sites. Choosing treatments that span and late development of experimental approaches, guide extend slightly beyond the full range of expected re- complete and efficient collection of data, and keep sponses helps to define the end points and establish the research on track. the limits of the system under study. Particularly in long-term studies, it is advisable .. Selecting the factors to study to retain some flexibility in the original design by The factors to be studied—another aspect of what— incorporating ways the experiment can be changed are usually specifically identified in the statement if future circumstances should require it (Leigh et al. of objectives. The factors chosen will depend upon ). To ensure the longevity of the field site, it is whether the study is primarily descriptive or experi- best if only minimum changes are made to the treat- mental in nature. In experimental studies, factors are ments. Changing the experiment to obtain more the vehicles through which the objectives are information in the short term generally results in achieved, and they are generally identified as treat- sacrificing the longevity of the treatments. It is some- ments. Factors may consist of one or several levels. times advantageous to incorporate innovations in For example, suppose your objective is to determine forest management practices into the study, but this if light affects the survival of lodgepole pine should be done only if the major objectives can be germinants on open harvested sites. To investigate retained. Another possibility is to modify the original this objective experimentally, you would identify light objectives and continue the experiment in a different as the factor to be tested. You might also want to form, but again longevity will be lost. A final, but more specifically compare how different light levels generally less desirable option, is to set aside the site affect seedling survival; then you would expand the indefinitely or reserve it for future use. light treatment to include several levels, such as full sun, partial shade, and full shade. .. Selecting the methods Constructing a schematic diagram of the bio- Methods can be considered the how of experimental logical cycle (or other process) is an effective way studies. The techniques chosen for the study will to identify what variables affect the process being be governed by the study objectives, and the most investigated. Diagrams help to clarify relationships effective means of achieving those goals. Usually, and suggest the most appropriate factors to study more than one method will achieve a particular (Figure .). For example, if you want to study initia- purpose, and for this reason a variety of methods for tion of reproductive buds, you will want to include field studies of tree seeds has been included in this climate, plant condition, and resource availability as handbook. Ultimately, the choice of the most suitable major factors in the experiment. On the other hand, technique will depend on the available resources. if you want to examine the factors affecting field In most cases, the final decision will be based on

section 1 planning tree seed research in the field 3  . Framework for evaluating the seed reproduction process in boreal forest trees (adapted from Zasada et al. 1992). A schematic diagram can help to clarify processes and suggest factors for the study. balancing the trade-offs between the detail desired process be automated? The choice may also be affec- and the constraints of time and money. ted by the logistics of the experimental site—certain Most research projects will employ a variety of techniques may not be suitable for field use. For ex- methods. Often the distinction between different ample, precise and automated methods may be ideal methods is determined more by the purpose than by for making a particular measurement, but the instru- the type and intensity of the monitoring. Note that ments may not be robust enough for field conditions different objectives do not necessarily require distinct or may require an external source of reliable power. and independent data collection efforts. There may After choosing the methods, it should be deter- be some overlap in the data needs. As long as the re- mined whether the research data are continuous or search objectives are kept clearly in mind, taking categorical. The term continuous implies that the advantage of this overlap can result in substantial measurements, in theory, belong to a numerical scale cost savings. consisting of an infinite number of possible values. Answers to the following questions will help in However, sometimes you need to measure a quality choosing appropriate methods: What is the primary or condition that cannot be expressed on a continu- purpose of the measurement? How well does the chosen ous scale. This discrete, noncontinuous type of data method quantify the factor or characterize the inten- is called categorical because it generally consists of sity of the response? How precise or accurate is the the number of observations falling into prespecified method? How many measurements are required? If classifications, groups, or categories (e.g., number of many or frequent measurements are required, can the seeds that have or have not germinated).

4 field studies of seed biology Continuous data can usually be analyzed using monitoring, effectiveness monitoring, project moni- parametric methods such as anova, regression, and toring, validation monitoring, and compliance manova (Sections ., ..). However, nonparametric monitoring. analysis is sometimes required for continuous data if Visual data are another significant source of primary the assumptions of anova, for example, cannot be scientific information, although they are not gener- met. Categorical data, on the other hand, are usually ally considered as data. Visual representations may analyzed using methods such as contingency tables be the most effective way to present information that and log linear models (Sections ., ..) although otherwise would be too unwieldy or difficult to alternative nonparametric techniques are available, understand (e.g., site maps or structural diagrams). if necessary. Some information can only be captured visually (e.g., Data can also be categorized by the type of meas- seed X-rays or photomicrographs of plant structure). urement used for collection. Determining the type Although not quantitative, visual data represent an of measurement needed helps to identify the type important source of research information, and a of information required, the frequency of data valuable means of portraying certain characteristics. collection, and the most suitable means of analysis. Unfortunately, visual data are underutilized in most Types of measurement include assessment, inventory, research studies. monitoring, and visual data. An assessment is an estimation or evaluation of .. Setting the time frame and determining the significance, importance, or value of a quality or a schedule character. It generally implies a subjective judgement Before starting the study, a schedule should be pre- (e.g., maturity) to determine placement in a class. pared to outline the temporal distribution of the The classification scheme may be based on some ar- major components of the study. This is the when of bitrary characteristic or a ranked order. Assessment experimental studies. Many field studies are short in data are usually nonparametric. duration, but some studies can be very lengthy, such An inventory is an itemized list or catalog that as the ecological studies of the Carnation Creek wa- may or may not be organized into groups. Usually tershed on Vancouver Island, which have been under the number of items in a group are simply counted, way for over  years. with no additional judgement or interpretation. The experimental design and type of data analysis For example, for an inventory of seeds in a seed will direct how often to collect the data (e.g., daily, bank, a count is made of the number of seeds by weekly, monthly), but the timing of treatments must species present in the soil. An inventory is usually also be taken into consideration when designing field a one-time measurement, but it can be repeated studies. Treatments may be applied only once, repeated periodically (e.g., annually). Greater use often can at fixed periods (e.g., annually), or even rotated. The be made of inventory data if the samples are strati- timing will also depend on what type of information fied in some way, for example, by making separate is required—whether you are interested in the direct seed counts at various depths of a soil core, rather effects in the year the treatment is applied, the re- than performing a single count of the total core. De- sidual (or carry-over) effects in subsequent years, or pending on the manner in which samples are taken, the cumulative effects of repeated treatments. inventory data can be parametric or nonparametric. The length of the study periods should be clearly The term monitoring is used to describe a series of defined, especially when planning a long-term study. observations made over time. The repetition of meas- The most suitable period length is defined by how urements to detect change over time is the quality long plot management can be kept constant. Period that distinguishes monitoring from the related proc- length might also be governed by the time when the esses of inventory and assessment. The data obtained first full assessment can be made (e.g., at the end of can be parametric or nonparametric. MacDonald et al. the first growing season), or when treatment differ- (), in compiling guidelines for monitoring water ences might first be discernible. quality, recognized seven types of monitoring: base- In some instances, period length may be used to line monitoring, trend monitoring, implementation apportion temporal variation (McRae and Ryan ).

section 1 planning tree seed research in the field 5 In the same way that blocks are used to control .. Basic concepts spatial variation among plots within a site, changes It is assumed that readers of this handbook have over time can be partitioned into periods. Although some knowledge of statistics, and will know where to period lengths may sometimes differ because of obtain assistance for particular statistical problems. operational constraints, analysis is simpler when The statistical discussions included in various chap- all plots have study periods of the same length. ters are intended only to provide general background on important aspects of experimental design and .. Choosing the test conditions data analysis, and to raise awareness of some poten- The next step is to determine where the factors will be tial pitfalls or problems that may be encountered in tested. Depending on the research objectives, the test specific topic areas. Discussions relating to some conditions are sometimes considered to be a factor common statistical methods can be found in the fol- of the experiment. If this is the case, you should lowing sections: summary statistics (Sections .., choose test sites or conditions that follow some sort .); anova (Sections ., .., ., .); regression of progression or gradient (e.g., small to large open- (Sections .., ., .); correlation (Section .); ings, low to high elevation). This will allow the results and chi-square (Sections ., ..). to be more readily generalized to other sites (if the Careful study of the proposed designs can be in- requisite experimental design criteria have been met). valuable during the planning stage (McRae and Ryan Most details relating to test conditions will be ). Trial analyses will demonstrate whether the specific to the study and what you are trying to ascer- contrasts of interest can be estimated, and will point tain. For further details refer to the section of interest: out deficiencies in the design and analysis methods. seed production (Section ), dispersal (Section ), A postmortem of similar experiments often provides predation (Section ), germination of seed banks data sets and estimates of experimental errors that (Section ), laboratory and field germination tests can be used to evaluate the proposed design. As in (Section ), and silvicultural practices (Section ). the actual experiment, there should be sufficient rep- lication to achieve the degree of precision required . Experimental Design to detect the treatment differences. If trial analyses reveal it is unlikely that differences will be found, the study may not warrant the investment. This is If you don’t deal with each of these levels of variation, especially critical for long-term studies. your sampled population may not be representative The distribution of replicates in space and time of your target population, and in that case is the most critical element of experimental design. a statistician or a sharp lawyer can make you Randomization provides for estimates of the experi- and your data look pretty lame. mental errors, which should always be reported, (MacDonald and Stednick ) either as the standard error of the mean or the difference between means (McRae and Ryan ). Once the objectives are identified and the factors, meth- Replication is generally accomplished by applying ods, and test conditions are established, attention treatments to two or more plots within the site should be turned to experimental design. The experi- (often divided into blocks) and/or by repetitions mental design will prescribe how essential elements of of the experiments at other locations or times. data collection (Stage II) and data analysis and inter- The allocation of replicates will be largely a func- pretation (Stage III) are executed. Field studies require tion of the objectives and the expected variability substantial commitments of time, labour, money, (MacDonald and Stednick ). The more sources materials, and maintenance; inadequate attention of variability you address, the more reliable your re- to details such as experimental design and data man- sults will be. In general, it is not efficient to test for all agement can pose considerable risks to the resources sources of variability everywhere. However, if you do invested in the project. Losses due to errors in not repeat any of your measurements, you have an experimental design may severely damage a scientist’s unknown source of error that will weaken all your reputation and will reflect badly on collaborators. subsequent conclusions. Repeated measurements

6 field studies of seed biology can give a better estimate of a variable such as seed Stednick ). For example, in natural resource production or field germination, but when you are management, the significance level is typically set at replicating your measurements, you have to be clear α = ., meaning that there is a  in  chance that an about the level of variability with which you are deal- observed difference will be due to chance. A strong ing. Measurement variability is very different from level of significance combined with high variability the variability between experimental units (e.g., field means that usually you will not detect a statistically germination plots). significant change until damage to the resource has Each time you design a project, you need to identify occurred. However, given the high natural variability all these potential sources of variation, and deter- in natural systems, it may be better to use a less strin- mine how you want to deal with them. If you don’t gent significance level in exchange for a higher level deal with each source of variation, your sampled of resource protection. Another example is power, population may not be representative of your target which is usually designated as -β. When comparing population. Hurlburt () uses the term pseudo- two sample means, the quantity β is known as a replication to refer to the testing of treatment effects Type II error, which is the probability of incorrectly with an inappropriate error term for the hypotheses concluding that two populations are the same when being tested. You can think of it as a source of vari- in fact they are different. Again, if a resource is slow ability which is inherent in the data but cannot be to recover or is of high value, you probably want to defined because of the sampling strategy. In other increase the value of α. In natural resources manage- words, if you have some sources of error in the data ment α should probably be set at . (MacDonald that cannot be tested, then typically you are dealing and Stednick ). with pseudoreplication. Excellent discussions of pseudoreplication can be One of the examples Hurlburt () uses is a found in Stewart-Oaten et al. (), Bergerud (), study to determine the effect of water depth on the and MacDonald and Stednick (). Additional rate at which leaves rot in a lake. Although this is not discussion of randomization and replication in a seed-related example, it is worthwhile using here relation to field studies of tree seeds can be found because it is so clear and succinct. Four bags of leaves in Section ... were placed together at one location at a depth of Blocking of the plots reduces experimental error  m, and another four bags were placed together at by removing any gradient effects in site variation. another location at a depth of  m. After some time Choosing blocks that are arranged contrary to the the bags were retrieved, dried, and weighed. If there field gradient will increase the experimental error, was a significant difference between the two sets but this is difficult to avoid because the field gradient of bags, all that can be said is that there was some is often unknown. Appropriate variables on the site difference between the two locations. To make an (temperature, soil, moisture) can be measured and inference about the effect of a particular water depth the results used as a basis for blocking. If elevations on leaf rotting in this lake, the bags would have to be of the site vary considerably, blocking would most distributed at the same depth around the lake. To likely be parallel to contour lines, and not perpen- make a more general statement, replicated samples dicular. The effectiveness of a block arrangement would have to be distributed at different depths in can be assessed only after the experiment has been several lakes. The design depends on the question run. A good strategy is to have a robust blocking you want to answer, but placing all the bags in one structure that allows for an environmental gradient place is pseudoreplication. From Hurlburt’s point of in either or both directions in a rectangular site view, you must have replication on at least one level. layout (McRae and Ryan ). See also Section .. If you don’t have the ability to test for differences, it In forestry research the same unit or process is is not an experiment. usually measured on more than one occasion. For Often you need to make statistical compromises, example, in trials to compare several treatments, and if so, you should be explicit about the statistical data are typically collected before and after treat- trade-offs that you have made, rather than letting ments are applied. Such data tend to be serially them be set by neglect or default (MacDonald and correlated, or autocorrelated, which means that the

section 1 planning tree seed research in the field 7 most recent measurements are dependent on, or to dispersal, Section  for seed banks, and Section  for some extent predictable from, earlier observations. seed germination tests. A more general discussion of Because this violates the independence assumption various types of sampling can be found in Cochran on which many standard statistical methods are () or Thompson (). based, alternative methods are required for their analysis. Two broad classes of methods have been . Data Management developed for this purpose: repeated-measures analysis and time-series analysis. For additional Data management protocols should be established background and discussion of this topic, refer to when the study is initiated. The type of data, experi- Nemec (). mental design, and method of analysis will guide how Carry-over effects from previous treatments are the records and data are organized and managed. a hazard of long-term studies in which multiple This section provides a brief overview of the major treatments are applied. When analyzing by anova points of data management, as well as some special or multiple linear regression, estimates of the direct considerations required for long-term studies. effects of later treatments must be adjusted for any residual effects remaining from previous treatments .. Establishing a coding scheme (McRae and Ryan ). A consistent coding scheme should be established to correlate all data records with the research plots and .. Determining the sample size treatments. The coding scheme is best defined in a To ensure that enough samples are collected for a table assigning unique label codes to identify field study—the how much of the experiment—it is advis- plots, factor levels, treatments, and replications. The able to determine the appropriate sample size specific table should indicate the exact units in which the to the parameter being studied. data will be recorded (e.g., millimetres, kilograms, Sample sizes for each measurement must be deter- or watts per square metre). For categorical data mined independently, because variability may be (Section ..), a brief description should be given different for different characteristics. For example, of the significance of each classification code (e.g., in the sample size required for measuring cone charac- Section .., for cones,  = scales fully open;  = scales teristics may not be the same as that needed for seed partly open;  = scales completely closed). characteristics, even for the same species, because Allow for some flexibility in the coding scheme of differences in the variability of the data (Carlson so that labels can be added if new treatments are and Theroux ). Environmental changes may also incorporated, or if treatments change over time. result in year-to-year variations, but these differences If treatments are changed, ensure that the coding can sometimes be minimized by adjusting all values scheme is annotated to relate the new treatments to to be relative to those observed in a particular year the original treatments. (Ager and Stettler ). The same format should be established for field Sample size is usually determined by applying and computer records so that data can be easily statistical efficiency calculations to a preliminary accessed for future examination or analysis. Where set of measurements (Sokal and Rohlf ; Ager feasible, coordinate with other agencies or researchers and Stettler ). See also Stauffer (, ) for to use standard codes or data-entry protocols. This sample-size tables oriented to forestry applications. will facilitate exchange of data between programs. For In the absence of any other information, a sample example, the standard coding formats used for the size of  is often a good place to start (MacDonald biogeoclimatic ecosystem classification data should et al. ; MacDonald and Stednick ). be used for all site and vegetation data. Standard spe- The topic of sampling, both how to sample and cies names and codes for British Columbia can be how many samples to collect, is a critical aspect of found in both access . and excel . files at the all field studies of tree seeds. For more detailed B.C. Ministry of Forests Research Branch ftp site discussions relating to particular subject areas, see (see Appendix C) in the directory/pub/provspp. The Section  for seed production, Section  for seed files are regularly revised and updated. If you want

8 field studies of seed biology to collect vegetation data, then you should follow a) Describing Terrestrial and Aquatic Ecosystems in the Field (in preparation ) which will update Lutt- merding et al. (). This is also a useful reference for making site descriptions (see Section ..). A variety of computer data entry and reporting tools (e.g., venus) are also available (see Appendix C for more complete information).

.. Creating a permanent file The permanent file should include the initial plans and objectives and all parameters of the experiment. A statistical guide should be included in the perma- nent file giving full details of the experimental design(s), the proposed method of analysis, and all associated computer programs. Include the type and number of annual data sets, and a list of the different annual records. Special notes about the trial should be recorded and arranged by date or other logical se- quence. Include maps giving details of the research sites, the location of the plots, and the arrangement of the treatment blocks and replications (see Figure .). Provide room in the structure of the permanent file so that you can add data and field notes for the current year and update the parameters, if necessary. It is useful to link computer data files to a spreadsheet or graphics program to produce a series of graphs depicting the different responses over time for each treatment. Create a summary table of the cumulative effects for each variate, giving the relevant summary statistics. Plan the permanent file so that computer formats b) and files will remain compatible over changes in computers and software. To ensure efficient data entry, carefully design data sheets and format computer files. The spreadsheet software into which you plan to import your data should guide the data file format. For most data, a row/column format is best. If you are uncertain about the type of software that will be used, a simple ascii (text) file format is recommended. The permanent file should also contain detailed directions for finding the plots again after installation.  . Maps giving details of the research site should The importance of this step cannot be emphasized be included in the permanent file. (a) Loca- enough, especially if different people are resampling tions where western larch and subalpine larch the plots. Several scales of maps are needed to relo- are sympatric (Carlson and Theroux 1993). cate plots. Section .. includes a more detailed (b) Sketch of investigated stands of Pinus discussion of recording site parameters for relocation. sylvestris (Bergsten 1985).

section 1 planning tree seed research in the field 9 .. Preparing to collect data and samples . Selecting and Describing the Study Site Computer-generated administrative aids (labels, data sheets, random order lists) will simplify data and .. Selecting the study site sample collection. Organic tissue and soil samples An essential part of planning is selecting a suitable collected during the study must be properly coded site—the where of the experiment. Site selection and archived for analysis or future reference. Pre- should take into consideration practical aspects such printed labels simplify collection of samples in the as accessibility, the frequency of site visits, and how field and act as an additional check that coding seasonal changes may affect access and any perma- sequences are complete. Colours and symbols nently installed instrumentation. (e.g., stars, circles, triangles) used in addition to, As early as possible in the planning process, or instead of, numerical codes will help to reduce contact the local forest district or the forest manage- errors, which may result from performing repetitious ment office responsible for the proposed study area. tasks under arduous field conditions. Establishing a good relationship with those ulti- The sequence prescribed by the randomization mately responsible for the site can have unexpected scheme can be used to arrange labels, sample con- benefits and will also serve to promote your research tainers, and data sheets. If you have a large number amongst the forestry community. Local staff may be of items, it may be convenient to subdivide them able to suggest potential sites that meet your criteria into smaller groups (e.g., by plot number). and provide more detailed information if they know Permanent markers (stamped metal or plastic the objectives and the key factors you wish to study. are best) should be generated for all treatments, and From them you can gain considerable information securely attached to durable, highly visible posts or and knowledge about local forestry practices that other stationary devices in the field plots. For further will directly and indirectly influence your work or details, see Section .., Table .. research, now and in the future. Because they are located near the site, they may be able to maintain .. Collecting the samples and recording the data security or assist with site maintenance. In addition, Data can be recorded in the field using manual if local forestry staff know about your study, the records or hand-held dataloggers or other automatic chances of the trial being damaged by concurrent recording apparatus. Pre-labelled sheets can be used industrial or silvicultural activities is greatly reduced. for manual data entry, or datalogger files can be pre- The scientific criteria for selecting a site depend on programmed with plot, treatment, and sample codes. the goal of the study, but all critical site-related factors Refer to Spittlehouse () and Section . for addi- must be identified. For example, if the objective of tional information on using dataloggers in the field. the study is to determine the difference in seed pro- Transfer of data is now relatively easy using com- duction between north- and south-facing slopes, puters and computer interface devices, but all files then site selection will be dictated by the aspect must be regularly backed up to avoid loss of data. and grade of the slope. In other studies, slope and You should have spare power sources, in case primary aspect would not be primary factors. If the goal is to equipment fails. describe seed production in mixed stands as opposed to uniform stands, then the primary selection criteria .. Reporting would be the species composition of the stands. For A complete analysis of the research and a summary long-term research on seed production in a natural report should be prepared annually or at the end of stand, it would be important to locate each site away each field season. This can be considered the so what from openings or roads. In this case, a fixed area on of the experiment—what do the results mean in the each site might be delineated in the centre of the greater scheme of things. Strive to disseminate as stand, with the trees surrounding the plot acting as a quickly as possible the interim results or updates at buffer zone to reduce edge effects. technical meetings, in short articles, or in newsletters. Site illustrations are useful in documenting the Prompt reporting will help maintain support while key elements of the field site (Figure .), and should the research is in progress. form part of the permanent file (Section ..). They

10 field studies of seed biology may also be used to find the plots again for repeated The choice of plot size often depends on stand measurements (Section ..). density and heterogeneity. To compensate for differ- ing stand densities or species mixes in a study, the .. Deciding on temporary or permanent plots plot size could vary to maintain a constant number A decision must be made whether to use temporary of trees or species types within each plot. See Smith sites (entirely new units are randomly selected for et al. () for an example of this approach. observation each time), or permanent sites (the Another approach for studying tree density effects same units are observed repeatedly over time). The is to use rectangles of fixed dimensions (width and choice of temporary or permanent plots depends length) for all sample areas. Tree density can be esti- on the degree of correlation you expect between the mated by dividing the number of healthy trees within initial and final plot values. If a high positive correla- a sample rectangle by the area of the rectangle. This tion is desired, permanent plots will generally give approach is preferable because the fixed dimensions better precision. If large-scale changes are expected provide consistent estimates of site variation across in the nature of the site, temporary plots should be all study areas, and ensure the validity of tests for tree used (Freese ). Sometimes a combination of density effects. temporary and permanent sites can be used—perma- nent (intensive) sites for detailed aspects of the study .. Installing, marking, and relocating the plots and temporary (extensive) sites for broadening the Once the experimental site has been selected, the number of samples and site types. plots must be identified and the boundaries clearly marked. Markings must be highly visible and dura- .. Determining size and shape of the plots ble. The choice of marking method will depend on a The size and shape of the plot depend on a number number of site factors such as the distance from the of factors, including the goal of the research, the cost road, steep terrain, annual snowpack, rocky ground, or time required for sampling, the required precision, or height of vegetation. The durability required of and the uniformity or heterogeneity of the area markers will depend on the amount of exposure to (Freese ). There are obvious trade-offs between the elements, the possibility of crushing or toppling plot size and homogeneity of samples. You want as by large animals (bears, moose, cows, humans), and large a sample size as possible, with good treated the total length of time the plot will be sampled. A buffers, but the larger the plot size, the more likely summary of important points for installing and you are to introduce heterogeneity (in soils, nutrient marking plots is given in Table .. regime, moisture regime, slope, etc.) into your plot After installation, the site location should be re- selection, thereby increasing the within-plot error corded in detail in the permanent file. This is an sources. To assess homogeneity, a full site description important step, and will prove particularly valuable of each plot is recommended. Plots should only be if the plots are resampled by different people or over accepted for inclusion in the study if the variation in many years. site type would not compromise the long-term re- sults. In general, moving more than one full site series • To locate the general vicinity of the site: Mark site (or other environmental gradient) within a plot is locations on topographic maps, forest cover maps, probably sufficient reason to abandon it. Larger plots airphotos, orthophotos, etc. Write out directions in- (more than  ×  m) should have multiple soil pits cluding distances (km) to each turning point and to ensure homogeneity. road names, etc., from likely starting points (towns). The duration of the study will also govern plot Use GPS locations if you can afford and have access size. If there is any possibility of continuing the study to this technology. for  years or more, consider the plot size carefully. For example, if your original objective was to study germ- • To locate the site from the point of access (e.g., road): ination and initial development, but later you decide Draw a site map of the plot(s) and surrounding area to extend the length of the study, you may be unable with local landmarks (e.g., roads, water, rocks, slopes, to do so if the plot size initially chosen was too small. directions, etc.). If there is more than one plot, ensure

section 1 planning tree seed research in the field 11 they are mapped in relation to each other as accu- (Agriculture Canada Expert Committee on Soil Sur- rately as possible, using compass bearings and dis- vey ), humus classification (Green et al. ), tance measurements. and for sites in British Columbia and some other areas, the appropriate biogeoclimatic ecosystem • To locate the plot(s): Flagging tape and painted classification (refer to the B.C. Ministry of Forests stakes will help you spot the plots once you are at the regional field guides listed in Appendix C). Topo- site (See Table .). Plots marked with metal stakes, graphic grid references are also useful to locate the pins, or tags can be relocated with a metal detector. general area of the site. Keeping the objectives of the study clearly in focus • Take photographs of the plot to have a visual record will help identify other factors that should be docu- of changes that occur and assist in relocating the mented in the site description because they might plots. Mark the photo points on your site map. affect the outcome of the study. For example, the percent cover of major non-tree species that com- .. Describing the site monly invade to sites following disturbance should General site characteristics should be described for be listed if their presence could influence the results a field site even though they may not be identified of your experiment. Soil profile details could be as the primary factors under investigation. A site included if the experiment would benefit from this description should include the slope, aspect, eleva- information. If the site has been harvested, the de- tion, longitude and latitude, soil classification gree of soil disturbance should be quantified and

 . Installing and marking the research plots

Stakes

Weight: This factor is critical (unless few stakes are needed) if the site is inaccessible and materials have to be carried a long way. In rocky ground, thinner stakes are easier to install. On steep slopes, stakes usually get pushed over in the winter, especially where there is a lot of snow and/or vegetation. Use strong, slim stakes and pound them far into the ground to reduce this problem.

Visibility: Stakes should be taller than the tallest understorey vegetation, but short enough that you can reach the top to pound it in. Allow enough length to compensate for the amount that is pounded into the ground. Ensure the stakes are clearly visible by painting the tops bright, contrasting colours (white, fluorescent pink, orange, or blue; not yellow, green, or dull or dark colours).

Wood: Pros: relatively lightweight; broader surface more visible when painted; easy to attach labels; moderate cost. Cons: bulky; eventually rot; can split and break; may be harder to pound into the ground; greater surface area, more easily pushed over by snow.

Steel Bend the ends of rebar stakes to prevent injury to people and animals. Pros: compact, long-lasting reinforcing (but rust); relatively cheap; easy to pound into even rocky ground; can be relocated with a metal bar (rebar): detector. Cons: heavy; not very visible even when painted, difficult when rusty; harder to attach labels; <1 cm diameter can bend fairly easily; larger diameters (>1 cm) are too heavy (except for short stakes). Aluminum: Use either conduit or Y-beam. Pros: lightweight; visible when unpainted; strong (doesn’t bend easily), won’t corrode, can engrave plot information directly on so don’t have to attach separate labels; can be relocated with a metal detector. Cons: expensive (3–4 times cost of rebar).

12 field studies of seed biology  . Continued

Installation

Pound stakes until they are as steady as possible. Carpenters’ hammers (unless they have metal handles) break too easily. A short-handled 2 lb. (0.9 kg) sledge hammer is ideal because the handle is stronger and the head has a broader surface area. If topofil (hipchain) is used to measure distances, remove the thread after measurement because it can entrap birds and other small animals and kill them.

To form Use one rope to measure the length of two sides of the plot (marking the middle), and a second square plots: rope for the diagonal length. A tape measure can be used instead if it is long enough. Install the first stake. Measure the distance to the diagonally opposite stake and install. Measure the length of a side towards a third corner from each of the first two stakes. Where these meet, install a third stake. Repeat the last two steps to locate the fourth stake. Ropes with loops on the ends (one the diagonal length and the other the length of two sides with the middle marked) or two flexible fibreglass tapes can be used to make the measurements.

For circular Install a single stake in the middle of the plot. Use a rope the length of the plot radius to measure plots: from the centre stake to the plot boundaries and mark with flagging tape.

Labelling

Labels are essential if there is more than one plot in the installation. Identify the plot with a number code and other pertinent information. (See also Section 1.5.1.)

Washers: Stamp large washers (3.5 cm diameter with 1.5 cm hole) with plot numbers using a die set, then slip them over the rebar stakes. Pros: easy to use. Cons: eventually rust so much you cannot read the numbers; work their way into the ground and must be excavated; can slip off and be lost if the stake is pushed over in the winter.

Aluminum Can be wired, nailed, or stapled onto wooden stakes, or folded around rebar stakes and stapled. sheets: Pros: easy to engrave; won’t corrode; easy to see; can attach them to the tops of stakes (no exca- vating); easy to mold to stake. Cons: easily ripped by animals or vegetation rubbing in winter, etc.; sharp edges unless each edge is bent. Plastic or Can be purchased from engineering or survey equipment suppliers either pre-numbered or blank. metal tags: Some suppliers will engrave custom numbers on blanks. Pre-numbered plastic livestock ear tags are also available from agricultural suppliers. Plastic tags come in different colours but may break or fade over time. Metal tags are more durable but less visible. Use coated wire to attach tags to plot stakes, trees, etc.

Flagging tape: If resampling frequently (e.g., every 1 or 2 years or less), use plastic flagging tape on stakes. Use the most durable winter-weight flagging; although more expensive, it lasts much longer. Use fluorescent pink, orange, etc. (same as for paint) for the best visibility. A long tail of tape moving in the wind will catch the eye better than many short pieces and wrap-arounds. Biodegradable tape is not recommended as it is almost impossible to see. If sampling is infrequent, don’t bother with flagging; it is not very durable, and animals chew on it. Rely on painted stakes, photos, and good site maps instead. Felt pen on flagging tape is OK for temporary labelling purposes (about one year), but not for long term.

section 1 planning tree seed research in the field 13 documented using the methods prescribed in the entered into the SiteTools software (available from Forest Practices Code Soil Conservation Surveys Guide- Research Branch, B.C. Ministry of Forests) to obtain book () (Appendix C). an estimate of site index. When a stand is present on the site, then the de- When good top height trees are not present on the scription should include an estimate of tree species site, the site index can be approximated through a site composition based on basal area. This can be done series–site index correlation, by which a site index is using variable-radius sample plots. The basal area estimated from the site series present. This method is factor of the prism or relaskop and species of “in” generally less accurate than the tree-based estimates, trees are used to estimate species-specific basal area and should not be used if good top height trees can (British Columbia Ministry of Forests ). Rela- be found. Site series–site index correlations are not skops are used most commonly, but a set of prisms yet widely available, but may be found in the Minis- works as well and is less expensive (about $ instead try of Forests field guides for Nelson (Braumandl and of $ for a relaskop). Curran ), Prince Rupert (Banner et al. ), and Environmental conditions, such as relative humid- Vancouver (Green and Klinka ), and in the scien- ity, rainfall, hourly temperature averages, and daily tific literature (Green et al. ; Klinka and Carter maximum and minimum temperatures, can be ; Carter and Klinka ; Wang et al. ; monitored using on-site dataloggers. Note that Kayahara et al. ; Wang et al. ). First approxi- climatic data collected from standard weather sta- mation provincial correlations are available in draft tions may not be sufficient to accurately document form (Meidinger and Martin []). factors that affect flowering, pollen dispersal, cone opening, and seed maturity at the stand level. . Analyzing and Interpreting the Data Weather variables monitored several metres above the ground may not reflect the conditions within the The great tragedy of Science: crown, or on the north and south sides of a tree. In the slaying of a beautiful hypothesis by an ugly fact. some cases it may be useful to establish correlations (T.H. Huxley) to capture these relationships. For further discussion on these and related topics, refer to Section ., Data management, and Section ., Designing an environ- For many researchers, the most enjoyable (and chal- mental monitoring program. lenging) part of a study occurs after the data have been acquired and entered into the database. At the .. Site index data analysis and interpretation stage (Stage III) the The site index is commonly used in forestry to meas- relevance of research results must be recognized and ure site productivity. The site index is the average articulated. If the project has been well planned height of top height trees (unsuppressed dominant (including site selection, experimental design, and or codominant trees) measured at breast height age analyses), this stage is usually straightforward. How- . The more productive the site, the higher the site ever, unexpected things happen, and you may need to index. Site index can be obtained in at least two ways: manipulate and analyze the data in ways not initially from tree measurements or from the site series. To planned. For example, look for confounding factors obtain accurate tree-based estimates of site index, that may be influencing your results, or try grouping good top height trees should be present in the plot. your data differently and reanalyzing. A description of what constitutes good top height The value of reanalysis is best demonstrated using trees can be found in Forest Productivity Councils an example (D. Coopersmith, pers. comm., ). It of British Columbia () and Soderberg and Nigh also demonstrates how a detailed site description can (). These publications also detail the sampling later be used for other purposes. protocol. The total height of the tree and its breast Recently, an analysis was performed on perma- height age are required to estimate site index. This nent sample plots at the Aleza Lake Research Forest information and the name of the tree species can be in north-central British Columbia (lat °'N, long

14 field studies of seed biology °'W). The stand had been logged in the s .. Obtaining site approvals using diameter-limit selection (all trees larger than For sites in British Columbia, researchers are respon-  cm were taken, and smaller trees were left). The sible for obtaining the B.C. Ministry of Forests site was a very productive moisture-receiving site at district manager’s agreement for the location and the base of a long slope. It was also micromounded, purpose of the research. The district manager will probably from previous windfall events in the stand. want to ensure that the project can be accommodated Some of the spruce were as old as  years, so it within the objectives of the management plan for the was probably  or more years since this site had site. Researchers must adhere to the Forest Practices been burned. An initial examination of the tree Code of British Columbia; for silvicultural system data showed that basal area and volumes had not and natural regeneration trials, this may require increased since the last evaluation in . This amendment of silviculture plans and cutting permits. was surprising because some very large spruce and Plans normally must be filed at least  year in advance subalpine fir appeared to be growing very vigorously with the district office. For trials not affecting silvi- on the site. culture prescriptions, the district manager must be A second analysis was performed. This time the notified a minimum of  months before the proposed trees were separated into two classes: those growing research work. in the wetter hollows of the micromounds (charac- Before beginning any study on developed lands, terized by Equisetum); and those growing on the check with the local offices of major utilities to ensure drier mounds of the site. The results of this reanalysis that site activities will not disrupt water, electrical, or were dramatic: all trees in the hollows showed little gas services in the area. Field personnel should know or no growth (in fact, large numbers had died since the name and telephone number of the appropriate the last evaluation), showing that trees on these utility companies to contact in case of emergency. microsites had not contributed anything to basal area and volume in the stand, while those on the higher .. Registering field installations microsites were still growing vigorously and adding Some regional offices maintain a list of the objectives significant additional growth. By not differentiating and locations of all known research plots within the between these two microsite types, much of the story region. Researchers establishing research plots or of these plots was lost in the “noise.” installations on provincial Crown land must convey Researchers should consult a statistician before the site location and other pertinent information embarking on any of the more elaborate statistical to the regional research manager, as well as to the analysis methods to ensure the proper application of relevant district managers. the techniques. A protocol for plot registration and map notation has now been established for all permanent sample . Administration of the Research Site plots (psp) by the B.C. Ministry of Forests for the forest inventory mapping system (famap). Map Field research must always be undertaken with the notations are made on all mylars furnished to the knowledge and approval of the land owner and the forest districts. When a district is proposing a stand local land manager. In British Columbia, researchers treatment, such as thinning or fertilization, all district wishing to locate research sites on provincial Crown mylars are checked for the area of the proposed treat- land must follow the regulations and guidelines set by ment. This is how the forest district avoids treating the B.C. Ministry of Forests and other agencies. The well sites, archaeological sites, and research plots. steps outlined in this section are specific for research There is a standard procedure for getting informa- sites in British Columbia, but are similar to require- tion entered on the map mylars, such as a harvesting ments in other areas. Ensure that you contact the tenure or an experimental project (ep), usually by agencies with jurisdiction over the area you have providing a sketch map and documentation. Note, chosen and that you know and follow the appro- however, that the researcher is responsible for keep- priate regulations. ing track of sub-eps in the permanent research file.

section 1 planning tree seed research in the field 15 .. Security unlikely to be discovered by passers-by. If working For security purposes, the location of research sites alone is necessary, you should know and closely ad- must be on file with the applicable district, regional, here to policy guidelines of the forest management and licensee offices. Installations that will be repeat- agency, your employer, and your local authority. edly visited (i.e., more than once) should be registered In British Columbia, the safety of crews working on forest cover maps as either a map notation (coded in the field is governed by Workers’ Compensation on the forest cover map to notify users that an activ- Board (wcb) regulations and Industrial Health and ity is occurring there) or a map reserve (to reserve Safety and Occupational First Aid Regulations. Ensure the site from harvest within a specified time period). that you are aware of and comply with all the require- Map notations or reserves can be critical in saving a ments—only a few are highlighted here. Regulations site from disturbance or inadvertent damage. stipulate that a Level I first aid kit and someone with Experimental plots benefit greatly from having appropriate first aid training must be on-site. Specific signs posted on the site. This will keep out most of written procedures for transporting injured workers the public. At the minimum, the sign should state must be developed and be present at the field site “Research Site, Do Not Disturb. If you would like before operations begin. more information, please contact the nearest district office.” Locate valuable equipment such as meteoro- .. Using registered seeds logical stations so they are not visible from the road; In British Columbia, only registered seeds may this will lessen the possibility of equipment being be used for reforestation on Crown land (Forest vandalized or used for target practice. Practices Code, Silviculture Practices Regulation, Sec. ()(a)). This regulation also applies to forestry .. Safety research trials if the seeds will be planted on Crown Ensure that you know the radio and check-in proto- land. Refer to the Forest Practices Code Guidebook: cols for the district you are working in (see B.C. Seed and Vegetative Material or consult with district Ministry of Forests Research Branch Operating staff for current seed use guidelines. The Seedling Policies and Procedures). Planning and Registry (spar) system can identify Use radio or cellphone communication when available registered seed sources. Contact the district possible. Radios are essential on active logging roads. office for assistance with spar and other Code-related The forest district office or logging company can matters. (See Appendix C for resources.) supply you with radio frequencies, but they are also usually posted at the beginning of the road. The .. Making seed collections appropriate frequencies can be programmed into If the seedlings resulting from individual seed collec- radios by staff of the B.C. Ministry of Forests Techni- tions will not be planted on Crown land, the use of cal and Administrative Services Branch (for ministry registered seeds is not required. However, if you plan employees) or at most radio shops. In the field, call to collect your own seeds, you must obtain a cone your location frequently and monitor the location of collection permit from the district office in which logging trucks so you can pull over well before you the collections will be made. B.C. Ministry of Forests meet them. Logging trucks always have the right-of- researchers are not required to have a permit, but way. Always drive with your headlights on when on they are still encouraged to inform district staff of logging roads. their intention to collect cones. Report your destination and return time before any Anyone making seed collections is responsible for field trip, and check in during the day so that someone rigorously adhering to all precautions restricting the knows where you are and your next stop. B.C. Minis- use of climbing gear and collection equipment. In try of Forests policy advises against working alone in British Columbia, aerial operations are subject to the field and strongly discourages the practice. This wcb regulations, the helicopter company must be policy relates specifically to situations in which an certified, and the pilots appropriately qualified for employee is working in a remote area off paved roads, making aerial collections. Refer to wcb regulations, and may be unable to call for help if injured, or is Eremko et al. (), and Camenzind () for

16 field studies of seed biology additional information on the safety aspects of tree understanding draw these circles closer together. seed collection in British Columbia. Opportunities for sustainability increase when we manage so that these spheres can overlap. . Ecosystem Management Information is a primary resource, and as re- searchers, it is our major contribution; the success From time to time, it is beneficial for researchers to of adaptive ecosystem management depends on the stand back and view their research in the larger con- generation and transfer of our scientific knowledge text in which studies are conducted. By viewing (Bormann, Brookes, et al. ). Monitoring and studies of tree seed biology in the broader perspective research must be integrated with decision-making of ecosystem management needs, research results can processes to continually improve the scientific basis have a greater impact and enhanced value to society. of ecosystem management (Jensen and Everett ). Ecosystem management is a scientifically based Thus, it is critical that we allocate our efforts to bridge land and resource management system that integrates this interface between science and management. In a ecological capabilities with social values and eco- topical article, Larsen et al. () defined  principles nomic relations to help sustain ecosystem integrity of ecosystem management which provide useful guid- and use over the long term. In recent years, the term ance to ecosystem researchers to make their research adaptive management has been used to describe a projects relevant to management needs for informa- modified approach to managing ecosystems. One of tion. Not all research projects will be able to strictly the main distinctions of adaptive management is that adhere to these principles, but they provide a useful it emphasizes learning through conscious experimen- reminder of context for natural resource studies. tation, monitoring, and adjustment (U.S. Dep. Agric. For. Serv. b). . Management and research must deal with large The goal of adaptive management is to create and landscapes. The cumulative effects of processes that maintain sustainable ecosystems. To achieve the goal typically function at smaller scales, such as stand- of sustainability requires that we integrate both the level silvicultural treatments, can be observed only if human societal and economic needs and ecological we step back to take a wide-angle view of the forest. processes. This concept may be visualized by viewing Some important processes, such as patterns of forest the needs of society and the earth’s ecological capacity distribution or natural disturbance, can be observed as separate spheres (Figure .). Knowledge and only at the landscape scale.

 . Sustainability can only be achieved when the needs of society and the potential capacity of the earth we live in overlap. Learning draws these circles closer together and increases our opportunities and options for sustainability. (Adapted from Bormann, Cunningham, et al. 1994.)

section 1 planning tree seed research in the field 17 . We must be concerned with long time frames. . Researchers must share sites so that they can Just as the extent, structure, and condition of today’s integrate their findings and investigate change in forests have been determined by harvesting practices each ecosystem component over many different that took place a century ago, so the impact of the spatial and temporal scales. Agencies must make current management activities will persist at least a long-term commitments to maintain research sites century into the future. as well as to fund basic site measurements. The mar- ginal cost of additional projects is quite low as long . We must consider both where and when we create as a base level of measurements exists. a disturbance. Important spatial and temporal com- ponents are associated with any forest management . We must simultaneously focus our collabor- activity or any natural disturbance. If, for example, ative research efforts on real landscapes. We w ill our management activities will disturb large areas in increase our understanding of the interactions and a given landscape over the next century, it makes a trade-offs only when experts from many fields apply difference whether the affected areas are contiguous their collective wisdom to the same piece of land or dispersed, and whether the disturbance occurs in a over the same time frame. Purely theoretical ap- single year or is spread over the full century. proaches to ecosystem management research have great merit, but ultimately the evaluation must be . We have enough scientific knowledge to start in the field. managing ecosystems, but we will never fully under- stand all aspects of forest ecosystems. We know a . We must remember that people are part of the great deal about some parts of forest ecosystems and ecosystem. Human activity has left an indelible mark at least a little about most parts; a prudent approach on our forest resources, and ultimately, it is people is to begin by using the best science we have available who decide which forest practices are acceptable. now, while we continue with our research. Our role as scientists and practitioners must be to: (a) identify and discourage those activities that will . We must synthesize the results of research that likely cause short-term or long-term ecosystem address many different ecosystem attributes and degradation, (b) clarify the trade-offs among many processes. We must combine what we know about acceptable management alternatives, and (c) identify ecosystem components and ecosystem processes to and encourage the alternatives that will most likely arrive at a more complete understanding of how eco- produce the desired outcomes. systems work and how they respond to disturbance. Synthesis also serves to identify the major gaps in . Summary our knowledge. A long-term experiment whose sole sponsor has left, . The complexity associated with ecosystem died, or lost interest is a sad orphan, management is so great that we must employ and adoption is seldom quite successful. mathematical models. Tracking details, measuring (Dyke ) interactions and trade-offs, dealing with long time frames, dealing simultaneously with many species, and mapping the results—all require the use of Planning constitutes the major activity associated computer models. with field studies, and may even take longer than the study itself. Care is needed in defining the experi- . We must facilitate cooperation and collabora- mental protocol, data management, and reporting tion. The complexity of forest ecosystems requires routine. Good plans are especially critical when the the attention of teams of scientists and managers main investigators are not readily available at all representing a wide range of expertise. times during plot establishment and site selection.

18 field studies of seed biology Flexibility is also required, and possible modifications The role of a scientist in the ecosystem manage- should be considered even while the study is being ment model is to provide information for the conceptualized. The plan must try to anticipate some decision-making process. Such information helps level of uncertainty and be flexible enough to cover to identify the current status of an ecosystem as unexpected conditions in the field. Change is inevita- well as potential options for addressing the social, ble, and consideration of alternative approaches during physical, economic, and biological issues (Haynes et the design stage will help to focus the planning effort al. [technical editors] ). This information helps and secure long-term success of the project. clarify feasible limits, options within the limits, Field experiments require sustained commitment consequences of those options, and trade-offs by the scientific staff so that the study will reach its between options. It is the role of the decision-maker full potential. Sustained commitment by funding to choose among options; it is not the role of science. organizations is also essential to maintain stability. The challenge for resource managers is to balance Finally, the information needs urgently required biological science with social science and with the by natural resource managers necessitates that the philosophical views of how society values renewable results of field studies reach the end user as quickly and nonrenewable natural resources (Haynes et al. and as accurately as possible. [technical editors] ).

section 1 planning tree seed research in the field 19 SECTION 2 DESIGNING AN ENVIRONMENTAL MONITORING PROGRAM

Every raincloud, however fleeting, leaves its mark, not only on trees and flowers whose pulses are quickened, and on the replenished streams and lakes, but also on the rocks are its marks engraved … (John Muir “Gentle Wilderness, the Sierra Nevada”)

. Background and frost-free period. Wind speed and direction are available for a few locations. For some parts of British Environmental and site factors influence the produc- Columbia, annual temperature and precipitation tion, dispersal, survival, longevity, and germination summaries by subzone can be obtained from the of tree seeds. Researchers must have a general under- biogeoclimatic ecosystem classification database standing of the effects of various environmental (see Appendix C). factors to select the most suitable location, time Site climate and site weather conditions involve frame, experimental techniques, and types of sensors on-site measurements of air and soil temperature, for field studies. The nature of these factors and the precipitation, humidity, wind speed and direction, overall objectives of the study will also determine solar radiation, and soil moisture. Monitoring usually which environmental variables should be measured, requires an electronic datalogging system. Weather and how frequently. data may only be needed for a short time during an Environmental variables such as temperature and event of interest (e.g., pollen release); in this case, precipitation may be considered in the context of you may need hourly rather than daily summaries. long-term average conditions, as ranges and extremes However, to characterize the climate (averages and (climate), or as day-to-day conditions (weather). Fur- variation), – years of data collection are required. thermore, environmental variables can be viewed at These data should be referenced to the nearest three scales: macro (or regional) weather, site weather, long-term weather stations to determine how and tree weather. The complexity involved in obtain- different the period being measured may be from ing data increases as we go from macroclimate to tree the “normal.” weather. Tree weather describes conditions in cones or Macroclimate and synoptic weather conditions can flowers, or beside germinating seeds. Small, delicate be obtained from the nearest Environment Canada or sensors, such as thermocouples, are usually required other government-operated weather stations, and to make these measurements. Variables of interest in may be adjusted for the elevation of the site of inter- regard to tree weather are temperature, radiation est. Usually, climate data are summarized as monthly balance, and soil moisture (for germination). The or annual values and include average, maximum, data can be used to develop physically based models minimum, and extreme values for temperature, total or regression models of tree conditions as a function precipitation, and derived data, such as degree-days of site conditions.

section 2 designing an environmental monitoring program 21 . Designing an Environmental Monitoring Program

In designing an environmental monitoring program for a research site, you must first decide which vari- ables you need to measure. For field germination studies, near-surface (– cm depth) soil temperature and soil moisture are the important variables. How- ever, soil temperature and moisture will be affected by a variety of other environmental variables. Soil temperature, for example, depends on soil moisture, solar radiation, wind speed, air temperature, soil tex- ture, and surface colour. On the other hand, surface soil moisture depends on rainfall, solar radiation,  . Climate station with wind direction and wind evaporation, vegetation cover (transpiration), soil speed sensor, a rain gauge (lower right), and texture, and soil temperature. The humidity of the tower with solar radiation, air temperature, and air and solar radiation can critically affect the initial humidity sensors. A robust tower is required at establishment of germinants through its effects on this site to support the large precipitation soil evaporation and plant transpiration. Humidity gauge used for winter snowfall measurements. also affects seed production through its effects on pollination. Slope and aspect affect temperature and however, is that you may be able to demonstrate dif- moisture because they influence the solar radiation ferences between treatments only when they are large. and rainfall reaching the surface. Wind is of interest Whatever the means of recording data, the com- primarily for studies of seed dispersal (see Section ). plexity of environmental factors and their interactions The frequency of environmental measurements necessitates careful planning of all field measurements. will vary depending on the type of measurement. Four steps to developing an environmental monitor- Light and temperature can vary rapidly and thus ing program are illustrated here using an example of require frequent monitoring. Relatively stable site a study to determine conditions that initiate flowering. factors, such as soil type, soil pH, presence and type of duff layer, biogeoclimatic zone, elevation, slope, . Why do you need environmental data? and aspect, may need only to be measured once. To determine weather conditions that initiate Researchers sometimes rely on environmental flowering, and their variation from year to year. data from the nearest weather station to provide data such as rainfall and daily minimum and maximum . What data are needed? temperatures, but if the microclimate of the site Air and bud temperatures and solar radiation, from is significantly different from that of the weather bud initiation through flowering (over  months or station it is advantageous to set up a small weather more). The year-to-year variation could be obtained station at the site (Figure .). Dataloggers can be by monitoring for many years, or by calculating used to continuously record a variety of environmen- regression equations that are based on weather data. tal variables (Figure .). Spittlehouse () provides Site weather conditions could be related to the near- guidance on using dataloggers in the field and the est long-term weather station to provide the data accuracy that can be expected from such measure- that would be needed to drive the model. Ideally, a ments. While it is tempting to collect large amounts physically based model of bud/flower temperature of weather data on the assumption that somehow as a function of site weather conditions and bud they will be useful, a few days of manual measure- characteristics should be developed to allow porta- ments under a range of weather conditions may be bility to other sites with a minimum of calibration. just as effective as installing electronic dataloggers Both methods require – years of on-site data for on the site. The disadvantage of manual sampling, development and validation.

22 field studies of seed biology . Methods for Measuring Environmental Factors

.. Soil temperature Near-surface soil temperature (– cm depth) can be easily measured, but measurements must be adequately replicated. Soil temperature varies substantially, not only horizontally and vertically, but temporally as well. Individual locations can be averaged by using a series of thermocouples connected in parallel. Data- loggers are a convenient way to monitor the number of sensors required to assess the spatial and temporal variability. The diurnal trend of the near-surface temperature parallels the diurnal course of solar radiation; thus a reasonable approximation of the daily maximum temperature can be obtained by making the measurement about an hour after solar noon. An estimate of solar noon in your area is avail- able on the Internet at http:/www.crhnwscr.noaa.gov/ grr/sunlat.htm. The average near-surface soil temper-  . Electronic datalogger used to monitor and ature (during the summer) can be approximated by capture data from a series of environmental measuring at about  a.m. solar time ( hours before sensors. The datalogger is housed in a solar noon). A comparison of treatments with this waterproof box (shown open) and data are approach requires that measurements be made under routinely retrieved using a portable computer. the same weather conditions. This manual sampling This datalogger can monitor many sensors at method will only be useful for showing differences once; less expensive dataloggers are available ° that will monitor only one sensor. larger than C and should only be used to give an idea of trends. Shade can significantly reduce solar radiation, . What needs to be done to get the data? resulting in a corresponding decrease in the near- Is continual monitoring necessary, or is a short-term surface temperature. On the other hand, shade also manual measuring program adequate? Fine wire reduces night-time cooling. When solar radiation thermocouples are needed in the buds to measure is reduced by over %, the surface temperature temperature; they are sensitive and inflict minimal can be approximated by the air temperature at damage. The site may need frequent visits to ensure . m above the ground. For more information that bud temperature sensors have not been on forest soil temperature, see Stathers and disturbed. Spittlehouse ().

. Can the work be done physically and what .. Soil moisture does it cost? There is no easy way to obtain good soil moisture Is the site readily accessible, and are equipment and measurements, and the difficulty increases as one personnel available? A datalogger-based monitoring gets closer to the surface. Gravimetric sampling and system would cost $ to $. Installation requires time-domain reflectometry (tdr) measure soil water – days depending on the number and location of content (Hook et al. ), but further work is re- sensors, and monthly site visits are required to check quired to develop tdr probes and techniques. tdr equipment and collect data. At least  day per month requires substantial replication, and although it is should be allowed per site for data processing and usually done manually, it can be automated. Water analysis—an important consideration that is content can be converted to soil water potential (or often overlooked. tension) using a soil water retention curve obtained

section 2 designing an environmental monitoring program 23 from undisturbed soil samples analyzed by a com- Radiant flux density is the energy in the light emit- mercial soil physics laboratory. ted, transmitted, or received per unit area (W/m2). Gravimetric sampling is labour intensive and Irradiance is the radiant flux density incident on a destructive. Some – replicates at each depth of surface; emittance is the radiant flux density emitted interest are required. It is best to use a sharpened by a surface. metal tube to take a soil core of known volume, The units and the instruments used for light rather than a grab sample. The sample is sealed in measurement will depend upon the intent of the plastic bags, and returned to the laboratory for study. Some radiometers (for example the li-cor weighing and drying. Gravimetric samples are pre- model li- radiometer) can be fitted with a variety sented on either a weight of dry soil or a volumetric of sensors to measure irradiance. A quantum sensor basis. The latter is the common approach and can be is used to measure photosynthetic photon flux den- converted to soil water potential (or tension) using a sity (ppfd) or par. A pyranometer (or radiometric soil water retention curve. sensor) is used to measure solar radiation. Photomet- Gypsum or fibreglass soil moisture blocks can be ric measurements using illumination units (lux or used to measure soil moisture potential (or tension) footcandles) should not be used in plant studies. in the  to -. MPa ( bars) range; they can be read Plants do not respond to the light spectrum in the manually or with a datalogger. Moisture blocks pro- same way as the human eye, so such measurements vide relatively coarse resolution, and require testing have no value unless the characteristics of the light over several drying cycles before installation. They source are precisely known (Salisbury and Ross ). may have poor contact with substrates such as par is usually the radiation measurement made when coarse sandy soil or partially decomposed organic assessing physiological responses such as plant produc- material and cannot be used at soil depths shallower tivity (although other wavelengths may have specific than  cm. photomorphogenic effects such as the induction of Tensiometers measure soil water potential in the flowering or cold hardiness). par is commonly meas-  to -. MPa (. bars) range. They are usually read ured in units of µmol • m-2 • s-1. Special sensors are manually but can be automated. As with moisture required to measure ultraviolet radiation, and various blocks, they cannot be used at depths shallower than filters are available that modify sensor output to  cm. Soil water potential can also be obtained by match the biological response of tissue. Longwave equilibrating soil samples with the air or filter paper radiation sensors are not easy to use, so longwave in a sealed container, then measuring the humidity estimates are usually obtained by subtraction of solar of the air or filter paper. In situ measurements of soil radiation from total radiation measurements (see water potential using soil psychrometers or hygrom- Black et al. ). eters is extremely difficult, particularly in the top The controlling influence of vegetation on the  cm of the soil. Further information on measuring light regime will render a shaded surface more moist soil moisture can be found in Schmugge et al. (). and cool than a bare surface. The amount of direct cover over the study area, the distance from the edge .. Solar radiation (light) of openings, and the aspect of the edge will influence Three ranges of the radiation spectrum are usually the light regime in openings. These influences can be considered when assessing the light regime at the estimated from measurements of above-canopy light earth’s surface: ultraviolet radiation from  to and the amount of cover. When measuring irradiance  nm, photosynthetically active radiation (par) under a plant canopy with uneven light levels, rea- from  to  nm, and solar radiation from  to sonable averages can be obtained by moving a small  nm. Radiation above  nm is called longwave sensor repeatedly along a track (Figure .), by using or thermal radiation. Different sensors are required a long linear sensor, or by using many spot sensors. to measure each of these bands of energy. There is a It is generally best to spend some time generating good correlation between the energy in each band radiation interception curves with an intensive meas- both above and below the canopy (Yang et al. ; urement program over a short period. These curves Alados et al. ). are used with continuously monitored above-canopy

24 field studies of seed biology reaching the forest floor passes between needles and other gaps in the canopy. Consequently, the change in the shape of the spectrum is not as great as in hardwoods where more radiation passes through the thinner leaves. The biggest change is in the in- crease in the ratio of red (– nm) to far-red (– nm). It changes from .–. under clear skies above the canopy to .–. under hardwood forest canopies, and to .–. under coniferous canopies. Light quality—the incident light spectrum—af- fects the germination of many conifer seeds (Section     . Automatic tram system that moves back and . . ) and the production of female cones (Durzan et  forth over a 50 m span to determine the al. ). For measurement of irradiances under for- variation in short- and longwave radiation, est canopies, see Black et al. () and Yang et al. and surface and air temperature under a forest (). The measurement of the total light spectrum canopy. The system is controlled by the datalogger in the tube hanging on the end. (System designed by R. Adams, B.C. Ministry of Forests.) radiation to give below-canopy data through the year. The variability or patchiness of the canopy may indicate that there is a range of light environments that must be quantified separately. Radiation rapidly decreases as canopy cover increases. The interception curve is of the form

(-KC) I = Ioe ,

where: I = the radiation at the forest floor,

Io = the radiation above the canopy, C = percent canopy cover (range –), and K = an extinction coefficient (range .–.).

Shaded and sunny areas of small openings and clear- cut edges can be determined using the formulae for length and direction of tree shadows at different  . Influence of forest canopy on the intensity and times of the day and year (Sit a). spectral distribution of solar radiation reaching Forest canopies change the quality as well as the the forest floor. The upper panel shows the intensity of light reaching the forest floor (Vezina and incident radiation from a clear sky during the middle of the day. The lower panel (note the Boulter ; Atzet and Waring ; Ross et al. ; difference in scale) indicates that pine and Messier et al. ). Figure . illustrates how the maple canopies have greater absorption in the spectral distribution is changed due to plant foliage middle range (400–700 nm) than in the near differentially absorbing and reflecting the various infrared range (700–750 nm). (Based on data wavelengths. The relatively thick needles of coniferous in Federer and Tanner 1966 and Vezina and trees transmit very little radiation and most radiation Boulter 1966.)

section 2 designing an environmental monitoring program 25 at a site requires a portable spectroradiometer. Both .. Air temperature and humidity Atzet and Waring () and Floyd et al. () con- A hygrothermograph in an instrument shelter ducted spectroradiometric analyses to determine the (Stevenson Screen) located on the study site can light-filtering capacity of coniferous forests. However, record air temperature and relative humidity for up the changes in light quality can simply be measured to a month before the chart requires changing. Elec- with a portable red:far-red meter, since most of the tronic temperature and humidity sensors can be canopy effects are due to the canopy cover shifting placed inside the Stevenson Screen. Smaller shields the ratio of red to far-red light. can be built or are available commercially, but some commercial varieties overheat under low wind .. Wind speed and wind direction speeds. Spot measurements can be made using Wind, acting either directly or by wind-induced aspirated or sling psychrometers. vibration, plays a major role in the distribution of pollen and seeds. Seeds of some species are very .. Plant temperature responsive to updrafts or vertical air movements (see Obtaining temperature measurement in cones and Section ..). Wind speed is a vector quantity with buds requires extremely small sensors. Thermocouples attributes of direction and magnitude, although only (Figure .) are the best option, being more robust and the horizontal component is usually measured. Cup or easier to make than thermistor or platinum resistance propeller anemometers are generally used to monitor sensors. They are best monitored with a datalogger. wind speed. They can be connected to a datalogger or Surface temperature can be measured using an infra- have their own display. Many ane-mometers come red thermometer with a narrow field of view. with a wind direction indicator. Topography and veg- etation cover affect wind speed and direction and .. Canopy cover care must be taken in locating the anemometer and Canopy cover is the environmental factor most im- wind vane. The sensors should be located – m mediately affected by forest harvesting activities and above vegetation canopy and away from clearcut by silvicultural practices (see Section ). It signifi- edges. Robust anemometers usually have stall speeds cantly affects the microclimate of a site, influencing of . m s–1 or greater. Low stall speed anemometers the solar radiation, air and soil temperatures, wind are required if you are interested in conditions at the speed, humidity and rainfall experienced at the edge of a clearing, in a small opening, or below the ground (Hanley ). Canopy cover is also impor- canopy. Hot-wire anemometers (commercial or tant because the position of vegetation within the home-made) can be used to measure wind flow canopy is used as a criterion for the relative domi- around cones and flowers, but they are delicate and nance of individuals within a plant community easily damaged. They can be monitored manually or (Section ..). with a datalogger. A discussion of wind dynamics and instrumentation can be found in Pearcy et al. ().

.. Precipitation Rainfall can be reliably measured with tipping-bucket or storage gauge. The gauge should be located in an opening where a line projected from the top of the gauge to the top of the surrounding vegetation has an angle of no more than ° to minimize any shading effects. Snowfall cannot be measured with a standard  . A fine wire thermocouple is used to measure tipping-bucket gauge. Although gauges that melt the the temperature inside the leader of a young snow and can be monitored with a datalogger are spruce tree. The thermocouple is monitored available, they are expensive. A low-power, reliable with a datalogger, as are the accompanying sensor that measures the depth of snow on the environmental sensors. The same technique ground can be used in conjunction with a datalogger. can be used to measure cone temperature.

26 field studies of seed biology Canopy cover is often expressed as a percentage and Brown  for a sample layout). The length of value, usually by species, growth form, or canopy the canopy intercept of each species along the line is stratum; in a dense or multilayered community, total measured from the tape or with a ruler. If the cano- vegetative cover may exceed %. The method pies overlap in layered vegetation, it may be desirable chosen to measure canopy cover depends on the to measure each height layer separately. Transect lines available technology and the type of site; some should be – m in length. Many short lines are methods are suitable for low herbaceous vegetation generally preferred to a few long lines; – transects or clearcut areas, while others are designed for are usually required for an adequate sample. Several forested areas. Bunnell and Vales () present a cover values can be calculated: comparison of different methods of measuring forest canopy cover. percent cover for each transect by species = Many researchers obtain percentage cover of length intercepted by a species × ; different species and canopy layers with the visual- transect length estimation technique (Mueller-Dombois and Ellenberg ). Cover can be estimated to the nearest percent cover of a species by sampling unit = percentage point or to the nearest th or th percen- sum of all transect lengths intercepted × . tile. Cover estimates may be restricted to the plots total transect length sampled being studied for germination or other responses, or may be used for more general descriptive purposes While this method is generally precise and accurate (such as describing the study site, Section .). The (Cook and Stubbendieck ), it can also be time visual-estimation method is especially suitable for consuming. grasslands or clearcuts, because of the low profile of the vegetation. Plot size for cover estimation averages about . m2 (either circular or square), but may be smaller when working in exclusively herbaceous veg- etation, or larger when working with tall shrubs and trees. A good guideline for plot size is that plot diam- eter should be approximately equal to the height of the vegetation being described. Visual estimates are subject to personal bias, thus human error will introduce variability into the data (Bunnell and Vales ). This can be checked and corrected (calibrated) by other people working on the same project. It is also useful to have examples of how different spatial arrangements affect one’s per- ception of canopy cover. Figure ., for example, compares different spatial arrangements of % canopy cover. These kinds of comparisons are espe- cially useful when observers are not experienced in canopy estimation methods. Canopy cover can be measured more objectively using a line-intercept method, which is suitable for woody plants, shrubs, and trees (Chambers and Brown ; Habitat Monitoring Committee ). A line or tape measure is stretched tightly across the  . Different spatial arrangements comprising vegetation between two stakes. The best sampling 50% canopy cover. Some experience may procedure is the stratified-random sample using a be needed to estimate different proportions baseline and perpendicular transects (see Chambers of cover.

section 2 designing an environmental monitoring program 27 Objective measurements of canopy cover can canopy cover. It is measured by sampling the foliage also be obtained with a point-intercept method or by using light penetration techniques (Gholz et al. (Owensby ; Levy and Madden ) or point- ; Smith et al. ; Fassnacht et al. ; Chen ). quadrat method (Chambers and Brown ). These In the former method, all the foliage in the shrub and methods use a point- or pin-frame, often consisting herb layers is removed from – samples of known of  pins spaced  or  cm apart, with pins posi- area (usually  m2). The area of the leaves is then tioned vertically or at an inclined angle. The frame is measured using an image analyzer. All the leaves from positioned randomly within the sampling units or a tree (or from a representative branch in each whorl) along a transect and a single pin lowered towards the are sampled and leaf area measured with an image ground. The first strike of any part of the vegetation analyzer. Trees of different diameter at breast height canopy becomes a “hit.” Each “hit” is recorded by (dbh) are sampled to produce a dbh/leaf area rela- species or growth-form (Chambers and Brown ). tionship (or sapwood cross-sectional area/leaf area) The sample size required for statistical adequacy is which is then used with stand dbh distribution to usually – pins. Several cover values can be calculate tree lai. Leaf area can be determined using derived from this information: percentage canopy light sensors such as the ceptometer and the lai-. cover for each species or life-form (Chambers and Both measure the “effective” leaf area and must be Brown ); percent total canopy cover; and percen- corrected for leaf clumping to get the true leaf area tage vegetation cover by species. The user should be index (Smith et al. ; Fassnacht et al. ; Chen aware that the line is the sample unit, so it is better ). These sampling techniques can be used to to have fewer points per line and more lines, rather determine how leaf area changes with height and than vice versa (Bonham ). The frame should to calculate foliage area density. be held vertically; if the frame is at an angle, the The canopy can be photographed from ground number of intercepts may increase and overestimate level using a camera fitted with a hemispherical or the cover. fisheye lens with a ° field of view. Film exposure In woodland areas, other instruments such as the must be standardized (Chen et al. ).The resulting moosehorn and the spherical densiometer are fre- photographic negatives, prints, or slides can be digi- quently used to measure tree canopy cover (Lemmon tized, and then analyzed by a computer program to ; Bunnell and Vales ). The moosehorn is a accurately measure canopy cover above the point of point-intercept method where the canopy is viewed measurement. Available computer programs include through a screen and coincidences between vegeta- solarcalc (Chazdon and Field ), gli (Canham tion and dots on the screen are tallied. The spherical ), sunshine (Smith and Somers ), and densiometer has a curved mirror with a grid that hemiphot (ter Steege ). This photographic reflects the overstorey at a particular point, then method is suitable in herbaceous, scrub, forested, or provides an estimate of the relative amount of the mixed cover, but has the drawback that considerable grid covered by vegetation. At each location, four office time is required to obtain cover estimates. readings (facing north, east, south, and west) are These same programs also model solar radiation recorded and averaged. input for the point at which the photograph was A canopy analyzer uses measurements from a taken (see Section ..), but the cover estimates fisheye optical sensor placed above and below the require fewer assumptions. plant canopy; in this way canopy transmittance data can be used to calculate the leaf area index and the .. Soil variables mean leaf inclination angle (Chen et al. ; Welles Soil nutrient levels are important because they affect and Norman ). The canopy analyzer functions in seed production, germination, and seedling growth. a variety of sky conditions, with overcast being the Three principal methods are used to diagnose nutri- best; the instrument can be used in canopies ranging ent deficiencies: deficiency symptoms, soil chemical in size from short grasses to forests. analysis, and foliar analysis. (For other methods see The area of leaf per unit area of ground (leaf area Morrison .) Soil chemical analysis has some value index - lai) is another measure used to quantify for diagnosing site nutrient status on sites where

28 field studies of seed biology foliage sampling is impractical. There are major Oxygen is usually a limiting factor only in water- problems with conducting soil chemical analysis in logged soils, where water may fill pore spaces. Oxygen forest soils. Typically, the root zone is not homogene- is difficult to measure in the field, but under suitable ous, often containing dissimilar horizons that may conditions, an oxygen electrode may be used. This yield different analytical values. Nutrient standards technique uses glass electrodes that are delicate and for forestry soils are not available, and criteria cannot easily broken, and is not generally suitable for field be extrapolated from one kind of soil to another. It studies. It is primarily designed for laboratory can be problematic to integrate these disparate results studies, but can be set up and operated adjacent to a to determine the nutrient status of the composite study site. A key requirement is constant-temperature soil profile. water, obtained from a thermoregulated circulator The high variability of some soils may require a or a large-reservoir flow-through system. Some large number of samples. The most useful routine instruments can be configured to determine oxygen soil chemical analyses for forest soil fertility in indirectly by heating the sample in a stream of inert B.C. are likely to be: pH, organic carbon concentra- gas and converting all oxygen-containing gases to tion, and total nitrogen concentration (Watts carbon monoxide or carbon dioxide. Refer to Pearcy [editor] ). et al. () for further information on such methods.

section 2 designing an environmental monitoring program 29 SECTION 3 NATURAL SEED PRODUCTION

O sweet spontaneous earth how often have the doting fingers of prurient philosophers pinched and poked thee , has the naughty thumb of science prodded thy beauty . (e.e. cummings)

. Background of seeds also tends to be poor (Edwards ; Caron and Powell a, b). Depending upon the The path to the production of a viable seed begins species, conifer seed production varies in length and with the growth and development of reproductive complexity of the production cycle (Figure .), repro- buds, continues with pollination and fertilization, ductive success (due to different sexual mechanisms), and ends with embryo development and seed matu- and the timing of natural seedfall (Zobel ). ration. Throughout all these developmental stages The reproductive structures of trees are derived losses occur for a variety of reasons; losses may be from reproductive buds. The time of initiation of due to environmental factors, or may result from male and female reproductive buds can vary from various diseases and animal predators that attack year to year due to factors such as the relative abun- cones and seeds. Researchers investigating tree seed dance of seed trees (trees/ha) (Smith et al. ) and production must be able to assess which and to what tree age (Caron and Powell b). Natural seed pro- extent these factors limit natural seed supplies. duction is rare in trees younger than  years. Angiosperms characteristically produce seeds an- Generally, the volume of seeds produced increases as nually, but production can vary considerably from the tree ages. Bergsten (), however, found no bio- year to year (Table .). Most conifers do not produce logical differences between mature Scots pine seeds collectable crops every year (Table .), a phenomenon obtained from young stands and those collected from called periodicity. Mature cones are produced at in- old stands. Environmental conditions, such as tem- tervals ranging from  to  years, and sometimes as perature, drought (Eis a, ), and nutrient infrequently as every  years. Crop yields vary in availability (Heidmann ), affect reproductive bud different years, and in poor crop years, the quality production. Environmental stresses can reduce the

section 3 natural seed production 31 1 year 4 years 1 year 2 years 2–4 years 1 year 1 year ); Wyckoff and Zasada ); Wyckoff 2 (1 / samara); no endosperm 50–100 seeds / cone no endosperm angled 20 hard, seeds + endosperm Numerous no endosperm 1–2 / stone; + endosperm 1 / samara + endosperm 3–5 carpels 1–2 seeds / carpel + endosperm Numerous; no endosperm Numerous; no endosperm Paired winged seeds Paired 3–6(samaras); cm long cones (2Brown cm) winter; over remain winged oval, contain nutlets Orange-red berry-like (1 finely surface cm), granular with wings Nutlets broader than body ofClusters bright red (1“berries” cm); globular ovoid or drupes samara Paddle-shaped, (3–5 cm) in large on female trees clusters small reddish to Yellow (10–15 mm) fleshy pomes not capsules; 2-valved hairy hairy green Round, that split into capsules 3 parts; seeds covered with fluffy hairs white Seeds Interval Ripen Sept–Oct;Ripen disperse Oct–Jan Aug–Sept; Ripen disperse Aug–spring Fall Aug–Sept; Ripen disperse Aug–spring late Ripen summer/fall Late summer/fall Late fall June–July May–July Appear with orAppear leaves before (Apr–May) previous Male, fall; female, Feb–May Apr–May previous Male, fall; female, Apr–June in Always in spring; often fall before Appear leaves Apr–June Apr before Appear (Apr– leaves June) Greenish yellow (3 yellow Greenish mm in numerous across); hanging cylindrical cluster; in male and female partsdifferent of crown male reddish Drooping catkins (5–12 female cm); cones woody catkins are (2 cm) urn-shaped (7White, mm), clusters in large drooping and flower staminate Male (2–4 strobile female cm); up at maturity break Small (3 mm) white in surrounded tight clusters bracts showy 4–6 white by (2–7 cm) Small (3 mm) male and female (yellowish) in flowers (greenish) twigs on clusters bunched pink fragrant to White (2blossoms 5–12 in cm); clusters flat-topped catkins and female Male catkins (2–3Male cm) with 40–60 stamens/ catkins female flower, (8–20 cm) with 3 stigmas/ flowers Monoecious; imperfect flowers Monoecious Monoecious; flowers perfect Monoecious Monoecious; flowers perfect Dioecious Monoecious; flowers perfect Dioecious Dioecious ssp. ssp. [1998]; Zasada et al. [1998] Seed production characteristics of hardwoods native to British Columbia. Sources: Schopmeyer (1974); Pojar and MacKinnon (1994 native to British Columbia. Sources: Seed production characteristics of hardwoods balsamifera balsam poplar trichocarpa black cottonwood bigleaf maple alder red arbutus paper birch dogwood Pacific ash Oregon crab apple Pacific Common nameCommon type Tree (description) (month) (month) (description) seeds/fruit crops Species Flowers Flowers mature Fruit # Average between  .  Alnus rubra Alnus menziesii Arbutus Betula papyrifera Cornus nuttallii latifolia Fraxinus fusca Malus balsamifera Populus balsamifera Populus Acer macrophyllum Acer

32 field studies of seed biology 4–5 years 2–3 years Good crops withalternate poor 2–7 / capsule; 77– 2–7 / capsule; 500 seeds / catkin no endosperm 1 / drupe 1 / acorn; cotyledons only, no endosperm seeds / 2–3 nutlike drupe + endosperm 14–18 seeds / capsule 5–7 seeds / capsule; 144–311 seeds per catkin 8–12 / capsule 15–36 / capsule 12–20 / capsule Catkins of tiny, greenish Catkins of tiny, with covered capsules down cottony Dark drupes (1 red cm) (2–3Acorns cm) in scaly cups shallow, round Purplish-black, berrylike drupe capsule 2-valved Small, hairycontains seeds 24–48 capsule; 2-valved capsules/catkin capsule 2-valved capsule 2-valved capsule 2-valved capsule 2-valved Seeds Interval May–June July–Sept Aug–Dec July–Sept July May–June May–June June–Aug May–July Apr–May Apr–June Feb–May Apr–July May–June Apr–June May May–July Apr–May Apr–June Male catkins (2–3Male cm); female catkins (4–10 cm) pinkish 5–10 white to (10–15flowers cm) in flat- topped cluster inconspicuous Tiny in hanging male, flowers; single or catkins; female, in small clusters ofLoose 5–12 tiny, clusters yellowish-green flowers Staminate catkins soft, silky Dioecious Monoecious; flowers perfect Monoecious Monoecious Dioecious Dioecious Dioecious Dioecious Dioecious Dioecious (Continued) ssp. quaking aspen cherrybitter Garry oak cascara peach-leaf willow willow Bebb’s pussy willow sandbar willow lasiandra willow Pacific willow Scouler’s Common nameCommon type Tree (description) (month) (month) (description) seeds/fruit crops  .  Species Flowers Flowers mature Fruit # Average between Populus tremuloides Populus Prunus emarginata garryanaQuercus purshiana Rhamnus Salix amygdaloides Salix bebbiana Salix discolor Salix exigua Salix lucida Salix scouleriana

section 3 natural seed production 33  . Seed production characteristics of conifers native to British Columbia (Eremko et al. 1989). (Cones refer to female cones only.)

Cone Cone- Years Viable seeds Position of Ease of Species length bearing age between per hectolitre cones in cone Common name (cm) (years) crops of cones crown detachment

Abies amabilis 9–13 20 2–3 30 389 Top ¼ Difficult amabilis fir Abies grandis 5–12 50 2–3 50 776 Top ¼ Difficult grand fir Abies lasiocarpa 6–12 20 2–4 40 582 Top ¼ Difficult subalpine fir Chamaecyparis 0.5–1.5 Unknown 4 or more 93 965 Throughout Easy nootkatensis yellow-cedar Larix laricina 1.5 40 3–6 32 000 Non-shaded Moderate tamarack part of crown Larix occidentalis 2–3 25 1–10 119 312 Non-shaded Moderate western larch part of crown Picea glauca 3–6 40 6 347 163 Top ⅓ Moderate white spruce Picea mariana 2.5 10 4 or more 108 000 Top ¼ Difficult black spruce Picea sitchensis 5–10 25–40 3–4 194 270 Top ⅓ Moderate Sitka spruce Pinus albicaulis 3–8 20–30 3–5 515 Throughout Difficult whitebark pine Pinus contorta 3–6 15–20 2–4 coast: 176 660 Throughout Difficult unless shore pine interior: 70 546 frozen Pinus flexilis 7–20 20–30 2–4 6 454 Throughout Moderate limber pine Pinus monticola 10–25 20 3–7 7 687 Top ¼ Moderate western white pine Pinus ponderosa 7–9 12–16 4–6 31 522 Throughout Difficult ponderosa pine Pseudotsuga menziesii 5–10 20–25 2–10 coast: 39 577 Top ½ Easy Douglas-fir interior: 70 343 Thuja plicata 1–2 20–30 2–4 897 837 Throughout Easy western redcedar Tsuga heterophylla 2–3 25–30 3–4 366 698 Throughout Easy western hemlock Tsuga mertensiana 2–8 30 3–6 356 428 Top ⅓ Easy mountain hemlock

34 field studies of seed biology number of reproductive buds or, in other cases, can is sometimes dispersed by wind, but generally angio- stimulate prodigious production of cones. Plant sperm pollination is less affected by climatic variables, growth regulators (pgr) such as gibberellins have although extreme conditions (cold temperatures, been used to increase cone production in conifer seed heavy rain) may still affect pollination success. orchards (Ross and Bower ; Ross ), but pgr Fertilization efficiency may be reduced due to poor levels are difficult to alter, for logistical reasons, in female cone production, self-pollination (which often natural stands. results in embryo abortion), lack of pollen tube growth, Pollen, produced in male cones or anthers, is or freezing temperatures (Shearer and Carlson ). transported to female cones or flowers in the process Some conifers (e.g., Douglas-fir) can produce seeds of pollination. Successful pollination results in the (megagametophyte, but no embryo) without fertili- fertilization of ovules; ovules then develop into seeds. zation, but other conifers (e.g., pines) require the Reduced pollination efficiency may be due to low presence of pollen to form seeds (Owens and Molder pollen-cloud densities (few pollen-cone buds initi- b). Additional background on the sexual repro- ated), climatic conditions (e.g., rain, frost), or the duction of conifers may be found in Owens and presence or absence of pollen vectors. In conifers, Molder (a, b, c, d, ). which are wind pollinated, the absence of wind, or Once fertilized, seeds may fail to mature due to barriers to wind may inhibit pollination. Thus, the abortion (which may be caused by self-incompatibility, positioning of cones relative to tree height or relative insects, or disease), or because of climatic conditions to the windward and leeward sides of a tree can in- during embryo development, particularly cool, fluence the frequency of filled seeds (Smith et al. ). cloudy weather during the summer (Eis ; Zasada In angiosperms, animals (insects, birds, and mammals) et al. ). Some conifers do not shed their seeds usually are the primary vectors of pollination. Pollen when they mature in the fall, and instead may retain

Mature seeds

 . Typical development and maturation cycles of British Columbia conifer seeds (Leadem 1996, adapted from Eremko et al. 1989). Most angiosperms exhibit a reproductive cycle similar to that shown for Douglas-fir, redcedar, true firs, and hemlocks.

section 3 natural seed production 35 their seeds in the cones several years, a phenomenon of this size probably would be sufficiently mature referred to as serotiny (see Section ..). to produce seeds (McCaughey and Schmidt ). Further information on tree seed biology may be found in Leadem (). Once a site has been selected, data on individual Seed production studies are usually undertaken to trees may be collected. Examples of the data that determine: could be included are (Alexander et al. ): • the quantity and quality of seeds that may be • dbh to the nearest . cm (trees . cm dbh produced relative to some variable, or and larger); • the reasons for seed loss. • total height, to the nearest . m; • crown class; Other, more specific objectives may include: • species; • to predict the frequency of good seed crops • average length of live crown to the nearest . m (e.g., relative to climatic variables); (average of four sides); and • to relate seed production to stand, tree, or crown • average width of live crown to nearest . cm characteristics; (average of two measurements). • to examine the relationship between pollen abun- dance and filled seeds per cone; .. Determining sample size • to relate the number of seeds per cone to cone age The choice of sample size, such as the number of seeds or cone size; to sample per tree, can be made by applying statistical • to determine the relationship between the number efficiency calculations to a preliminary set of meas- of seeds in the cone half-face and the total number urements (Sokal and Rohlf ; Ager and Stettler of filled seeds per cone; ). See also Stauffer (, ) for sample size • to determine the date of cone and seed maturation; tables prepared specifically for forestry applications. or Sample sizes for measuring cone characteristics • to establish the relation between seed quality and will depend on the species and the sites from which collection date, or cone handling methods. the cones were collected. Carlson and Theroux () randomly selected  cones each from some sub- Several examples of seed production studies are alpine larch, hybrid larch, and western larch collections. described as case studies in Section .. Only five cones were selected from six other western larch collections because initial sampling error esti- .. Collecting stand and study plot information mates indicated that five cones would be adequate. Before conducting seed production studies in natural Sample sizes for seed measurements should also be stands, data should be collected on the tree and stand determined before the study. For a study of western characteristics known to influence natural seed pro- larch and subalpine larch, length, width, and thick- duction. Examples are: ness were measured on only  seeds randomly • density (number of seed trees per hectare); selected from each lot; initial sampling estimates in- • spatial arrangement of seed trees; dicated this would enable standard errors to within • age of seed trees; % of the mean (% confidence) • evidence of past production; (Carlson and Theroux ). • evidence of animal use (e.g., squirrel caches, cones Environmental changes may result in year-to- that have been broken or split); year variations in cone and seed measurements. • height and diameter at breast height (dbh); Ponderosa pine seeds collected in , , and  • assessments of the general health and vigour of the showed negligible differences in seed weight, length, crowns; and and width when comparisons were made within the • basal area values (in square metres per hectare). same year. However, differences were found in all Specific selection criteria may be included, for three measures when year-to-year variations were example the basal area of all Engelmann spruce removed by adjusting values to be relative to those trees with dbh of . cm and larger, because trees observed in  (Ager and Stettler ).

36 field studies of seed biology . Predicting Natural Seed Yields For estimates of Douglas-fir, grand fir, and western white pine cone crops, Eis (a, ) counted It is often desirable to be able to predict the occur- cones on one side of mature trees in July. Counting rence of natural seed production, to better was done using -power binoculars mounted on a understand what factors promote seed crops, to tripod at a permanent station that offered a good determine whether seed production will be great view of the crown. Cone counts were multiplied by enough to merit collection of the crop, or to provide conversion factors (obtained by comparing binocular advance notification for organizing pre-collection observations with physical cone counts on felled activities. In the sense used in this section, a distinc- trees). Weather variables were derived from various tion is made between prediction and correlation. expressions of temperature, precipitation, sunshine, Prediction is the objective of these studies (we are and wind velocity. Starting  months ( months for trying to predict natural seed production) and corre- western white pine) before the cones matured, cone lation is the means to do so (correlations with various estimates were correlated with all monthly meteoro- variables are used to predict the size of the crop). logical parameters. Where several meteorological variables were important in the same month, the data .. Correlation with weather variables were combined and analyzed by stepwise, forward, Many models for predicting the size of natural seed multiple regressions. crops have been developed, and those based on cli- Caron and Powell (b) correlated annual pro- matic variables indicate that the influence of weather duction of black spruce seed cones with warm weather conditions may be cumulative. In Douglas-fir and in early May and early July and with low June rainfall, grand fir, a cool, cloudy summer – months all in the year preceding maturation. Cone produc- before crop maturation appears to be a prerequisite tion data were recorded branch-by-branch during for abundant lateral bud initiation. These conditions later spring. Seed-cone estimates of previous crops must be followed by cold, sunny weather through the were obtained from a combination of () cones per- winter (– months before maturation); a wet sisting on the trees, () stubs and basal cone scales left April ( months in advance) to promote lateral bud on the bearing shoots where squirrels had removed differentiation; and a warm, dry, sunny June before cones, and () cones or stubs on nearby shoots of pollination ( months before maturation) (Eis a, comparable size and position within the crown when b). (See Figure . for a summary.) The impor- shoots of bearing type had been removed. tance of dry summers to floral initiation has also Mosseler () used accumulated growing been demonstrated in other species, such as spruce, degree-days (gdd) to predict when cones of black larch, and ponderosa pine (Eis and Craigdallie ). spruce and white spruce could be collected without

Seedfall

Aug Sept

0

 . Climatic conditions required for cone crop production in Douglas-fir (Eremko et al. 1989).

section 3 natural seed production 37 adversely affecting seed quality. Accumulated gdd is .. Correlation with aspect and slope a cumulative sum of the degrees of temperature above Aspect and slope can significantly affect cone produc- °C counted on each day that the daily mean tem- tion, especially in northern regions. For example, perature exceeds the °C threshold. In this study, black spruce trees growing on southerly aspects bore Mosseler based the gdd on the simple mean of the . and  times more seed cones and pollen cones, maximum and minimum daily temperatures recorded respectively, than trees growing on northerly aspects at the Atmospheric Environment Service (Environ- (Simpson and Powell ). Variations in slope and ment Canada) weather station nearest to each site. aspect can be difficult to depict, yet Simpson and Cones were harvested at intervals of  gdd begin- Powell effectively conveyed their results by using ning at about  gdd. Mosseler found that natural concentric circles to show the percentage of cones seed release in white spruce occurred between  produced in all compass directions (see Figure .). and  gdd. Cones from black spruce can be col- lected as early as  gdd and white spruce as early .. Correlation with crown size and crown class as  gdd without significant losses in seed yield In a closed canopy, the crowns of the trees forming or quality. Similar results were found for white spruce the canopy are touching and intermingled so that in Alaska (J. Zasada, pers. comm., ). light cannot directly reach the forest floor. However, Note that when attempting to correlate environ- dominant trees have crowns extending above the mental factors to seed production, it is important to general level of the canopy and thus receive full light place sensors as near as possible to where pollen and from above and partly from the side. The crowns of seed cones are produced to ensure you are monitor- codominant trees, which form the general level of the ing the conditions actually present in the canopy. canopy, receive full light from above, but compara- Also, because comparable events in the reproductive tively little light from the sides. The relatively more cycle are not always synchronous, male and female favourable light environment for tree crowns in the flowers, for example, may not experience the same upper canopy appears to enhance the cone produc- climatic conditions, so the environmental effects may tion of dominant and codominant trees. be different. In paper birch, male flowers are induced For example, dominant and codominant crown in May before bud burst and thus must depend on classes of Engelmann spruce produced three-quarters resources stored in overwintering materials. Female or more of the total seedfall in an experimental forest flowers develop in late June to early July, so they are in the Colorado Rocky Mountains (Alexander et al. able to draw on current metabolites for their growth ) (see Case Study , Section .). Also in black (Macdonald and Mothersill ). spruce, dominant trees produced almost three times

a) b) c)

 . Percentages of black spruce trees (concentric circles) 8–12 years old from seed, growing on slight (2–12%) slopes and on various aspects (Simpson and Powell 1981), which in 1980 bore: (a) more than five, (b) more than 15, and (c) more than 25 pollen cones.

38 field studies of seed biology as many cones as codominant or the intermediate and of cone-producing branches. He concluded that trees. Intermediate trees, on the other hand, produced total cone production was related to the square of the about twice as many seeds per cone as dominant trees trunk diameter just below the lowest living branch   2   (Payandeh and Haavisto ) (see Case Study , Sec- (DB in Figure . ). He concluded that cone produc- tion .). Note, however, in exceptionally good cone tion was not related to the total amount of dry matter years, trees in all crown classes produce cones, not in the tree, but rather to the amount of dry matter just the dominant and codominant trees (J. Zasada, accumulated in the neighbouring trunk and branches pers. comm., ). adjacent to cone production sites. Thus, cone pro- One possible reason for the periodicity observed duction per branch depends on the resource status of in conifers is the substantial drain that cone produc- a branch, to which at least part of the resources may tion evidently places on the tree’s resources. In be imported from other branches or the trunk for Douglas-fir, decreased needle, shoot, and xylem ring local cone production. In this way, the investment in growth was noted in good seed years in the trees that seed production in individual branches may not nec- regularly produced cones (Tappeiner ). No such essarily cost the whole plant its vegetative growth or reductions were seen in trees that did not produce future survival. cones. Similar effects have been seen in grand fir, western white pine (Eis et al. ), subalpine fir, .. Sampling methods using bud counts and mountain hemlock (Woodward et al. ). Eis (b, ) developed a sequential sampling meth- Seki () wanted to know the specific location of od to estimate white spruce and western white pine resources used to produce seeds in Abies mariesii, so cone crop potential in the fall preceding the seed year. he studied the allometric relationship between cone The method is based on the cumulative total count of production and the productivity of the entire crown female buds from one branch per tree collected from

 . Position of measurement for trunk diameters, the diameter of the base of a branch, and main axes for estimating of the number of cones (Seki 1994). Allometric relationships between various parts of a tree can be used for relating cone production to tree dimensions.

section 3 natural seed production 39 the third whorl from the top. Bud counts from three  . Cone crop rating based on the relative number terminal nodes on a branch of the fourth or fifth of cones on the trees (Eremko et al. 1989) stem node may also be used, but with slightly lower based on dominant and codominant trees only accuracy. Trees should be – years old, – m high, of dominant class, with well-developed Class Rating Definition crowns. The observer must be able to distinguish repro- ductive buds (both male and female) from vegetative 1 none No cones buds (identification based on general morphology, 2 very light Few cones on less than 25% location in the crown and along the branch, and col- of the trees our). When the cumulative bud count falls between 3 light Few cones on more than 25% given limits, cone crop potential can be classified with of the trees % probability, and no further samples are required. 4 light Many cones on less than 25% Male pollen buds can be used in birch and alder to of the trees indicate the next year’s seed production. Male buds 5 medium a Many cones on 25–50% of the trees are easily identifiable any time after September, and a can be counted from the ground to provide reason- 6 heavy Many cones on more than 50% of the trees able estimates of female catkin production the a following spring (J. Zasada, pers. comm., ). 7 very heavy Many cones on almost all of the trees A multistage variable probability sampling method, originally developed to estimate seed orchard effi- a Crops rated as class 5 or higher are generally considered ciencies, could be applied to assess seed production collectable. in natural stands. Bartram and Miller () first implemented a standard multistage approach in many seed orchards over several years. The effective- The rating of potential cone crops is highly subjec- ness of this approach was evaluated against several tive and dependent on the surveyor’s experience. The alternative methods using the efficiency data initially number of cones produced—and their distribution collected for the study. Refer to the original paper through the crown—varies considerably with tree for an example using this methodology in coastal species. Thousands of cones can constitute “many” Douglas-fir seed orchards in British Columbia. on a spruce tree; the same number could be classed as Mattson () also suggested a multistage approach “few” on a mature cedar. to evaluate red pine cone and seed production. In this A method based on seedfall data has been used in scheme, the first stage is based on weather factors and Oregon and California for rating cone crops of Abies, the second stage on insect predators. Pseudotsuga, Tsuga, and Chamaecyparis (Zobel ). Seeds were collected from traps approximately once a .. Scales for rating cone crops month over a -year period. The monthly trap sam- Crop rating is an operational assessment procedure ples from a site were usually combined, except where used by the B.C. Ministry of Forests to determine seed production was high enough to separately count whether developing cone crops are collectable individual traps. Basal area of each tree species over (Eremko et al. ). Suitable stands are located, and  cm dbh in each stand was measured using a wedge the relative size of developing cone crops is assessed prism, with each trap as a sample point. Seed produc- in late June or early July. A visual assess-ment is made tion effectiveness of a site was expressed as the annual of the relative number of cones in the cone-bearing seedfall per square metre of basal area of each species. portion of dominant and co-dominant tree crowns. In another study, seed production of Engelmann The number of cones on each cone-bearing tree and spruce was based on seeds captured in traps and percentage of trees bearing cones in the stand are also grouped into categories (Table .). assessed. Observations are grouped into classes Note that there may be some discrepancy between depending on the relative number of cones observed the cone crop rating and the number of seeds col- on the tree (Table .). lected in seed traps. Such discrepancies can occur

40 field studies of seed biology  . Rating of seed crops by number of filled seeds fertilization take place in the same growing season, per hectare (Alexander et al. 1982) but the total cycle usually lasts about  months. Under natural conditions, seed maturation is delayed Filled seeds per hectare Seed crop rating by a period of dormancy until the following year (Figure .); however, under favourable conditions < 25 000 Failure in seed orchards, pollination, fertilization, and 25 000–125 000 Poor seed maturation can occur within the same year 125 000–250 000 Fair (El-Kassaby et al. ). 250 000–625 000 Good In conifers, male and female strobili appear on the same tree (with the exception of yew). However, the 625 000–1 250 000 Heavy distribution of cones within the crown varies with > 1 250 000 Bumper the species (Table .), and even within the same species, male and female cones may occur in different parts of the crown. In hardwoods, it may be necessary in areas where there is heavy predation of cones by to identify male and female clones before monitoring, squirrels. Thus, generally it is best to count when since dioecious hardwoods, such as Salix, Populus, cones have attained maximum physical dimensions, and Fraxinus, bear male and female flowers on and before squirrels begin to harvest. different trees. Cone crop estimates also can be obtained by direct sampling of cone-bearing regions or fertilized Monitoring pollen flowers. For example, cone crops of eastern redcedar Pollen abundance in the air during female receptivity (Juniperus virginiana) were estimated by multiplying is believed to be closely related to seed production. the average number of cones per sample branch Estimates of pollen abundance can be used to formu- (–) in October by the cone-bearing canopy late a relationship to () total seed production for the foliage (Holthuijzen et al. ). stand, and () total filled seeds per cone. In lodgepole pine, the number of male meristems produced on .. Monitoring the seed crop individual trees was correlated to the frequency of The sequence and length of different components filled seeds on those trees (Smith et al. ). Weather of the reproductive cycle must be understood when data for previous and current year also can be planning and executing seed production studies be- incorporated to develop predictive models for seed cause different components are not the same in each yield. Possible relationships that can be studied are species. For example, you need to know the length of the amount of rain during flower initiation and the entire reproductive cycle of each species involved temperature minima during critical stages of cone in the study, since this will determine when monitor- maturation (Stoehr and Painter ). ing should begin. You must also know the timing of Many different kinds of pollen samplers have been other critical events, such as pollination, fertilization, used to assess pollen abundance. Each has its advan- and periods of bud dormancy, to ensure you are at tages and disadvantages, but often the choice depends the right place at the right time. on the financial resources available. The least expen- For Douglas-fir, redcedar, spruces, true firs, and sive approach is a microscope slide placed on a flat hemlocks, the development and maturation cycle surface or on the ground. The results from such a takes about  months (Figure .). For these species, method may have little relationship to the actual male and female strobili appear in the spring, and densities experienced at the female cone level, but seeds mature in the fall of the same year. In maple, it may be possible to correlate the data with crown alder, birch, Garry oak, and willows, seeds are also measurements. produced in the same year as the female flowers. Another inexpensive method used in Sweden and However, in pines, complete development takes Finland is to trap old pollen strobili that fall to the  months because fertilization is delayed for  year ground to obtain estimates of pollen cone production after pollination. In yellow-cedar, pollination and (Leikola et al. ). At the other end of the spectrum

section 3 natural seed production 41 are automated air samplers that pull a known volume long) with a fitted rubber stopper is used to protect of air through the sampler so that air movement is the catching surface from contamination before in- dynamic. This differs from strip chart recorders, stallation and after collection. The traps are collected which are “passive” and depend on natural wind and and replaced daily. air movement to adhere pollen to the “sticky” surface. Smith et al. () sampled airborne pollen for den- The abundance of pollen in conifer stands can sity estimates of lodgepole pine at canopy level near be estimated using a -day pollen monitor (Webber the centres of two squares that made up a central and Painter ). Several monitors (three is good, rectangle surrounded by a  m bank. Air samples depending upon the size of the plot) should be placed were taken at -minute intervals over  or  days in the experimental sites  week before expected pol- with Kramer-Collins air samplers (Kramer et al. ). len shed and left in the field until the pollination Pollen counts averaged over the  peak days were used period is completed. The monitor is mounted on a to calculate relative pollen densities in the  stands pole  m above the ground and always turns into the chosen for study. Pollen cone production was estimated wind. The monitor consists of a permanent chart by counting the number of terminal meristems pro- wrapped around a drum, which is rotated with a ducing male strobili. Using binoculars, terminal clock mechanism. The chart is made of mylar coated meristems were counted for either the entire tree, with petroleum jelly so that pollen will adhere; heat- or  or  meristems were counted on a portion ing the petroleum jelly slightly creates a smooth, even of larger trees, and that portion was estimated as a coat. Since the drum completes one turn each week, percentage of the total surface area to provide a pollen charts must be changed weekly. Pollen charts meristem total for the tree. Estimates ranged from are assessed in the laboratory, where pollen densities,  to  male meristems per tree. To check the timing of dispersal, and pollen identification can be consistency of the technique,  trees were counted determined on a daily basis. Proper evaluation of on consecutive days. Of the  counts that differed pollen charts depends on the experience and exper- on the  days, the second day had the smaller count tise of an analyst familiar with pollen density patterns.  times. The smaller count averaged % of the Sarvas (, ) used different types of pollen larger count for the  trees that had male meri- samplers to estimate pollen density in Scots pine stems. Using a similar sight estimation of female (Pinus sylvestris) and Norway spruce (Picea abies), cones on trees that were later cut down so that cones and was able to closely relate flowering to heat-sum could be counted, Elliott () and Smith () calculations. He placed all his pollen samplers on found that their under- or overestimation deviated towers at the height of the female flowers. Zasada et from the actual count by an average of %. al. () used this method for white spruce. Sarvas Pollen from different species can usually be identi- also used a small globe sampler to measure pollen fied microscopically (Figure .). In a study of black rain density. The globe shape was chosen because it spruce, the pollen catch was systematically examined more closely resembled the shape of a female cone, (-power magnification) on the four directional and thus better approximated the pollen density pat- faces of each trap (Caron and Powell a). Pollen terns expected on a “cone-shaped” surface. identification to the species level (or at least genus) Another pollen trap described by Caron and was accomplished by comparing pollen samples Powell (a) consists of a glass rod ( mm diameter collected directly from trees with micrographs and ×  cm long); one end is coated with a thin layer of species descriptions (Richard ; Adams and white petroleum jelly to serve as the catching surface, Morton ). In mixed stands comprised of species the other end is tightly fitted through a rubber stop- with similar-looking pollen, it is advisable to install per into a hole on a wooden base. The square wooden additional pollen monitors in pure stands of the base is grooved to slide into a holder, which can be species located near to the study site. Pollen density set so that the edges are aligned to the four cardinal records from mixed stands can then be compared directions. Each trap holder is protected from rain by to those from pure stands to determine the relative polyethylene film installed on a wire frame – cm pollen abundance and time of pollination of different above the base. A vial ( mm diameter ×  mm species (Stoehr and Painter ).

42 field studies of seed biology Monitoring seed cones descending branches within the lower two-thirds of This section focuses on monitoring female conifer the crown (Shearer and Schmidt ). In British Co- cones, although the same procedures could also be used lumbia considerable overlap of the seed and pollen for the flowers, fruits, and seeds of hardwood species. cones occurs within the lower half of the crown To sample for cone production (either male or (Owens and Molder a, b) (Table .). female cones) it is necessary to determine where In species such as whitebark pine, cone scars can the cones are produced. In western larch, most seed be monitored to estimate past cone crops (Morgan cones are produced on ascending branches or on and Bunting ) (Figure .). Morgan and Bunting recent terminal leaders within the upper third of the chose a  m transect that contained  mature, crown; most pollen cones are found on horizontal or cone-producing whitebark pine trees with crowns

a) b)

c) d)

e) f)

 . Scanning electron micrographs showing whole pollen and details of the exine. (a), Chamaecyparis nootkatensis (×1100); (b), Betula (×860); (c), Abies amabilis (×400); (d), Pinus contorta (×720); (e), Pseudotsuga menziesii (×360); (f), Tsuga heterophylla (×540). (Owens and Simpson 1986).

section 3 natural seed production 43 Similarly, in Douglas-fir, it is possible to trace pedicle remains to estimate previous cone production (Tappeiner ). In Abies, cone spindles remain on branches for several years after the cones have disin- tegrated; these also might be used to estimate previous production (J.C. Tappeiner, pers. comm., ). In a study of ponderosa pine, four branches in the upper half of the crown were randomly selected and permanently marked for the presence of male and female flowers (strobili), conelets, and mature cones (Heidmann ). Flowers were counted in July of each year for  years. Because of the great number of male flowers on some branches (as many as  clus- ters per branch), an average was determined for a sample of  clusters, then multiplied by the number  . The oval, raised cone scars of Pinus albicaulis of clusters to obtain the total flower count for that can be counted and aged by the nearby branch. All female flowers were counted. annual bud scars on twigs (Morgan and Fourteen western larch stands ranging in age from Bunting 1992).  to  years were monitored by Shearer and Carlson () in Idaho, Montana, Oregon, and Washington. Using binoculars, they estimated the readily visible from the ground from at least two angles. number of new seed cones in spring. Five trees with The data were obtained by visiting each transect in late the greatest seed cone counts were climbed and the July or early August (before appreciable harvesting by number of developing cones was estimated by count- red squirrels and Clark’s nutcrackers); binoculars ing the number of branches with seed cones, and new were used to count the mature cones visible from seed cones (living and dead) on six random branches the ground. Each tree was climbed to access cone- (two from each third of the crown). The number of bearing branches normally found in the uppermost potential seed cones was estimated by multiplying the portion of the canopy; cone-bearing branches are average number of cones per sample branch by the visibly shorter and stouter than other branches. Five number of cone-bearing branches. Seed cone survival branches were sampled that bore either cones or re- was estimated in August by counting the number of cent cone scars. The mean number of cones or cone cones that matured on the six branches selected in scars was calculated for each sampled stand. The the spring. Seed cone mortality was determined by transformed values of the nonzero data were stand- subtracting surviving cones from the total cones ardized by calculating z (the difference between counted at the first visit of the year. During the first the individual observation and the means of all visit, researchers marked  cones on the two trees observations, divided by the standard deviation of all bearing the most cones at each site. During subse- observations). The z-scores were calculated separately quent visits they documented cone development, as for scar and cone counts, then combined for classi- well as the time and cause of cone damage. Dead fication into poor, average, or excellent cone crops. cones were removed and the probable cause of death Morgan and Bunting recommend counting imma- was identified. ture cones as an index of cone production in the following year. Another method involves counting Cone and seed analysis immature cones on high-resolution aerial photo- Initially developed for southern pines, cone and seed graphs. The immature cones are readily visible from analysis is an excellent procedure for identifying above; they occur at the ends of upswept branches actual and potential seed production and the causes near the top of crowns and their deep purple colour of seed loss in conifers. Bramlett et al. () provide contrasts with the foliage. complete background and procedures.

44 field studies of seed biology Cone and seed analysis is based on calculating cone and seed efficiencies would require some four critical ratios (efficiencies), which are used modifications since, in species such as Salix and to identify the sources (stages) in which major Populus, catkins are comprised of capsules, each of losses occur: which has several to many seeds. In Alnus and Betula, catkins are more like conifer strobili. In Acer and number of cones harvested cone efficiency = Fraxinus, fruits are paired or single samaras, respec- number of conelets initiated, tively, each containing one seed per samara. Refer to Table . and to Section .. for further information number of filled seeds seed efficiency = on hardwood fruit characteristics. number of fertile sites, Whether the method is used for conifers or hardwoods, two cautions should be considered in extracted seeds per cone extraction efficiency = conducting cone and seed analysis and extending the total filled seeds per cone, and results to the species: . If at all possible, the cone analysis should be number of germinated seeds germination efficiency = repeated during another good seed crop year. total filled seeds. . If an unharvested stand can be found near the study plot, cones should also be collected from the The analysis requires the determination of: unharvested stand for comparison. • the potential number of seeds per cone; • the total number of seeds per cone; Filled seeds per cone • the number of extracted seeds per cone; Measurements of the number of filled seeds per cone • the number of filled seeds per cone; and are obtained primarily for predictive purposes. • the number of empty and insect-damaged seeds Numbers are used to plan the size of cone collections per cone. in a particular area, or to estimate the potential of a site for natural regeneration. Large samples are Note that the number of filled seeds must be generally not needed. For example, in ponderosa pine determined in addition to the total number of seeds. only  closed cones from each lot were required to This is essential to reflect the actual seed production obtain good corre-lations between filled seeds per potential of the species. cone and kilograms of seeds per hectolitre of cones Commercial services are available if you do not (Ready ). wish to perform your own cone and seed analyses Determining the total number of filled seeds per (refer to Portlock [compiler] ). cone is time consuming, as it requires complete dis- Cone and seed analysis has been applied in British section of the cone. Special tools are needed as most Columbia to analyze seed production of lodgepole cones are hard and woody. For these reasons many pine and Douglas-fir (McAuley a, b). For studies have attempted to relate the number of filled, the analysis, samples were randomly selected from sound seeds seen in the cone half-face to the total five sacks among those filled that day. Random sub- number of seeds in the cone (see Figure .). Schmid samples consisting of one cone per sack were placed et al. () tested several sampling designs to deter- in separate bags for subsequent analysis. Based on mine the accuracy and precision of each design in previous experience, a sample size of  Douglas-fir estimating the mean numbers of filled seeds. They cones per orchard ( cones for lodgepole pine) was found that half-face counts on  cones (two cones considered to yield a reasonably precise estimate of from each of  trees) from a ponderosa pine stand single, orchard-level means. Samples for cone and estimated the filled-seed percentage for whole cones seed analysis of western larch consisted of  cones within ± units of the mean. Olsen and Silen () collected from each of  individual trees per hectare multiplied the number of filled Douglas-fir seeds (Stoehr and Painter ). seen in the cone half-face by . for an estimate of the Hardwood trees could also be assessed using total seeds per cone. From each . L of undried coneand seed analysis methods. Determining the cones, they cut  cones in half longitudinally,

section 3 natural seed production 45 counted the number of full seeds on one cut surface, British Columbia tree species follows (summarized then dried and extracted the cones to determine the in Table .). In addition, various cone and seed at- total number of filled seeds. tributes (such as colour, weight, and length) can be Half-cone counts have been used extensively in used to indicate seed maturity. Assessment of seed British Columbia to determine whether developing maturity may be the objective of the study or may be cone crops are collectable. Recommended collection important for obtaining the best-quality seeds for standards based on filled seeds in the cone half-face another study. are given in Eremko et al. () for Abies amabilis, Because conifer and hardwood seeds can vary so Abies grandis, Abies lasiocarpa, Chamaecyparis greatly, the procedures for collecting, processing, and nootkatensis, Larix occidentalis, Picea glauca, Picea storing seeds of various species are discussed sepa- mariana, Picea sitchensis, Pinus contorta, Pinus rately in Section . according to the characteristics monticola, Pinus ponderosa, Pseudotsuga menziesii, of their fruits. Thuja plicata, and Tsuga heterophylla. .. Description of conifer and hardwood fruits . Determining Fruit and Seed Maturity and The dry multiple fruit of a conifer is called a cone or Quality strobilus (plural strobili). A female cone consists of a central axis supporting overlapping bracts, each of Understanding fruit and seed morphology is vital in which subtends a scale bearing naked seeds. Gymno- designing and implementing a seed production study. sperm, another term for conifer, means “naked fruit,” A brief description of the seed-bearing structures of referring to the fact that conifer seeds are borne

 . Longitudinal and transverse sectioning of cones: (a) longitudinal sectioning of an interior spruce cone; (b) sectioned Douglas-fir cone; (c) transverse sectioning of a lodgepole pine cone; (d) sectioned lodgepole pine cone (Eremko et al. 1989). The number of filled, sound seeds seen in the cone half-face can be used to estimate the total number of seeds in the cone.

46 field studies of seed biology naked on the ovuliferous scales of their cones. A male The seeds of hardwoods are enclosed in protective cone consists of a central axis supporting spirally fruits that vary considerably in size, colour, and arranged microsporophylls bearing pollen sacs that structure. The seeds of bigleaf maple and Oregon ash contain the pollen grains. Conifers in British Colum- are contained in dry winged fruits called samaras. In bia produce several to numerous seeds in a single maple, two winged seeds are joined to form a V, but cone. An exception is Pacific yew, whose fruit is a red, in ash, each fruit contains only a single winged seed. berry-like aril that contains a single “naked” seed. The fruits of red alder, birch, poplar, and willow are

 . Seed-bearing structures of trees occurring in British Columbia

Fruit type Definition Example achene Dry, indehiscent one-seeded fruit. Betula acorn One-seeded fruit of oaks; consists of a cup-like base and the nut. Quercus garryana aril Exterior covering or appendage that develops after fertilization as an Taxus brevifolia outgrowth from the point of attachment of the ovule. berry Pulpy fruit developed from a single pistil and containing one or more immersed Arbutus menziesii seeds, but no true stone. capsule Dry, many-seeded fruit composed of two or more fused carpels that split at Populus, Salix maturity to release their seeds. catkin Spike-like inflorescence, usually pendulous, of unisexual flowers (either staminate Alnus, Betula, Populus, Salix or pistillate). Also used to describe the fruit. Compare strobile. cone Dry multiple fruit of conifers. A female cone consists of a central axis supporting all B.C. conifers, except Taxus overlapping bracts, each of which subtends a scale bearing naked seeds. A male cone consists of a central axis supporting spirally arranged microsporophylls bearing pollen sacs that contain the pollen grains. Syn. strobilus. drupe Fleshy indehiscent fruit, usually one-seeded, containing a seed enclosed in a hard, Cornus, Prunus bony endocarp (pericarp). Syn. stone fruit. nut Dry, indehiscent, one-seeded fruit with a hard wall. Quercus garryana pome Many-seeded fruit of the apple family consisting of an enlarged fleshy receptacle Malus fusca surrounding the papery, fleshy pericarp. samara Dry, indehiscent winged fruit; may be one- or two-seeded. Acer (two-seeded), Fraxinus (one-seeded) strobile Spiky pistillate inflorescence or the resulting fruit; not a true strobilus. Alnus, Betula, Populus, Salix (pl. strobiles) Syn. female catkin. strobilus Male or female fruiting body of the gymnosperms. all conifers, except Taxus (pl. strobili)

Notes: carpel: simple pistil or single member of a compound pistil. imperfect flower: flower which contains either, but not both, functional male or female parts. indehiscent: refers to dry fruits that normally do not split open at maturity. nutlet: nut-like fruit or seed, as in Alnus or Betula. perfect flower: flower that contains both pistil and stamens. pericarp: wall of a ripened ovary that is homogeneous in some genera and in others is comprised of three distinct layers: exocarp, mesocarp, and endocarp. Syn. fruit wall. pistil (or pistillate): the female part of angiosperm flowers, containing the ovary, from which seeds develop. staminate: referring to male angiosperm flowers, containing the stamens, from which pollen is produced. stone: part of a drupe consisting of a seed enclosed in a hard, bony endocarp as in Prunus and Cornus.

section 3 natural seed production 47 catkins (or strobiles), which develop from the spike- like female flowers. The drooping catkins of poplar and willow comprise many capsules that split open at maturity to release many seeds per capsule. The catkins of birch break up at maturity to release the small winged nutlets. The female catkins of alder are woody cones; the cones contain oval nutlets that do not break up at maturity. The fruit of Garry oak is an acorn, consisting of a hard-coated nut in cup- like base. Several hardwoods have fleshy fruits surrounding  . Anatomy of a mature Douglas-fir seed. Ninety their seeds. The fleshy fruit of Pacific dogwood, bitter percent elongation of the embryo is the cherry, and cascara is a drupe, sometimes called a recommended standard for collection stone fruit. A drupe usually contains a single seed (Leadem 1984). enclosed in a hard, bony ovary wall (the stone). The arbutus fruit is a berry, a pulpy fruit developed from a single pistil (female part of a flower) and containing white cedar (Thuja occidentalis) seeds makes it diffi- one or more immersed seeds, but no true stone. The cult to determine if the seeds are filled. Briand et al. Pacific crab apple is a pome, a many-seeded fruit con- () therefore used swelling of the embryo area as sisting of an enlarged fleshy receptacle surrounding a a means of classifying developed from undeveloped papery ovary wall. seeds. Seed colour can also be used as a key to viabil- ity, and is discussed in more detail in Section ... .. Assessing embryo development Destructive methods of seed assessment include The most commonly used indicators of maturity in cutting seeds open to expose the embryo. This proce- conifer seeds are cone and seed colour, degree of cone dure allows for a greater variety of measurements, opening, condition of the megagametophyte, and such as embryo length, embryo cavity length, and length of the embryo (Edwards ; Shearer ; cotyledon length. Alternatively, you can germinate Eremko et al. ). Cones lose moisture as they the seeds and determine the anatomical characteris- mature, and cone colour usually changes from green tics of the embryos. Cotyledon numbers of ponderosa to brown. In the field, specific gravity of the cones pine were determined by germinating  seeds, and has been used to monitor maturation of Douglas-fir selecting  germinants for scoring (Ager and cones (Shearer ). The rate of maturation is in- Stettler ). fluenced by the number of degree-days (Mosseler See Sections .. and .. for quick tests and ), elevation (Shearer ), and latitude. other viability tests. Conifer seeds should not be collected until embryos fill at least % of the embryo cavity (Figure .). .. Assessing seed colour Although collection can begin when embryos fill % Colour is frequently used as an indicator of both cone of the cavity, collecting seeds when embryos are more and seed maturity. In some instances, the purpose of mature will result in better-quality seeds (Edwards the study may be to assess seed colour as an indicator ; Zasada ; Eremko et al. ). of seed maturity. In other instances, determining ma- Embryo development and size may be determined turity (using colour) may be simply a tool to ensure destructively or non-destructively. Non-destructive that the best quality seeds are collected. methods depend on an external visual assessment Seed colour is one of the more difficult indicators of the seeds. For example, with paper birch it is to quantify, as it relies on the subjective judgement possible to distinguish viable well-filled seeds from of the observer, and cone and fruit colour can vary non-germinable seeds by viewing the seeds with a among different individuals of the population. Sev- dissecting microscope equipped with substage illumi- eral instruments, such as Tristimulus colorimeters nation (Bevington ). The small size of eastern and video imaging systems (McGuire ), can be

48 field studies of seed biology used to quantify seed colour and reduce the subjec- Bract length was measured from the base to the tip of tivity of colour readings. the pointed apex; width was measured at the widest Seed colour variation in ponderosa pine was point of the bract. quantified by constructing a -seed gradient with Large differences in cone morphology may be seeds from the entire collection (one seed from each noted between stands and between years. Abnormal of  trees) (Ager and Stettler ). Trees were then cone morphology may also be observed, for example, scored by comparing the adaxial (exposed) surface “forked” cones, proliferated cones (with needles of five typical seeds from a given tree with the gradi- formed at the apex), and combinations of male and ent. Mottled seeds were evaluated on overall shade. female in the same cone. (See Zasada et al.  for Although there were large colour variations among examples in white spruce.) the populations studied, the seeds of a single tree were remarkably uniform when compared to seeds Seed dimensions from different trees. This uniformity is probably a Measurements of seed size (length, width, and result of the high heritability and maternal control thickness) will depend on the anatomical charac- of seed morphology in pines (Kraus ). teristics of the seed (Figure .). In ponderosa pine, Seed colour can be used as a key to the viability of Ager and Stettler () defined seed length as the willow and poplar. In willow the presence or absence distance between the micropylar and basal ends, and of the embryo can be determined by the dark green width as the maximum distance across the seed of the cotyledons showing through the transparent perpendicular to the long axis. Length and width data seed coat. were based on five seeds per tree.

.. Measuring cone and seed dimensions

a) Cone dimensions Cone length can be measured using vernier calipers (. mm precision) (Caron and Powell a). Depending on the type of data presentation or data analysis, it may be convenient to group measurements of cone length into classes. Bergsten () initially grouped cone length measurements of Scots pine in- to  classes (. mm each) from . to . mm, but subsequently combined them into six length classes. Temperature and humidity may affect some cone measurements. In western larch and subalpine larch, Carlson and Theroux () measured cone length b) and diameter on both wet and dry cones, because moisture differentially influences their shape. They hydrated dry cones by placing them in a chamber at % humidity for  hours, then measured cone diameter at the midpoint along the longitudinal axis of the cone. Cone measurements are sometimes used as stable taxonomic markers to distinguish between species of the same genera, and their hybrids. Carlson and Theroux () measured the length and width of five scales and five bracts of western larch and subalpine  . Tree seed anatomy (longitudinal sections): (a) larch, randomly selected from the middle one-third of red alder, an angiosperm; and (b) Douglas-fir, each cone (measured when dry) to the nearest . mm. a gymnosperm (Leadem 1996).

section 3 natural seed production 49 In western larch and subalpine larch, Carlson and If X-ray equipment is available, seeds can be Theroux () measured seed length, width, and placed on celluloid film and exposed to X-rays (see thickness to the nearest . mm. Width and thick- Section ..). Once developed, the films can be ness were measured at the widest part of the seed, placed on a microfiche viewer (of the type commonly then each seed was sliced longitudinally. The thick- used in libraries). Precise seed dimensions can be ness of the seed coat was measured to the nearest obtained by direct measurement of the projected . mm midway between the base and apex of images. Actual and projected dimensions can be the seed. Sampling was done on  seeds randomly compared to calculate an appropriate conversion selected from each lot, as initial sampling estimates factor. If the size and shape of seeds are suitable, an indicated that this sample size would enable standard overhead light projector and  mm camera film can errors within % of the mean with % confidence. be used in a similar manner. Briand et al. () used a dissecting microscope Anatomical measurements were made on white equipped with an ocular micrometer to measure the spruce seeds by cutting the seeds longitudinally and small seeds of eastern white cedar (Thuja occidentalis). measuring the embryo length, embryo cavity length, Seeds were positioned such that the micropylar end and cotyledon length with a micrometer mounted in was facing up and the concave face of the seed was the eyepiece of a binocular microscope (Zasada ). towards the viewer. The following measurements When multiple embryos were present, embryo meas- were determined to the nearest . mm: length and urements were made on the dominant embryo. width of the seed and the embryo area, length of the Samples consisted of  white spruce seeds taken from right wing, and right wing width measured at the the central portion of four cones from each tree. In midpoint (Figure .). many conifers, seeds at the apical and basal portions Extremely small seeds of Salix and Populus, which of the cone are poorly developed (Bramlett et al. ). can be especially difficult (and tedious) to measure, can be graded by sifting them through a set of soil .. Estimating seed weight and volume screens. Although this method is not as precise as Seed weight can be expressed as the fresh weight (fw) using a micrometer, it is effective and less expensive or dry weight (dw) of seeds. The expression used for (J. Zasada, pers. comm., ). seed weight will depend on the context in which it is used. International seed testing rules prefer the use of fresh seed weight (before drying in an oven), whereas ecologists more often use the dry weight of seeds. See Section .. where fresh weight and dry weight are more thoroughly discussed. Seed weights should be determined to at least two significant figures. The sample size required to estimate seed weight varies with the species and the variability of the crop. For example, two -seed rep- licates per tree were used by Ager and Stettler () to determine the weight of ponderosa pine seeds. International standards for sample sizes for weight measurements may be found in International Seed Testing Association () or the Association of Offi-   . Outline drawing of a typical seed of Thuja cial Seed Analysts ( ). Seed weights of tree species   occidentalis (Briand et al. 1992) showing occurring in British Columbia are listed in Table . . significant seed dimensions. LEA = length of For serotinous cones of species such as jack pine and embryo axis; W = width of entire seed; LRW = lodgepole pine, the volume of cones can be determined length right wing; WRW = width right wing; by immersing individual cones in a graduated cylin- WEA = width embryo axis. der containing water and a wetting agent (Rudolph et

50 field studies of seed biology al. ). A similar procedure has been used effec- studied. Conifers generally require some effort to tively for white spruce cones (Zasada et al. ). extract the seeds from the cone, and hardwood seeds are enclosed in a hard or fleshy fruit which must be . Collecting and Processing Seeds removed to obtain the seeds. Another factor affecting seed collection is the In many studies, seeds are an end product by which capacity of seeds for long-term storage. All conifer successful reproduction is assessed. Thus, efficient seeds and many hardwood seeds can retain viability methods of collecting, extracting, and storing seeds for long periods if seed moisture content (mc) is must be known. The method selected for collecting reduced to low levels (–%) and the seeds are and extracting seeds depends on the species being stored at subzero temperatures. Such seeds are called

 . Seed sizes of tree species occurring in British Columbia

Seeds per gram Seeds per gram Scientific name Average Range Scientific name Average Range

 Tsuga heterophylla 655 416–1119 Abies amabilis 25 18–36 Tsuga mertensiana 251 132–458 Abies grandis 50 26–63 Abies lasiocarpa 85 52–108 Chamaecyparis nootkatensis 240 145–396  Juniperus scopulorum 60 39–93 Acer macrophyllum 7 6–8 Larix laricina 701 463–926 Alnus rubra 1468 844–2396 Larix lyallii 313 231–359 Arbutus menziesii 570 434–705 Larix occidentalis 302 216–434 Betula papyrifera 3040 1344–9083 Picea engelmannii 300 152–709 Cornus nuttallii 10 9–13 Picea glauca 405 298–884 Fraxinus latifolia 18 13–21 Picea mariana 890 738–1124 Malus fusca 119 Picea sitchensis 465 341–881 Populus balsamifera 3766 3583–3949 Pinus albicaulis 6 5–7 ssp. balsamifera Pinus banksiana 290 156–551 Populus balsamifera 1652 1233–2070 ssp. trichocarpa Pinus contorta var. contorta 263 225–300 Populus tremuloides 8353 5984–10 707 Pinus contorta var. latifolia 263 225–300 Prunus emarginata 15 9–19 Pinus flexilis 10 7–14 Quercus garryana 0.19 0.17–0.22 Pinus monticola 60 31–70 Rhamnus purshiana 27 11–42 Pinus ponderosa 25 15–51 Salix amygdaloides 5720 Pseudotsuga menziesii 85 63–117 var. glauca Salix bebbiana 5500 Pseudotsuga menziesii 95 65–100 Salix discolor no data available var. menziesii Salix exigua 22 000 Taxus brevifolia 34 32–36 Salix lucida ssp. lasiandra 25 000 Thuja plicata 915 447–1307 Salix scouleriana 14 300

Sources: Stein et al. 1986; Wyckoff and Zasada [1998]; Zasada and Strong [1998]; Zasada et al. [1998].

section 3 natural seed production 51 orthodox in their storage behaviour. Some hardwood berries are usually collected in the fall by stripping seeds do not store well, remaining viable only for or picking by hand directly into bags or baskets, or several weeks up to – years. These seeds are called by shaking or flailing the fruits from the plant onto recalcitrant. They must be stored at relatively high a canvas spread on the ground (Johnsen and moisture content (–%) and above zero tempera- Alexander ). tures, and may require other special handling. With all collection methods, safety precautions must be rigorously maintained. Safety belts and .. Conifer seeds straps must be checked at least twice each day. Tools such as pruning poles and cone rakes should not be Collecting conifer seeds carried while the tree is being climbed. For aerial Conifer cones may be collected by climbing (Yeatman collections, the helicopter company must be certified, and Nieman ) or felling trees. Many aerial cone and the pilots appropriately qualified. Aerial collec- collecting techniques are also available (Camenzind tion operations in British Columbia are subject to ). Aerial methods are much more efficient, Workers’ Compensation Board regulations; make especially for species that produce cones in the upper sure that you have access to current regulations crown, but collection costs are much higher since the appropriate for the area, and confer with persons use of a helicopter is required. Advantages and disad- experienced in cone collection operations. vantages of various cone collection methods may be found in Camenzind (). The choice of method Extracting conifer seeds for specific cone collection projects depends both on Serotinous cones such as black spruce may require the crop and the techniques available. Factors to a period of high temperature to open the cone consider include species, crop size, quantity of cones scales, and sometimes may need multiple extrac- to be collected, site characteristics, the capabilities of tion cycles, as for example, the procedure used by each harvesting technique, safety, efficiency, and cost. Haavisto et al. (): For relatively small trees, and where conditions . soak cones in lukewarm water for  hours, permit, cones and fruits can be collected using a fruit . oven-dry cones at °C for – hours, and picker with a hydraulic lift. If cone-bearing regions . tumble cones in a revolving screened drum for are clearly visible, branches can be shot down with  minutes. a rifle. Occasionally, cones may be collected from squirrel caches, but it is not recommended because Using this procedure, an average of eight seeds per the seeds may be infected with moulds and other cone still remained after the th cycle (average seeds/ pathogens (Sutherland et al. ). cone = ). Collecting Pacific yew and Rocky Mountain juniper Note that the application of this procedure and the seeds requires strategies different from most other ones that follow will depend on the degree of serotiny British Columbia conifers. Both Pacific yew and of black spruce cones (see Section ..). Rocky Mountain juniper are dioecious and bear Mosseler () used only two seed-extraction their fleshy fruits only on female trees. cycles (sec) to remove most of the seeds from black The fruit of Pacific yew, which ripens in late sum- spruce cones. The first sec consisted of oven drying mer or autumn, consists of a red, fleshy, cup-like aril at °C for  hours. A second sec was conducted bearing a single hard seed. To prevent losses to birds, after a -hour water soaking treatment, which was yew fruits should be picked from the branches by followed by drying at °C for  hours. Few seeds hand as soon as they are ripe (Rudolf ). remained in the cones following this extraction pro- The scales of the female flowers of Rocky Moun- cedure, and no further attempt was made to retrieve tain juniper become fleshy and fuse to form small, the remaining seeds. Seeds were counted with an indehiscent strobili commonly called “berries.” electronic counter and were judged to be filled if they Immature berries are green; ripe berries are blue and sank in % ethanol. Verification of ethanol separation covered with a white, waxy bloom. The fruit coat of was made by cutting sample seeds from the filled seed Rocky Mountain juniper is thin and resinous. Juniper fraction, and crushing seeds from the empty fraction.

52 field studies of seed biology Although multiple extraction cycles were also improvised means in a well-vented laboratory oven used, the method used by Caron and Powell (a) with a circulating fan, over a hot-air register or radia- differs significantly from the previous two, in that the tor, or similar location. black spruce seeds are not heated during extraction. Cones should be shaken or slowly tumbled to Instead, after the cones were shaken individually in a extract the seeds from the opened cones. Small-lot covered jar to dislodge seeds, the remaining seeds collections of seeds can be efficiently extracted using were extracted with forceps. This shaking and seed- a multiple compartment tumbler-drier (Leadem and extraction step was repeated two or three times until Edwards ). Although some wings are loosened all seeds were extracted. Cone scales were separated during tumbling and preliminary cleaning, many into three general categories (basal, central, and conifer seeds must be dewinged. Wings of most pines apical) before being counted. Central scales, which and spruces separate readily from their seeds; the spread apart considerably on cone drying to permit wings are hygroscopic, so slight misting can facilitate easy release of seeds, were considered potentially seed their removal. For Douglas-fir, larch, and true firs, bearing (fertile). The extracted seeds were separated wings can be gently broken. Wings cannot be into filled and empty seeds by alcohol flotation removed from western redcedar or yellow-cedar (% ethanol) after dewinging. X-ray analysis (see without damaging the seeds. Section ..) indicated that .% of the seeds that Wings can be removed from small quantities of sank contained well-developed megagametophyte seeds by rubbing the seeds between the hands or tissue and a fully developed embryo, whereas .% against a screen or roughened surface. The same of those that floated were empty or had a rudimen- principle is employed for larger quantities by gently tary embryo. Empty and filled seeds were counted tumbling dry or wetted seeds in a rotating container and weighed to the nearest . mg. Cones (with seed such as a cement mixer. Loosened wings, small parti- wings) were dried in a forced-draft oven at °C for cles, and dust are removed from good seed in final  hours and weighed to the nearest . mg. cleaning. Small lots may be effectively cleaned using In jack pine, which is a predominantly serotinous a laboratory aspirator (Edwards ) or by flotation species, individual cones were dipped in boiling water in water. for up to  seconds to break the resinous bonds The seeds of Pacific yew may be extracted by mac- between cone scales (Rudolph et al. ). The cones erating the fleshy “berries” in water and floating off were dried in a circulating oven at °C until they the pulp and empty seed (Rudolf ). Alternatively, were fully open, after which the cone scales were the fruits can be soaked for – days in warm water, removed and the seeds were extracted by hand. then rubbed over screens and washed thoroughly to Seeds of most conifers (Douglas-fir, larch, western float off light seeds. The viability of yew seeds can be redcedar, western hemlock, etc.) are obtained by maintained for – years if, just after extraction, they drying cones to open them, shaking out the seeds, are dried at room temperatures for – weeks, and separating the seeds from cone scales and debris, then then stored in sealed containers at –°C. loosening the seed wings, and finally separating clean After twigs, leaves, and other debris have been re- full seeds from wings, dust, empty seeds, and other moved with a fanning mill (air separation combined small particles. It may be advantageous to run closed with screens), Rocky Mountain juniper seeds can be cones over sorting tables or screens to remove foliage extracted by running the fruit through a macerator and debris before the cones open. On freshly picked with water and floating away the pulp and empty seeds cones of many species (e.g., Abies), pitch is soft and (Johnsen and Alexander ). Dried fruits should be sticky. Chunks of pitch that become attached to soaked in water for several hours before macerating. extracted seeds may be extremely difficult to remove. Seeds should then be dried to less than % moisture Therefore, true firs should not be heated, but left content (mc) and stored between – and +°C. under cool, dry conditions on trays to disintegrate For additional information on conifer seed collec- naturally. Most other conifer species require only tion, processing, testing, and storage, refer to Stein et good ventilation and slight heating for several days to al. (), Edwards (), Eremko et al. (), and open the cones. Small lots of cones can be dried by Leadem et al. ().

section 3 natural seed production 53 .. Hardwood seeds Another good index of maturity is the presence of Hardwoods are more variable than conifers in the a firm, crisp, white, fully elongated seed within the time of flowering, seed maturation and dispersal, samara. The clusters can be picked by hand or with the type of seed-bearing structures (fruits), and the pruners and seed hooks. Fully dried samaras may be number of seeds per fruit (Tables ., ., .). Many shaken or whipped from branches of standing trees hardwoods are dioecious; in species such as ash, onto sheets spread on the ground. aspen, willow, and cottonwood, seeds are only pro- After collection, leaves and other debris can be duced on female trees. Since the fruits of species such removed by hand-stripping, screening, or using a as maple or ash contain only one seed, collection of fanning mill. Since the pubescence on the pericarp hardwood seeds may be more labour intensive. For can be very irritating to the nose and skin, a face convenience of discussion, the maturation, collection, mask and rubber gloves should be used when work- and processing of hardwood seeds is discussed by ing for extended periods with bigleaf maple seeds. fruit type. Maple seeds generally are not extracted from the samaras following collection. However, dewinging Samaras (Acer, Fraxinus) reduces weight and bulk for storage, since wings ac- Bigleaf maple seeds are double samaras, which turn count for about –% of samara weight (Zasada from green to reddish brown when ripe. The pericarp and Strong []). Empty samaras can be removed has a dry, wrinkled appearance when fully mature, readily on a gravity table. and the surface is covered with dense, reddish-brown Fraxinus samaras should be spread in shallow lay- pubescence. Within the pericarp is an embryo with ers for complete drying, especially when collected associated seed coats, but there is no endosperm. early (Bonner ). Dried clusters may be broken Seed collection may begin when the Acer samaras are apart by hand, by flailing sacks of clusters, or by fully ripened and the wing and pericarp have turned running fruits through a macerator dry. Stems and tan or brown (Zasada and Strong []). Acer seeds other debris can then be removed by fanning or with may be picked from standing trees or collected by air-screen cleaners. shaking or whipping the trees and collecting the samaras on sheets of canvas or plastic spread on the Catkins (Alnus, Betula, Populus, Salix) ground. Samaras may also be collected from trees Birch catkins should be collected while strobiles are recently felled in logging operations, and sometimes still green enough to hold together, or immediately gathered from the surface of water in pools or streams. after a rain to keep them from shattering (Brinkman Bigleaf maple seeds should be collected before a). In Populus and Salix, catkins should be the fall rains. Once the fall rains start, seed moisture collected as close to the time of seed dispersal as content () may increase from  to % (dry weight possible (Wyckoff and Zasada []; Zasada et al. basis) to as high as %. If bigleaf maple seeds re- []). Timing of collection can be based on catkin main attached to the tree, they may germinate colour (which changes from green to yellow or (Zasada ). Moisture also affects the longevity of yellow-brown) and the condition of the capsule. It bigleaf maple seeds, which apparently can exhibit is often best to wait until a few capsules start to split either orthodox or recalcitrant seed properties (Figure ., stage b) and then collect catkins from (Zasada et al. ; J. Zasada, unpublished data). The the plant, since this usually results in the most rapid significance of collecting before or after the start of opening and efficient seed extraction. Note that fall rains is that bigleaf maple seeds with low  be- insect-damaged capsules may appear to be dispersing have more like orthodox seeds, while seeds collected seeds, but are often still immature. Once capsules at high mc have characteristics similar to recalcitrant begin to open, the rate of seed dispersal is deter- seeds. The pubescent pericarp may play an important mined by weather conditions; under warm, dry, role in the moisture content of the samaras. windy conditions all seeds may be dispersed within Ash fruits occur in clusters of one-seeded samaras, a few days. and are collected in fall when their colour has faded If only limited numbers of seeds are needed, from green to yellow or brown (Bonner ). branches with attached, immature catkins of Populus

54 field studies of seed biology and Salix can be collected and ripened in a green- Populus catkins should be spread out in thin layers house or controlled environment (Wyckoff and in pans or on screens at room temperature (Wyckoff Zasada []; Zasada et al. []). Catkins must be and Zasada []). Seeds will be shed in – days, handled carefully after they have been removed from depending on the ripeness of the catkin. Seeds can be the tree. During transport catkins should be loosely extracted from the catkins with a shop-type vacuum packed in paper bags to allow for drying. Catkins cleaner with a clean cloth bag substituted for the dust placed in a warm dry spot will open in a few days, bag. Populus seeds can be freed from their cotton by and seeds can be collected as the capsules open. tumbling the seeds in a rotating drum or a stream of Since alder catkins do not disintegrate at maturity, relatively high-pressure air. For small quantities of they may be collected from standing or recently felled seeds, the uncleaned seeds can be placed between two trees as soon as the bracts (scales) start to separate on soil sieves and a high velocity air stream applied to the earliest-ripening strobiles. tumble the seeds in the container. Seeds should be After collection, catkins from Betula papyrifera extracted and placed in subfreezing storage (- to can be air dried on newspapers at room temperature -°C) as soon as possible, since seeds stored at –°C (–°C), and the achenes separated from catkin lose viability quickly. Storage with a desiccant appears bracts using a series of standard sieves, or with an air- to provide long-term benefit for Populus seeds driven seed blower (Bevington ). Seed samples (Wyckoff and Zasada []). can then be stored dry in sealed containers at -°C Salix catkins should not be left at ambient tem- until used. peratures, and seeds should be extracted and stored

a) e)

f)

b)

c)

g)

d)

 . Salix capsules at various stages of opening (a-e) and the dispersal unit at various stages (f,g) (Zasada et al. [1998]). (f) shows hairs while still in the capsule; (g) shows hairs fully deployed and separating from the seed. Seeds should be collected when capsules start to split (b).

section 3 natural seed production 55 at low temperatures as soon as possible (Simak ). acorns should be kept under moist, cold conditions. The seeds should be separated from the cotton to As a member of the white oak group, Garry oak ex- reduce bulk, and because storage with the cotton hibits recalcitrant storage behaviour (Section .), so may reduce viability (Simak ). To clean small- to the mc must not drop below –%. medium-sized lots, place catkins in a single layer in screen-covered boxes in a relatively warm, dry area Drupes (Cornus, Prunus, Rhamnus) (–°C, –% relative humidity), with good air Dogwood fruits are ovoid drupes which ripen in fall. circulation (Zasada et al. []). If capsules are be- To reduce losses to birds, fruit should be collected as ginning to open when collected, opening will be soon as ripe by stripping or shaking from the branches. completed in ‒ days. The seeds separate easily from Ladders may be useful for collecting fruit from taller the cotton if the catkins and the cotton containing trees (Brinkman a, b). the seeds are placed in a container, so the material Bitter cherry fruits should be collected in late can be blown in an air stream or tumbled in a cement summer or early fall when fully mature and dark red. mixer. Seeds can be separated from coarser and finer Fruits are collected by hand-stripping, or by spread- residue by passing them through a screen or sieve. At ing sheets of suitable material under trees to catch the this time seed mc should be close to the –% rec- natural fall or fruits shaken off the trees (Grisez ). ommended for storage (Simak ). To maintain Fruit may be carried in bags, but boxes or baskets maximum viability, seeds should be placed in sealed provide better protection against bruising and spoilage. containers and stored between - and -°C. Cascara fruits should be picked in late summer or Note that the seed quality of both Salix and fall. The fruits are relished by birds so they should be Populus can be graded to a certain degree by passing harvested about  weeks before they are fully ripe seeds through a nest of soil sieves. In general, the (Hubbard ). largest and best seeds will be found on larger sieve To extract seeds of fleshy fruits, most species can openings (J. Zasada, pers. comm., ). be macerated in a blender. Maceration can be facili- Alder strobiles will open after being exposed in tated by softening fruits for – days in running water drying racks in a well-ventilated room for several (or with daily water changes). The mixture is then weeks at ambient air temperature (Schopmeyer ). placed in water to separate the pulp and empty They can be opened in a shorter time by drying them seeds from the good seeds by flotation. Seeds are in a kiln at –°C. Most seeds will fall out of the thoroughly air dried and placed in sealed containers strobiles during the drying process; however, the for storage at –°C. remaining seeds may be extracted by shaking or Dogwood stones can be sown without extracting tumbling if necessary. them from the fruit, but seeds to be stored usually are cleaned to reduce bulk (Brinkman b). If fruits Nuts (Quercus garryana) cannot be cleaned soon after collection, they should Garry oak acorns are brown when they ripen in late be spread in shallow layers to prevent excessive heat- summer and early fall; they may be collected from ing, although slight fermentation may facilitate the ground, or flailed or shaken from branches onto removal of the pulp. The stones can be extracted by canvas or plastic sheets (Olson ). Garry oak macerating the fruit in water and allowing the pulp belongs to the white oak group, which is character- and empty stones to float away. Clean, air-dried ized by seeds with little or no dormancy, so acorns stones may be stored in sealed containers at –°C. should be collected soon after they have fallen to For bitter cherry it is usually desirable to clean retard early germination. seeds of all pulp and juice (Grisez ). Cleaning is The only processing required before storing or sow- done by macerators with water to float off or screen ing Garry oak acorns is removal of loose cups, twigs, out the pulp. Small quantities may be cleaned by and other debris (Olson ). However, the propor- soaking and rubbing over a screen. Fermentation tion of sound seeds can be increased by removing has been used to soften fruit, but germination may defective, hollow, and partially consumed acorns, be severely reduced if seeds are allowed to become either by flotation or by hand. To retain viability, too warm or to ferment too long.

56 field studies of seed biology Cascara fruits can be allowed to decay for a few collected either by picking the fruit from the tree or by days to soften the pericarp, but usually fruits are run gathering fallen fruit from the ground (Crossley ). through a macerator with water soon after collecting, Pacific crab apple seeds may be extracted by then the pulp is skimmed off (Hubbard ). putting the fruits through a macerator with water, floating off the pulp, and screening out the seeds. Berries (Arbutus menziesii) Seeds should be dried to less than % mc and stored The fruit of arbutus is a berry with a thin, rough, at –°C (Crossley ). granular skin, which is bright red or orange red when ripe. Berries can be collected from standing trees . Assessing Factors that Reduce Seed Yields from October to December (Roy ). Arbutus berries can be dried at room temperature Seed yields are sometimes lower than expected or or seeds can be separated from the pulp immediately predicted and we must identify when or why these after being collected. Fresh or dried fruit can be losses occur, either to verify the value of predictive soaked in water in a warm place to soften the pulp. equations or to prevent future losses. In this section, Fruits then can be macerated and the seeds separated we examine the effects of serotiny and predation on from the pulp by flotation. Seeds or uncleaned ber- seed yields. Seed crop losses may occur due to envi- ries should be thoroughly dried, then stored in ronmental factors, disease, or animal predation, and airtight containers at –°C (Roy ). can be analyzed using life tables (Figure .). Life tables quantify the magnitude and sources of loss Pomes (Malus fusca) and are helpful in interpreting seed crop failure. The pomes of Pacific crab apple are yellowish to reddish Life tables might also be applied to hardwood when they ripen in late fall. Ripe crab apples may be flower production and seed development.

Age interval Number Mortality Number Percent (months) cones alive factors dying mortality

0–1 1182 C. pinus pinus 37 3.13 Abortion 27 2.28 Missing 1 0.08 Breakage 2 0.17 Unknown 9 0.76 insects 76 6.42

1–2 1106 Abortion 13 1.10 Shoot borer 23 1.95 Missing 1 0.08 37 3.13

2–5 1069 Abortion 122 10.32 Missing 5 0.42 Squirrel 4 0.43 131 11.08

Conelets remaining 938 Total mortality 244 20.54

 . Partial life table for 1981 jack pine conelet crop, Oneida County, Wisconsin (adapted from Rauf et al. 1985). Life tables quantify the magnitude and sources of loss and are helpful in interpreting seed crop failure.

section 3 natural seed production 57 .. Assessing serotiny Classes of resin-bond rupture Some conifers do not shed their seeds when they . fully open cone scales free over –% of cone surface mature in the fall, and instead may retain their seeds . partly open scales free over –% of cone surface in the cones for several years. This is termed serotiny, . closed scales free over –% of cone surface but is sometimes called canopy banking (as opposed to seed banking in the soil). Serotinous species retain Classes of weathering as index of age their seeds in tightly closed cones until high tempera- – yr no evidence of weathering tures (such as those achieved in a forest fire) open the – yr weathered over –% of surface cones. The degree of serotiny appears to depend on – yr weathered over –% of surface such factors as the frequency of fire, the local climate, – yr weathered over –% of surface and hybridization between interior populations that + yr weathered over entire surface are predominantly serotinous and coastal popula- tions that are not. Serotiny has great silvicultural .. Assessing predation significance because large quantities of seeds are Seeds represent an excellent food source because potentially available for release after fires or of their stored reserves, thus mature seed crops are harvesting. attractive to insects, birds, squirrels, or other animals. In British Columbia, coastal lodgepole pine is This section primarily describes predation of imma- primarily non-serotinous, whereas interior lodgepole ture seeds (pre-dispersal); for a detailed discussion of pine usually bears serotinous cones (Eremko et al. ). the predation of mature seeds, see Section . In both varieties, cones remain on the trees for many During excellent seed years there are usually more years, but freshly ripened cones have the highest than enough seeds to support both animal predation number of viable seeds. Jack pine are serotinous over and natural regeneration. In moderate years, how- most of their range, although southern sources tend ever, predation can present a problem. Since predator to be non-serotinous. Black spruce cones are semi- populations usually lag a year or so behind abundant serotinous; the cones remain on the tree and the seed crops, a mast year is often followed by a poor seeds are viable for several years (Safford ), year with higher predator populations. Insect and and sometimes as long as  years (J. Zasada, pers. disease damage to seeds and cones may range from comm., ). moderate to severe, and sometimes can result in To estimate the quantity and quality of seeds the loss of an entire seed crop (Miller et al. ; available for regeneration, it may be necessary to Schmid et al. ). Depending on the type of insect assess the age of serotinous cones. Eremko et al. or disease, the attack may occur any time from bud () provide photographic examples of lodgepole initiation to final seed development. Damage may pine cones in different age classes, and recommend result in cone or seed abortion or in partial or com- that, for lodgepole pine, only cones in classes I and II plete destruction of cones or seeds (Mattson ). (i.e., less than  years old) be collected. The cones Effects are sometimes indirect, for example, insects or should be only partially weathered and completely disease may cause the premature opening of cones so closed. that seeds are shed before they are fully developed. Viability of seeds in serotinous cones of harvested Insect predation can alter cone crop phenology trees can decline rapidly, and older cones present (Rauf et al. ) and seed dispersal, and may cause in the slash may have to be discounted as a source conelet and cone mortality. Seed losses due to insect for natural regeneration of a site. Ackerman () predation can be determined by dissecting the cones found that  years after logging there was a sub- and examining cone length, width, and the number stantial decrease in the germination percentage of of sound, hollow, and insect-damaged seeds (Schmid seeds. To conduct his study Ackerman devised et al. ). The percentage of seeds damaged in each scales to classify the degree of serotiny and degree cone may vary, depending upon the insect species. of weathering of lodgepole pine cones present in In areas where squirrel predation can have a major logging slash: impact on natural seed production, it is advisable to

58 field studies of seed biology collect cones early, but only if seeds can be ripened suf- . Experimental Design ficiently under artificial conditions. Hurly et al. () found that intensive harvesting by red squirrels began “Cheshire Puss,” she began, “would you tell me, please, in early September, and most caching occurred in late which way I ought to go from here?” September and October. Early in this period most cones “That depends a good deal on where you want to go to,” cut were eaten rather than cached. Caches are easily said the cat. found; cones can be recovered from the caches within (Lewis Carroll “Alice in Wonderland”)  weeks following the peak of caching behaviour. More information on cone and seed insects is available in Hedlin (), Hedlin et al. (), Ruth A study design is a plan for obtaining the maximum (), and Ruth et al. (). amount of information from available resources (Sit Microbial diseases may also be considered seed ). A good design should begin with clear, well- predation, and substantial cone and seed losses due defined objectives. Three general objectives of natural to disease occur each year. For further information seed production studies are: on cone and seed diseases of North American • estimation (e.g., how many seeds per cone?) conifers, refer to Sutherland et al. () and • modelling (e.g., what is the relationship between Ruth et al. (). seed production and stand, tree, and crown characteristics?) .. Using X-ray analysis to determine causes • comparison (e.g., is seed morphology the same of loss in cliff and swamp areas?) Seed X-rays are a quick and effective way to analyze seed production, but they depend upon the use of .. Estimation studies expensive X-ray equipment. If such equipment is To estimate a parameter such as the average number available, X-radiography can provide non-destructive of seeds per cone or the total number of seeds in a measurements of the number of filled, immature, plot, proper sampling design must be considered to and empty seeds, as well as the numbers of seeds ensure that the estimates are unbiased. Many sam- which have been damaged or attacked by insects (Fig- pling designs can be used, such as simple random ure .). In research studies, comparison of seeds to sampling, cluster sampling, stratified sampling, and their X-ray images facilitates the efficient removal of multistage sampling. For detailed discussions on empty seeds. For detailed procedures, see Section these and other sampling schemes, refer to Cochran .. and Leadem (). (), Thompson (), and Buckland et al. ().

a) b) c) d)

 . X-rays of tree seeds (Leadem 1996). X-rays are used to determine whether seeds are fully developed, damaged, or have been attacked by insects. (a) mature seed: c = cotyledon, m = megagametophyte, r = radicle, s = seed coat; (b) immature seed; (c) insect larva; (d) damaged seed.

section 3 natural seed production 59 Regardless of which sampling design is chosen, Y = a ,  + e b-cX sampling should be done through a random mecha- nism. This will ensure that no systematic bias will be has three parameters (a, b, and c) and requires at least introduced to the data. Sometimes, due to convenience  data points. or convention, an investigator may subjectively select The data collected should also cover the full range samples that are considered typical for the popula- of interest. For example, suppose you want to model tion of interest. These samples, called representative the relationship between cone production and accu- and judgement samples, are discouraged because mulated growing degree-days (gdd). If you want they are subject to personal bias and their statistical to use the model to predict cone production for properties are unknown. Systematic samples are often – gdd, then the data you use in developing taken because of their ease of execution. However, the model must span the range – gdd. The they can be unreliable, especially when the sampling resulting model would only be suitable for predic- scheme coincides with an underlying pattern in the tions within this range; extrapolations beyond the sampling population. It is best not to consider sys- range would be unreliable. tematic samples for estimation. In general, more data points are needed for com- To capture the variability in the population of plex relationships than for simple relationships. interest, the sampling design must provide an ad- equate sample size. The sample size depends on the .. Comparative studies variability in the population, the accuracy desired, In contrast to sampling for estimation and modelling, and the cost. You may want to consider stratifying the comparative studies require an experimental design. collection of samples (e.g., collecting from different In a comparative experiment, treatments are randomly levels of the crown of a tree) to reduce variation and assigned to a number of experimental units (the better understand effects of position (vertical and smallest collection of the experimental material to horizontal). For estimation type studies, the sample which a treatment is applied). If you wish to compare size can be determined using confidence interval seed morphology in two different habitats (e.g., cliff methods. See Section .. for a discussion and an and swamp), five sites each can be selected randomly example of sample size determination methods from all cliffs and swamps within the population of using confidence intervals. interest. Within each site,  trees can be selected for cone measurement. In this example, a site is the ex- .. Modelling studies perimental unit; a tree or a cone is a subsample. To sample for modelling, the sampling guidelines Comparisons based on a single application of the discussed above should be followed. All variables treatments are unreliable because variations are ex- involved in the model must be sampled from the pected between experimental materials. Differences same sampling points. For example, if you want to between a cliff site and a swamp site could be due to relate the number of seeds per cone with the number differences in the habitat, or to natural variation from of exposed seeds in the cone half-face, then the total site to site, or both. The only way to distinguish seeds per cone and the seeds in the half-face must be the possible causes of variation is to replicate the determined from the same cone. treatments. To model a relationship, there must be enough Replication of a treatment is an independent data to capture the relationship between the vari- observation of the treatment. The number of replica- ables. A general rule is to have at least  data points tions is the number of experimental units to which a per parameter involved in the model. For example, a treatment is assigned. Replication should not be straight line model, confused with subsamples, which are multiple meas- urements of a single treatment. In the cliff/swamp Y = a + bX, example, each treatment is replicated five times. The  trees within each site are subsamples. Pseudo- has two parameters, Y-intercept (a) and slope (b), replication occurs when replication is claimed when and requires at least  data points. A logistic model, in fact there is none. Pseudoreplication usually leads

60 field studies of seed biology to underestimation of the variability in the data. See analysis depends on the design plan, while the design Bergerud () for additional discussion of pseudo- plan is strongly influenced by the analysis method replication. deemed to be the most suitable for the data. The The number of replications necessary for a study analysis method should conform with the design depends on the variability in the data, the size of of the study, the nature of the data, and the study difference you wish to detect, the significance level objectives. desired, and the desired statistical power. Power analysis is the computation of statistical power for .. Estimation studies an experimental design, and should be carried out If the objective of a study is sampling for estimation, before the experiment to determine the amount of then care must be taken to ensure that the formulae replication required. For more discussion on the use for computing mean, total, and standard error are of power analysis for sample size determination, see appropriate for the chosen sampling scheme. A com- Cohen () and Nemec (). mon mistake is to use formulae for simple random Random assignment of the treatments to the sampling design in more complex designs, which experimental material is also essential to sound results in underestimation of the standard error of experimentation. Randomization assures that no the estimate. That is, the estimate would appear more systematic bias is introduced to the experiment, reliable than it really is. Nemec () provides an and the natural variation is approximately the same example that illustrates the consequences of using within each treatment group. Sometimes random simple random sampling formulae for data collected assignment of the treatments to the experimental from cluster sampling. material is not possible. In the cliff/swamp example, it is not possible for the experimenter to assign a cliff .. Modelling studies or a swamp to a particular location; an area is a cliff When the objective is to sample for modelling, then or a swamp before the experiment is even conceived. regression and correlation are typical analysis meth- In this case, to satisfy the randomization criteria, cliff ods. Depending on the relationship between the and swamp sites must be randomly selected from variables of interest, linear or nonlinear regression all cliff and swamp sites within the population of may be required. If the goal is to determine the best interest. Subsamples for measurements must also be set of variables for predicting a relationship, then randomly chosen within each experimental unit. stepwise regression can be used to systematically The design of a comparative experiment depends eliminate any unnecessary variables. largely on the treatments to be compared, the experi- Regression assumes that the residuals (the differ- mental material available, and the type of data to be ence between the observed data and the predicted collected. Common experimental designs employed values) are normally distributed, with a mean equal in seed production studies include completely to zero and a constant standard deviation. The nor- randomized design, factorial designs, and random- mal distribution of the residuals can be checked ized block design. For discussions on these and other using a normal probability plot on the residuals. An experimental designs, see Sit (). apparently straight line indicates that the residuals It is vital that the sampling design and experimen- are approximately normally distributed. Regression tal design optimize all essential factors of the study. also assumes that the residuals are: a) independent of Researchers should discuss their designs and analysis the values in the explanatory variables (x-variables), plans with a statistician before implement-ing a study and b) have equal variance for all values of the ex- to ensure that all relevant factors have been considered. planatory variables. The independent and equal variance assumptions can be checked by plotting the . Data Analysis residuals against the predicted values derived from the regression model. A random scatter of the points The success of an experiment requires both a well- implies that both assumptions are satisfied. designed plan and an appropriate analysis method, Violation of the normality and equal variance because the two are closely related. The method of assumptions sometimes can be corrected by

section 3 natural seed production 61 transforming the data using square root, natural log, that is, it explains most of the variation in the data or exponential functions. Transformation should not with the minimum number of variables. Rawlings be done routinely without first checking the resi- () may be consulted for further information on duals. Keep in mind that the regression assumptions regression analysis. See also Sit and Poulin-Costello are for the residuals, not for the data. It is possible () for additional discussions on nonlinear to have non-normal data, but normal residuals. A regression. common mistake is to examine the data and apply If the objective is to assess the strength of the transformation when the data are not normal or relationship between two variables, then correlation have unequal variance. analysis can be used. There are two types of correlation: Regression is a robust procedure against slight Pearson product-moment correlation coefficient, departures from normality and equal variance when r(p), and Spearman’s rank order correlation coeffi- the data set is large. That is, with a large data set, you cient, r(sp). The Pearson correlation assesses the can still use regression on the data (without transfor- linear relationship between two variables (see mation) for slightly non-normal residuals. However, Figures .a and b), and is based on the observed like most statistical procedures, regression is not ro- data. Spearman’s correlation assesses the monotone bust against independence. That is, regression results relationship between two variables, that is, whether are invalid if the residuals are dependent (e.g., when the two variables have a strictly increasing (linearly large residuals tend to associate with large x-values.) or nonlinearly) or strictly decreasing relationship Provision for randomization during data collection (see Figures .c and d). Spearman’s correlation is will ensure that the data, and thus the residuals, are based on the rank order of the data, with tied scores independent. assigned the average of the scores that would have To assess the goodness of fit of a model to the been assigned had no ties occurred. data, the coefficient of determination, r2 value, can be A correlation coefficient must have a value between calculated. The coefficient of determination represents + and -. A positive value implies that the two vari- the proportion of variation in the data explained by ables increase together; a negative value implies that the model. The higher the r2 value, the more varia- one variable increases as the other variable decreases. tion is accounted for by the model. The r2 value is A Pearson correlation coefficient near zero implies directly related to the number of explanatory vari- there is no linear relationship between the two ables in the model: the more explanatory variables variables, but the two variables may be related in a there are, the higher the r2 value. When comparing nonlinear way (see Figures .c, d, and e). A Spear- several regression models, it is more suitable to use man’s correlation coefficient near zero implies 2 the adjusted coefficient of determination (r adj) which that the two variables do not increase or decrease is r2 modified by the number of explanatory variables together, but they may be related in a curvilinear 2   in the model. A model with large r adj is favourable, manner (Figure . e).

a) b) c) d) e)

 . Correlation coefficients for hypothetical relationships. r(p): Pearson product-moment correlation coefficient; r(sp): Spearman’s rank order correlation coefficient.

62 field studies of seed biology .. Comparative studies For discrete data such as seed crop rating or the If the objective is to compare the effects of several number of full and empty seeds on a tree, contin- treatments on seed production, then analytical meth- gency table tests (chi-square test, Sections . and ods should be used. The method chosen depends on ..) or log-linear models could be used. If data are the nature of the data and the design of the study. collected on the same units over time and the objec- For continuous data such as seed weight, seed length, tive is to assess trend, then repeated measures analysis or seed width, methods such as the t-test and analysis methods should be considered. See Nemec () for of variance (anova) F-test could be used for anal- detailed discussions of repeated measures analysis. ysis. Both the t-test and the anova F-test assume normally distributed residuals. This assumption can . Seed Production Case Studies be checked by plotting the residuals in a normal probability plot (see Section ..). If the residuals Six seed production case studies, taken from the are far from normal, then nonparametric procedures literature, are summarized below. To highlight the such as the Wilcoxon tests could be used. Refer to design and analysis aspects, the studies are presented Sections ., .., ., and .. for discussions of in point form. The cautions given at the end of each anova analysis. See Sit () for a detailed discus- case emphasize the items that require special atten- sion of anova. tion to ensure that study objectives are met.

CASE STUDY 1: Estimating potential Engelmann spruce seed production on the Fraser Experimental Forest, Colorado (Alexander et al. 1986) Objectives . Regression was used to relate the number of filled • To predict the frequency of good seed crops. seeds per trap and the total seedfall per trap. • To relate seed production to stand, tree, and or . Stepwise regression was used to select the best set crown characters (sampling for modelling). of stand, tree, and/or crown measures for Study Design predicting seed production.  . The sampling was carried out over a long period . Transformation of the data may be considered to of time (annually for  years). correct for heterogeneity of variance before . Thirteen permanent sample plots with  seed regression; possible transformations are square traps were randomly located in each plot. root and natural log. . Seed trap contents were collected each fall and Cautions again the following spring. • Sampling units should be randomly selected from . Only filled seeds were counted; the response all possible units. variable was the number of filled seeds per trap. • Seed traps should be randomly located within Data Analysis each sampling unit (sample plot). . The sample mean (by plot) was the best estimate of • Seeds from several traps should not be bulked. average number of filled seeds per trap. • If data are collected over a long period of time, . anova was used to test for location and year check whether the model residuals are effects. independent; and consider using time-series . Seed counts were transformed (x + ⅜ ) to models or repeated measures (incorporating lag stabilize variance. variables in the regression).

section 3 natural seed production 63 CASE STUDY 2: Comparative seed morphology of Thuja occidentalis (eastern white cedar) from upland and lowland sites (Briand et al. 1992) Objectives adjust the α-probability level for simultaneous • To test whether a relationship exists between seed comparisons to reduce the risk of Type I error. morphology and the habitat where seeds are . Satterthwaite’s approximation (Zar ) was used produced (cliff and swamp). to compute % confidence intervals based on the • To explain the greater root plasticity among t-distribution. upland seedlings. . Pearson product-moment correlation coefficients Study Design were computed between all characters. . This is a one-factor completely randomized design Cautions with subsamples. • Since cliff and swamp could not be assigned to an . Three cliff sites and three swamps were randomly area, sites were randomly selected from all cliffs selected. and swamps within the population of interest. . Ten trees were sampled at each site; five cones were • Be careful when identifying the experimental unit. collected from each tree for measurements. In this example, an individual site is the experi- . Responses included total number of seeds, mental unit, not tree, or cone. number of fully developed seeds per cone, seed • The trees in the two habitats should be as similar as fresh weight, seed length and width, embryo area possible to avoid confounding the habitat and tree length and width, and right wing length and characteristic factors (e.g., cliff sites had older trees). width. • If the two habitats had trees of different ages, age Data Analysis could be used as a covariate in the analysis of co- . anova was used to compare the responses of the variance, provided that the covariate (age) is not two habitats (at significance level .). affected by the factor of interest (in this case, . Sequential Bonferroni technique was used to habitat).

CASE STUDY 3: Cone size and seed yield in young Picea mariana trees (Caron and Powell 1989a)

Objectives Data Analysis • To investigate the variation in cone size, seed yield . Correlation was used to assess the relationships of per cone, and seed weight from cones collected in the nine response measures.  plantations in three consecutive years. . Regression was used to relate the number of filled • To determine the correlation between cone size, seeds per cone to the number of pollen cones seed yield per cone, and seed weight. per tree; logarithmic transformation was used on • To examine the relationship between pollen the response variables to correct for unequal abundance and filled seeds per cone. variance. Study Design Cautions . Five plantations (, , , , and  years from • Correlation can be used to assess the relationship seed in ), located in northwestern New between two variables, but Pearson correlation can Brunswick, were used in the study. assess only linear relationships. It is possible that . Two study areas were selected within each planta- two variables are nonlinearly related and the tion; trees were randomly selected for measurement. correlation coefficient is near zero. . Responses included cone length, cone weight, total • A variable that shows a high correlation to seed scales per cone, potential filled seeds per cone, yield per cone may not be the best predictor total seeds per cone, total filled seeds per cone, for seed yield; another variable that is nonlinearly seed efficiency, weight of  filled seeds, and related with seed yield may be a better predictor. weight of  empty seeds. • Always plot the data in a scatter plot.

64 field studies of seed biology CASE STUDY 4: Prediction equations for black spruce seed production and dispersal in northern Ontario (Payandeh and Haavisto 1982) Objective was fitted to the data to relate seed viability (Y) • To use nonlinear regression to relate the number with seed cone age (X). of black spruce seeds per cone with cone age and . An exponential decay-exponential model, crown class. B e-B3X2 B e-B6/X2 Study Design Y = B X 2 + B X 5 , . Data on seed production (number of seeds per cone and cone age in years) were collected from was developed to relate estimated seedfall per black spruce in three crown classes: dominant, hectare (Y) with strip width (X) and distance codominant, and intermediate. from stand edge (X). . Two sets of data on seed dispersal across the Cautions stripcuts were also available for modelling. • Enough points are needed to cover the entire Data Analysis X-range. -B X . A simple exponential decay function, Y = Be 2 , • Know the form of the equation, and the deriv- was fitted to the data to relate the total number of atives with respect to the unknown parameters, seeds per cone (Y) with cone age (X) for each and an estimate of the parameters (starting point crown class. for iteration). . An inverse sigmoidal function, • Models should be compared based on adjusted r2. • Do not extrapolate results from the fitted models -B X B Y = B - B(1 - e 2 ) 3, beyond the range of the original data.

CASE STUDY 5: Estimating sound seeds per cone in white spruce (Fogal and Alemdag 1989)

Objectives Data Analysis • To determine whether the number of filled seeds . The mean and coefficient of variation were cal- per cone half-face is a valid indicator of the total culated for each of the four variables for each number of seeds per cone. location and crop year. • To determine the relationship between the num- . anova was use to compare locations and years ber of filled seeds per cone and cone length and based on the number of seeds per cone. diameter. . Scattergrams were prepared for each location and • To determine whether the relationship is the same year to visually assess possible relationships across time and location. between number of sound seeds per cone and Study Design number of sound seeds per section, cone length, . Cone data were collected from three white spruce and diameter.  plantations in  and . . Multiple regression was used to relate the number . Seed counts were made on  cones from each of of sound seeds per cone with the following  trees at each location. independent variables: number of sound seeds per . Measurements included cone length and maxi- section, cone length, and cone diameter. Eight mum diameter, number of sound seeds per section models were fitted to the data. on one cone half-face, and number of sound seeds Cautions per cone. • Use adjusted r2 to compare models, not r2.

section 3 natural seed production 65 CASE STUDY 6: Consistency of cone production in individual red pine (Pinus resinosa) (Stiell 1988)

Objectives Data Analysis • To compare production by stand and by . Linear regression with square root transformation individual trees at two dates ( and ). was used to relate crop size to tree size at both • To relate cone production to stem diameter and dates, and to relate  crop size to  crop size. subsequent diameter growth. . Potential cone production was approximated Study Design using the sum of both mature and aborted cones.     . Data were collected from an -year-old red pine . Relationship between crop size to – plantation that was established as a spacing trial. basal area growth was also analyzed. . Permanent sample plots were established for each Caution of six spacings. • Use adjusted r2 to compare models. . Cone counts were made on mechanically selected, numbered trees in  and .

66 field studies of seed biology SECTION 4 SEED DISPERSAL

Lo! sweetened with the summer light, the full-juiced apple, waxing over-mellow, Drops in a silent autumn night. (Alfred, Lord Tennyson “The Lotus-Eaters”)

. Background with the seed coming to rest at the spot where it will eventually germinate or die. While trees remain Seeds may have many potential fates, as shown by the stationary over most of their life span, their seeds descriptive model (Figure .), which follows the dis- and pollen can travel great distances during dispersal. persal of the seeds of eastern redcedar. Seed dispersal Effective seed dispersal, by enhancing the capacity of refers to the movement of seeds or fruit, beginning individuals to colonize new locations, may determine with seed release from the parent tree and ending the survival of the next generation of plants.

 . A descriptive model of eastern redcedar (Juniperus virginiana L.) cone-crop dispersal from June through May of the following year (Holthuijzen et al. 1987). Numbers are percentages of the total cone crop and are means for four sample trees.

section 4 seed dispersal 67 There are six major types of seed dispersal: wind • What is the temporal distribution of seeds: dispersal, vertebrate dispersal (ingestion), ant disper- – over a day? sal, ballistic dispersal (where the seeds are ejected – over a season? explosively from a seed pod), adhesive dispersal (seeds – over a year? that have hooks, barbs, or sticky substances that cling – over several years? to fur or feathers), and unassisted dispersal (where no obvious dispersal adaptation is present) (Hughes • How does opening size (or any of the other factors et al. ). Seeds and fruits of British Columbia tree that affect dispersal patterns) influence the density species are usually wind dispersed, vertebrate dis- and/or distribution of seeds? persed (ingestion), or unassisted (gravity). A second • What proportion of dispersed seeds undergo form of vertebrate dispersal is also found in British secondary dispersal? Columbia, where highly nutritious, long-lasting seeds • Which species exhibit secondary dispersal? are moved to food caches and stored for later use. • Under what conditions does secondary dispersal This section will look at primary and secondary occur? dispersal of British Columbia tree species, some • How do primary and secondary seed dispersal methods for quantifying seed dispersal, and typical patterns affect what seral communities are likely to methods for analyzing the data. become established during primary or secondary succession? .. Why study seed dispersal? • How do different silvicultural treatments affect the Seed dispersal is of interest to plant ecologists and distribution of seeds? to researchers studying evolution (see Harper ). Seed dispersal patterns influence the genetic structure .. Mechanisms of seed dispersal of tree populations, variation in the composition of Seed dispersal has two phases (Watkinson ): forest stands, and the success of many silvicultural primary dispersal, in which seeds travel from the prescriptions for natural regeneration. Many studies parent tree to the surface of the ground; and second- use tree seed dispersal as a starting point, because ary dispersal, during which the seeds are moved by natural regeneration of a species requires suitable one or more agents after hitting the ground. levels of seed production and seed rain (the overall Primary dispersal may be passive (the seeds fall input of seeds per unit area per unit time). Estimates to the ground because of gravity), generally found of stand-level seed production and seed rain are often in large-seeded species such as Garry oak or Rocky a component of silvicultural system trials. Mountain juniper, or dispersal may be aided by Questions that might be asked in seed dispersal traits that facilitate active seed movement by wind, studies include the following: water, or animals. For seeds of most western conifer species, wind is the primary dispersing • What is the primary seed dispersal mechanism for mechanism (McCaughey et al. ), so seeds of a species? white spruce, subalpine fir, western larch, and • How does the seed dispersal pattern of one species western white pine, for example, have aerodynamic affect establishment of another species? (For exam- adaptations such as wings to aid in the dispersal ple, interspecific competition for germination sites.) of seeds. • What is the species composition of the seed rain, Wind dispersal is also common in northern angio- and how does it vary from year to year, or from sperm tree species, and many have evolved structures place to place on the landscape? to optimize the distance their seeds are carried. The • What is the spatial distribution of seeds relative to major categories of wind-dispersed angiosperm good germination spots, source trees, etc.? Are fruits are samaras (the self-rotating, winged seeds there differences among species? What are the of most Acer and Fraxinus spp.), plane-winged seeds primary factors affecting the distribution? (like those produced by Alnus spp. and Betula spp.), • What spatial patterning is exhibited (in terms of and the light plumed seeds produced by Populus uniformity, clustering, linear gradients)? and Salix.

68 field studies of seed biology Many trees and shrubs have brightly coloured, crusted snow, accumulating in large numbers in nutritious, fleshy fruits that are consumed by birds small depressions. and other animals. Among British Columbia tree species, this dispersal mode is used by wild cherries .. Timing of seed release (Prunus spp.), hawthorns (Crataegus spp.), mountain The timing of seed rain for different species can be ash (Sorbus spp.), Pacific dogwood, and cascara. placed into three categories: () species whose seeds Other trees have large wingless seeds that are often mature in summer and disperse during the current moved to distant microsites by hoarding animals or growing season; () species whose seeds mature in birds. Several British Columbia tree species, such as late summer and are dispersed during the dormant Garry oak, yew, and several pine species including season; and () species whose seeds mature in late whitebark pine, use this dispersal mechanism. Clark’s summer, but dispersal is delayed for several to many nutcracker (Nucifraga columbiana) is the primary years (species with serotinous and semi-serotinous dispersal agent of limber pine and whitebark pine cones) (Zasada et al. ). seeds. These seeds may be moved long distances to caches under forest litter. Some seed predators (Sec- . Species that disperse seeds in summer include wil- tion ) inadvertently act as dispersers because many lows, trembling aspen, and balsam poplar. The of the hoarded seeds are never consumed and germi- dispersal period for these species is usually not nate in the caches (Hutchins and Lanner ). more than  month. Secondary dispersal refers to the movement of . Fall and winter seed dispersal occurs in most western seeds after they have fallen to the ground. Secondary conifers, as well as birch, alders, and some willows dispersal can result in very long-distance seed move- (McCaughey et al. ; Zasada ). Timing of ment, but more often results in movement over only seed dispersal from mature conifer cones and alder short distances (Zasada et al. ). Even seeds catkins is determined by the occurrence of weather adapted for dispersal by wind or birds can be moved which dries them, opening the scales and allowing by other dispersal agents before they eventually come the seeds to be released (Harrington et al. ). In to rest. Seeds may be cached by chipmunks, but be general, wet weather keeps cones and catkins closed, redistributed by water during spring runoff or moved and wet weather following dry weather closes cat- by wind across snow. kins, terminating a dispersal period. Water is the agent with the greatest potential for In fall-dispersed seeds, dormancy require- long-distance secondary dispersal of seeds. Tree ments are satisfied after seeds have reached the species found in floodplains often have their seeds ground. In winter- or spring-dispersed seeds, the dispersed by water, and the movement of seeds on dormancy requirements may be partially or com- rivers has been observed for many species. Seeds of pletely met while the seeds are still attached to the Populus seem to be adapted to this type of dispersal parental tree. In some species this results in germi- as they readily germinate and root under water nation while seeds are still attached to the tree (Zasada et al. ). (e.g., bigleaf maple) (Zasada ). The importance of over-snow dispersal depends . Delayed dispersal occurs in several serotinous spe- on the time of seed dispersal, the quantity of seeds, cies, such as black spruce, jack pine, and lodgepole and the timing of annual snowfall (Dobbs ; pine (see Section ..). Black spruce retains its Matlack ). Seeds dispersed before the first winter seeds in semi-serotinous cones for many years, and snow cannot be transported in this manner. annual seedfall occurs as cones gradually open. Secondary seed dispersal may result in movement Seed dispersal is usually greater in late spring and of seeds over a short distance, however, the move- summer, but some seeds may be dispersed year- ment may be very important, such as when seeds are round (Zasada ). Fire flexes the scales of moved to a better microsite than would have resulted serotinous cones, thus large quantities of seed may from primary dispersal (Zasada et al. ). Seeds be dispersed immediately after a fire. Timing and released during the winter from western hemlock, length of the dispersal period depends on fire Alnus, and Betula can be dispersed by wind across intensity and weather. Most serotinous species have

section 4 seed dispersal 69 hairs or wings, adapting them for dispersal by wind When seeds are eaten, birds and mammals can (Hughes et al. ). Wind dispersal may be en- defecate or regurgitate the seeds far from their point hanced in the immediate post-fire period because of origin. Generally, among fruiting species, small fire opens the canopy and clears the ground of seeds are dispersed farther than large seeds (Hoppes obstacles to the passage of wind and seeds (Hughes ). The dispersal distances for ingested seeds are et al. ). limited by gut passage rates, which vary from a few minutes in frugivorous birds to several months in .. Dispersal distance ungulates (see review by Willson ). The direction The distance a seed travels from its parental source of seed movement and the local density of seed de- depends on its mode of dissemination—gravity, position will be influenced by the behaviour of the animals, or wind. Dispersal distance is often expressed particular frugivore (Stiles ). Caching of seeds by as a dispersal curve (Figure .), which is the frequency squirrels and chipmunks also extends the dispersal distribution of dispersed seeds versus the distance distance of the seeds. Clark’s nutcrackers carry seeds from the seed source. long distances to caches under forest litter, where, if Heavy, nonwinged seeds usually depend on gravity conditions are favourable, seeds may subsequently or animals for dispersal. When gravity is the sole germinate (Tomback ). means of dispersal, the seeds will remain very close to Wind-dispersed seeds generally travel farther than the parental tree. The distance these seeds travel may animal-dispersed seeds (Willson ). For compara- depend on the slope, with seeds travelling farther on tive tables of dispersal mechanisms and distances, see steep slopes. Many non-winged seeds also rely on ani- Hughes et al. (). Species that most efficiently dis- mals either as primary or secondary dispersal agents. perse seeds are the willows, aspen, and balsam poplar When seeds are dispersed by animals, the distance the (Zasada et al. ). Observations show that these seeds travel from the source can be highly variable. seeds can be dispersed in relatively large quantities to

 . Seed dispersal curves for nine conifers of the Inland Mountain West (McCaughey et al. 1986). Dispersal charac- teristics of different species can be compared by showing the relative number (percentage) of seeds found at different distances from the seed source.

70 field studies of seed biology at least several kilometres from the nearest source usually more important (Greene and Johnson ). (Zasada ). Thus, the variation in dispersal distance between Many external factors affect the distance that wind- trees of the same species is probably due more to dispersed seeds will travel. Wind speed is a primary their location (and exposure to wind) than to factor, with strong winds dispersing seeds greater genetic differences. distances than light winds, and prevailing winds usually determining the direction of dispersal. Wind .. Quantity and quality of dispersed seeds speed also affects abscission, but the speed required The regeneration potential of a site is often related to cause seed abscission depends on how many ab- to the quantity of filled seeds reaching the soil sur- scission layers are present (Greene and Johnson , face. This varies substantially among species and ). The wind speeds required to actually achieve years. Many angiosperm species, such as Betula and seed abscission in most species is demonstrably Alnus, can produce substantially more seeds than greater than median wind speeds reported for North conifers, and do so over shorter intervals (Eremko et American weather stations, resulting in seed dispersal al. ; Zasada et al. ; see also Tables . and .). distances being greater than would otherwise be However, the germination of angiosperms such as expected (Greene and Johnson ). However, Betula is generally lower than that of conifers (Zasada standard wind measurements are very different et al. ). from wind speeds within the trees, which are usually The quality of dispersed seeds may vary due to lower; even high winds are rapidly reduced within insect and disease attack (affecting cone opening and the canopy. Thus, median wind speeds from a refer- seed release), and the activity of animals, particularly ence station can be used only as an index of general birds. For white spruce, quality was highest when seeds conditions. were dispersed in September, but quality declined Seeds are likely to travel farther from trees that are after that (Dobbs ; Zasada ). Other species in exposed positions, such as on ridgetops. Within a such as paper birch disperse high-quality seeds both stand, air speed will depend on stand density and early and late in the cycle (Zasada et al. ). structure. Stands where the trees are closely spaced will have low horizontal air speed. .. Climatic conditions Rising thermal winds can also disperse seeds uphill Weather (e.g., rain, heat, storms, drought) can have a in mountainous terrain at mid- to lower elevations major influence on seed dispersal affecting both pri- (McCaughey et al. ); updrafts are more important mary and secondary dispersal. Seeds may fall from in dispersing light seeds. Dispersal may be more fre- the parent tree as the bracts and fruits dehydrate and quent in the early afternoon when more abscission dehisce (e.g., Salix spp. and most conifers), or the events take place because of low relative humidity entire cone may disintegrate (e.g., Abies spp.). Abscis- and high wind speeds (Greene and Johnson ). sion of seeds increases with higher lateral winds and Dispersal distance is also dependent upon the tree lower humidity. Prolonged dry weather may cause characteristics, size of the seed crop, and seed mor- cones to open prematurely, and storms may blow phology (see Section ..). Seeds are likely to catkins and immature seeds to the ground. disperse farther from tall trees, from fruits or cones Temperature also plays a major role in seed disper- concentrated near the top of the tree, and from sal of several species. In British Columbia, lodgepole dominant trees. pine, black spruce, and jack pine have serotinous or There can be considerable variation within a single semi-serotinous cones. Seeds are not released until species in dispersal distance; such variation can affect the resin binding the cone scales is melted by fire or sibling competition, density-dependent predation or high temperature, so in years when temperatures parasitism, and the probability that seeds of particu- do not reach a certain threshold, seeds may not be lar individuals will locate canopy gaps (Greene and released. Winds are a major dispersal agent for seeds Johnson ). Intraspecific variation in dispersal after a fire or hot weather, but logging can also be a distance may be due to differences in seed size and dispersal agent when seeds are spread with logging shape, but vertical and horizontal wind intensities are slash (Fleming and Mossa ).

section 4 seed dispersal 71 In species such as Picea, seeds are released while distribution of seed dispersal across openings such as the cones are still on the tree, which allows the seeds clearcuts (McCaughey et al. ). to travel long distances. In Abies species, seeds are In contrast, the distribution pattern of animal- wind-disseminated after the cones disintegrate on the dispersed seeds is highly variable. One example is the tree in September and October. Other conifer species clumping pattern of whitebark pine trees resulting release cones with the seeds still attached, so dispersal from seed dispersal by the Clark’s nutcracker distances are relatively short for these species. Ponder- (Guiguet and Beebe ; Hutchins and Lanner ). osa pine cones, for example, fall to the ground with Seeds distributed by frugivores follow a dispersal the seeds still inside. The seeds are released when high pattern similar to that of wind-dispersed seeds. temperatures dry the cones and cause the scales to open. Seedfall is highest near the source, but if the tail The seeds of some species can germinate while of the seed shadow crosses the edge of a treefall still attached to the parental tree. Germination of gap in the forest or bird perches in an open field, maple seeds can occur on the tree after dormancy there can be another, smaller seedfall peak, which requirements have been met and if environmental produces a bimodal dispersal pattern (McDonnell conditions are suitable (Zasada ). The viability of ; Hoppes ). these germinants depends on suitable conditions; low Secondary dispersal alters the primary dispersal temperatures and low humidity can kill the seedlings pattern. The subsequent effects of wind or water on before and after they are dispersed. seeds on the ground results in the clustering of seeds within depressions. Rocks and vegetation can act as .. Dispersal patterns barriers to seed movement, catching seeds moving The dispersal pattern of seeds is closely linked to the horizontally along the surface. Clustering can also action of their primary dispersal agent. Regardless of result from animals moving seeds to caches. dispersal mode, the highest levels of seedfall are found within the stand. Generally, the farther away from the .. Dynamics of seedfall source, the fewer the seeds, and the more variable the Specific morphological adaptations have evolved to density. In animal dispersal, the pattern is more vari- aid the dispersal of wind-dispersed seeds. Some seeds able because dispersal is independent of wind direction. have plumage, others have wings. Mechanically, Wind-dispersed seeds can be considered as com- plumage and wings operate in different manners ing from a point source (a single tree releasing seeds), (Niklas ); plumage causes parachute-like behav- or as an area source (a stand of trees dispersing seeds iour, wings cause helicopter- or glider-like behaviour into an adjacent clearcut) (Greene and Johnson ). (Table . and Figure .). Such structures slow the With wind-dispersed seeds, the highest numbers of rate of fall, allowing lateral winds to carry the seeds seeds are found close to the source; the quantity of greater distances before coming to rest on the ground seeds decreases rapidly with distance downwind (Farmer ). The large plumage of Populus spp. acts from the seed source, and continues at a low level as a parachute, decreasing the terminal velocity and (McCaughey et al. ). This results in a U-shaped allowing the seeds to remain airborne longer.

 . Seed dispersal mechanisms of winged seeds (after Niklas 1992; Farmer 1997)

Wing type Species examples Mechanism

Plumage Populus, Salix Parachute: decreases terminal velocity Winged Plane-winged Betula, Thuja plicata, Chamaecyparis nootkatensis Glider: linear gliding flight Autogyroscopic Acer, Picea, Pinus Helicopter: autorotation creates lift

72 field studies of seed biology a) b) smaller the glide angle, the larger the dispersal range of the seed or fruit. For more information on the aerodynamics of plane-winged and autogyroscopic fruits and seeds, see Ward-Smith (). The mean terminal velocity of seeds may vary considerably among populations of some species (e.g., lodgepole pine), while being fairly constant within other species (e.g., most spruces). The size of the seeds and of their wings determine the maximum speed of descent (terminal velocity) of a seed. Small seeds with large wings probably disperse farther than larger seeds with small wings (McCaughey et al. ). Variation in terminal velocity due to seed size could c) d) enhance dispersal distance (Greene and Johnson ). The terminal velocity of seeds can be determined by dropping seeds in still air (e.g., within a closed stairwell) and measuring their descent time with a stopwatch. Reported values for representative western tree species are given in Table ..

 . Examples of dispersal mechanisms of winged  . Mean terminal velocities reported for seeds seeds: (a) plumage (Salix); (b) winged- (with seed wings attached) of some British autogyroscopic (Pinus); (c) plane-winged Columbia tree species (Alnus); (d) winged-autogyroscopic (Acer). Sources: (a) Zasada et al. [1998]; (b), Mean terminal (c), and (d) “The Secret Life of Tree Seeds” velocity poster, B.C. Ministry of Forests, Victoria, B.C. Species (m/s) Source

Hardwoods Winged seeds or fruits are produced by gymno- Balsam poplar 0.28 Greene (unpublished) sperms (e.g., Pinus, Picea) and a host of angiosperms Trembling aspen 0.39 Greene (unpublished) (e.g., Acer, Betula). There are two categories of winged Paper birch 0.55 Björkbom 1971; Greene seeds: plane-winged and autogyroscopic. In plane- and Johnson 1995 winged seeds, the seed coat or fruit wall grows more or less symmetrically with the longitudinal axis, gen- Conifers erating a more linear gliding flight. In autogyroscopic White spruce 0.57 Zasada and Lovig 1983 seeds, lift is created by wings that permit autorotation Western hemlock 0.60 Greene and Johnson 1995 during free fall, such as the helicopter-like movement Sitka spruce 0.60 Greene and Johnson 1995  of maple samaras (Niklas ). Lodgepole pine 0.60–1.0 Greene 1990 Plane-winged seeds and fruits benefit aerodyna- Engelmann spruce 0.61 Greene and Johnson 1996 mically by concentrating their centres of mass in a Black spruce 0.61 Greene and Johnson 1989 position relative to the chord of their wings (see Niklas ), which stabilizes the location of the centre of White spruce 0.62 Greene and Johnson 1995 pressure (where resultant aerodynamic forces act on Douglas-fir 0.93 Greene and Johnson 1995 the wing). The precise position of the centre of mass Tamarack 0.96 Greene (unpublished) determines the incidence angle at which equilibrium Western redcedar 1.25 Greene and Johnson 1995 occurs, this in turn determines the glide angle. The

section 4 seed dispersal 73 .. Approaches to Studying Seed Dispersal there are difficulties in replicating the sampling. Therefore, there is usually a high degree of uncer- Most basic studies of seed dispersal include docu- tainty associated with descriptions of seed rain menting seedfall beneath a parental canopy. The most patterns (e.g., maps of seed rain density) within a common approach to sampling seed rain is to use stand or across a block. seed traps. Seed traps are suitable for seeds dispersed To minimize the uncertainty inherent in docu- by wind as well as by vertebrates that ingest seeds or menting seed rain patterns over space, use the largest fruit and then defecate or regurgitate them. Pivotal possible seed trap. With increasing seed trap size, to these studies is the determination of a suitable size, there is a decrease in sampling error and the prob- number, and placement of the seed traps. It is also ability that trap-to-trap differences are due to chance. important to keep in mind that it is viable seeds Although larger traps are more cumbersome, using that are of interest in seed dispersal studies. See . m2 traps instead of . m2 could reduce the uncer- Section . for tests for seed viability. tainty level by a factor of . If you are using small Many studies use a one-dimensional approach, traps, cluster two to four seed traps around a point. where seed traps are used to determine the seed Keep in mind that these are subsamples of one dispersal distance in one direction (generally down- experimental unit; having additional traps does not wind). These types of studies produce a dispersal increase the number of replications of the design. curve. A mathematical equation can then be fitted to An alternative two-dimensional approach may be the data. This approach is suitable when the objective taken when studying trees with large seeds (e.g., Carya, is to determine the distances which tree seeds can Juglans, Malus, Quercus, some Acer spp.) which fall disperse, or for making various kinds of comparisons. primarily beneath their own tree crowns. Dispersal A one-dimensional approach can be used to study of large seeds can be effectively studied by mapping the genetic structure of populations, successional the resting location of all seeds, or determining seed dynamics after natural disturbance, and tree invasion density in sample quadrats within a fixed radius of into grasslands, tundra, or old fields. In forestry, dis- the parental tree. persal curves are used to evaluate prescriptions for In a three-dimensional study, the seed shadow is natural regeneration in strip cuts, patch cuts, and followed over time. Most ecological studies of seed clearcuts, which depend on a satisfactory density of biology and plant demography are conducted over tree seeds dispersing from the unlogged forest into several years because of natural variation in seed the centre of the cutblock. production and other factors. The periodicity of In a two-dimensional approach, data from seed natural seed production (Section .) usually requires traps are collected to provide information on the many years of monitoring to obtain a good picture of number and distance of seeds dispersed in all direc- mean seed rain density and its variance. tions. A dispersal curve extending in all directions Biologists have studied the fate of individual seeds, from a point source describes the seed shadow or even of artificial seeds (e.g., Augspurger and generated by an individual tree. A seed shadow is Franson ) under conditions of controlled release therefore an area of dispersed seeds, centred on (or (e.g., Greene and Johnson , ). Such studies downwind from) a seed-producing individual or are useful to assess the rate of fall and the horizontal stand. A two-dimensional approach would be used distance travelled by different species when seeds are to determine the effectiveness of leaving seed trees released from different heights or under different in a clearcut to provide seeds for the natural regen- wind conditions. This information is typically used eration of a site. to describe the basic biology of a species (e.g., Seed rain variability and sampling problems make McCaughey and Schmidt ), or to subsequently it difficult to accurately describe seed deposition in model its dispersal behaviour (e.g., Greene and two dimensions. It is not always clear whether point- Johnson ). to-point differences in seed rain density are actually It is possible to distinguish between primary and due to the change in distance from the source, or to some forms of secondary dispersal on the basis of sampling error. In conducting studies of seed rain, where the seeds are found (see Matlack ). For

74 field studies of seed biology wind-dispersed seeds, one could assume that most A problem, especially for plumed seeds, is retaining seeds found in elevated seed traps are the result of them in the trap after falling. Many kinds of seeds primary dispersal, and any seeds found underneath can be lost through wind gusts, flooding, and move- are the result of secondary dispersal (horizontal ment by animals. Deep-walled seed traps, adhesive movement). For other types of secondary dispersal, surfaces, cover screens, and frequent monitoring can seed density can be determined and then the area help retain the seeds (see Section ..). sampled again at a later date to determine if any of Some seeds are inevitably consumed before you the seeds have been removed (see also Section ). can count them, and exclusion of predators may Secondary dispersal by water has generally been noted therefore be necessary. Most insects are so small it is in the literature as an observation, because of the tech- difficult to exclude them, but mammals and birds can nical difficulties in tracing the movements of seeds. be excluded using coarse-weave wire screening or hardware cloth. Make sure the grid size is not too . Measurements and Methods small to exclude any of the seeds of interest, nor large enough to permit rodents. An – mm grid size is .. Basic considerations good for most conifer seeds. (Refer to Table . for Mapping the resting spots of large seeds can be facili- sizes and weights of British Columbia tree seeds; and tated by clearing the forest floor under the canopy Section  for more information about exclusion of of the parental tree and slightly outside the crown predators). If it is important to know the portion projection, or by spreading tarpaulins under the tree that are secondarily dispersed by animals, it may crown. Individual seeds can either be removed or be possible to modify some of the methods from marked (paint or nonphytotoxic compound) after Section  for this purpose. counting to ensure they are not counted twice; this is The more frequently that you can monitor and especially important if repeated measurements are count your seeds the better; detailed phenological taken. Leaving marked seeds on the ground permits interpretations are then possible (or may even be you to determine if they are being removed by birds an objective of the study), and some of the risks or rodents. To study the timing of seed dispersal, discussed above can be minimized. Weekly monitor- seeds or fruits should be collected two or three times ing is recommended during the period of active per day, which will provide a good estimate of the dispersal (unless more frequent monitoring is neces- rate of dispersal (J. Zasada, pers. comm., ). sary); this can be decreased to biweekly or monthly The design, distribution, and monitoring of traps monitoring the rest of the year. Some researchers are a primary concern of forestry researchers study- count and evaluate seeds at the trap site; others ing tree seed dispersal. Many studies of wind- and prefer to bag the contents of each trap and evaluate vertebrate-dispersed (ingested) seeds (see Hoppes them later. However, this last method requires ) measure seed dispersal by collecting seeds after organization and commitment to avoid a backlog they fall in some type of seed trap. You may find that of unexamined seeds. collaborating with an ecologist interested in litter fall A special problem is assessing the dispersal of or entomology will maximize your sampling system, seeds that can germinate on the tree, such as bigleaf as plant detritus and insects are often caught in the maple (Zasada ) or true firs and western hemlock seed traps. which can germinate either in cones in the tree or in The ideal height of the seed trap opening is flush cones on the ground, (e.g., squirrel caches). Since the with the forest floor, because it is the level at which dispersal of maple seedlings may occur many months seeds would naturally rest before germination. How- after seed dispersal, seed traps would most likely be ever, there are difficulties with low-lying seed traps: removed and sampling stopped before this event. It water may accumulate, seeds may be washed out, may be necessary to sample germination in the tree or rodents may enter the trap and eat the seeds. and in cones to determine their proportion of the Seed traps may be set higher to avoid seed deflection total crop. While it might be useful to determine the by ground foliage, or to continue collecting seeds success of these germinants in finding a suitable after snowfall. microsite after dispersal and surviving, that could

section 4 seed dispersal 75 be very time consuming. By measuring the effective of these phenomena appear in the literature as dispersal rather than seed rain, no distinction need be observations, and no methods have been found for made between the dispersal of seed and germinants. measuring the quantity and distance of this type of Such measurements can be facilitated by deploying dispersal. Potential methods include mapping the an array of trays filled with sterilized potting soil. presence of seeds in “deposition” sites such as river Other methods are discussed in Section .. bends compared to other locations; using nets or Generally it is difficult to measure dispersal by other barriers to collect seeds; and analyzing vertebrates that hoard seeds. Seed traps are not rec- isozymes of individual trees or clones (since poplars ommended as the sole measuring tool, but they can and other floodplain species tend to spread by be used in combination with cache searches. Cache coppicing) and comparing “downstream” and the locations can be mapped, but with this method there “upstream” individuals. is no way to determine what proportion of the seeds will remain uneaten, or their germination potential. .. Seed trap design Another method measures “effective dispersal,” in The most widely used seed trap is a fixed-area tray, which dispersal is inferred from the number of seed- usually rectangular, which excludes rodents with  or lings counted during the next growing season. To  mm grid hardware cloth. Adjustments will have to determine the amount of seed that is being removed be made for some larger seeds, such as oak and bigleaf by hoarding vertebrates, two sets of traps can be used: maple, as the – mm grid size is too small for them one that excludes predators and one that allows seed to pass through. The same trap design could be used removal (see Section  for methods of measuring for both wind- and vertebrate-dispersed seeds. For seed predation). more information on designing traps for predator Measuring secondary dispersal over snow requires exclusion, see Section . different techniques For example, the primary disper- Proper drainage must be provided, as well as an sal agent for Betula lenta is wind, and seed release is easy way to remove and count seeds. Large aluminum from September through March. Secondary dispersal baking pans and plastic greenhouse trays have been occurs when seeds are moved horizontally across the used as the basic seed trap, with holes punched for snow. Both primary and secondary dispersal can be drainage and hardware cloth crimped over the top monitored simultaneously if the seed trap for primary to keep out birds and rodents. A good basic design dispersal is suspended above the snow: any seeds that is one with a wooden frame, with metal window accumulate under the trap must have arrived there screening (about  mm grid) stapled to the bottom, by horizontal movement. Snow under the trap (the allowing water drainage but retaining seeds top  cm) can be collected from traps or protecting (McCaughey and Schmidt ; Youngblood and platforms, and melted to extract seeds for counting Max ). A wooden lid with permanently stapled (Matlack ). Total seed deposition by both pri- hardware cloth (Figure .a) eliminates the need to mary and secondary means can be estimated by repeatedly unstaple the hardware cloth. The lid must collecting snow samples from unprotected areas. To be precisely crafted to fit tightly over the base with no limit the impact of footprints in the snow (because room for rodents to enter. Other trap designs are seeds accumulate in hollows), treatment plots should shown in Figure .. A seed trap with a wooden lid be approached from downwind. It is also possible and permanently stapled hardware cloth (Figure .a) to control for seeds present in the snow before the will deter predators and provides easy access for beginning of an experiment by covering additional monitoring. A trap made from a galvanized flue quadrats with polyethylene sheeting to prevent any thimble (Figure .b) can be placed flush with the seed deposition during the experiment and then surface, but leaves accumulating on the surface may sampling them at the end (Matlack ). blow away resulting in the loss of seeds. A trap made Secondary dispersal in water by rivers is important from a tractor funnel (Figure .c) will retain leaves to species that live on floodplains. Seeds are also and seeds. The recessed surface will help to retain moved from their original positions by rain. Reports the contents.

76 field studies of seed biology Species with light seeds and those with appendages the seeds can easily be wafted back out of the trap. for air flotation (like those of dandelion, fireweed, Sticky traps consisting of an adhesive such as Tangle- aspen, and willow) require specialized traps. Other foot™ on replaceable index cards, filter-paper disks, traps do not work as well for these species because or cardboard sheets have been found effective. Sticky traps are messy to make and maintain, and they capture detritus and insects as well as plant seeds, thus should only be used when absolutely necessary. In areas where wind and dust are prevalent and traps for light seeds are required, funnel traps and glued- soil depression traps work well (Johnson and West ). For light seeds such as Betula and Alnus, a Lid deep-walled funnel trap with walls above the rodent- excluding screen can prevent seeds from wafting out of the trap (Zasada and Gregory ; Figure .c). Water-filled trays have been used to capture and retain willow and aspen seeds (Walker et al. ). The dispersal unit of these seeds usually stays attached Base to the water surface once it lands and, because these species germinate relatively quickly in water, viability can be tested at the same time (Wyckoff and Zasada []). Wet soil is also a good medium for catching and holding these types of seeds (Zasada et al. []). To avoid freezing when measuring seed dispersal dur- ing winter, kerosene can be used rather than water (Matlack ). Both water- and kerosene-filled trays should be inspected frequently (even daily) because leaf litter can accumulate and decrease the effective seed collection area. To exclude rodents, a bag or tray can be suspended above the forest floor (Hughes et al. ), and the guy wires or a flexible tripod of intersecting wires can be used to hold open the mouth of the bag. However, rodents can still climb into the traps with the aid of vegetation or snowpack. Cattle, bears, or heavy snow may also cause traps to collapse. To facilitate the handling of suspended bags, Velcro™ tabs are recommended to attach the bags to the frame. A combination design has flexible, replaceable bags (e.g., nylon window screening, woven grain bags, polyester cheesecloth, or remay) that can be changed regularly and the contents tallied in the  . Seed trap designs: (a) a trap with a wooden laboratory. The bags are held within a rigid frame   lid and permanently stapled hardware cloth; (similar to Figure . a without the bottom screen) (b) a trap made from a galvanized flue which is laid on the forest floor and covered with a thimble; (c) a trap made from a tractor rodent-exclusion screen. funnel. Source: (b) and (c) after Zasada Another approach is to fill traps with potting soil, and Gregory (1972). and then count the number of seeds that germinate.

section 4 seed dispersal 77 . Experimental and Sampling Design because seed rain density decreases and variability increases with distance from the seed source. As a .. Estimating seed rain density general rule, the number of seed traps should double Replication is a major problem in many studies. Both for each tree-height away from the seed source. Al- replication of seed traps within a treatment site and though the number of traps can be fewer nearer the replication of treatment sites can be limited by time source, it may be problematic if near traps are and money. For example, to compare seed rain den- clumped together (D.F. Greene, pers. comm., ). sity in a treatment and a control site, a researcher Unless the source is a monoculture, the non-random must decide how many samples (seed traps) will be distribution of species requires that traps be spread taken, and how many treatment and control sites to out along the forest edge. Indeed, because of this use. A common design in silviculture is the paired- non-random distribution of source trees, you should site experiment. In this design two adjacent and avoid having a small number of traps near the forest presumably similar sites—a treatment site (e.g., boundaries. clear-cut) and a control site—are compared, then Increasing the sampling intensity with distance is the difference between the two is monitored. Often especially important when identifying the maximum several samples are taken from each site. The dispersal distance (Portnoy and Willson ). The assumption is that any observed difference after final distance will depend on such factors as the size, treatment is due to the treatment. In reality, the weight, and aerodynamics of the seeds. For example, lack of replication of the experimental units (sites) sampling dispersal of seeds that can travel long dis- means that you cannot separate the site effect from tances, such as willow, will require a larger number of the treatment effect in the predicted error value. traps laid out over a larger area than a species such as For a more complete discussion of experimental subalpine fir, which has a shorter dispersal distance. design, see Sections . and . and MacDonald The strength and direction of the prevailing winds and Stednick (). will also affect the placement of seed traps. In par- Determining the number of seed traps needed ticular, consider the frequency of gusts which may within a site should be done very early in designing cause abscission of the seed, and updrafts which your experiment in consultation with a statistician. A may result in seeds travelling beyond the limit of pilot study or data sets from similar experiments may the study layout. be used to make a preliminary assessment of the seed The problem of how much total trap area is re- rain variability and determine the number of seed quired at each distance will depend most strongly traps required to capture that variability. Time and on source density and, sadly, luck. Luck is involved money restrictions may preclude installation of all because many species are markedly variable in the the traps required. Compromises are made in most production of seeds. Most have temporal coefficients studies, and it may be preferable to limit the number of variation of . (oaks, pines) up to almost . of seed traps rather than limit the number of experi- (most conifers, a few hardwood species). Years of mental units (sites). In general, it is most efficient to virtually no seed production occupy about % of use nested sampling to characterize your variability, long-term records. A simulation performed on a - instead of taking one large sample. For example, by year record from New Zealand showed that sampling taking four smaller subsamples from one site, vari- for  consecutive years would be required to obtain ability can be estimated within the site. However, apparent mean production values within two-fold remember that these are subsamples, not replicates; of the observed long-term mean (D.F. Greene, pers. to treat them as replicates would be pseudo- comm., ). Ideally, therefore, an investigator replication (Hurlburt ; MacDonald and must either wait to put in the traps until binocular Stednick ). estimates indicate a reasonable seed supply, or be The number of seed traps should increase with in- willing to continue the study for several years. How- creasing distance from the seed source (Hoppes ) ever, you can estimate the total trap area required.

78 field studies of seed biology Using data from long-term studies, Greene and more practical to replicate seed rain studies over Johnson () estimate mean annual seed produc- time, (e.g., by measuring treatment and control sites tion per square metre (Q) as: in three consecutive years). Several precautions should be taken: take samples at essentially the same Q= B0.92 m-0.58 N , time from the treatment and control sites; ensure that the control site is comparable to the treatment site; where: B = mean source basal area (m2), and check that local events that affect trends do not m = individual seed mass (grams), and occur at one site but not at the other (MacDonald N = source density (number/m2). and Stednick ). When to start and stop, and how often to sample For example, suppose you wish to estimate seed will be determined by the timing of seed release of production in a stand of Engelmann spruce (mean the species. It is best to sample more frequently dur- seed mass . g, mean basal area of source trees ing the period of heaviest seed rain, usually the first . m2, and density of source trees ./m2). Well several weeks of seed release. Weather conditions inside the forest in an average year you could expect may also influence your schedule; sampling should about  seeds/m2, and at the forest edge, about half be more frequent in windy conditions, since wind that amount ( seeds/m2). As a rule of thumb, at increases abscission rates, and seeds may be removed  m from the forest edge you could expect about from traps by wind and rain. % of the deposit well within the forest (D.F. Greene, Site information should be collected to charac- pers. comm., ), or about . seeds/m2. Thus, to terize the study area (see Section .). However, if register a single seed at  m, quite a large trap area you are modelling how seeds disperse from a tree is required. To be cautious, the minimal estimate of or from a stand edge, some additional data will be the required trap area should be increased -fold, required: because you may well be sampling in a poor year. In • seed rain density under the tree, or within the general, investigators use relatively small amounts of intact stand; trap area, and published studies may therefore be • approximate heights from which the seeds are dominated by “mast-year” examples (D.F. Greene, released; pers. comm., ). • seed samples to measure mass and area to deter- You may wish to examine the final resting spots mine wing loading, and terminal velocity when of individual seeds, in which case the horizontal dropped in still air (Greene and Johnson ); distance and direction travelled may be noted (e.g., • information on dispersal agents, such as prevailing Zasada et al. ), or the microsite attributes of rest- wind velocities at different heights (Section ..) ing spots recorded (e.g., Janzen et al. ). and relative abundance of seed-dispersing verte- Whatever the measurement method employed, brates; each seed trap should provide a single value for the • landscape features that impede (or enhance) the number of viable seeds intercepted per square metre flow of wind or water, or attract or repel seed- per year. This point-measurement of seed rain den- carrying birds or mammals (Johnson et al. ). sity is usually the standard unit for further analysis. The point measurement is often extrapolated from Estimating seed rain from a point source seed traps with collection areas of less than . m2, or To study seed dispersal from a single source is averaged over several years. Usually only filled, (individual tree), for both wind- and vertebrate- viable seeds, or the ratio of viable seeds to the total dispersed seeds, the source tree should be sufficiently captured, are of interest. See Section . for methods isolated from other trees. Contamination of seed to determine viability. traps with seeds from nearby trees is probably the Since many study areas do not have analogous most significant problem in this type of study. The treatments replicated in separate stands, it is often type and size of trap used will depend on the seed

section 4 seed dispersal 79 characteristics of the species being studied and the area. Such layout patterns are appropriate for mature types of predators expected (see Section ..). uncut forest stands, and under uniform shelterwood The layout of traps around a point source is the and seed tree canopies. When studying a stand com- same for both one-dimensional and two-dimensional posed of a single species, or if you are only interested studies, except that sampling may be more intensive in the seed dispersal characteristics of one species, a in a two-dimensional study. The objective of a one- trap suitable to just that species should be chosen. dimensional study is to derive a dispersal curve (as For seed rain mapping, sampling on a regular grid described in Section .) in one dimension; the ob- is more practical than random sampling (for examples, jective of a two-dimensional study is to map changes see Carkin et al. ; Noble and Ronco ; Alexan- in seed rain in two dimensions. The difference be- der ; McCaughey and Schmidt ; Matlack ; tween one- and two-dimensional studies lies more in Youngblood and Max ). If a grid is used, ensure presentation of the data than in the design. For both that the grid interval is not a multiple of mean inter- types of studies an array of traps is arranged around tree distance or mean crown diameter. For example, the parental tree. While the ideal trap arrangement if the trees are very uniform and have a mean crown should be random, it does not account for the vari- diameter of  m, grid sampling at , , , or  m (etc.) ability of seed dispersal increasing with distance would have a greater-than-random chance of repeat- from the source (thus the number of seed traps should edly sampling under the same part of the trees (e.g., also increase with distance). For this reason most adjacent to the bole, or at the periphery of a tree crown). seed-trap layouts use a systematic design—a circular Seed-trap layouts suitable for quantifying the seed arrangement with the diameter of the circle increas- input into a forest opening would use a systematic ing with distance from the starting point (Figure .), layout (two variants are shown in Figure .). The or a systematic linear arrangement (Figure .). number of seed traps increases as distance from the When species produce large seeds dispersed by area source increases, permitting a researcher to sam- gravity, the seeds primarily fall directly beneath the ple rare long-distance seedfall events. Although such parental trees. Three methods are available: each seed sample arrays are two-dimensional, they describe location can be mapped, seed traps may be set out, or seed dispersal in only one dimension, with multiple density determined in an array of survey quadrats transects of seed traps serving primarily as subsamples (see Sections . and .). for describing seed input at different distances from Estimating seed rain from an area source the seed source. Results are portrayed as seed disper- To estimate the overall seed input to a unit of land sal curves, as shown in Figure .. with seed-bearing trees, seed traps should be distri- Comparisons between tree species are generally buted randomly throughout the stand or treatment based on stand-level measurements. To study species

a) b)

 . Schematic of the distribution of seed-traps placed around a point-source. Each box represents a seed trap. (a) concentric circles; and (b) a cross (after Hoppes 1988).

80 field studies of seed biology a) b)

 . Recommended seed-trap layouts at a forest edge for an area source. Sampling density increases with distance from the seed source: (a) traps distributed at regular 10 m intervals; (b) traps distributed randomly within each distance category. at the stand level, several seed traps (suitable for the ably be required to obtain a good picture of overall species under study) must be used in each stand to seed inputs. Long-term studies (– years or more) provide a reliable measure of seed rain density. The may be necessary to get a reasonable idea of annual number of traps within a stand has a relatively small periodicity of seed rain (D.F. Greene, pers. comm. ). effect on the overall power of a test, so it is better to have more stands per treatment than to have more . Data Analysis traps per stand. When seed production levels are low, seed rain becomes more variable and spotty, so the The analysis of seed rain data follows the norms of number of seed traps per stand should increase to most sample surveys and of those experiments that sufficiently characterize the variability. It usually depend upon sampling within experimental units. requires many years of monitoring to get an accurate If you are also interested in spatial patterns of seed picture of mean seed rain density. The number and dispersal, then specialized statistical tools may be distribution of traps should be based on what is re- required. So far, modelling of seed rain patterns is quired to adequately sample in the poorest seed year. really only feasible in the simplest scenarios (e.g., The most difficult situation occurs if the compos- around widely spaced seed trees or at cutblock edges). ite seed rain of an entire tree community is to be sampled. The type(s) of trap used will depend on the .. Descriptive analysis different species being sampled. For example, to Single-source and area-source (stand-level) seed rain document seed rain of all trees into a boreal forest density can be described by a measure of the central site might mean collection of the wind-dispersed tendency (e.g., mean, mode, or median values) and seeds of birch, aspen, balsam poplar, willows, white the variation (e.g., standard deviation or % con- and black spruce, balsam fir, and lodgepole pine. fidence interval) in trap-to-trap measurements. Questions a researcher must ask are: What kind of Seed traps are often deployed to determine what trap arrangement and what type of traps would be proportion of the forest area under study receives an needed (spatial and temporal)? Could the same type adequate seed rain density (i.e., density above some of trap be used for all species? Would the trap array arbitrary threshold) and an even distribution (disper- have to differ among species? Would trapping “sea- sion) of viable seeds (i.e., high densities in some traps son” differ? An array of different kinds and densities may not compensate for few or no seeds in other of seed traps, monitored at different times, will prob- traps). In stands where extreme values prevail, using

section 4 seed dispersal 81 the mode or median to describe central tendency is  . Split-plot-in-time analysis of variance (ANOVA) usually more appropriate than using the mean. This table for a hierarchical sampling design would be the case, for example, where there are mostly zero or many seeds per tray, rather than an Source of variation Degrees of freedom Test for effect even (or constant) range in the number of seeds per tray. In these situations, the spread about the norm is Stand, N (n-1) = 2 — better described using percentiles or quartiles rather Treatment, T (t-1) = 3 MST / MSN*T than standard deviation or confidence intervals. N*T (n-1)(t-1) = 6 — Results (in significant digits) should be expressed in Year, Y (y-1) = 4 MSY / MSY*N terms of the method or measurement employed (size Y*N (y-1)(n-1) = 8 — of seed trap and sample size, or total seed trap collec- Y*T (y-1)(t-1) = 12 MS / MS tion area, in this case). Y*T Y*N*T Y*N*T (y-1)(n-1)(t-1) = 24 — .. Comparative analysis Subsamples, P(TNY)(p-1)tny = 2040 — (subsamples nested Treatment comparisons can follow standard analysis within treatments, of variance (anova) approaches. This assures that the stands, and years) variance is appropriately partitioned. For example, Total: tnyp - 1 = 2099 the comparison of seed rain under four different sil- vicultural treatments in three separate stands might Note: Lowercase letters represent the number of levels of the be as follows: all of the four treatments, T, would sources, (e.g., Treatment (T) has four levels, t = four treatments; n = three stands; p = 35 subsamples; have to be applied within each stand (e.g., number y = 5 years). of blocks = three), with extensive subsampling in each treatment unit (assume p =  subsamples), and over several years (assume y =  years). The anova and the data from year-to-year are dependent, then table and appropriate F-tests would then be set up as a repeated-measures analysis would be appropriate. in Table .. If the number of seed traps differs The main objectives of repeated measures analysis among stands, observations should be weighted by are to check if there is a trend over time, to take into the number of subsamples per treatment cell when account the inherent variation of a site, and to see conducting anova or regression. if the trend is the same for all treatment levels. When the number of subsamples in the treatment Repeated-measures data can also be analyzed using cells varies, the degrees of freedom (df) also vary: if multivariate anova with the multiyear data as response vectors. Refer to Moser et al. (), Potvin et al. individual counts are Pijk, (), Meredith and Stehman (), Gumpertz and then: Brownie (), and Nemec () for more detailed discussions and a wider range of options for the t n y Σ Σ Σ - analysis of repeated measures (see also Section ..). total df =    pijk , and i= j= k= If significant effects are found, a suitable multiple t n y subsample df = Σ Σ Σ (p - ) comparison method may be used to identify which i= j= k= ijk means are significant. However, if your goal is to de- where: termine if a treatment—or several treatments—were i = treatment, significantly different, sufficient information may be j = stands, and gained by the anova. Presentation of your anova k = years. results, with a graph of your data, generally provides an effective visual comparison between treatments. Multiyear data collected from the same fixed It may not be necessary, or even relevant, to have a network of seed traps can be treated as a split-plot- comparison between plot A in year  and plot D in in-time anova, as laid out in Table .. If data are year . If you do require multiple comparisons, Day collected over time from the same sampling units, and Quinn () suggest Scheffé’s method for

82 field studies of seed biology unplanned comparisons, or Dunnett’s test when a This equation was used by Youngblood and Max () control is compared to all other treatments. A small to describe seeds originating within a mature forest number of planned contrasts (not more than the and dispersing from a forest edge into a clearing. degrees of freedom for that source) do not need any Advanced statistical regression analysis of seed multiple range type of correction, the p-values of dispersal data typically consists of (iterative) non- their associated t-values or F-values can be used linear curve fitting; see Sit and Poulin-Costello () without correction. For many non-orthogonal con- for details on fitting data to the negative exponential trasts, a Bonferroni correction can be used; otherwise model and related functions using the sas statistical use Scheffé’s method, since it is naturally very con- package. There are advantages and disadvantages to servative. For more information see Milliken and both these models. The inverse power model has the Johnson (). Duncan’s multiple range test and the advantage that it transforms to a straight line when it Student-Newman-Keuls (snk) test are also com- is plotted on log-log paper. Thus the numerical val- monly used. Refer to Sit () for more discussions ues of a and b can easily be estimated. The negative on anova and multiple comparisons for various exponential model transforms to a linear relation types of experimental designs. when plotted on semilog paper, and the probability density y remains a finite number as the distance .. Regression analysis from the source x converges to zero. The disadvan- The main objective of many seed dispersal studies is tage of both models is that neither provides any to relate seed rain density to distance from the seed insight into the mechanistic attributes of dispersal source. The relationship of seed rain density, or the and their effects on dispersal curves. probable fate of any individual seed, is well described There appears to be little difference between the by the dispersal curve. The typical shape of the inverse power and negative exponential model in frequency distribution of seeds as a function of the predicting actual dispersal curves (Niklas ). Both distance from the source plant is a concave negatively models have difficulties in predicting dispersal curves sloping line (Zasada ). The two common math- because variations in weight, size, and shape of seeds ematical expressions for the dispersal curve are: the or fruits will affect the dispersal curve. The height at inverse power model (Gregory ): which seeds are borne on the plant, the ambient wind speed, and directional components (lateral wind di- y = ax-b , rection) causing seed release or abscission will also affect dispersal curve characteristics. There is also the where: y = the probability density associated problem with describing the number of seeds plotted with the dispersal, as a function of distance from a point source. The x = the distance from the source, and inverse power and the negative exponential models a and b = unknown values that can be adequately describe one-dimensional dispersal empirically derived; curves, but in reality seeds are seldom disseminated in this manner; spatial distributions in two dimen- and, the negative exponential model (Frampton et al. sions are more common. ): With more complex statistical models, it is possi- ble to incorporate additional information such as the y = ae-bx , “strength” of the seed source. For example, the basal area of trees at the seed source has been incorporated where: y = the probability density associated as an additional independent variable to predict the with the dispersal, density of Engelmann spruce seeds at various dis- x = the distance from the source, tances downwind of a seed source (McCaughey and e = the base of natural logarithm Schmidt ). Other terms could be added to pro- (.), and vide a more accurate picture of seed dispersal, such as a and b = unknown values that can be release height above the ground, terminal velocity of empirically derived. the seeds, and wind velocity.

section 4 seed dispersal 83 .. Spatial analysis For information on other mechanistic models, refer Seed dispersal in two dimensions can be described by to Greene and Johnson (, , ) and generating a map of seed rain density. Data are col- Andersen (). lected from a systematic array of seed traps, and An advantage to the mechanistic approach is that interpolated between observation points to generate data from a variety of plants growing in very different an isopleth map of seed rain density (e.g., Engle ; habitats can be placed within a single objective Augspurger and Hogan ). This can be done with classification scheme based upon the aerodynamic standard interpolation algorithms in statistical pack- properties of airborne spores, pollen, seeds, and ages such as sas and systat, with or without various fruits. However, most models make a large number smoothing options. The problem with this method is of assumptions (Greene and Johnson ), so the the assumption that no sampling error occurred (i.e., resulting predictions may be far from reality, in parti- that all trap-to-trap differences represent real trends cular for light seeds. Seeds of willows and poplars are in seed rain density over the distances concerned). often carried above the height of formation (where These types of errors can be reduced by the use of they are produced). Most mechanistic models do not large traps and replication over time. address the question of how long seeds stay airborne Refer to Robertson (), Isaaks and Srivastava and how that relates to the distance travelled. In a (), Legendre and Fortin (), and Rossi et al. study on white spruce (Zasada and Lovig ), seeds () and their references for more details on the were found to follow very complex flight patterns use of geostatistics. These techniques are presumably that may or may not be based on terminal velocity. applicable to describing trends in seed predation Direct observation reveals a substantial number of (Section ) and seed bank patterns (Section ) as well. ups and downs in the flight path of individual seeds. Some commercial software packages for geostatistical Populus and Salix seeds also follow complex flight analysis are listed in Appendix C. paths that would seem to defy description by a mechanical model (J. Zasada, pers. comm., ). .. Mechanistic modelling In addition to statistical methods, mechanistic mod- els are another option for fitting observed trends in seed dispersal behaviour. These models predict median horizontal distance travelled by the seed crop away from a single tree, using information such as the release height above the ground, horizontal wind velocity, and the terminal velocity of seeds falling in still air. For example, Okubo and Levin () applied a tilted Gaussian plume model to predict the mode of the dispersal curve:

 - xm = h Ua /Us for heavy seeds or fruits (Us> ms ) and

 -1 xm = h Ua /W* for light seeds or fruits (Us< ms )

where xm = the modal distance, h = the height of seed release,

Ua = the ambient wind speed, Us = the seed terminal velocity, and W* = the vertical airflow mixing velocity attending turbulence.

84 field studies of seed biology SECTION 5 SEED PREDATION

Every part of nature teaches that the passing away of one life is the making room for another. (Henry David Thoreau)

. Background studying seed predation. This section deals with pre- dation on seeds that are mature; predation on seeds Studies of seed predation are important to under- that are not fully developed is discussed in Section ... standing how seeds are lost between dispersal and Seed predation studies usually have the objective germination. Research has shown that seed predators of determining the number of seeds lost to predation. can account for over % of the loss of a viable tree Questions that might be asked in seed predation seed crop (Gashwiler ), including between  and studies include: % of the cones removed by squirrels (Hurly et al. ). In severe cases, up to % of the seed crop may • Which species or species groups are preying on be destroyed by predators, which can exert a signifi- the seeds? cant influence on patterns of plant recruitment, plant • Which species of seeds are being preyed upon? species diversity, and plant community structure. Not • What proportion of seed loss can be attributed only can seed predation affect the process of natural to predation versus other losses? regeneration but it can also undermine the success of • What proportion of seeds are lost to predation artificial seeding efforts. by specific predators/predator groups? A further rationale for studying seed predation is • What proportion of seeds are lost to predation the lack of knowledge about the nature and magni- before versus after dispersal? tude of seed predation on tree seeds of western North • How does the pattern of predation change over America, especially hardwood species. While predation time in the short term (single year) and the long of conifer seeds was investigated fairly extensively term (multiyear)? from about  to , research has tapered off in • How does predation differ among different distur- recent decades. This loss of interest may coincide with bances, ecosystems, sites, or other factors? the rise of reforestation by tree planting rather than • How does providing alternative foods and seed by natural regeneration or aerial seeding. The current mixes affect seed predation? strong interest in maintaining “natural” levels of • How does seed predation affect recruitment of biological diversity (e.g., tree genetic diversity) as new trees? well as the search for more cost-effective means of • How do fluctuations in predator and prey popu- reforestation may help to renew interest in natural lations affect seed predation? regeneration. Unfortunately, there is a lack of recent published accounts describing or assessing methods . Seed Predators used to carry out seed predation investigations. The material that is available is often unclear or incomplete; Although studies of the predators themselves are an this section seeks to address the information gap by essential component of seed predation research, de- describing and assessing some common methods for scribing detailed methods for taking a census of seed

section 5 seed predation 85 predators is beyond the scope of this manual. Instead and the ponderosa pine seed moth (Cydia piperana), we provide basic information about common seed which is especially destructive to pine seeds in west- predators, suggest when and why we should study ern North America. For more information on cone them, and include references for detailed methodology. and seed insects, see Hedlin et al. (); common There are three main groups of seed predators: insect pests of conifer cone and seed orchards small mammals, birds, and invertebrates. Of these, Table . in Finck et al. (). For information seed predation by small mammals has been the most on diseases, which are another form of seed preda- studied (West ). Although the role of birds and tion, see Sutherland et al. (). invertebrates in seed predation is less well docu- For most research, knowing what species or spe- mented, these groups can also destroy significant cies groups are eating seeds will be enough, although amounts of seeds (Gashwiler ; West ). Within it is always helpful to know which are most abundant. all three groups, some species specialize in feeding in Wildlife and insect pest inventories can be valuable trees while others are ground feeders. sources of information on the species of small mam- Mice, voles, shrews, chipmunks, and squirrels are mals, birds, or invertebrates present in the study area. small mammals that commonly eat tree seeds. In For simple observational techniques, see Bookhout British Columbia, the deer mouse (Peromyscus (editor, ) for small mammals and birds, and maniculatus) is perhaps the single most important Southwood () and Pedigo and Buntin () consumer of tree seeds. Chipmunks (Eutamias for invertebrates. townsendii on the coast and E. amoenus in the Seed predator censuses are needed when it is im- interior) and voles (Microtus and Clethrionomys portant to link the numbers of seed eaters to the species in the interior) have also been identified as number of seeds eaten and for studies that seek to significant seed predators (Sullivan et al. ). Red determine the proportion of seed loss attributable squirrels (Tamiasciurus hudsonicus) are known to either to different causes or among specific seed harvest –% of the cone crop of some conifer predators. Censuses are usually done before the species, and up to % of the cones from any one study—to establish a baseline—as well as during the tree (Hurly et al. ; West ). study. For established census techniques, see von Bird species that prey on seeds or cones before Trebra () and Sullivan (a) for small mam- dispersal include hairy woodpeckers (Picoides mals; Franzreb () and Millikin () for birds; villosus), Clark’s nutcrackers (Nucifraga columbiana), and Hulme () for invertebrates. Von Trebra red crossbills (Loxia curvirostra), and white-winged (), Sullivan (a), and Gashwiler () also crossbills (L. leucoptera) (Eremko et al. ). About incorporated surveys of animal populations into % of the annual diet of red polls (Carduelis flam- research on conifer seed predation. mea) consists of paper birch and Alnus spp. seeds Observations about possible seed predators in the (White and West ). Common ground-feeding study area are also important in helping to determine species include juncos (Junco oreganus), varied the approach and methods used to study seed preda- thrushes (Ixoreus naevius), song sparrows (Melospiza tion. For example, different techniques will be melodia), fox sparrows (Passerella iliaca), white- required to study animals that eat seeds on the tree crowned sparrows (Zonotrichia leucophrys), pine as opposed to those that eat seeds on the ground. siskins (Carduelis pinus), and golden-crowned spar- rows (Zonotrichia coronata) (Eremko et al. ). . Approaches to Studying Seed Predation Insects are the most commonly studied group of invertebrate seed predators, although some attention Studies of seed predation can be divided into those has also been paid to mollusks. All conifers have in- that examine predation on natural seed crops or on sect species complexes that attack their reproductive artificially introduced seeds. Studies of natural seed structures (Finck et al. ). Some examples of insect crops can focus on either pre-dispersal (in the tree) or seed predators are the western conifer seed bug post-dispersal (on the ground) predation. Predation (Leptoglossus occidentalis), which attacks the seeds on artificially introduced seeds can be studied using of various species from British Columbia to Mexico, either unmarked seeds or seeds marked with paint.

86 field studies of seed biology .. Natural seed crops versus artificially predators are probably best studied using artificially introduced seeds introduced seeds placed inside exclosures. For smaller Natural seed crops provide seeds of natural abun- seeds (e.g., most British Columbia tree species) mesh dance, species composition, and distribution in both size should not present a problem unless fine mesh is time and space. They do not alter the behaviour or used to exclude invertebrates. Although the screen populations of the seed predators being studied (be- can be removed during seedfall, it would be difficult yond normal fluctuations). Studying predation to be sure that was no predation occurred during on natural seed crops is appropriate to examine this period. predator–prey interactions, to avoid confounding the results with unnatural predator responses, and to .. Predation on natural seed crops study natural regeneration without artificial seeding. Studying predation on natural seed crops involves Introduced seeds may artificially increase the food first determining the species and numbers of seeds source beyond natural background levels, which available for predation. Pre-dispersal seed numbers could elevate predator numbers or alter their behav- may be estimated by counting the number of seeds, iour in other ways. The quantity of available food will cones, or other secondary reproductive structures on also be increased if only filled seeds are used (not all representative trees in the study area. Such estimates natural seeds will be filled). must be done before any predation begins and are Natural seed crops are required for studies of pre- essential for studies of pre-dispersal predation. As dispersal seed predation, as no techniques for artificially with all estimates, the problems associated with attaching seeds to trees have been documented to date. error must be taken into account (see Section . Using natural sources of seeds also enables researchers for methods used to estimate natural seed produc- to separate pre-dispersal from post-dispersal predation. tion). See Figure . for an example of the life However, studies of natural seed crops require the ad- table approach. ditional preliminary step of determining the species and Pre-dispersal estimates can also be used to establish numbers of seeds available, which is not necessary when the baseline for post-dispersal (ground) predation using introduced seeds. studies, but trapping seeds on the ground is enough Artificially introducing seeds is probably the best to give an estimate of the number of seeds available approach for experimental research because the in- for ground feeders (see Section . for detailed meth- vestigator can start with the same number and odology on seed trapping). If trapped seeds are species of seeds in each experimental unit. This is compared with pre-dispersal estimates, it is possible also the obvious approach for studying the effects of to separate seed predation (or at least seed loss) seed predation on reforestation through artificial occurring before and after seed dispersal. seeding. The spatial variability and unpredictability Pre-dispersal predation can be assessed by of natural seed supply would require a larger sample comparing the estimated number of seeds or repro- size and preliminary surveys (seed trapping) to deter- ductive structures (e.g., cones) on selected trees mine an adequate sample size for the experimental before and after predation (e.g., see West ). This design. Because seeds can be introduced artificially is probably the easiest method to use, but the error at any time, this approach is also appropriate for associated with estimating seed numbers may be research on the time of year that seeds are least or high. Another method is to compare estimates of most vulnerable to predation. Researchers can also the number of seeds or reproductive structures on use both natural and artificially introduced seeds the tree before predation with the number of seeds to study different aspects of predation in the collected in seed traps on the ground—after dispersal same project. but before ground predation. This method assumes For exclosure-type studies, there may be a conflict that predation is the only source of seed loss before between the size of seeds and the mesh size of devices dispersal. It is also theoretically possible to place used to exclude predators, particularly birds. Seeds exclusion devices (e.g., screens or cages) around that are too large (e.g., Garry oak acorns, winged maple certain branches to prevent predation. Seed predation seeds) to pass through the mesh required to exclude can then be assessed by comparing seed number

section 5 seed predation 87 estimates on protected branches with numbers on effects of declining seed numbers (i.e., because preda- unprotected branches. We have found no docu- tors may make less effort as seed numbers go down mented examples of this last method. and therefore predation would decline at a different Post-dispersal predation is usually determined by rate). An advantage of marking seed locations, even comparing the number of seeds or germinants found without replacement, is that it could help determine on the ground in an area that is subject to predation, how many seeds are lost to other causes, such as ger- with the number of seeds or germinants found in a mination or rot. comparable area where predation has been excluded. Both marked and unmarked introduced seeds can Approaches to exclusion are discussed in more detail be used to help determine loss to different predators in Section .. under Unmarked seeds. The numbers and to causes other than predation, such as being of seeds before and after predation in fixed areas with- unable to relocate seeds. Glass beads, the same size as out exclusion could also compared. This approach the seeds being studied, have been used to determine does not allow any assessment of the number of seeds the size of the loss due to the inability to relocate lost to other causes. seeds (Johnson and Fryer ).

.. Predation on artificially introduced seeds Unmarked seeds The first step in a study on artificially introduced Experiments that use unmarked seeds are relatively seeds is to distribute the seed. This can be done simple to set up and require no specialized equip- from the air over large areas or by hand over ment or materials. For these reasons, more seeds can smaller areas. be monitored for the same effort, which can improve Large-scale distribution is used for operational sample size. However, naturally dispersed seeds must seeding and this method can be used for research on be excluded or background seed rain recorded to the impact of predation on artificial seeding for re- separate unmarked experimental seeds from generation. Seed distributed this way is similar to naturally dispersed seeds. naturally dispersed seed in that the researcher has no Unmarked seeds can be studied both with and control over the number of seeds per experimental without exclosures, employing methods similar to unit, although the spatial distribution of seeds may those used for studying post-dispersal predation on be less variable than with natural dispersal. Seed traps naturally dispersed seeds. Distributing unmarked can be used to evaluate seed distribution following seeds in defined areas and then counting the survi- aerial seeding. vors one or more times over one or more seasons is Smaller-scale hand seeding is more labour- the simplest procedure. However, to determine other intensive but better suited to studies requiring tight causes of seed loss or to distinguish among predators experimental control, because the same numbers of (when using unmarked seeds) it is necessary to selec- seeds can be placed in each experimental unit. With tively exclude different categories of predators (e.g., hand seeding, there are two possibilities: birds, small mammals, invertebrates). With selective . unmarked seeds can all be distributed at the exclusion of predators, unmarked seeds can be used beginning of the study and the remaining seeds to distinguish among broad predator groups, but not counted one or more times, potentially until no among individual predator species. more seeds are found; or Different predator groups can be physically . the location of each experimentally distributed excluded from seeds with different types of cages seed can be marked (e.g., with toothpicks) and the (exclosures). Consumption can be compared among missing seeds replaced at each monitoring date. different exclusion devices and with no exclusion to assess the proportion of seed loss attributable to A single input of seeds may more closely mimic each group. Studies by Gashwiler () and Hulme natural seedfall patterns (and therefore predator () are good examples of this approach. Excluding response) and is less time consuming. Replacing all predators may provide some information on seeds is more labour intensive, but the pattern of other types of seed loss, such as germination or seed consumption could be determined without the decay.

88 field studies of seed biology Marked seeds of seeds will help alleviate this problem. Counting Seeds can be marked with either paint or radio- germinants only may underestimate predation since isotopes. Experiments that use marked seeds can some ungerminated seeds could escape predation provide more complete information about causes of and germinate later. A combination of approaches seed loss because the recovery rates are generally high allows the researcher to separate seed loss to germi- (Lawrence and Rediske ; Fraser ) and nation compared to other causes (including individual predator species can sometimes be predation) (see Johnson and Fryer ). distinguished by distinctive marks left on the seed The simplest way to quantify seed predation is to remains. The location in which a recovered seed is count seeds before and once after predation within a found may also provide clues to what ate it (for single year. This approach is useful for pilot studies to example, seed remains found in the burrow of a provide a broad estimate of predation and for mak- particular species). Recovering marked seeds is time ing quick comparisons among several treatments or consuming, and therefore not suited to studies that sites. However, both tree seed crops and predator require a large number of seeds. populations can fluctuate significantly within and Radioactive marking requires highly specialized among years, so results from single counts cannot be equipment and facilities and the laboratory and extrapolated to other seasons or years. operators must be properly licensed to handle Monitoring seed loss several times within one radioactive material. However, at the appropriate year can provide information about the seasonal concentration, radioisotopes do not appear to affect vulnerability of prey seeds. Examples of factors that germination of tagged seeds and yield the highest can affect seasonal seed predation rates include the recovery rates (Lawrence and Rediske ). abundance of other, preferred food sources in sum- Other substances used for marking seeds include mer, and the absence of migrating bird species in plastic paints of various colours (Liddle et al. ), winter. If seeds are trapped for monitoring predation invisible fluorescent paints (Colbry ), and Day- on natural seed crops, patterns in vulnerability can Glo fluorescent dyes (Fraser ). Although paints be correlated with patterns in seed availability. The do not involve the same difficulty in handling as ra- frequency of monitoring has varied in previous dioisotope markers or require specialized recovery studies from two or three samplings (Gashwiler , tools, neither the effect of paints (plastic and ) to weekly samplings for several months fluorescent) on germination nor their resistance to (Lawrence and Rediske ). The former focused abrasion is known. Latex, used to bond fluorescent on specific periods, such as overwinter survival of dye to seeds, provides resistance to abrasion but will seeds, while the latter was able to follow the precise also lower germination rates (Fraser ). Predators fate of seeds tagged with radioisotopes. might also be repelled or attracted by the paint and Multiyear sampling is essential for studying thus bias estimates of predation (e.g., birds see and predator–prey interactions, predicting the long-term respond to colours), but there is no information patterns of predation, studying the effects of distur- available on this potential problem. The technique bances such as forest harvesting, and determining the may also be unsuitable for tiny seeds. Although re- impact of predation on tree regeneration from seed. covery rates are good, they are probably not as high As with single-year studies, monitoring frequency as radiotagged seeds for the same amount of effort. within any one year can vary.

.. Quantifying seed predation . Methods, Techniques, and Equipment Regardless of the approach taken, predation can be quantified by counting seeds or germinants, either See Sections  and . for information on surveying once or many times after predation. Counting num- natural seed crops. bers of seeds is the most common procedure, but could result in overestimating predation because .. Distributing seeds losses due to other causes, including germination, Large-scale distribution of seeds can be accomplished will be counted as “eaten.” Marking seeds or locations with either a fixed-wing aircraft or helicopter fitted

section 5 seed predation 89 with various types of seeders (Mitchell et al. ). be larger for birds, but . cm may still allow several The quantity and uniformity of seed distribution are bird species such as juncos, chickadees, and small controlled by the calibration of the seeder and meth- finches to enter (Gashwiler ). Therefore, to ex- od of flying. Larger areas can also be operationally clude bird species but allow entry by small mammals, planted on the ground using seeders attached to mesh sizes >. cm but <. cm are recommended. machines that create scarified planting spots or The wood frame seed trap (described in Section furrows. This method requires fewer seeds than ..) can be adapted as a vertebrate exclosure where aerial seeding. a design with a lid is required. This design allows for easy access to the exclosure to count seeds and/or .. Excluding seed predators germinants. However, unlike seed traps, exclosures The choice of exclosure design and materials depends should not have window screening on the bottom, as on which predator group or combination of predator this could impede germination of seeds and requires groups you want to exclude. Table . summarizes the removal of all vegetation in the exclosure. exclusion choices for each of the three main predator Exclosures designed to exclude only small mam- groups and combinations of predators. Ground-feed- mals have sides made of a strip of wire mesh topped ing birds and small mammals can be prevented from with a strip of sheet metal and no lid. The height of gaining access to seeds with cages made of wire mesh the sides depends on the type of small mammal to be (hardware cloth) on wooden frames, with or without excluded. Bending the sheet metal outward helps to sheet metal. Invertebrates can be excluded with fine prevent the animals from getting in (Figure .). mesh or sticky barriers, or can be removed from Joints between pieces of sheet metal must be smooth selected areas with chemical poisons. and tightly sealed since chipmunks have been able to Similar designs can be used for both birds and climb exclosure walls by getting a toehold in the small mammals, but bird exclosures must have mesh seams (Wagg ). Vegetation that the animals could over the top, whereas small mammals can be excluded climb to get into the excluded area must also be re- with open-topped designs as long as the walls are tall moved on a regular basis. The depth to which sides enough and of materials the mammals cannot climb are buried will depend on how soft the soil is and (e.g., sheet metal). The walls of small mammal ex- what species of predators are in the area. Walls buried closures must also extend below ground, to prevent  cm deep have successfully prevented invasion, but the animals digging their way in. even burial up to  cm may still allow entry of some Exclosures may be square, rectangular, or cylindri- animals (Gashwiler ). Sheet metal could alter the cal, and enclose areas from . to  m2 and be from microclimate within smaller exclosures, so larger . to . m tall. Mesh sizes smaller than  cm will areas are recommended for such designs. Seeds could effectively exclude small mammals (Wagg ; Gash- then be placed in the centre of the exclosure to avoid wiler ; Sullivan and Sullivan ). Mesh size can microclimate edge effects. Wire mesh allows the entry

 . Summary of exclosure choices for seed predators

Predator(s) to be excluded Exclusion device

Birds Wire mesh cage with mesh lid, mesh >1 cm and <2.5 cm Small mammals Wire mesh and sheet metal cage with no lid, sides buried Invertebrates Pesticides and/or sticky barriers Birds and small mammals Wire mesh cage with mesh lid, mesh <1 cm Birds and invertebrates Lidded mesh cage (as above) with pesticides/sticky barriers Small mammals and invertebrates Wire mesh and sheet metal cage (as above) with pesticides/sticky barriers All three groups Very fine mesh cage with lid and sides buried

90 field studies of seed biology of seeds from natural sources and should not alter Sticky strips could also be laid around the perimeter microclimatic conditions inside the exclosure. of the excluded area, although they would have to be Flying invertebrates can only be physically excluded checked regularly to remove debris that might pro- with a fine mesh (e.g., window screening). Therefore, vide a “bridge.” such exclosures are only practical for studies using Chemical poisons have also been used to separate artificially introduced seeds, because most seed from invertebrate predator groups from each other and natural sources would also be excluded. Flightless from vertebrate seed predators. Note, however, that insects (such as ants) can be prevented from gaining poisoning small mammals for this purpose is not access to seeds placed on an elevated platform by legal in British Columbia (Mitchell et al. ), and in coating the underside of the platform with a sticky any case is considered ineffective because reinvasion substance, such as Tanglefoot™ (Heithaus ). is rapid (Sullivan b; Mitchell et al. ). Because

 . Small mammal exclosure described by Wagg (1964). The three illustrated wall designs show: (a) Simple vertical wall, (b) hardware cloth wall with sheet metal bent downward to the outside, and (c) hardware cloth and sheet metal wall with top bent horizontally to the outside and supported by additional wooden frame. Different widths of sheet metal and hardware cloth should be tested; however, Wagg recommended that the sheet metal be at least 45 cm wide for designs a) and c) and that the bent portion be at least 15 cm wide.

section 5 seed predation 91 of the potential for poisoning non-target species we Before placing seeds in the field they may be slightly do not recommend using chemical exclusion. moistened with a % Rhoplex solution to minimize any loss of the tracer through weathering. .. Marking and recovering seeds A sodium iodide crystal scintillator is used to relo- cate radioactively tagged seeds in the field (Lawrence Radiotagged seeds and Rediske ; Radvanyi ). Portable scintillo- In Canada, use of radioisotopes requires licensing meters are designed for rugged use and are battery from the Atomic Energy Control Board of Canada. powered with a hand probe. A Geiger-Mueller Proposals are reviewed to determine how the radio- counter is not sensitive enough to gamma radiation isotope is being used, how often it is used, what the to be effective. The range of the scintillator is about concentration is, whether it occurs naturally, and  cm in air and  cm through soil. what the half life is (C. Smith, Univ. B.C. Radiation To locate tagged seeds or hull fragments, either a Safety Officer, pers. comm., ). An environmental dial reading or earphones can be used. With the review, specific provisions for disposal of the probe held approximately – cm away from the material, or amendments to an existing licence for radiating source, detecting whole seeds or larger seed particular uses may be required before approval is coat fragments is quite easy even  months after granted. Research that uses low concentrations of a placement of the seeds (Radvanyi ). When a seed short-lived isotope (especially a naturally occurring is missing from the point of initial placement, a spiral one) will be subject to fewer restrictions and diffi- search pattern with the scintillometer probe should culties in obtaining approval. It should be noted that be conducted until the seed is found. federal regulations concerning use of radioactive materials are being rewritten. Painted seeds In several older studies, the radioisotope Scan- Plastic paints and Day-Glo fluorescent dyes can be dium46 was used to tag seeds because it is a strong seen in daylight. Day-Glo pigments fluor-esce under gamma emitter, has a half-life of  days, has low visible wavelengths such as violet, blue, and blue- solubility, and is not phytotoxic. This half-life is green (Fraser ). Invisible fluorescent paints considered short and the concentrations used appear white in daylight but require a source of ( microcuries per seed) very low. However, there longwave ultraviolet light to cause fluorescence. may be isotopes available that pose a lower risk to the Both plastic and invisible fluorescent paints can be environment and could be adapted for this applica- sprayed onto seeds (Colbry ; Liddle et al. ). tion using the methods, summarized below, from The D-series of Day-Glo pigments has increased the older literature. We have not found any recent stability in direct sunlight and can be applied using published accounts of the technique. the methods of Fraser () by: () immersing seeds 46  ° Scandium , in the form of ScCl solution, is first for minutes in a constantly stirred, C solution of diluted to a working solution of  microcuries/mL . g powdered dye in  mL acetone, then removing (Lawrence and Rediske ). A drop of the sur- and air drying on paper towel, or () immersing factant Tween- added to the working solution seeds until completely coated in a : solution of Dow increases penetration of the seed coat by the radio- Latex -R and distilled water (constantly stirred), tracer. The tagging procedure is standardized by removing seeds and placing in a constantly agitated soaking  cleaned seeds for  hour in  mL of container of powdered dye until thoroughly coated. diluted Sc46 solution. Seeds are removed and air Excess dye can be removed by screening. The coated dried for  hours. The initial activity of the seeds are then air dried on paper towels. The second tagged seeds should average about  microcuries method makes the dye very resistant to weathering, per seed. but does reduce germination. Sc46 at a concentration of  microcuries per seed Recovery of painted seeds is labour intensive and does not appear to impair the germination percent- time consuming, and involves sifting through the site age of tagged seeds (Lawrence and Rediske ). for seeds. Locating seeds marked with invisible fluor-

92 field studies of seed biology escent paints is also a difficult task, and a longwave ground before and after predation. An estimate of p is ultraviolet light source is required for recovery. Or- given by the formula: ganic dyes such as Day-Glo fluorescent pigment number of seeds remaining fluoresce under daylight conditions and recovery of pˆ =  - . marked seeds can be as high as % (Fraser ). number of seeds available

Interpreting marks on seed remains The approximated standard error of this estimated Marks left on seeds fed to specific captive predators proportion is given by the equation can also be compared to marked and recovered seeds. Redpolls and chickadees slit the seed coat and remove pˆˆ( - p) S.E.(pˆ) = , the embryo of birch seeds (J. Zasada, pers. comm. n ). For illustrations and descriptions of marks left by other specific predators, see Lawrence and Rediske where n is the number of seeds available. (, ) and Radvanyi (, ). Radvanyi () described marks made by captive predators Example of white spruce seed as follows: To compare the proportion of seeds of the same spe- • Mice and voles generally remove a third to half cies taken by two different groups of predators, use the seed coat on one side of the seed and consume either a z-test when n is large (both n(p) and n(-p) the entire endosperm and embryo. The edges of must be greater than  for the two sets of predation the remaining seed coat are scalloped but entire. data), or a contingency table chi-square (χ2) test. • Chipmunks chew the seed in half, usually with the Let pˆ , n denote the proportion of seeds eaten by plane of the cut edge at right angles to the long axis and number of seeds available to predator , and pˆ, of the seed. The chewed edges of these seeds tend n the same for predator . The estimated difference to splinter and are more deeply cleft than those between the proportions of seeds lost to predator   eaten by mice. compared to predator is . (pˆˆ - p) , with the approxi- • Shrews generally make a smaller opening in the mated standard error seed coat than do mice and chipmunks. The   chewed edges are more finely serrated and the pˆˆ( - p) pˆˆ( - p) S.E.(pˆˆ - p ) = + . endosperm incompletely removed.   n n • Insects exhibit considerable variation in the size and nature of the opening in the seed coat. To test the null hypothesis that the difference between these two proportions is zero versus the . Data Analysis alternative hypothesis that the difference is not equal to zero, use the z-test with the test statistic, Much of the information about experimental design pˆˆ - p and sampling considerations discussed in seed dis- z =   persal studies (in Section .) applies, with some S.E.(pˆˆ - p) adaptation, to seed predation studies. Analyses for seed predation studies general seek to: when the sample size is large. The computed test sta- • estimate the proportion of seeds lost to seed preda- tistic is compared with tabulated values from the tors; and standard normal table (z-table). The null hypothesis

• compare these proportions among different seed (of no difference) is rejected if |z| > zα/ where zα/ is species, different groups of predators, or different the tabulated z-value corresponding to a cumulative site conditions. probability of ( - α/). If the large sample size requirement for the z-test The proportion (p) of seeds lost to predators over is not satisfied, then the contingency table approach time can be estimated from the number seeds on the can be used to make comparisons. In this case, the

section 5 seed predation 93 actual seed counts are used as the data rather than the table approach is suitable for comparing more than proportions lost and remaining. Table . shows the two predators and more than two site conditions (e.g., data structure. three or more site preparation treatments, or seral stages). One requirement of the chi-square test is that the expected count in each cell must be greater than .  . Two-dimensional contingency table for To compare more than two factors, a log-linear analyzing seed losses to two predators model which is a generalized approach to analyzing multidimensional contingency tables can be used. Number of Number of Row seeds not eaten seeds eaten total For further discussions on categorical data analysis methods, see Agresti (), Chapter  of Johnson and Bhattacharyya (), and Lesperance (). Predator 1 n(1, not eaten) n(1, eaten) n 1 When monitoring seed predation behaviour over Predator 2 n(2, not eaten) n(2, eaten) n2 time, two different methods can be used to measure Column total n(not eaten) n(eaten) N the proportion of seeds lost to predation:

 where: n(, not eaten) = number of seeds not eaten for method Measure the proportion based on the ini- predator  tial number of seeds available and the number of n(, eaten) = number of seeds eaten for predator  seeds remaining at each measurement time. These n(, not eaten) = number of seeds not eaten for are, in fact, cumulative proportions. The resulting predator  time plot will have a decreasing pattern. The data n(, eaten) = number of seeds eaten for predator  obtained from this method can be used to determine n(, not eaten) + n(, eaten) = n how much seed to put out to have adequate germina- n(, not eaten) + n(, eaten)= n tion for regeneration.  N = n + n = total number of seeds available method Measure the proportion based on the number of seeds available at the beginning of each The chi-square test can be used to compare the distri- time period and the number of seeds remaining at bution of the seed counts across the two categories for the time of measurement. The resulting time plot will the two predators. The chi-square test statistic is given by not necessarily be decreasing. It will likely have a cy- clical pattern, showing the times at which predation (observed - expected)2 χ2 = Σ is at its highest or lowest. These data can be used to all cells expected determine the optimal time for releasing seeds for where observed represents the observed count in the best germination results. sample, and expected represents the expected count. . The expected counts can be computed by multiplying Table illustrates the two methods for computing the corresponding row and column totals, and then predation proportion over time using hypothetical data. dividing by the grand total. For example, the ex-  . pected number of seeds not eaten for predator  is: Comparison of methods for calculating propor- tion of seeds lost to predation over time

n × n(not eaten) E(1, not eaten) = N . Number method  method  of seeds cumulative proportion eaten χ2 The observed value is compared with a tabu- Time not eaten proportion eaten per time period χ2 lated value, α having degrees of freedom equal to   (number of rows - )(number of columns - ). 0 100 0 0 Both the z-test and the contingency table chi- 1 90 0.1 0.1 square test can be used to compare the proportion 2 72 0.28 0.20 of a particular species of seed lost to several different 3 66 0.34 0.08 predators in two different site types (e.g., different 4 53 0.47 0.20 site series, logged versus unlogged). The contingency

94 field studies of seed biology SECTION 6 SEED BANKS

The wingéd seeds, where they lie cold and low, Each like a corpse within its grave, until Thine azure sister Spring shall blow. (Percy Bysshe Shelley “Ode to the West Wind”)

. Background on or buried in forest floor). Recent results from a seed burial study on southern Vancouver Island (C.L. Many of the viable seeds produced by trees fall to the Leadem, unpub. data ) suggest that the seeds of ground, become buried in the soil, and do not germi- many British Columbia conifer species and some nate for several years. Seeds of other species may be hardwood species germinate within the first growing retained by trees for many years before they are re- season when buried outside. A few hardwoods (e.g., leased and germinate. These dormant, viable seeds, alder and birch species) persisted for up to  years stored in either the soil or in tree canopies, are called after burial and may last even longer. Seeds of pin seed banks. This chapter deals with soil seed banks cherry (Prunus pensylvanica) are known to remain only; canopy seed banks are discussed in Section .. dormant in soil for several decades (Marks ). In because the methodology is similar to that used for contrast, the viability of seeds of Populus and Salix pre-dispersal surveys. species lasts from only a few hours to a few weeks Knowledge of the species composition, numbers, (Haeussler et al. ) and, therefore, these are not and distribution of seeds in soil seed banks is impor- considered seed bank species. tant for understanding and predicting natural Questions that might be asked in seed bank stud- regeneration and revegetation after disturbance; ies include the following: developing effective vegetation management pre- scriptions; and describing overall floral diversity. • What species are represented in the seed bank? Seed banks of tree species in northern temperate • How many seeds of each species are present in the and boreal forests, such as those found in British seed bank? Columbia, have not been studied extensively. Accord- • How many of the seeds are viable? ing to Archibold (), conifer seed viability may last • How many of the seeds found in seed banks will from  to  years under controlled conditions, and germinate () under controlled conditions and/or perhaps as long as  years for white spruce (see Sec- () in the field under natural conditions? tion .). The longevity of angiosperm tree seeds in • What is the vertical distribution of seeds? artificial storage (freezers and refrigerators) ranges • What is the horizontal distribution of seeds? from a few months to decades, depending on the spe- • How is seed distribution in the soil related to cies and storage conditions. For more details see seed source? Schopmeyer (technical coordinator, ). • How is germination of seeds affected by Although there has been much research into opti- disturbance? mum artificial storage conditions to maintain seed • How long can seeds remain viable in the soil? viability, little is known about how long tree seeds • What conditions break the dormancy of buried remain viable under natural conditions (i.e., either seeds?

section 6 seed banks 95 . Approaches to Studying Soil Seed Banks seeds present. However, the seed separation process for direct counts is extremely time consuming, espe- The most common approach to studying existing cially where the density of seeds is low. Also, to seed banks involves collecting soil samples from the determine how many seeds are viable, additional tests area of interest. Species, numbers, and distribution must be done (e.g., tetrazolium stain). Often a high are then determined either by separating the seeds proportion of seeds are non-viable, so a large number from the soil and directly counting and identifying of seeds must be tested to get an accurate estimate of them (direct count method), or by allowing seeds to the viable proportion. In addition, small seeds may germinate from the soil samples in a controlled envi- be missed or hard to identify. ronment and counting and identifying the germinants With sample germination, only viable seeds are (sample germination method). With either direct counted. This method is less labour intensive than counts or sample germination, vertical distribution direct counts and can yield good results when the can be assessed by dividing soil samples into layers objective is to determine the number and species of parallel to the soil surface. viable seeds present in the soil (Gross ). Some Two additional approaches have seldom been used species are more easily identified as plants (germi- but are essential for meeting some of the above objec- nants or seedlings) than as seeds. It takes longer to tives. Monitoring germination from seed banks in the get results from sample germination because the field is used to determine the number and species monitoring period required is at least – months. of seeds that will actually germinate under field The main problem with sample germination is that conditions and thus contribute to post-disturbance some species and individuals will probably be missed, regeneration (Yearsley ). Studying seed mortality because their germination requirements are not met. and the duration of dormancy under natural condi- Thus, seed numbers can be underestimated and tions in the soil requires burial of known quantities species composition biased. Finally, the number and of seed which are retrieved at regular intervals and species composition of ungerminated seeds (whether tested for viability (e.g., Granstrom ). These two viable or non-viable) cannot be determined with approaches can be used together to enhance the in- this method. formation collected. Other approaches to studying germination are discussed in Section . (seed germi- .. Assessing vertical distribution nation under controlled laboratory conditions) and For vertical distribution, layers can correspond either Section . (seed germination under field conditions). to the functional layers of forest floor (i.e., lfh layers: litter, fermentation, and humus layers) or to layers of .. Seed separation versus direct counts equal thickness. Functional layers can also be defined Direct counts are appropriate when it is important simply as forest floor (organic layers) or mineral soil. to do a complete inventory of seeds present including The functional division will provide information that viable and non-viable seeds. Sample germination is can be linked to other soil biological processes such more suited to pilot projects where a rough estimate as rates of organic matter accumulation and decom- of the number and species of viable seeds is needed. position, soil fauna (including seed predators), soil Both techniques are appropriate when the objective mixing, etc. These layers often vary considerably, is a baseline inventory of numbers and species com- however, so the volume of soil involved will have to position. The most thorough approach is to first be determined for each layer. Also, environmental separate seeds from the soil, count them, and then conditions such as temperature may vary with depth. germinate the separated seeds. Another approach is Equal-thickness layers are the best means to generate to separate seeds from the samples after a period of depth distribution patterns for seeds. These distri- germination. butions can probably be more easily linked to Direct counts yield the most accurate measure of environmental conditions and the division of the species and numbers of seeds present in the soil samples is easier because no judgements about the seed bank (see Brown ). This method also pro- boundaries between functional layers are required. vides data on the number and species of non-viable However, because the lfh layers vary in thickness,

96 field studies of seed biology seeds from one functional layer may be compared there are few large roots and little or no coarse litter to seeds from another (e.g., litter with fermentation). or other organic material at the surface (Figure .). Augers do not work as well for collecting forest floor .. Monitoring germination in the field samples because there are too many roots. The auger Monitoring germination in the field is used to deter- may crush or tear samples because of the high con- mine what germinates from the seed bank under tent of partially decomposed organic matter, natural conditions (including various disturbance especially in the litter layer. regimes), and/or the long-term contribution of the seed bank to natural regeneration. Field monitoring will not provide any information about non-viable seeds and viable seeds that have not germinated, and the information is likely to come only from seeds close to the surface. Also, with this method there is little control over conditions such as predation or unplanned disturbances. Field germination can be done in conjunction with environmental monitoring to determine the conditions that result in germina- tion. Seed trapping should also be part of field germination studies to help separate the seed bank germinants from recent seed rain germinants. Moni- toring should be carried out over several weeks to months per season, and for more than one season, to describe the seed bank flora, because conditions in  . Using a soil auger to remove a soil core for any  year can have a profound influence on whether seed bank studies. seeds germinate and survive as plants.

.. Seed burial experiments A sharp serrated knife (e.g., a new bread knife) The age of seeds found in natural seed banks cannot works well to cut samples of forest floor (Figure .a). be determined. This is essential to understanding and Pruning clippers will cut through the finer roots, and predicting the length of viability and therefore the a small pruning saw and/or long-handled pruning potential for germination. Burial experiments can be loppers can be used to cut through larger roots. You used to determine how long seeds can remain viable may have to cut a wedge of forest floor away from in the soil. Such experiments can never completely one side of the sample to gain access to it, especially mimic natural conditions because the seeds are for samples thicker than about  cm (Figure .b). usually placed in a mesh bag to avoid confusion with Sample locations should be moved a few centimetres naturally occurring seeds and for easy retrieval. Mesh away from trees or stumps to avoid large roots that bags may exclude invertebrate and other seed preda- can take up a large portion of a small sample and bias tors and thus bias estimates of seed loss in the soil. the volume collected. Use a flat trowel or spatula to To avoid this problem, seeds could be radioactively lift the samples out after the sides have been cut (Fig- tagged, buried without enclosing them in mesh bags, ure .c). A Japanese garden knife is sturdy enough to and retrieved using a scintillometer (see Section ), lift the samples out, and is sharp enough to cut the but recovery of seeds may not be as complete. soil. An alternative is to lift out a larger volume of soil than is actually needed with a sharp shovel and then . Methods, Techniques, and Equipment trim the sample to the required size. Square samples ranging from  to  cm square .. Collecting and preparing soil samples (Matlack and Good ; Brown ) are easy to Soil augers are best suited to collecting soil samples in handle and fit into standard inserts for greenhouse grasslands or in the mineral layers of forest soils where trays. Samples smaller than about  ×  cm are diffi-

section 6 seed banks 97  . Method for cutting a square forest floor sample: (a) cut the sides of the sample with a knife; (b) cut and remove a wedge of forest floor beside the sample; and (c) cut the bottom of the sample and lift out with a spatula. cult to keep intact unless they are thin (e.g., <  cm). have just gone through winter in situ. Samples col- The thickness of the sample may vary depending on lected in summer or fall should be stratified for at soil thickness and the part of the profile of interest. least  weeks at –°C. For more information about Auger sizes range from about  to  cm in diameter; stratification of seeds or samples before germination,  or  cm are common sizes. They are capable of refer to Sections .. and .., and Tables . and .. removing cores up to  cm thick. If vertical distribution information is desired, cut Keep square samples intact until they are divided the square samples into layers parallel to the soil sur- into layers by placing them directly into inserts and face (Figure .). A sharp serrated knife and clippers then into standard plastic greenhouse trays for trans- make it possible to cut layers of forest floor as fine as port. Avoid compressing samples unless vertical  cm thick, if samples are small and moist enough to distribution is not important to the study. If the trays hold together. This is easier to do in the lab than in must be stacked, invert strong greenhouse trays over the field. Samples collected with an auger can be di- full trays to take the weight, or provide some other vided in the field by gradually pushing the sample support for the upper layers of trays. Plastic sheets out of the auger (Figure .a), measuring the desired or remay must be placed between stacked trays to thickness, and slicing the layers off with a sharp ser- prevent seeds falling through the drainage holes into rated knife (Figure .b). lower samples. If vertical distribution is not impor- tant or samples are divided into layers in the field .. Seed separation and direct counts (such as those collected with an auger), then the For direct counts, seeds must first be separated from samples may be put into paper bags for transport. If the rest of the soil sample. Seed separation involves plastic bags are used, allow for air circulation to pre- some or all of the following steps: dispersing or vent samples from going mouldy and killing seeds breaking up the soil sample, floating and removing before they have a chance to germinate. larger pieces of organic debris, washing the remain- Samples collected in the summer and fall will ing sample through sieves of various sizes, and contain seeds from the current year’s crop. Samples floating and removing seeds (see Malone ; Benoit collected in the spring will lack seeds that have germ- et al. ). A similar technique called elutriation uses inated over summer or been lost to winter mortality a modified pneumatic root elutriator (designed to (e.g., predation). If seasonal patterns of seed bank separate organic matter from soil) to separate seeds numbers are important, then samples should be from the soil (Gross ). collected in both spring and fall. Solutions of hexametaphosphate or Calgon ( g/L) Samples collected for immediate germination in and sodium bicarbonate ( g/L) are used to disperse the spring do not need further treatment since they or break up the soil sample (Benoit et al. ).

98 field studies of seed biology  . Preparing square soil samples for greenhouse germination: (a) a sample is split into layers (parallel with the soil surface) using a cardboard box template as a guide to ensure the layers are of uniform thickness; (b) each layer is placed in an individual greenhouse tray insert; and (c) inserts are placed in greenhouse trays.

a Magnesium sulphate (Epsom salts) can also be added (Malone ). Soil separation may also be promoted by adding detergent to eliminate surface tension (J. Zasada, pers. comm., ). After the soil is mixed vigorously ( minutes) or allowed to soak ( min- utes) in this solution, the organic material—including the seeds—floats to the top. The suspended material is passed through one or more sieves to separate remaining soil and organic matter particles from the seeds. A single fine sieve can be used for a small volume of sample material, or a coarser sieve for large seeds. If you are trying to extract seeds of a particular species of known size, the mesh size of the sieves can be selected to maxi- b mize retention of seeds and exclusion of the other materials. For small seeds, a wide range of seed sizes or large volumes of sample material, samples should be washed through several mesh sizes (e.g., . mm down to . mm). The size of the finest-mesh sieve should be less than that of the smallest seeds (if known). The material left in the sieves is transferred to filter paper to dry for  hours. Dried seeds are separated from the other debris by hand, using a dissecting microscope if necessary, and tallied by species. Reference collections of seeds are used to identify seeds (the University of British Columbia Botanical Gardens have some voucher specimens). The viability of most seeds can be determined using tetrazolium stain (described by Moore ). Seeds  . Dividing a soil core into layers. For each layer of species that do not stain reliably with tetrazolium the sample is pushed out of the auger and may be tested for viability by germination in a growth   (a) measured, then (b) sliced off and placed chamber or other means. See Section . and Leadem in a labelled bag. () for more information on seed viability tests.

section 6 seed banks 99 .. Germinating seeds in samples liner in the container will prevent tiny seeds being Samples are usually germinated in a greenhouse, but lost through the drainage holes. they can be placed in a growth chamber or kept out- Samples should be randomly distributed in a side. Because environmental conditions can be finely greenhouse since conditions usually vary throughout adjusted, a growth chamber is useful for controlled the building. Rotating samples periodically will en- experiments or for testing seeds separated from soil sure that all samples experience all conditions. If samples. Growth chambers, however, are too small to possible, try to record the temperature manually in be used for large volumes of soil. A greenhouse is several different areas in the greenhouse to determine essential if the samples are to be germinated in the how much variation there is. You may have to adjust winter. In the greenhouse, temperature can be kept the watering regime if samples dry out at different relatively steady with a computerized system, or may rates in different areas. fluctuate by up to °C using manual thermostats. Samples must be protected from contamination by Light and watering regimes can be maintained auto- wind-dispersed seeds, even in the greenhouse. Remay matically with timers or computer control. Samples is an effective barrier against unwanted seeds but lets kept outside must be adequately protected from con- in light, air, and water. However, any barrier must be tamination by outside seeds. Outside germination easy to remove for germination counts. Instead of a conditions cannot be controlled, but it is still a useful barrier, you can distribute trays of sterilized potting way to monitor a large number of samples where green- soil among the samples and estimate contamination house space is limited. If the location is close to the by counting germinants in the potting soil. site where the samples were collected, conditions can Water the samples frequently (as often as once a be similar to those experienced by the intact seed bank. day) as they may dry out quickly and both seeds and Inserts in greenhouse trays are the most efficient germinants are vulnerable to drought. During germi- way to fit samples into a given space (Figure .). If nation, samples should be kept above freezing and space is not limiting, any size or shape of plastic pot below °C. Temperature is often kept on a diurnal will do as long as the samples are treated consistently pattern that is warmer in the day than at night which (i.e., do not put some in deep pots and others in shal- can be synchronized with the light regime to achieve low pots). Samples may be mixed with or placed over a specific daylength. Light supplementation may be a sterilized growing medium, such as potting soil, to especially important for samples germinated in the provide extra soil for growth of germinants and to winter. If known, temperature and light conditions help prevent thin or small samples from drying out. can be set to mimic natural daily and seasonal The samples may be left intact or broken up. A remay regimes, as these will give results most similar to field germination. Germinants should be clipped off or pulled as soon a they have been positively identified. Some species are distinct even at the cotyledon stage and can be removed quickly. However, most germinants will need to be grown until they produce true leaves and, sometimes, reproductive structures, before they can be identified. New germinants that cannot be ident- ified immediately must be marked to distinguish them from older unidentified germinants. Otherwise, new germinants may be mistaken for germinants that were counted on previous sampling dates but have since died, resulting in underestimated seed numbers.  . Soil samples in the greenhouse. Standard Mark each new germinant with a toothpick, a small plastic inserts and trays efficiently accommo- loop of thread or wire, or a collar cut from a plastic date the large number of samples required to drinking straw (J. Zasada, pers. comm., ), using a adequately characterize a seed bank. different colour for each sample date. Toothpicks are

100 field studies of seed biology suitable where there are only a few germinants spaced larger plots can be used to maximize the area sampled well apart. Thread or wire loops or straw collars work with fewer plots. Plots should still be small enough to best where there are many germinants. allow for access without walking in them to look for Another method is to transplant unidentifiable germinants. The abundance of germinants should be germinants as soon as they emerge. However, this taken into account, if possible, when deciding on plot approach includes a number of drawbacks: more size. In general, the more abundant the germinants space is required for the individual pots; more time is the smaller the plot can be. Smaller plots will also be needed to transplant and care for all the germinants; easier to track germinants when other vegetation is ungerminated seeds could be removed from the sam- abundant. Larger plots are appropriate in areas with ple with the soil around the transplants roots; and few germinants and sparse vegetation. For studies mortality may be high due to the transplanting proc- where soil samples are also taken to compare field ess. Transplanting is recommended only for species results with the overall seed bank, the monitoring that must be grown to a large size or for a long time plots should be the same size, shape, and distribution before a positive identification can be made (see as the soil samples. Vertical distribution may be Franklin ). gauged by scraping off layers of soil of known thick- The samples should be monitored frequently (two ness and then monitoring germination. or more times a week), especially at the beginning of Like greenhouse germinants, individual field the germination period, until the rate of germination germinants should be marked as they emerge. Loops and mortality has been established. Besides drought, of coloured wire or plastic drinking straw collars may germinants can be lost to attack by fungus, mould, in- be best because they are less likely to be eaten or re- sects, and other pests. Frequent monitoring will help moved by natural causes, and will not rot. It is also you observe potential problems so that solutions can useful to map the location of germinants within the be found before many seeds or germinants are lost. monitoring plot to help keep track of them and pro- After an initial flush, germination often slows vide information about the horizontal distribution down. Stirring, crumbling, or turning samples over of germinants. If only the identity and number of can stimulate renewed germination by exposing germinants are of interest, then the germinants can ungerminated seed to light. Varying the temperature be clipped off or pulled out as soon as they are regime can also help, or samples can be put through identified. For studies on the contribution of the seed another cycle of cold stratification. Samples should bank to natural regeneration, markers will have to be monitored as long as seeds are still germinating, remain on the germinants to track them over time. If if possible. Several months will be required in most so, the original markers will have to be replaced with cases, and possibly more than one year. larger ones as the plants grow. The study site should be monitored frequently .. Monitoring germination in the field (two or more times a week) because germinant mor- (See also Yearsley  and Section , Table ..) tality can be high, especially during a dry, hot spell. The study site must be clearly marked on a map with Good access to the site is essential, otherwise moni- written directions so that it can be easily relocated. toring frequency may be compromised. Monitoring Within the site each monitoring plot must also be should begin as soon as snow (if present) has melted marked. Depending on the layout, tall stakes (rebar and continue as long as new germinants are being or wood) painted and flagged can be used to mark found. Recording and monitoring soil environ- the boundaries of larger areas enclosing several mental conditions (e.g., moisture, temperature) monitoring plots. Each corner of the monitoring plot along with above-ground conditions (e.g., tempera- should be marked with a short piece of rebar or large ture, precipitation) will help to explain the response spike, painted and flagged at the top. An accurate of buried seeds. map of the study site showing the locations of all the In the field, seed bank germinants must be distin- monitoring plots in relation to each other, and to guished from those of recent seed rain. Records important permanent site features, is also essential. should be kept of potential sources of seeds in the If only field monitoring is being carried out, then vicinity of the study area and of the timing of seed

section 6 seed banks 101 dispersal, especially wind-blown seeds. Seed traps can The causes of seed loss may be difficult to deter- also be used to estimate the amount and species of mine. Where germination has taken place soon after seeds in the current seed rain (see Section ). Trap burial it may be hard to tell whether the seeds germi- numbers, size, and distribution should be the same as nated or simply rotted away. Losses can also be the monitoring plots. Combining field monitoring caused by fungi, microorganisms, or predators that with determining the seed bank contents of soil sam- chew through the seed bags. Undamaged seeds can ples removed from the site, will provide information be tested for viability using a variety of standard about which species are definitely not in the seed methods (see Section . and Leadem ). bank. Although barriers (e.g., remay) can be spread over the plots to exclude current seed rain, they may . Experimental and Sampling Designs significantly alter natural conditions (e.g., raise tem- peratures). Both covered and uncovered plots can be .. Seed bank inventory studies installed but this will increase the number of plots Seed bank inventory studies involve determining the required for adequate replication. number, species composition, and distribution of seeds in the soil. The sampling design employed de- .. Seed burial experiments pends on the distribution of seeds in the study area Mesh or cloth bags made of nylon (e.g., nylon stock- (or on what the researcher believes the distribution ings), fibreglass screening, or other synthetic fibres is). Except for the case where the researcher is inter- can be used to contain replicates of seeds for burial. ested in assessing the horizontal distribution of seeds, Natural fibres such as cotton are less suitable because random sampling should be used. Random sampling they may rot if the seeds are to be buried for more is based on the notion that each soil sample has an than a few months. If necessary, seedlots can be pro- equal probability of being selected, and selecting a tected from larger seed predators by enclosing each soil sample in no way affects the selection of any batch of bags in hardware cloth cages (Haywood ). other samples. Random sampling ensures that no Batches of seeds to be exhumed on different dates systemic error is introduced into the data. For should be buried far enough apart so that it is possible assessing horizontal seed distribution, systematic to dig up each one without disturbing the remaining sampling—usually using a grid—should be used. batches. Seeds should not be buried much deeper If it is known that seed distribution is different than they are likely to occur under natural conditions for different site characters, such as site series, then (although this may not be known for some species). the study area should be stratified by the site charac- However, it is useful to contrast more than one depth, ter before sampling. Stratified sampling often especially if environmental conditions (e.g., soil tem- produces more accurate estimates. The stratification perature) can be monitored at the same time. Most criteria should be chosen such that the variability tree seeds in British Columbia are probably found within a stratum is smaller than that between strata. within – cm of the soil surface. Stratification also allows seed bank inventory by Bags containing seeds can be buried by removing stratum. intact blocks of forest floor, placing a bag in the hole, If the researcher does not know the seed distribu- and replacing the soil block (Granstrom ); or by tion or a suitable stratification criterion, then simple digging holes and backfilling without trying to main- random sampling should be used for the entire study tain soil integrity (Leadem ). To approximate area. If the researcher knows a suitable stratification natural conditions, seed containers should be in criterion, but is unable to stratify the study area be- contact with the soil. fore sampling due to lack of knowledge of the study Seeds should be recovered at least once a year for area, then either simple random sampling with post- several years. Estimates of the number of years to plan stratification or double sampling for stratification for can be based on what is known about seed longe- could be used. For both sampling schemes, a simple vity under artificial storage conditions. Exhuming and random sampling of the study area is first conducted. examining seeds at different times of the year can show In addition to the sampling variable of interest, the how seed losses vary depending on seasonal conditions. researcher would also collect data on the stratifi-

102 field studies of seed biology cation variable. In the case of post-stratification, the A serious mistake in many previous seed bank data would then be stratified based on the observed studies has been to pool soil samples (combine and values of the stratification variable. Post-stratification mix), then remove subsamples for seed bank deter- is helpful if the study area cannot be stratified before mination. This practice results in losing information sampling; however, it will likely result in unequal about variation among samples. Such variation is an sample size per stratum. In the case of double sam- important descriptor of the spatial distribution of pling, the data in the initial sample are classified into buried seeds, and is essential to understanding the strata. A second sample is then selected from the relationships between the distribution of seed sources initial sample using stratified sampling. In double and the distribution of seeds in the soil. In addition, sampling, the researcher can control the sample size this information will help future researchers choose in each stratum. See Thompson () for a thorough appropriate sample sizes for forest soil seed banks, discussion on various sampling schemes. since so little is currently known. Data from groups The number and distribution of seeds in seed of samples can always be pooled after collection from banks is highly variable, so the larger the number of the original, individual samples. samples collected the more representative the results For more discussion on experimental design, see will be. A larger number of small samples are gener- Sections ., ., ., and ... ally considered to represent the seed bank better than a few large (e.g., greater than  ×  cm) samples .. Comparison studies (Bigwood and Inouye ; Benoit et al. ). Al- Comparison-type studies require ample replication though a large number of large samples would be and randomization. Replication is an independent ideal, bigger samples are difficult to collect intact and repetition of the experimental factor(s) and ensures almost impossible to slice into uniform layers. In ad- that study results are not by chance. For example, if dition, the volume of soil may be too great to process. a study seeks to compare the number of viable Large samples can be collected by taking a series of Douglas-fir seeds in the seed banks in two different smaller, contiguous samples. This technique allows site series, then several locations per site series should for spatial distribution mapping at a fine scale. be randomly selected for measurement. A location is However, because the individual samples within a an experimental unit for the factor site series. The contiguous group are not independent, they cannot number of replications is the number of randomly be used for frequency calculations. Another advan- selected experimental units per site series. Within a tage of small samples is that they fit better between location, multiple soil samples might be collected for the areas that cannot be sampled in many forest soils, measurement. These soil samples are called subsamples. such as tree roots, rocks, and fallen logs. This results A common mistake is to have a single location for in fewer sample locations being moved to avoid these each site series and regard the soil samples within a obstructions. location as experimental units. This situation is called The number of soil samples collected depends on pseudoreplication, because the researcher assumes how accurate the estimate needs to be, how often the the experimental factor is replicated when in fact it is estimate can be wrong, how much variability is in the not (see Section .). A design with pseudoreplication data, and what resources are available. The minimum could indicate differences between the two locations, number of soil samples can be determined based but no conclusion could be made about the two on the confidence interval formula generated from site series. preliminary samples. Note, however, it may be im- Randomization refers to the random assignment practical to collect and assess the seed bank content of the experimental factor to the experimental unit. It in these preliminary samples. The total volume of soil is a means for reducing systematic errors in the data. samples sufficient to be representative of a seed bank In the case of site series, it is not possible to randomly has been estimated to be  cm3 for pasture land assign site series to a location—a location belongs to (Forcella ), but for forest soils, sample volumes a certain site series before the experiment is conceived. range from  cm3 (Brown ) to   cm3 To compensate, locations must be randomly selected (Matlack and Good ). from all possible locations available for the

section 6 seed banks 103 experiment for a particular site series. Randomiza- Monte Carlo method could be used to repeatedly tion also includes random selection of soil samples sample from the data set. (van der Kamp 1995). within a location for measurements. For more discus- The vertical distribution of seeds can be compared sions on experimental design, see Sections ., . and using multivariate analysis. For example, to compare ., and Sit (). seed distribution among three soil layers (e.g., litter, fermentation, and humus) between two different site . Data Analysis series, several soil cores are randomly taken from each site. For each core, the three layers are identified Summary statistics such as means and standard de- and the number of viable seeds are counted. Since the viations may be calculated to describe the seed bank depth of each layer may vary from soil core to soil for inventory purposes. Be careful that the computa- core, the analysis should be based on number of seeds tion formula used corresponds to the sampling method. per soil volume. Because the numbers of viable seeds A common mistake is to use the formula for simple in the three layers are interdependent (a soil core random sampling in all situations. For example, if a with a high number of seeds in the top layer would site is first stratified by site series or disturbance level, likely have high number of seeds in the lower layers), then the formula for stratified sampling should be used. viable seeds per volume in the two sites for the three See Cochran () and Thompson () for the for- soil layers must be compared simultaneously using mulae for the different types of sampling methods. multivariate analysis of variance (manova). If the test anova can be used to compare the number of vi- is significant, then separate analysis of variance can able seeds among several site factors (e.g., site series, be used to determine which soil layers differ in the site preparation treatments, seral stages). The design mean number of viable seeds per volume for the two of the study will determine the type of anova (one- site types. If the manova is not significant, then you way, factorial, or split-plot) that is suitable. For this could conclude that the vertical distribution of viable type of study, each area representing a level of the site seeds is the same for the two site types. factor of interest is the experimental unit. If several For burial experiments, regression analysis may be sample plots are included in each area, then these appropriate to characterize the pattern of seed viabil- plots are subsamples only and cannot be considered ity over time in soil. Since at each collection date, a replicates. If only one area is sampled for each level of different bag of seeds is extracted from the ground, the site factor, then the study will have no replication. the data collected at each date are independent, and anova can still be used to compare the areas, but any regression is possible. If the data are recorded as per- differences can only be attributed to the fact that each cent viable seed per bag, then a transformation of the level occupies a separate area, not to the different data may be necessary before regression. Transforma- levels of the main site factor. The results cannot be tion of data should not be done automatically for extended to other areas with similar site factors. percent data; the original data should always be Spatial analysis methods should be considered to analyzed first. If the residual analysis indicates that assess the horizontal distribution of the seeds. For the regression assumptions are strongly violated then this objective, the data must be collected systematically. transformation of the data could be considered. As The location (x,y coordinates) and status (viable, not regression is a robust technique, it is valid even if the viable; or present, absent) of seeds at each location residuals are slightly different from the normal distri- must be recorded. To determine whether the distri- bution. See Section . for more discussion of bution of seeds is clumped, regular, or random, the regression analysis.

104 field studies of seed biology SECTION 7 SEED QUALITY AND VIABILITY

Though I do not believe that a plant will spring up where no seed has been, I have great faith in a seed. Convince me that you have a seed there, and I am prepared to expect wonders. (Henry David Thoreau)

.. Factors Affecting Seed Biology and winter. Emergence occurs as temperatures rise again in the spring. Sometimes, seeds fail to germi- .. Factors affecting dormancy and emergence nate because water and gases cannot permeate the In many tree species, seed maturation is accompanied seed coat. Under natural conditions, such seed coat by induction of a state of dormancy. Viable seeds are dormancy may be removed through interaction with considered dormant when they are placed under con- chemicals in the soil solution. This chemical action ditions favourable for growth, yet fail to germinate. can break down resistant seed coats or leach chemical Dormancy is a mechanism whereby species can en- inhibitors from the seeds. Dormancy of some seeds hance their survival by delaying germination until may be broken after the seeds pass through the diges- conditions in the external environment are conducive tive systems of birds or other animals, but this is not to active growth (Osborne ). The expression of a common means of releasing dormancy in British dormancy is under genetic control (Naylor ), but Columbia tree species. (See Section .. for dormancy- is also strongly influenced by environmental factors breaking methods). Some species, such as Salix and (Steinhoff et al. ; Rehfeldt , ). Populus, do not become dormant and generally Dormancy is advantageous for seeds that mature germinate a short time after maturity. in the late summer or early fall, since seeds that ger- minate in the fall could be immediately exposed to .. Factors affecting germination harsh winter conditions. Seedling mortality likely would be high under such conditions. In nature, Moisture dormant seeds remain inactive until favourable grow- Seeds naturally dehydrate as they mature. When the ing conditions occur the following spring. Some moisture content (mc) of a mature seed falls below seeds may remain dormant for two or more growing %, the seed can survive an extended period of seasons and, depending upon the species and the artificial storage (Table .). (An exception is Garry environment, can remain viable for many years. The oak, a member of the white oak group; the seeds ex- major factors affecting seed dormancy are species, hibit recalcitrant storage behaviour and must be stored seed source, crop year, and environmental factors at % mc or more. See Section ...) Metabolic such as temperature and moisture. activity is very low in seeds with less than % mc, Tree seeds are generally released from dormancy so seeds must be rehydrated to physiologically active only after they have been exposed to the cold, wet levels (usually % mc or more) for germination to conditions typically found in nature during the fall proceed. Although dry seeds absorb water rapidly,

section 7 seed quality and viability 105  . Moisture content guidelines for orthodox tree temperatures. Germination is dependent on all these seeds (from Leadem 1996) processes, and thus is strongly affected by temperature. All seeds have an optimum temperature or tem- Moisture content perature range for germination. For some species, (%) Physiological status the optimum temperature range is relatively narrow, while other species may be able to germinate over a <5 All water is chemically bound; removal may wide temperature range. Dormancy-release treat- be detrimental ments such as stratification may broaden the range 5–10 Seeds may be stored for prolonged periods of temperatures over which germination may occur at low temperatures (-18°C) (Section ..). <20 Seeds may revert to dormant state For most British Columbia tree seeds, the optimal 25–30 Reduced risk for premature germination temperature range for germination is between  and during stratification (2–5°C) °C. In general, germination is considerably slower 30–45+ Moisture level of fully imbibed seeds in when temperatures fall below °C. The seeds of preparation for stratification or sowing some hardwood species (e.g., Acer, Populus, Salix) can germinate at –°C, but at very slow rates (Wyckoff and Zasada []; Zasada et al. []; Zasada and physical properties of the seed coat, such as waxiness, Strong []). Abies seeds are reportedly capable of hairiness, and thickness, may impede or restrict the germination while buried in snow. Prolonged expo- entry of water into the seed. sure to temperatures of °C or higher is usually Once seeds are fully hydrated, moisture content lethal to germinating seeds. and respiration remain relatively constant as the es- sential growth processes of germination take place. Light The embryo grows primarily through cell division Many tree seeds (from both conifers and hardwoods) and elongation of existing cells. Cell elongation is require light to germinate, although the seeds of promoted by the transport of sugars, which increases several British Columbia conifer species appear to the ability of embryo cells to take up more water. As germinate equally well in light or darkness (Li et al. more water is absorbed by the embryo, the increased ). For those species with a light requirement, if water pressure assists in the elongation of the radicle, all other environmental conditions have been satis- enabling it to break through the seed coat, which by fied, seeds lying on or near the soil surface will then has become softened or weakened. Water uptake receive enough light to trigger germination. Seeds continues following radicle emergence. Young germi- buried too deeply in the soil (more than . cm) nants are very vulnerable to drought because seedling likely would not receive enough light to germinate. tissues are soft and unlignified; thus the availability As with other physiological processes, seeds must be of adequate moisture (both soil and air) is critical at hydrated to respond to the light stimulus. The light this time. requirement for germination may be lessened by treatments such as stratification. For example, seeds Temperature of species that require light for germination are able After an extensive study of more than  herbaceous to germinate in darkness once they have been species from a variety of habitats, plant families, and stratified. life cycle types, Baskin and Baskin () concluded, The light stimulus is received through the phyto- “Temperature, through its influence on dormancy chrome system, which operates as an on/off switch for and germination, is the primary environmental factor many physiological processes in plants (Figure .). regulating germination, and light and soil moisture In light-sensitive seeds, germination is usually stimu- are of secondary importance.” lated by exposure to red light (– nm) and This conclusion undoubtedly is true for most tree inhibited by exposure to far-red light (– nm). seeds. Metabolic processes such as water uptake, gas Absorption of far-red light converts the pigment diffusion, and respiration all proceed faster at higher phytochromefar-red (usually the active form) back to

106 field studies of seed biology been displaced by water. The seed coat acts as a barrier to oxygen for the embryo during germination, but the coat is no longer an obstacle once the radicle emerges through the micropyle.

Other factors The failure of a seed to germinate is not always linked to dormancy. Poor germination may be caused by seed immaturity—a problem common in high- elevation or high-latitude areas where the growing season may be shortened by adverse weather condi- tions. Insects, fungi, and other pests may attack seeds and severely diminish seed quality and viability    . (Hedlin et al. ; Sutherland et al. ; Sutherland Absorption of far-red light converts the pig-  ment phytochrome (usually the active and Glover ). Soil conditions, such as texture, far-red moisture, and degree of compaction, can also affect form) back to phytochromered (the inactive form) (Leadem 1996). This reaction is revers- seed germination. Soils that absorb solar radiation ible, depending on the relative amounts of red and hold moisture may speed the rate of germination and far-red light. In sunlight, red light is and increase the survival of germinants (Section ..). predominant, whereas far-red light is predominant in canopy-filtered light. . Seed Testing in the Laboratory

The variety and complexity of environmental factors phytochromered (the inactive form). This reaction is encountered under field conditions make it difficult reversible, depending upon the relative amounts of to assign causes for the results obtained in the field. red or far-red light. The intensity of light required to Did an area fail to regenerate naturally because of activate the phytochrome system is low, and about poor seed production, predation, or seed dormancy?  µW/cm2 (comparable to bright moonlight) can be Or was the failure caused by environmental condi- enough. The phytochrome system has ecological tions such as drought or low temperatures during the significance for the establishment of trees from light- emergence period? Often, it is not possible to sepa- sensitive seeds. Sunlight under open conditions is rate biological from environmental factors. For this rich in red light, whereas light filtered through a for- reason, it is advisable to conduct tests under more est canopy is predominant in far-red light. The ratio controlled conditions in the laboratory. Laboratory of red to far-red light also varies, depending on tests serve as controls for the tests being conducted whether the canopy consists primarily of conifer or in the field, and help identify (or at least eliminate) hardwood trees (Section ..). certain factors as causative agents.

Oxygen .. Sampling methods Most seeds cannot germinate without oxygen, because Detailed sampling procedures are prescribed for use oxygen is required to support the respiration that by certified seed testing laboratories (Association of fuels the seed germination process. Oxygen require- Official Seed Analysts ; International Seed Testing ments vary by species, but most tree seeds are able to Association ). The sampling procedure begins by germinate at concentrations well below the % by taking small portions, primary samples, at random volume found in normal atmosphere; oxygen is from different positions in the seed source (e.g., seed- therefore not generally considered to be a limiting lot). These primary samples are combined and mixed factor in seed germination. In flooded soils, however, to form a single composite sample. This composite the amount of available oxygen can be limited sample, after thorough mixing, is subdivided into a because the air usually found in soil pore spaces has number of smaller samples (two or more) that are

section 7 seed quality and viability 107 taken to the laboratory for testing. These subsamples across the back edge of the pan. Place small cups or are referred to by seed analysts as the submitted sam- beakers (usually –) randomly on a tray or large ples. Submitted samples are often larger than required sheet of newspaper. With a single sweep of the for the laboratory tests. Thus, the submitted samples dustpan, uniformly distribute the seeds over the are further reduced to working samples in the labora- containers on the tray. Whatever seeds fall into the tory. All tests are then carried out on the working cups become the working sample. If not enough samples. Different tests require different sizes of seeds fall into the cups, return the remaining seeds to working samples. the dustpan and make a second pass. Continue until Seed analysts use these specialized terms to keep a sufficient working sample is obtained. track of the various steps in the sampling and testing process, but the procedures are the same as those . Modified halving method This is good method if used in most research studies. For example, suppose you have to do a lot of sampling. Construct a grid of you have to determine the quality of seeds produced  mm (¼") or  mm (⅜") plywood (Figure .b). by a given stand. Depending on your experimental Note that all cells are open at the top, but alternate requirements, you would collect a certain number of cells have cardboard squares stapled to their bases. cones. The cones (and the seeds they contain) are the Place the grid over a tray or large sheet of paper and primary samples. All these cones and their seeds are pour the seeds evenly over it (using the dustpan put into a single container, and become the composite sweep as in [ii]), covering the entire grid. When the sample. After the seeds have been extracted from the grid is lifted, some of the seeds will be retained by the cones, they are taken to the laboratory for testing, cells with bases, while the rest of the seeds will remain and become the submitted sample. Most likely you on the tray. Repeat the process until the required have collected more seeds than required for testing, amount of seeds are collected in the grid. so the submitted sample must be reduced to become the working sample, which for a standard germination The description of sampling methods given above test is four replications each of  seeds. is only a brief synopsis of the topic of sampling. Me- Mechanical equipment may be used (see Edwards chanical methods that require specialized equipment and Wang ) to obtain submitted and working are available for sampling large quantities of seeds. samples, but for most research purposes where there For more complete information, see Edwards () is a large quantity of seeds, they may be sampled by or Edwards and Wang (). hand. To obtain the submitted sample, with the fingers and thumb kept straight and together, push your hand Number of samples to the required depth in the container (Figure .a). Generally, four replications of  seeds are used for Close the fingers tightly around a portion of seeds germination tests (Interna-tional Seed Testing Asso- and withdraw the hand. ciation ; Association of Official Seed Analysts In the laboratory, the submitted sample must be ). However, either the number of replications or thoroughly mixed, then divided to give the proper the number of seeds may be altered to suit experi- working sample. The following sampling methods mental requirements. The number of seeds per can be carried out using readily available, or easily replication may be reduced when few seeds are constructed, equipment. available (e.g., for germination tests of seeds from controlled crosses), but test results may be unreliable . Spoon method Pour the seeds evenly over a tray or if fewer than  seeds per replication are used. large sheet of paper. Using a spoon or spatula, remove Reducing the number of replications is not recom- small portions of seeds from several random posi- mended; with a limited number of seeds it is better tions until the required amount of seeds is obtained. to have fewer seeds per replication and increase the This method is best used on small-seeded species. number of replications. For example, if only  seeds are available, six replications of  seeds will . Random cups method Pour the seeds into an provide better estimates of experimental error than ordinary dustpan so that they are evenly spread three replications of  seeds.

108 field studies of seed biology .. Seed purity, seed weight, and weight (dw) basis. Seed moisture content is usually moisture content calculated as: Seed purity test results report the composition (by 100 weight) of the pure seeds of the named species, the seed moisture content (%) = (M - M) × , (M - M) seeds of other species, and inert matter. Seed weight is generally expressed as the weight of  pure seeds, where: or as seeds per gram. M = weight of the empty container and cover, Seed moisture content (mc) is defined as the M = weight of the container, cover, and seeds quantity of water lost when the sample is dried under before drying, and specified conditions (see below). By international M = weight of the container, cover, and seeds convention, the mc of seeds is expressed as a percent- after drying. age of the fresh weight (fw) of the original sample. This is different from other expressions of mc for Determining seed moisture content is critical for scientific purposes, which are usually made on a dry long-term storage (Section .), and for some dormancy a) b)

1) Place open hand into the container. (1) Construct a grid from plywood; alter- nating cells do not have a bottom.

(2) Insert hand, with fingers open, deep (2) Pour seeds evenly over the grid. into the container.

(3) Close fingers around the sample and (3) The working sample is retained in the grid; withdraw the closed hand. the remaining seeds are left in the tray.

 . a) Sampling seeds by hand. b) Sampling seeds with a grid.

section 7 seed quality and viability 109 release treatments (Section ..). The moisture con- actual number of filled and empty seeds (e.g., when tent of some angiosperm seeds may be difficult to assessing direct seeding trials, when testing the via- determine accurately because of their large size and bility of seeds collected from seed traps, or when the presence of volatile substances. Such seeds may using the data to calculate the regeneration potential have to be cut in pieces (halves or quarters) or based on the seeds available on the site). However, in ground before testing, and the moisture content all cases, the number of filled seeds is of critical determined by Karl-Fischer titration (Hart and importance. How, for example, do you interpret a Golumbic ) or other method. reported germination of %? You must know the The most commonly used method to determine number of filled seeds to respond. If the seeds are dw is to dry the seeds in a forced-draught oven at % filled, then germination is only %, but if only °C ±°C for h ± h (Association of Official Seed % of the seeds are filled, then germination is %. Analysts ; International Seed Testing Association To ensure that only filled seeds are used in the test, ). First, the empty container and cover are seeds may be X-rayed before testing, and the empty weighed (covers and containers should have match- seeds removed. Otherwise, ungerminated seeds re- ing numbers in case they become separated). Then at maining at the end of the test must be examined to least two working samples of – g each are placed in determine whether the seeds are filled or empty. The the separate containers; the containers are covered seeds may be cut open, or they may be dried and and weighed. The seeds are placed in a preheated X-rayed (see Section .. for details). Tetrazolium oven, and dried in the containers with the covers chloride can be used to assess the viability of different removed. At the end of the drying period, the covers tissues of ungerminated filled seeds (Section ..). are replaced, and the seeds and containers are weighed again. All weights are recorded to three decimal Surface sterilization places. In damp weather, it is recommended that In some instances, mould can significantly reduce containers and covers be dried, and cooled in a germination of infected seeds, especially if the seeds dessicator for at least – minutes, before they are poor quality. Surface sterilization of seeds with are used. hydrogen peroxide may be beneficial, but sterilization The methods for reporting seed purity, seed treatment should be considered the exception rather weight, and seed moisture content were developed than the rule. Germinating seeds are extremely primarily for use in the international seed trade to sensitive to phytotoxic substances, so preliminary ensure standardization by approved laboratories of testing is essential. Tests should be done on a small international seed testing associations (Association sample of dry seeds. If germination is improved by of Official Seed Analysts ; International Seed the treatment, sterilize dry seeds by immersing them Testing Association ). Standardized methods are in % hydrogen peroxide (HO) for  minutes, beneficial in that they allow easy comparison of re- followed by three rinses with de-ionized water. sults, and provide protocols for the expression of seed It is possible to quantify the degree of mould in- characteristics. Use of such protocols, however, does festation (or other characteristic) by grouping the not prohibit modifying the means of reporting seed seeds into classes according to predetermined criteria characteristics as required for research purposes. (see Table .). Assessing the seeds for mould at the end of  week and again at the end of the test is .. Preparing seeds for testing usually enough to obtain meaningful data. Such data can be analyzed using nonparametric methods Determining filled seeds (Sections . and ..). Laboratory germination tests are generally conducted on filled seeds under specified conditions. For both Hydration of seeds laboratory and field studies, valid comparisons of Before beginning the germination test, seeds of germination cannot be made unless the total number most British Columbia conifer species are stratified. of filled seeds used in the test is known. It is some- Table . (conifers) and Table . (hardwoods) pre- times argued that it is not necessary to determine the sent treatments currently used in British Columbia.

110 field studies of seed biology Seeds must be physiologically active to respond to Each replication should be labelled with the ap- treatment (Section .), so most conifer seeds are propriate code for species, seedlot, treatment, and soaked in water for  hours at room temperature replication number. (Four replications of  seeds (–°C) before stratification or testing. Notable are generally used. See discussion above.) Seeds that exceptions are Abies seeds, which are soaked for  do not require stratification may be surface-dried on hours, and western redcedar seeds, which are not paper towels and incubated immediately after soak- soaked before germination tests. For soaking, seeds ing. Seeds of species that require chilling are put in should be covered with a volume of de-ionized water capped plastic vials or plastic bags for stratification (or tap water if it is of reasonable quality) equal to at at –°C, according to the recommendations for the least twice the volume of the seeds. species (Tables . and .). The volume of the stratification container should be much larger than that of the seeds to allow ample space for air above  . Classification of mould infestation in seeds the seeds. If cold storage area permits, it is sometimes convenient to stratify seeds in the containers that will Class Infected seeds (%) be used for incubation. To schedule the work load to coincide with a 10 standard work week, it is convenient to begin soak- 2 1–25 ing seeds on Monday (-hour soak) or Tuesday 3 26–50 (-hour soak) to start the experimental incubation 4 51–75 on Wednesday. Since tests are conducted normally 5 76–100 for a specified number of weeks (usually –) (see Table .), tests that begin on Wednesday will end

 . Stratification and incubation regimes for British Columbia conifer seeds(Leadem 1996)

Treatment Incubation Species name Soak Stratification Temp (°C)a Length (days)

Abies amabilis 48 hours b 4+12 weeks c 25/15 28 Abies grandis 48 hours b 4+12 weeks c 25/15 28 Abies lasiocarpa 48 hours b 4+12 weeks c 25/15 28 Chamaecyparis nootkatensis 10–28 days d 16–20 weeks 30/20 21 Picea glauca 24 hours 3 weeks 30/20 21 Picea sitchensis 24 hours 3 weeks 30/20 21 Pinus contorta 24 hours 3 weeks 30/20 21 Pinus monticola 48 hours b 4W+8C e 30/20 21 Pinus ponderosa 24 hours 3 weeks 30/20 21 Pseudotsuga menziesii 24 hours 3 weeks 30/20 21 Thuja plicata none f none 30/20 21 Tsuga heterophylla 24 hours 4 weeks 20°C28 Tsuga mertensiana 24 hours 4 weeks 20°C28

W = warm stratification; C = cold stratification. a The first temperature is given during the -hour light period, the second temperature is given during the -hour dark period. If only one temperature is shown, light is given for  hours, but the temperature does not alternate. b Seeds soaked for  hours receive a water change after  hours. c Stratification-redry treatment: seeds are soaked for  hours, drained to remove excess water, and placed, with no surface drying, at –°C for  weeks. After stratification for  weeks, the seeds are dried to % moisture content, then chilled for an additional  weeks. d Water should be changed every second day. e Warm/cold stratification: seeds are soaked, drained and kept at –°C for  weeks, then stratified for  weeks at –°C. f Seeds should be heavily misted for several days after sowing.

section 7 seed quality and viability 111 on Wednesday, allowing  days of the work week for Stratification cleanup or other tests. Stratification is the most consistently effective dormancy-release treatment for British Columbia .. Dormancy-breaking procedures tree seeds. Stratification enables seeds to germinate Dormant seeds can be stimulated to germinate using more quickly and completely, and can sometimes treatments that emulate natural conditions or satisfy eliminate the need for other special conditions, such certain physiological requirements (Taylorson and as light or the close control of temperatures. Even Hendricks ). The choice of a suitable dormancy- when the final germination percentage remains the release treatment can increase germination rates, and same, the germination rate of most tree seeds is often broaden the range of environmental conditions un- improved by stratification, especially when seeds are der which germination can occur. incubated at low temperatures (Figure .) (Table .).

 . Stratification and incubation conditions for British Columbia hardwood seeds

Treatment Incubation Species name Soak Stratification Temp (°C)a Length (days)

Acer macrophyllum 48 hours 45–130 days 20 28 Alnus rubra 24 hours 14–28 days b 30/20 21 Arbutus menziesii 24 hours 60 days c –– Betula none none 30/20 21 Betula papyrifera var. neoalaskana none none 30/20 21 Cornus nuttallii 24 hours 90 days c –– Fraxinus latifolia 24 hours 2W+7C d 30/20 56e Malus fusca 48 hours 90 days c –– Populus balsamifera ssp. balsamifera none none 30/20 10 Populus balsamifera ssp. trichocarpa none none 30/20 10 Populus tremuloides none none 30/20 10 Prunus emarginata 48 hours 90–126 days c –– Quercus garryana 48 hours none 20 28 Rhamnus purshiana none none – – Salix amygdaloides none none – – Salix bebbiana none none – – Salix discolor none none – – Salix exigua none none – – Salix lucida ssp. lasiandra none none – – Salix scouleriana none none – – Salix spp. – – 30/20 14

W = warm stratification; C = cold stratification. a The first temperature is given during the -hour light period, the second temperature is given during the -hour dark period. If only one temperature is shown, light is given for  hours, but the temperature does not alternate. b Ager et al. (). c Schopmeyer (technical coordinator, ). d Warm/cold stratification: seeds are soaked, drained, and kept at °C for  months, then stratified for  months at –°C (Schopmeyer, technical coordinator, ). e International Seed Testing Association (). – no information available.

112 field studies of seed biology a) Lodgepole pine b) Sitka spruce

c) Douglas-fir

 . Germination of (a) lodgepole pine, (b) Sitka spruce, and (c) Douglas-fir at different temperatures and after stratification for 0, 3, 6, and 18 weeks (Leadem 1996; data from Jones and Gosling 1994).

 . Summary of stratification methods: (a) Conventional stratification; (b) Stratification-redry; (c) Stratification (bigleaf maple); (d) Stratification (warm + cold); (e) Stratification (hardwoods)

(a) Conventional stratification

Process Soak Stratify Incubate

Time 24 or 48 h 3–4 weeks 3–4 weeks Temperature 20–25°C 2–5°C 20–25°C mc to >30% 30–60% 30–60%

Stratification simulates winter conditions by exposing moist seeds to cold temperatures. Seeds are soaked in water (hydrated) usually for  hours, drained, then placed in a plastic bag or other container, and refrigerated (–°C) for several weeks. With the exception of western redcedar seeds (not considered to be dormant), all British Columbia conifer seeds require strati- fication for best germination (Table .). Although Salix and Populus seeds are not stratified, many other British Columbia hardwoods (e.g., Acer, Arbutus, Cornus, Fraxinus) have a chilling requirement (Table .). Even hardwood seeds that can ger- minate without stratification (e.g., red alder) often benefit from chilling when they are incubated under low temperatures (Ager et al. ). Damaged seeds, or those of low vigour, may deteriorate during stratification (Leadem ); in such cases, the seeds should be sown without chilling.

section 7 seed quality and viability 113  . (b) Stratification-redry

Process Soak Stratify Redry Stratify Incubate

Time 48 hours; change 4 weeks 4–8 hours 12 weeks 3–4 weeks after 24 hours Temperature 20–25°C 2–5°C 20–25°C 2–5°C 20–25°C mc to >30% 30–60% to 25% 25% 25–60%

Conventional stratification techniques may be in-sufficient to stimulate germination in some conifer species. The true firs (amabilis, grand, and subalpine) respond best to a two-part stratification called stratification-redry (Edwards ; Leadem , ). Seeds are hydrated for  hours and then stratified for  weeks at –°C; seed moisture content is high, usually above %. The seeds are then dried to –% mc and chilled for an additional  weeks. At such low moisture contents, seeds receive the extended chilling they require, but moisture levels are too low to permit emergence of the radicle (i.e., evi- dent germination). The stratification-redry treatment has also been found effective for some sources of Douglas-fir seeds, but not for other tree species.

 . (c) Stratification for variable dormancy (hardwoods)

Process Soak Stratify Incubate

Time 48 hours; change X weeks (to 5% germ.) 3–4 weeks after 24 hours X = 60–120 days Temperature 20–25°C 2–5°C 20–25°C mc to >30% 30–60% 30–60%

Some species such as bigleaf maple require extended stratification, but the optimum duration for individual seed sources is unknown. An empirical procedure for seeds with variable dormancy is to place the hydrated seeds (> % mc) at –°C, and maintain them at low temperatures until about % of the seeds germinate. For bigleaf maple, this is about – days (J. Zasada, pers. comm., ). Germination of the least dormant individuals at low temperatures generally indicates that dormancy also has been released in the remaining, more dormant seeds, and that the seeds may be transferred to warmer temperatures for testing or seedling production.

114 field studies of seed biology  . (d) Stratification (warm + cold)

Process Soak Stratify-warm Stratify-cold Incubate

Time 48 hours; change X weeks (to 5% germ.); 6 weeks 3–4 weeks after 24 hours X = 3–5 weeks Temperature 20–25°C 20–25°C 2–5°C 20–25°C mc to >30% 30–60% 30–60% 30–60%

A variation of stratification (c) is the dormancy treatment used for western white pine. The usual recommendation for releasing dormancy in western white pine is  days warm stratification (–°C) followed by  days cold stratification (–°C). However, the duration of warm stratification varies, depending upon the seed source. Seeds are kept under warm conditions until about % of the seeds show evidence of germination, then the seeds are immediately transferred to cold temperatures (D.W.G. Edwards, pers. comm., ).

 . (e) Stratification for variable dormancy in deeply dormant hardwoods

Process Soak Stratify Incubate

Time Until mc = Y X+2 weeks (to 10% germ.); 3–4 weeks X = 1–8 months Temperature 20–25°C 2–5°C 20–25°C or mc (e.g., Y = 30%) Y% mc store at 2–5°C, 10% mc

A procedure developed for beechnuts and other European hardwood seeds by Suszka () may also prove effective for removing the dormancy of British Columbia hardwood seeds. It is similar to the variable-dormancy treatment described above, but also involves hydrating the seeds to a predetermined moisture content (Y), depending on the species (e.g., % mc for beechnuts), then maintaining the seeds at this mc for X+ weeks at –°C. The duration of treatment, represented as X (in weeks), is the time when % of the seeds have germinated. This length of stratification is enough to break dormancy, but because seeds are chilled at reduced moisture levels, germination is prevented. After treatment, the seeds can either be sown, or dried to below % mc and stored for several years (Muller and Bonnet-Masimbert ; Muller et al. ). Such dor- mancy-breaking treatments are usually applied after storage, but they can also be applied before storage (i.e., immediately after collection). The time period X can be considered as an indication of the degree of seed dormancy, and potentially could be used to compare the dormancy levels of different seed sources. The period X is – months for beechnuts (Fagus sylvatica), – months for wild cherries (Prunus sativum), and – months for ash (Fraxinus spp.) (Muller ; Suszka et al. ).

section 7 seed quality and viability 115 Other stratification treatments for the white and red light treatments and one W Subalpine larch seeds and other species that are incandescent bulb for the far-red treatment difficult to germinate may be stratified in situ using (Haeussler and Tappeiner ). a procedure that more closely approximates natural • An inexpensive red/far-red light source may be conditions under the snowpack. To stratify subalpine made from a desk lamp and cellophane paper (from larch, Carlson () used plastic tubes (. cm diam- art supply store); the red light (transmission range: eter  cm long) which were filled to within  cm – nm) provided by a red or white incandes- of the top with a peat-perlite mix, then thoroughly cent bulb (W) or a cool white fluorescent tube wetted. Seeds were covered with about  mm of soil, filtered through two layers of red cellophane or red firmly pressed, and covered with  mm of fine gravel Plexiglas (Witham et al. ); the far-red light (trans- to prevent soil from splashing during irrigation. The mission range: – nm) provided by a W or trays of tubes were thoroughly watered, covered with W incandescent bulb filtered through four layers clear polyethylene to retain moisture, and placed in a of blue, one green, and two layers of red cellophane. cold room at °C for  days. After  days, the tubes High wattage bulbs are not recommended because were removed from cold storage and placed under they generate too much heat, and may bleach the pig- conditions suitable for germination. ments in the cellophane with prolonged exposure. Yellow-cedar seeds can be difficult to hydrate and With low-wattage bulbs, the filter may be placed in require exceptionally long stratification. The seeds are front of the light source and tightly taped to the soaked for  days at room temperature (–°C), lampshade. An alternative method is to place the then stratified (–°C) for  months. Even with long sample in a light-tight box with the cover removed stratification, the seeds often germinate poorly. It and replaced by the filter. may be necessary to pregerminate the seeds by put- ting them on damp peat in shallow dishes, covering Energy levels from most light sources tend to be the dishes with plastic wrap, and incubating them at higher in the red region than in the far-red portion constant °C. As the seeds germinate, they can be of the spectrum. Haeussler and Tappeiner () pricked out into nursery containers. compensated for the lower energy levels in the far-red region by exposing the seeds to red light for  minutes Light treatments and extending exposure to the far-red light source to A number of tree species require light to release seeds  minutes. Light energy levels of red and far-red from dormancy (Section ..). Experimentally, light sources do not have to be exactly equivalent. Betula treatment may be given in the form of a single papyrifera seeds demonstrated definite red/far-red exposure prior to incubation, or as daily exposures responses to red (– nm) and far-red (– throughout the incubation period. Studies involving  nm) light sources which measured  W m–2 the responses of seeds to light require suitable sources and . W m-2, respectively (Bevington ). of red and far-red radiation. Filters must restrict the Conditions for dark (controls) can be established wavelengths to within a narrow band, and provisions by wrapping germination dishes (or other contain- must be made to reduce heat levels around the seeds ers) in aluminum foil or other opaque covering. The if exposure times are extended. A transparent water dishes should only be examined in a dark room bath at least  cm deep is an inexpensive and effective under the illumination of a dim green safelight. Use way to absorb excess infrared radiation. of a green incandescent bulb is not recommended, Before using any filter system, the transmission as such light sources can emit in the red and far-red spectrum should be determined with a spectropho- regions. A safelight can be constructed of two W tometer. Some sources for red/far-red light include cool white fluorescent lamps covered with  layers the following: of green cellophane. Radiation from this light source did not induce germination when used to count • Light sources can be constructed using Corning Betula papyrifera seeds (Bevington ). A green Plexiglas filters (red light  nm; far-red light safelight can also be made from a flashlight by  nm) with two W cool white fluorescent tubes covering the lens with an appropriate filter.

116 field studies of seed biology Other dormancy-release treatments tests, however, the relatively favourable conditions of Other dormancy treatments (Table .) will be only standard tests may give an overly optimistic view of briefly described here because they are not widely germination. Valuable data can be obtained by con- used for temperate tree species. Scarification is an ducting germination tests under conditions similar important technique for breaking the dormancy of to those found in study sites. Temperatures used many hard-seeded legume tree species that are an should range from suboptimal to optimal (and important component of tropical forests. Hard seed possibly beyond) to gain a fuller appreciation of coats are a means of protecting seeds from fungal and species’ response. Conducting tests under the rela- insect attack under conditions of high temperatures tively cool temperatures that mimic field conditions and high humidity. Mechanical or chemical degrada- may require more time, but will be more relevant to tion of the seed coat is necessary for germination, understanding responses in field studies. and in nature is often facilitated by seeds passing The measures of germination used for comparing through the intestinal tract of birds and other animals. laboratory and field results are also important. Since, Few temperate forest species require scarification in natural conditions, the speed and time of emergence —Schopmeyer (technical coordinator, ) does not can be critical (e.g., in areas where moisture is readily recommend it for any British Columbia trees—but available only in early spring), measures such as ger- seed coats of pines are sometimes clipped to facilitate mination rate and speed may be the best indicators of germination (Hoff and Steinhoff ; Leadem ). field performance. Laboratory tests, by eliminating Application of plant growth regulators (especially some of the variability associated with field tests, can gibberellic acid and cytokinin) have been shown to assist in interpreting field data so that the factors enhance germination of angiosperms, but have lim- affecting germinant establishment and survival may ited effectiveness for conifer species (Leadem ). be more clearly identified.

.. Laboratory germination tests Incubation of seeds Standard germination tests are widely used because The temperature and photoperiod conditions for they provide consistent results and allow comparisons incubation will be determined by the experimental of tests conducted in different laboratories. For field requirements. Standard incubation conditions commonly used for British Columbia tree seeds are °C for  hours (with light) and °C for  hours  . Dormancy release treatments for tree seeds (dark). The true firs (Abies spp.) generally respond (Leadem 1996). better to °C for  hours and °C for  hours (Leadem ), with light being given during the Treatment Description high-temperature period. The seeds may be incubated in  ×  cm plastic Stratification Moist chilling at 2–5°C; removes boxes, filled with a medium consisting of two layers metabolic blocks, weakens seed coats, of filter paper (such as Whatman #) covering one increases germination promoter levels layer of Kimpak™ (a multilayered crêped wadding). Light Exposure to specific wavelengths; For this size of container,  mL of de-ionized water stimulates the phytochrome system is added to moisten the media; this amount is Leaching Soaking in water; removes inhibitors   from seed coats sufficient for a germination test of – weeks dura- tion (provided the lids fit tightly and there are no Scarification Chemical (sulphuric acid) or mechanical (abrasion) treatment: cracks in the boxes). The seeds are spread evenly on breaks down seed coats the moist filter paper so that no two seeds are touch- Plant growth Enhances natural levels in favour of ing and all are in direct contact with the media, then regulators (hormones) germination regulators the lids are replaced on the boxes. Petri dishes filled High oxygen Supplies respiration; removes with several layers of filter paper may also be used, metabolic blocks concentrations but Petri dishes have a smaller surface area for test- ing, and the medium tends to dry out more quickly.

section 7 seed quality and viability 117 Test environments are fairly consistent over the the substrate. Thereafter, the elongating hypocotyl incubation period since most laboratory tests are rises into a vertical position and the radicle starts conducted in covered dishes incubated in controlled to elongate. environment chambers. However, the dishes should For nursery or field tests, test duration is typically be randomly arranged on shelves in the chamber to – weeks, but may be longer depending upon guard against the introduction of systematic error environmental conditions. See Section . for infor- due to consistent differences in light intensity, tem- mation on field germination tests. perature, or other factors. Random label lists can It is best to write entries on data sheets when be generated from the codes used to identify seed counting germinants, rather than entering data di- source, treatment, replication number, or other rectly into a datalogger or computer, since it is easy experimental variables. to make errors during the counting process. The first day that visible signs of germination activity (chitting) Germination criteria occur should be noted on the data sheets, as this will The criteria for germination may be the cracking be later used to indicate the initiation of the germi- of the seed coat, or development of all structures nation curve. The number of germinated seeds is necessary for a normal seedling (i.e., root, stem, cotyledons). For many studies, seeds are considered to have germinated once the length of the radicle is four times the length of the seed coat. Use of a radicle length shorter than four times is not recommended because of the greater probability of counting ab- normal (“stunted”) germinants as “normal.” For Abies species, which have relatively large seeds, a radicle that is twice the length of the seed coat may be satisfactorily used as a germination criterion. Typically, for research studies, germinants are counted  times a week for the duration of the test, which is usually – weeks in a standard laboratory test (Tables . and .). During peak germination periods, it is advisable to count daily. Many service laboratories count germinants once a week, which is too infrequent for research studies that require precise information on when and how changes in germination occur. Under field conditions or in the nursery, the term emergence is generally used instead of germination. In epigeal germination (Figure .b), the standard criterion for emergence is the time when the seed coat has lifted off the soil surface or, in hypogeal germination (Figure .a), when the epicotyl is clearly evident. Salix and Populus germinants (Figure .) exhibit a  . Stages of germinant development in hypogeal departure from the usual pattern of epigeal germina- and epigeal germination (Leadem 1996): tion (Simak ). Willow and poplar seeds contain (a) Garry oak, an angiosperm, illustrates only a large embryo, surrounded by a transparent hypogeal germination, in which cotyledons coat. Within the first day of germination, the hypo- remain below the ground; (b) white spruce, a cotyl increases in length and a ring of fine hypocotyl gymnosperm, exhibits epigeal germination, in hairs (the coronet) arises and attaches the seedling to which cotyledons are raised above the ground.

118 field studies of seed biology 1 2 345 6 7 12 hrs 24 hrs 24–36 hrs 36–48 hrs 48–72 hrs 3–5 days 10–14 days

 . Stages of germination for Populus seeds, showing time period in which each stage usually occurs (Wyckoff and Zasada [1998]). Within the first day of germination, the hypocotyl increases in length and shows a positive geotropic bending (Stages 1, 2). Hypocotyl hairs (the coronet) arise and attach the seedling to the substrate (Stage 3). Then, the elongating hypocotyl rises into a vertical position, and the radicle emerges (Stage 4). The seed coat bursts and is removed as the hypocotyl elongates and the cotyledons expand (Stages 5, 6). Epicotyl development begins after about 10–14 days (Stage 7).

recorded in columns under the date on which the resulting data have large variance, then the results counts are made. If large numbers of abnormal must be narrowly interpreted concerning seed origin. germinants are observed, a classification system On the other hand, a data set with small variance (Clark ) may be used to record the nature of the would suggest a more generalized species response; it abnormality. On the last day of the test, the number may also suggest that factors other than seed source of germinants is recorded, as well as the number of should be examined for their impact on germination. ungerminated seeds. The reason(s) for lack of germi- The estimated variance may be used to demonstrate nation should be noted, if known. If seeds have not the benefits of certain treatments; the germination of been X-rayed before testing and a precise result is stratified seeds, for example, is far less variable than required, cutting tests (Section ..) should be done that of unstratified seeds. on all ungerminated seeds to determine the exact Germination rate has both practical and ecological number of filled seeds in the test. significance. The rate at which seeds germinate has Additional information on methods and procedures long been recognized as an element of seed vigour, for testing tree seeds of Canadian conifer species can and an indication of the ability of a germinant to be found in Edwards (). become successfully established as a seedling (Leadem ). Many seed treatments increase the Germination measures rate of germination, but not the total germination. In Germination percentage, the most common natural regeneration studies, germination rate may be expression of seed germination, is calculated as: more important than total germination, particularly for sites where moisture and plant competition are number of germinated seeds × % limiting factors. Germination rate is often expressed number of filled seeds as R, or the number of days it takes % of the sown

The estimated variance, although not a germina- seeds to germinate. A similar term, R', or germination tion measure per se, is a valuable aid for interpreting speed, is the number of days for % of the germinat- germination data. In some instances, the estimated ing seeds to germinate. Differences in germination variance may be as important as the mean germina- rates also can be presented graphically using non- tion percentage. Consider a study to examine the linear regression analysis procedures (Tipton ) effects of different seed sources on germination. If the (see Section .).

section 7 seed quality and viability 119 Germination value () (Czabator ), an ex- the true firs, which germinate slowly, is usually low pression that combines the speed and completeness (about –). Germination values of spruces gener- of germination into a single number, is calculated as: ally are intermediate (–). Germination values have no units, and have not been widely accepted by  = peak value () × mean daily germination (), those who prefer separate reporting of germination rates and total germination. where:  = the maximum quotient obtained by ... Quick tests and other viability tests dividing the number of accumulated A standard germination test requires a minimum of daily germination by the correspond-  weeks to complete; with stratification, the test can ing number of days, and take  weeks or longer. Sometimes standard tests  = total germination divided by the cannot be done because of time constraints or the number of days in the test. lack of adequate facilities. In such cases quick tests of seed viability can provide reasonably good estimates The absolute magnitude of  depends upon of seed quality. The quick tests most commonly used the species, but values usually range from  to  for tree seeds are the hydrogen peroxide, tetrazolium, (Table .). Because of the germination characteristics X-ray, and cutting and excised embryo tests. No of different species, a  of  means something dif- single quick test is best in all situations, and each ferent for pine than for fir or for hemlock. Pines tend has its advantages. to have relatively high  values (i.e., more than ) The basic principle behind all quick tests is that because they germinate very quickly, while the  of the seeds are treated by some “quick” procedure, then classified according to established criteria. Quick test results of several samples can be calibrated by corre-  . Germination values for British Columbia conifers lating the percentage of germinable seeds determined by quick test to the percentage of seeds that germi- Species Germination value () nate in a standard test. Quick tests may take less time than standard germination tests, but they are usually Pacific silver fir 10 more labour intensive, and the results can be more grand fir 12 variable than results from standard germination tests. subalpine fir 13 For further information about quick tests and  Douglas-fir, coastal 40 other tree seed testing methods, see Leadem ( ),  Douglas-fir, interior 52 Edwards ( ), Association of Official Seed Analysts (), International Seed Testing Association (), western hemlock 19 and Edwards and Wang (). The specific proce- western larch 52 dures used in the B.C. Ministry of Forests Tree Seed lodgepole pine, coastal 52 Physiology Laboratory are given in Clark (). lodgepole pine, interior 58 western white pine 18 Hydrogen peroxide test yellow (ponderosa) pine 45 Of the three tests, the hydrogen peroxide method is Sitka spruce 35 the only one that actually measures growth. The interior spruce 40 primary advantages are objectivity and simplicity, Sitka/interior hybrids 36 and since this test requires less time and less equipment than most other viability tests, it is also western redcedar 25 the least expensive. yellow-cedar 5 The hydrogen peroxide test requires  days to complete and can be difficult to do on small seeds. It Source: D. Kolotelo, B.C. Ministry of Forests, Tree Seed Centre,   Surrey, B.C. from results of germination tests con- is carried out by cutting – mm off the micropylar ducted from 1990 to 1995. end of the seed coat, and incubating the seeds in a

120 field studies of seed biology % hydrogen peroxide (HO) solution at °C. The be avoided since dark staining may mask weakened test is ended after  week, and seeds with radicles tissues. The intensity and location of the stain is an longer than  mm are counted as viable. indication of whether the embryo is vigorous enough to produce a viable seedling. The uniformity of Tetrazolium chloride test staining and the rate at which staining develops The tetrazolium chloride () test focuses directly in different areas may indicate weakened tissue. on the physical and physiological condition of the Necrotic, unstained areas generally are of greater embryo and endosperm (or, in conifers, the mega- significance than stained areas, especially if they oc- gametophyte). Evaluation is based on the degree and cur in the shoot or radicle meristems. In the radicle location of stained and unstained areas. Because area, the meristem is located just behind the radicle results can be obtained within – hours, tetra- tip, while in the shoot, meristematic growth emanates zolium is faster than all quick tests except the X-ray from the base of the cotyledons. Meristematic areas method. However, the interpretation of staining must be well stained to produce a viable seedling. patterns relies heavily on the expertise of the analyst. For additional information, refer to Moore (), To conduct the test, seeds are soaked in water Leadem (), and International Seed Testing Asso- overnight to soften the coats, then a thin longitudinal ciation (). slice is cut through the coat and storage tissue to has- ten penetration of the tetrazolium (,,-triphenyl X-ray test tetrazolium) solution (Figure .). The seeds are The X-ray method is the most rapid of the quick soaked in a %  solution at °C for – hours. The tests. Only a few minutes are required to produce an time required for adequate staining varies with the X-ray image, and a large number of seeds may be species and seed source; excessive incubation should examined in a short time. Soft (low-energy) X- radiation does not affect seed germination or cause any apparent chromosome damage (Kamra and  A. 1 B. 1 Simak ). Viability evaluation is based on a before before physical examination of seed contents, and results cut have been shown to correlate well with germination cut test results (Leadem ). The primary drawback is the high cost of X-ray exposure and developing equipment; but once equipment is acquired, the cost of materials compares favourably with most standard testing methods. Celluloid film or photographic paper may be used A.2 B.2 for X-ray exposures. Kodak Type M industrial X-ray after after film provides good resolution and a permanent record, but requires a darkroom and developing apparatus. Polaroid film can be used for making seed radiographs (Edwards ); a darkroom is not required but the film is more expensive than X-ray film or paper. Photographic paper is less expensive than X-ray film and can be processed in an instant processor, but the images have relatively poor resolu- tion and are not permanent unless special provisions  . Cutting diagram for the tetrazolium test. A thin longitudinal slice is cut through the seed are made. Photographic paper is normally used when coat and storage tissue to hasten penetration a permanent record is not required. of the tetrazolium solution. Cuts may be made A monitor can be attached to the X-ray machine horizontally to the long axis of the seed (1a, and the images viewed directly. The advantage of b), or perpendicular to the long axis (2a, b). such a system is that no developing is required; the

section 7 seed quality and viability 121 disadvantages are the lack of a permanent record, and through the seed between the prongs of the forceps. the much higher cost of equipment. Another method is to place the seed flat on a firm Seeds can be placed directly on the X-ray film or surface, and to slice it parallel to the cutting surface photographic paper, but for most routine work a (i.e., horizontally). A third, but less desirable method, holder is used. Holders may be clear plastic boxes or is easier to perform under field conditions, and is compartmentalized trays, but any material intended suitable for small seeds such as spruce, lodgepole for use as a seed holder should first be tested for X- pine, western redcedar, and yellow-cedar: lay the seed ray penetrability. The seeds and film or paper are flat on the cutting surface and make a vertical cut placed in the shielded cabinet of the X-ray machine, downwards. Since the seed is cut through its narrow- and the exposure is made. Typical settings for a est dimension, it may be more difficult to accurately Faxitron (brand name) X-ray machine are  mA and assess storage tissue development. See Eremko et al.  kV with an exposure time of  minutes. The film or () and Kolotelo () for diagrams and addi- paper is developed, and each seed image is examined. tional information. Seed development and viability are determined by evaluating the density, shape, and location of opaque Excised-embryo tests matter (bright areas) in the X-rays. If the purpose is The excised embryo test is generally less used than to determine the presence of filled and empty seeds, other quick tests because it is more labour intensive, then the seeds in the holder must be compared to the and interpretation may be more difficult. Seeds for corresponding X-ray images of the same seeds. Empty the excised embryo test are soaked in tap water for seeds may be removed using forceps or a vacuum – hours. Species that require mechanical or pencil (the type used for manipulating electronics chemical scarification must first be given the appro- components). Care must be taken not to disturb the priate treatment. Embryos are excised from soaked seeds in the holder during the X-ray process. seeds with the aid of a scalpel or razor blade, then X-rays are best performed on dry seeds (<% mc) incubated on moistened filter paper for – days at because moisture (which appears opaque and bright –°C with  hours of light per day. Evaluation is in X-rays) tends to obliterate the details of seed con- based on chlorophyll development and growth of the tents. X-rays may still be used on moist seeds instead embryo. The test is effective for hardwood species of a cutting test, or to determine the number of because the seeds turn green quite readily, and is a ungerminated filled seeds left at the end of a germi- recommended procedure for Fraxinus spp. and Malus nation test. Simply dry the remaining seeds at room spp. (International Seed Testing Association ). temperature (–°C) for – hours (or overnight), Evaluation in conifers can be more difficult because then X-ray as usual. embryo extension occurs before changes in colour. The excised embryo test relies heavily on the skill Cutting tests of the analyst, and embryos must be rejected if they The cutting test is done by cutting a longitudinal section become damaged. Refer to the International Seed through the seed to expose the embryo and storage Testing Association () for detailed procedures. tissue. Although not as reliable as viability tests, cutting tests are often used in field situations to assess seed Respiration measures development and the presence of insects or disease. Oxygen use (respiration) is relatively easy to measure Take – seeds at random and examine them by in the laboratory, and is a direct indicator of the slicing each seed into equal parts with a razor blade physiological state or health of the seed. To determine or scalpel. Unless the seed has been exactly bisected, respiration rates, seeds are incubated in a phosphate you cannot observe the exact extent of embryo elon- buffer solution (to maintain seeds in good physio- gation. The contents of each seed are more accurately logical condition) in a temperature-controlled appraised if a -power hand lens is used. The pre- cuvette. Respiration is measured as a function of the ferred method for slicing a seed is to stand it on its rate of oxygen depletion of the solution. For further narrower edge on a cutting surface, using forceps to information on the significance and determination of hold it in place. A vertical cut is then made downward seed respiration, refer to Leadem ().

122 field studies of seed biology . Field Tests of Tree Seed Germination for this purpose, germination plots may be installed under different forest cover treatments. Canopy Evaluation of germination success in the field requires effects may be sampled over a range of random or introducing a fixed number of seeds to a microsite, fixed points (e.g., various distances from a forest then counting the number that germinate over some edge) differing in their subcanopy light regime, time interval. Some questions may lend themselves to thereby lending themselves to analysis by correlation modifications of laboratory methods for studying or regression methods. Alternatively, canopy treat- seed germination (Section .), but because experi- ments may represent separate stand treatments (e.g., mental conditions are so difficult to control, field different silvicultural systems) which would be tested trials are not suitable for investigating the physiologi- by anova. Sample points should be situated randomly cal mechanisms affecting germination. The greatest within the treatment blocks, and the canopy charac- advantage of field tests is that germination responses teristics of each microsite should be documented to treatments can be directly observed under field using the appropriate cover- or light-measuring conditions, providing a better understanding of the methodologies described in Section .. Even if the ecological implications of the treatments being applied. primary interest is the response to treatments at the stand level, high spot-to-spot variation in canopy .. Experimental design and analysis effects makes it desirable to collect enough microsite Field germination trials may evaluate treatments im- information to analyze plot-to-plot variation as well plemented at the stand level (e.g., canopy thinning), (e.g., by regression analysis or analysis of covariance). or at the level of individual germination plots or microsites (e.g., seedbed types). Care must be taken .. Delimiting the site to recognize how treatments are nested and repli- One of the first requirements for evaluating field cated. The layout of treatments and monitoring plots germination is a means of delimiting the microsite must be appropriate for statistical tests to answer the under study, and to contain the seeds being tested, so questions posed, and statistical tests must match the that sampling of sprouted seeds is limited to those experimental design. introduced to the site. Plots should be distributed in unbiased and One approach is to spread and evaluate seeds only representative locations within uniform sites (see within a fixed radius (e.g.,  cm) from a tagged cen- Section . for discussion of site selection). Variability tre pin, or between two pins marking the diagonal can be high, and (despite preventative measures) corners of a square or rectangular quadrat that is some animal damage can be expected. A rough esti- placed on the plot only during establishment and mate of – plots per treatment combination can monitoring. This results in less impact to the micro- be used, although you should determine your own environment, but with no protection, the seeds may sample size needs based on the variability of the site be washed away or removed by birds and rodents. (Section ..). When testing treatments, such as dif- Another option is to set out a rigid circular or rec- ferent site preparation methods, it is important to tangular plot perimeter (e.g., using plastic lawn have plots in multiple independent replications of edging or wood) (Figure .). This method constrains each treatment, not just in one stand or cutblock; the movement of seeds, but may modify the micro- this will help avoid a problem of pseudoreplication. climate. A tall, solid frame may alter subtle microsite Statistical analysis of experimental factors (e.g., seed- effects, so frame height should be kept minimal. bed type, site preparation method, silvicultural Smaller frames may be more suitable for testing system) can be performed using analysis of variance. smaller microsites, such as those prepared Continuous independent variables (e.g., duff thick- by mounding. ness, canopy opening) are best assessed by regression Seed samples should be located within the plots, analysis. Experimental factors and continuous vari- but away from the edge. Several tree species or seed- ables can be combined in analysis of covariance. lots can be tested in the same plot, although interior The purpose of many field germination studies is fences of interlocking metal window screening are to test for different degrees of canopy influence, and recommended to keep different subsamples of seeds

section 7 seed quality and viability 123 unsown, and all germinants counted, and the mean density used to adjust the germinant counts in the plots with the introduced seeds. The degree of error due to physical loss (as opposed to biological loss) of seeds can be quantified by plac- Lid ing randomly on the site several replicates of glass beads the same size as the seeds. Refer to Johnson and Fryer () for additional details.

.. Preparing the seeds The seeds used for germination trials should be locally collected, or obtained from seed sources matched as closely as possible to ecologically similar sites and within the same relatively narrow geographic and alti- Base tudinal range. It is inappropriate to conduct studies (and extrapolate results) when seeds are not geneti- cally adapted to the specific site in which they are sown. Seeds can be placed in experimental plots directly  . A recommended frame design for delimiting after collection. Note, however, that in commercial field germination plots. This design is effective seed collections, the seeds are usually dewinged dur- in constraining the movement of subsamples ing processing. Also, if the seeds have been prepared within the plot, and excluding seed predators. for nursery sowing, they may have been stratified before shipping. These practices may be acceptable if you are testing spot-seeding methods and the same from becoming mixed. This is especially important practices will be used in operational situations. How- if the plot is not level, is subject to flooding, or if ever, if you are interested in evaluating natural seed animals move the seeds. rain, you may not want the seeds subjected to any treatments before sowing. .. Excluding other seeds Seeds scattered on the surface of the seedbed You should check to ensure that the experimental site sometimes cannot germinate because they are perched has not been contaminated by natural seed rain. Seed on obstacles or otherwise have poor contact with the rain from most conifers can be considered negligible substrate material (though they may eventually be if the plots are located more than three tree-heights washed in by rain). If the direct effects of the seedbed from mature trees. But when testing germination of and the microsite are of greater interest than docu- hardwoods that disperse over long distances (e.g., menting natural losses to the seed population, push aspen, cottonwood, birch, alder), seed rain contami- the seeds into the substrate or sprinkle some material nation cannot be ignored, even in the middle of a on top of the seeds. This approach may result in large clearcut. During the season when they are dis- higher germination levels, but it is rather artificial. persing, seeds can be excluded with nylon window If unstratified seeds are used, it is better to sow screening, cheesecloth, or remay (which allows rain- them during the season in which they would natu- fall penetration); coverings can be removed after a rally be dispersed (e.g., fall for most conifers, spring fixed number of test seeds have been introduced. for Populus spp., late spring or early summer for as- Such protective devices cannot validly be left in place pen and willows) so they can meet their stratification during the actual germination experiment, because and/or germination requirements over the natural they can potentially modify the micro-environment progression of seasons. Unstratified conifer seeds to a degree that the plot is no longer representative of might also be sown in spring, but stratification may the microsite being tested. Alternatively, equivalent be inadequate under such conditions (e.g., Dominy plots (identical area and seedbed makeup) can be left and Wood ).

124 field studies of seed biology If stratified seeds are used, they must be sown as seeds into different vegetation types, and noted dif- early as possible in the spring. If the seeds are not ferent degrees of seed predation among vegetation present on the site before the time they would ordi- types. In some cases, a more realistic estimate of a narily emerge, they may not follow the same site’s regeneration potential might be obtained by germination pattern as naturally dispersed seeds calculating seed-to-seedling ratios from data (J. Zasada, pers. comm., ). High germination gathered from unprotected sites (e.g., Noble and rates generally can be expected when stratified seeds Ronco ; Alexander ; Cain ; McDonald are sown in spring. and Abbott ).

.. Excluding predators .. Monitoring germinants Losses to seed predators are often the most serious The survival of newly germinated seedlings is often obstacle to obtaining good field information on seed examined in association with germination studies. germination (Section .), especially for relatively Monitoring of germination is usually required to large-seeded species, such as Douglas-fir, ponderosa capture the natural time span in which germination pine, grand fir, maple, and oak. The use of predator occurs, which for many habitats in British Columbia odours is sometimes an effective deterrent, but provid- may be spread over – weeks. Simply counting ing highly palatable alternative foods (e.g., sunflower germinants at the end of the growing season is not seeds) can reduce—though not eliminate—losses of recommended (unless you are primarily interested conifer seeds to small mammals (Sullivan a). in net recruitment) because many seedlings die and Offering alternative foods may be suitable for di- may be largely decomposed before the end of the rect seeding operations, but may not be an option for season (Gashwiler ). Monitoring at intervals of experimental studies where experimental seed losses – weeks is recommended, with all germinants are unacceptable. Full physical exclusion is generally removed or tagged at each interval. For species such the best approach. Devices range from small plastic as willows and aspen, whose seeds germinate within berry baskets to cone-shaped hardware-cloth tents – days and all germination occurs in a -week pe- (Frenzen and Franklin ; Mitchell et al. ; riod, monitoring at -week intervals or more often Adams and Henderson ). See Section . for a will be required. full description of exclusion devices. The mesh must Differential tagging of new germinants at each be small enough to exclude deer mice without monitoring interval (i.e., each cohort) is desirable, detectably modifying the microclimate; – mm because cohorts may differ in their susceptibility to mesh is generally adequate. The lower flange must drought and pests. Researchers often use coloured also be anchored to the soil and preferably buried toothpicks or plastic cocktail swords to mark indi- to prevent rodents burrowing under to get the seeds. vidual seedlings (e.g., Brown et al. ), but these The best exclosures are large wooden frames (– become impractical if germinant densities are high,  cm on a side) similar to the seed traps described or if frost-heaving is a problem. Wire hoops are pre- in Section .. The lower frame can be buried in the ferred because hoops are more difficult to displace soil, with a tight-fitting screened lid resting on top than markers stuck into the ground. Plastic-insulated (Figure .a). The lid can be removed for monitoring coloured wire (telephone wire or garden twist-tie and, to minimize internal shading, the entire unit can wire) can be cut into – cm lengths and looped be set flush with the ground surface. around the base of each seedling. Other options in- Instead of excluding seed predators from germina- clude tags used for banding birds, and sections of slit tion plots, many researchers consider them to be part plastic straws, which can be numbered with water- of the local environment and do not try to exclude proof ink. them. Zasada et al. () introduced seeds of several conifer and hardwood species to unprotected burned . Experimental Design for Germination Studies seedbeds and then monitored net germination (emergence) and early survival. Similarly, Burton and Most environmental studies involving tree seeds are Bazzaz () introduced unprotected hardwood designed to compare how different treatments affect

section 7 seed quality and viability 125 seed germination. Germination test conditions and (e.g., pioneer versus climax). Species could also be procedures are often governed by seed testing rules selected if one has an interest in the responses of (Association of Official Seed Analysts ; Interna- different species to a particular variable, such as tional Seed Testing Association ), at least for temperature. many laboratory experiments. Regardless of whether Choosing different seed sources generally implies or not tests are conducted under standard conditions, that one is interested in the effects of genetic varia- once the test environment has been determined, the tion. For example, seed source may be included as an next task in designing an experiment is to determine experimental factor if one wants to compare the dif- which factors (and levels of those factors) will be ferences between northern and southern populations selected for study. of the same species, between coastal and interior seed sources, or between low-elevation and high-elevation .. Experimental factors seed sources. A factor is a variable that may affect the response of There are two main groups of seed treatments: () an experiment, and has, in general, more than one treatments that are applied before the germination level. A particular factor is chosen because the experi- test, and () treatments that are applied during the menter wants to test or compare how the different germination period. Some examples are as follows: levels of that factor affect the measured response. A factor can be classified as either fixed or random, . Treatments applied before the germination test: depending on how the levels are chosen. A fixed a) dormancy release treatments (e.g., stratification, factor has levels that are determined by the experi- scarification); menter. If the experiment is repeated, the same factor b) upgrading treatments (e.g., specific gravity levels would be used again because the experimenter separation, polyethylene glycol); is interested in the results for those specific levels, and c) cold storage conditions (e.g., number of years the results would be applied only to those levels. A stored; storage at +°C versus °C); and random factor has levels that are chosen randomly d) seed moisture content (e.g., % mc versus from the population of all possible levels. If the % mc). experiment is repeated, a new random set of levels . Treatments applied during the germination period: would be chosen. The experimenter is interested in a) environmental conditions (e.g., temperature, generalizing the results of the experiment to a range moisture stress); and of possible levels and not just to the levels selected b) daylength or thermoperiod (e.g., different day/ (Sit ). For example, the factor “seed source” is night hours, different day/night temperatures). considered random if the sources are chosen from the full range of sources available in the province, and if .. Experimental designs the purpose of the experiment is to extend the results to the species as a whole. However, to examine the Single factor effects of latitude on germination, and seed sources An experiment involving a single factor has a one- are chosen from particular latitudes to test this effect, way design. Depending on how the factor levels are then the seed source factor is considered to be fixed. assigned to the experimental units, the design could The factor and levels of a factor chosen for com- be completely randomized, or a randomized block. In parison depend on the underlying objectives of the a completely randomized design, there are many study. In general, a particular species is selected for homogeneous experimental units; each experimental study because the species may exhibit difficulties with unit is randomly assigned to one of the factor levels. germination or dormancy (e.g., Abies requires excep- Each factor level often has an equal number of tionally long stratification to germinate well) and experimental units, or replications, although such a information on the specific germination behaviour is balanced design is not necessarily required. If the required. Species could be selected by their presence experimental units are not homogeneous, they could in a particular biogeoclimatic zone (e.g., coastal ver- be arranged into groups or blocks, according to some sus interior), or their position in seral succession common characteristic (e.g., location, aspect) so that

126 field studies of seed biology the variation within a block is smaller than the responses to treatment effects should be consistent variation between blocks. Within each block of from block to block. For example, to compare the experimental units, factor levels are assigned to the effect of two different daylengths on seed germi- experimental units at random. In essence, a nation rate of lodgepole pine, a randomized block randomized block design has several blocks of design could be used with coastal and interior seed experimental units, with a completely randomized sources being selected as the blocking criteria. This is design within each block. (See Figure . for an legitimate if seed source does not alter how daylength example using two levels of one factor.) affects germination rate. That is, the longer daylength should be more (or less) effective than the shorter Multiple factors daylength for both coastal and interior seed sources. Carefully choose the blocking criteria. Since the If, however, seed source alters the effects of daylength experimental units within individual blocks are (for example, longer daylength increases rates of the different, their responses to the factor levels are coastal seed source, but decreases rates of the interior expected to be different. However, the relative seed source), then seed source is not a suitable blocking criterion. If how seed source will influence the effects of daylength on germination is not known, a) or if the goal is to find out how the two factors—seed source and daylength—interact with each other, then a completely randomized design involving both factors should be used. In a factorial design experiment, more than one factor is involved, and all levels of one factor are combined with all levels of the other factors. In the daylength–seed source example, a factorial experi- ment could be designed to assess the effects of daylength and seed source on germination rate. Each experimental unit would be randomly assigned one level of the daylength treatment and one level of the seed source treatment. The assignment of one factor level to an experimental unit should not affect the assignment of any level of the other factor. The pri- b) mary advantage to using a factorial design is the ability to examine both daylength and seed source effects on seed germination, plus the combined effects of daylength and seed source. A factorial experiment may be carried out in a completely randomized or randomized block design. Assigning the factor levels to the experimental units completely at random is easy to accomplish. However, it is sometimes advantageous to do the random assignment at several levels. For example, consider an experiment that examines the effects of cold storage conditions (+°C versus -°C) and daylength (-hour day versus -hour day) on seed  . Layouts for one factor with two levels (X = 8- germination (Figure .). Four hundred seeds are hour daylength, O = 16-hour daylength): (a) available for the experiment. In a completely ran- completely randomized design, and (b) domized factorial experiment, each seed would be randomized block design. randomly assigned one of the four treatment combi-

section 7 seed quality and viability 127 nations. In this case, an individual seed is the experi- daylength to the two groups of seeds is completely mental unit for the factors cold storage condition and random. The experimental unit for the daylength daylength. However, it may not be efficient to assign treatment now consists of a group of  seeds. This is treatment combinations to each seed. Since the cold a split-plot design with cold storage as the main plot storage treatment must occur before the daylength treatment and daylength as the split-plot treatment treatment, the experiment could be designed differ- (Figure .b). ently. The seeds could be grouped into  trays of A split-plot design has the characteristic that the  seeds each, and each tray could be assigned to one two treatment factors have different experimental of the two cold storage treatments (five trays at +°C units, and the experimental unit for the split-plot and five trays at -°C). Each tray of  seeds repre- factor is contained within the experimental unit sents one experimental unit of the cold storage of the main-plot factor. The randomization of the treatment (Figure . a). split-plot factor is restricted in that both levels of After cold storage treatment, each tray of seeds daylength treatment must occur within each tray of could be subdivided into two groups of  seeds. seed. In addition to ease of execution, the split-plot Within a tray, one group of seeds would be exposed design also yields more precise information on the to  hours of daylight, the other group would be ex- split-plot factor, but at the expense of losing informa- posed to  hours of daylight. The assignment of tion on the main-plot factor. For further discussion of these and other types of experimental designs, consult Anderson and McLean (); Steel and a) Torrie (); Sokal and Rohlf (); Mead (); Milliken and Johnson (); and Sit ().

.. Replication and randomization An experimental unit is the smallest collection of the experimental material to which one level of a treat- ment factor may be applied. Germination tests, for example, are usually conducted on groups of  seeds; for such tests, a group of  seeds represents one experimental unit. A replication is an independent application of a factor level. A factor level is consid- ered to be replicated if it is applied to two or more experimental units. The number of replications of a level is the same as the number of experimental units to which a factor is assigned (Sit ). For example, b) if each factor level of a germination experiment was assigned to four experimental units, then the experi- ment would have four replications. Replication quantifies the size of the experimental error, so that treatment factors can be properly compared. An unreplicated study has weak comparison power and can only be viewed as a one-time occurrence for which the results cannot be generalized. Differences observed in an unreplicated study could be due to the treatment, or to random variation; without replica- tion it is not possible to determine the cause of the observed variation.  . The two stages of a split-plot design (see The number of replications required to detect dif- explanation in text). ferences between treatments will depend upon the

128 field studies of seed biology variability of the experimental material. Seed testing treatment levels to the experimental units, and, where rules (Association of Official Seed Analysts ; necessary, random selection of sampling units within International Seed Testing Association ) prescribe an experimental unit for measurements. four replications of  seeds for germination tests, because conditions for laboratory tests are relatively . Data Analysis in Germination Studies uniform. More replicates are required for nursery and field tests. Nursery-test results tend to be more The method of analysis depends on the design of the variable than laboratory tests, because of changing experiment and the type of data collected. For con- conditions within greenhouses (e.g., shading, drying tinuous data such as percent germination, analysis of of blocks near edges of watering booms). In the field, variance (anova) and regression are suitable analysis tests are subjected to all the vagaries of field environ- methods. For discrete data, such as germination status ments: seeds may be washed or blown away, eaten by (germinated, not germinated), categorical data analysis predators, or simply lost (hard to tell a small dark methods such as a chi-square test are more appropriate. seed from a small dark piece of soil). When only a limited number of seeds are available, .. anova such as in experiments using seeds derived from con- Understanding the proper application of error terms trolled genetic crosses, the number of seeds per is essential when using anova for data analysis. A replication may have to be reduced to achieve suffi- common mistake is to use the experimental error cient replication to determine differences between term to test all effects. The experimental error is only treatments. The minimum number of seeds per suitable for testing when the design is simple. In a replication depends upon the variability of the test randomized block design, for example, main effects material. For tests conducted in closed dishes in con- are often tested by the block-by-treatment interaction trolled environment chambers, for example,  seeds terms. The following two examples show the error per replication might be used and still assure detec- term structure in anova tables for a one-factor tion of statistical differences. It is advisable, however, completely randomized design and a two-factor to increase the number of replications (perhaps from randomized block factorial design. four to six) whenever the number of seeds per repli- cation must be reduced. One-factor completely randomized design For germination tests conducted in controlled To comparetwo levels of soil storage conditions environment chambers, the issue arises as to whether ( year versus  years),  bags of  seeds are buried controlled environment treatments are truly replicated underground. At the end of year , five bags of seeds when only one chamber is used for each experimen- are randomly pulled out of the ground for germi- tal condition. More than one chamber per condition nation. The remaining  bags of seeds are assessed must be used to achieve true replication. The cost of at the end of year five. The percentage of seeds controlled environment equipment generally prohib- germinated is recorded for each bag. A bag of seeds its the use of more than one chamber, but in reality, is the experimental unit for soil storage treatment. use of only one chamber per condition constitutes   pseudoreplication. In most tree seed studies, however, the variance due to the effects of treatments (i.e., Source of variation Degrees of freedom Error term stratification, seed source) is usually far greater than the variance due to within-chamber variation. None- Treatment, Tt-1 = 2-1 = 1 B(T) theless, pseudoreplication should be acknowledged Bag, B(T)(b-1)t = (5-1)(2) = 8 — when presenting and interpreting results. Randomization is required for sound experimen- Total (b)(t)-1 = (5)(2) - 1 = 9 tation as it helps to reduce systematic bias within the experiment. Randomization should occur at several levels: random selection of experimental units for The term B(T), usually denoted as the experimen- treatment assignment, random assignment of tal error, is the correct error term for testing soil

section 7 seed quality and viability 129 storage treatment effects. Note that the total degrees anova assumes that residuals must be independ- of freedom in an anova table should be one less than ent, normally distributed, and have equal variance. the total number of measurements in an experiment. These assumptions must be checked to ensure the analysis is appropriate. See Section .. for more Two-factor randomized block factorial design discussion of anova assumptions. For anova tables To compare the effects of two stratification treat- for other designs, see Chapter  of Sit (). ments (e.g.,  weeks,  weeks) and three germination temperatures (e.g., °C, °C, °C) on white spruce .. Categorical data analysis seed germination, seeds from four different seedlots, If the data collected in an experiment are categorical randomly selected from all available seed sources, are (e.g., the degree of mould infestation, see Table .), used in a study. Six batches of  seeds are available then anova is not suitable for the analysis. Categori- from each seedlot. For each seedlot, one of the six cal analysis methods such as the contingency table stratification-temperature treatment combinations chi-square test allow you to check whether the pro- will be randomly assigned to an individual batch portions of seeds in the classes are similar for the of seeds. It is expected that the stratification– treatments. Refer to Sections . and .. for exam- temperature effects on white spruce seed germination ples of categorical data analysis. are consistent across seedlots, hence seedlot is acting as a block in this design. A batch of seeds represents .. Regression the experimental unit for the stratification and Regression is a common method for modelling the temperature treatments. Percent seed germination relationship between several variables. In seed germi- is recorded for each batch of seeds. nation studies, you may want to model the rate of   germination over time. Since the shape of the curve relating percent germination and time is not a Source of variation Degrees of freedom Error term straight line, nonlinear regression should be used for modelling the data. The exponential Gompertz func- Seedlot, Ll-1 = 4-1 = 3 — tion is particularly suitable for germination data (Tipton ). Cumulative germination percentage Stratification, Ss-1 = 2-1 = 1 L*S can be fitted to the Gompertz curve of the form: Temperature, Tt-1 = 3-1 = 2 L*T S*T (s-1)(t-1) = 2 L*S*T Y = A exp [-exp(B - Ct)], L*S (l-1)(s-1) = 3 — where: L*T (l-1)(t-1) = 6 — Y = cumulative germination percentage at L*S*T (l-1)(s-1)(t-1) = 6 — time t; exp = exponential function; Total (l)(s)(t)-1 = 23 A = parameter corresponding to the final germination percentage; B = parameter reflecting the start of The term L*S*T is often called the experimental germination; error. However, it is only the correct error term for C = parameter indicating intrinsic rate of testing stratification-temperature interaction (S*T). growth (i.e., germination speed); and Stratification (S) and temperature (T) effects are t = time (e.g., number of days or number tested by the corresponding seedlot interaction terms of weeks). (L*S and L*T) because S and T are replicated by ran- domly chosen seedlots. The terms L, L*S, L*T, and In regression, germination data points at various L*S*T are not testable because these terms include times t are used to estimate parameters A, B, and C. the seedlot factor which is not replicated (there is The usefulness of the fitted regression model depends only one of each seedlot). on the suitability of the chosen function. A general

130 field studies of seed biology rule for nonlinear regression is to use the simplest different species). The analysis would begin with model that best fits the data. For ease of interpreta- estimating the model parameters (A, B, and C) for tion, the form of the model should also be each replication of the treatment factor. The param- compatible with the underlying biological mecha- eter sets thus estimated would then be used as data in nism driving the system. For example, both an a multivariate analysis of variance (manova). If the exponential function and a polynomial function have manova is significant, then univariate anova would an increasing trend. However, the exponential func- be done on each parameter separately to determine tion is more suitable for modelling growth data, which parameters are significant. This curve-fitting because growth is well understood (biologically) to approach to comparisons has several advantages. It be exponential in nature. Thus, parameters expressed appropriately takes into account the time-to-time in an exponential function have more meaningful correlation in the data. By reducing the data to a few interpretations than parameters expressed in a poly- parameters, it simplifies the manova. Also, with the nomial function. For a full discussion of commonly appropriate choice of a model, features of the germi- used models for nonlinear regression and practical nation curve that are of most interest to the hints for fitting nonlinear models, see Ratkowsky experimenter (e.g., time when germination is first () and Sit and Poullin-Costello (). observed, maximum germination speed, and final Nonlinear regression can also be used as a tool for germination percentage) can be directly compared. comparing trends (e.g., comparing the germination Examples of this type of data analysis can be found in trends of seeds receiving different treatments or of Leadem (); Sit (b); and Stoehr et al. ().

section 7 seed quality and viability 131

SECTION 8 SILVICULTURAL PRACTICES AND TREE SEED BIOLOGY

Some seeds fell by the wayside, …some fell upon stony places, …and some fell among thorns; …but others fell into good ground … (The Bible, Matthew :–)

. Background Regeneration silviculture is based on two impor- tant principles of forest ecology: Tree seed studies are often conducted or repeated • Some level of disturbance (natural or artificial) is under field conditions to better understand the usually required to free plant growth resources and significance of seed ecology in forest regeneration. provide growing space for new trees (Bazzaz ; The incentive for much forestry research on seeds is Canham and Marks ). directly related to testing alternative silvicultural • Seed germination and seedling emergence are cru- treatments that facilitate natural regeneration. This cial steps in the life cycle of many plant species, section will briefly review forest practices that affect and only a narrow range of conditions is suitable regeneration by seeds, and offer some suggestions for for seedling establishment (Grubb ; Harper studying seed dynamics under field conditions. ; Oswald and Neuenschwander ).

.. Principles of forest stand manipulation Much of the experimentation and monitoring In silviculture, the environmental factors discussed in associated with silvicultural research is therefore Section  are manipulated to enhance the regenera- concerned with assessing the degree of disturbance tion, establishment, and growth of desired tree crops. achieved, or with evaluating the success of young Most silvicultural practices are designed to alter either trees in a variety of natural or modified microsites. the canopy (the above-ground growing space), or the seedbed (the substrate for seedling establishment and .. Standard silvicultural practices the below-ground growing space). Forest management activities are implemented over Promoting forest regeneration from seeds requires wide areas and long time periods. Timber harvesting, a favourable combination of seed supply, seedbed, and road development, resource zoning, and fire protec- environmental conditions (Figure .), so many silvi- tion policies all affect large areas of land at the forest cultural practices are designed specifically to enhance or landscape scale. However, to researchers studying these factors. Silvicultural practices may range from seed ecology, activities performed at the stand level specialized procedures to induce tree seed production are more relevant. Typical stand-management activi- to the multipurpose practices of canopy opening ties may include resource inventories, protection from and forest floor disturbance. Should these activities wildfire and pests, timber harvest, and stand renewal. be unable to regenerate the desired tree species at Some activities, such as inventories, have no effect on target stocking levels, then specific site preparation a stand, while other activities, such as logging or pre- operations are undertaken to create or improve scribed burning, can be extremely disruptive. The microsites so they are more suitable for tree fundamental principles of sustainable resource seedling establishment. development and environmental protection assume

section 8 silvicultural practices and tree seed biology 133 that, whatever the type of stand manipulation, all stand entry into the stand for timber harvest) is typi- activities should be conducted in a manner that cally used to describe the entire silvicultural system. facilitates stand maintenance, rejuvenation, or In each system, the availability of tree seeds is largely restoration. determined by the density and distribution of the A silvicultural system is a set of stand management residual mature trees left in the stand. Five silvicul- treatments for forest tending, harvesting, and replace- tural systems used at the Lucille Mountain Project ment. Except for a brief overview, it is beyond the are illustrated in Figure .. scope of this manual to describe the range of prac- tices that comprise different silvicultural systems (see, • A clearcut system creates stand openings that are for example, Matthews ). Each silvicultural system dominated by exposed, full sunlight conditions. is composed of many individual components, and • A seed tree system is similar to a clearcut system each component requires testing and modification to in that it creates a microclimate characteristic be applied effectively in a given forest type. Individual of open conditions, but a few scattered trees are stand management treatments may be prescribed to retained to provide seeds for natural regeneration. alleviate some limiting factor, but in practice, numer- • In shelterwood systems the density of residual trees ous treatments usually are enacted as a package. is greater, so that the retained overstorey provides The amount of mature canopy retained during protection (from sun-scald, frost, etc.) to the regeneration of a stand (or the nature of the first regenerating tree crop.

 . Effective natural regeneration depends on an adequate seed supply, a suitable seedbed, and an appropriate environment. All sides of this “natural regeneration triangle” must be adequate to achieve successful natural regeneration (from Roe et al. 1970).

134 field studies of seed biology • Clearcut, seed tree, and shelterwood systems Silvicultural systems were originally designed to regenerate even-aged stands. In selection systems, facilitate natural regeneration, usually by seeds. single trees or small groups of trees are harvested However, if natural regeneration proves unsuccessful to regenerate the forest in smaller canopy gaps, or too unpredictable, dependence on natural seed maintaining continuous forest cover and an availability can be bypassed through artificial regen- uneven-aged structure to the tree population. eration, which introduces seeds or seedlings for stand renewal. Direct seeding can be undertaken in a broadcast manner (often from aircraft), but it is a) more effective if efforts are focused in spots or strips that have been prepared to favour germination and establishment (Mitchell et al. ). By planting seedlings, germination and early growth occur in the generally more favourable environment of forest seedling nurseries. Coppice systems count b) on the vegetative sprouting of stumps or roots (e.g., the profuse suckering of trembling aspen after harvest), which also bypasses the greater risks of reproduction and establishment of hardwoods from seeds. Successful seedling establishment is a good indica- tor of the degree of canopy opening and forest floor c) disturbance that can be tolerated without degrading the ecosystem. For experimental purposes, some silvicultural practices may be performed and moni- tored on a relatively small scale—on research plots rather than on the entire stand. Treatments might include mounds made by hand or burning slash and d) forest floor with a propane torch. However, care should be taken when extrapolating the effects of microscale treatments to the probable effects of macroscale disturbance. The disturbance created by large equipment on soil properties, for example, is not equivalent to the effects created by hand equipment. e) Many treatments only produce reliable results if they are implemented with large machines over several hectares.

. Effects of Canopy Manipulation

A complex of irradiance, temperature, humidity, f) wind, and other microclimate factors are associated with the shading and sheltering influence of forest canopies. These factors change in proportion to the  . Illustration of stand structure resulting from degree of canopy opening in silvicultural systems. different silvicultural systems used in the Lucille Mountain Project in the Engelmann Indeed, silvicultural systems are classified in large Spruce–Subalpine Fir (ESSF) biogeoclimatic part according to the degree they open the canopy zone, Prince George Forest Region, British in the first, or regeneration, cutting (Matthews ; Columbia (adapted from Jull et al. 1996). Klinka et al. ).

section 8 silvicultural practices and tree seed biology 135 The removal of part or all of the tree canopy re- canopy cover provides protection from sun scalding, leases light, water, and nutritional resources for seeds photoinhibition, desiccation, and radiation frosts and seedlings, but it also often results in develop- that might critically affect the survival of young, ment of ground and shrub canopies that impose unlignified seedlings. more restrictions than the original overstorey. Some interactions with other canopy-related factors may .. Temperature be difficult to anticipate, for example, the effects of Canopy removal may have a greater influence on the one canopy layer on another layer, or the effects of temperature than on the light properties of micro- different vegetation layers on the same microsite. sites (Figure .). Total forest canopy removal results in higher (and potentially lethal) soil temperatures .. Light and more extreme temperature fluctuations The most immediate and dramatic effect of tree har- (Hungerford and Babbitt ; Stathers and Spittle- vesting is increased light levels in the understorey house ), both of which can negatively affect seed (Figure .). Ecosystems vary in the degree to which germination and seedling survival. On the other increased light levels stimulate the growth of under- hand, complete canopy removal and some forest storey (shrub and herb) vegetation, and such growth floor disturbance are often beneficial at high eleva- may negate in a few years the effects of canopy tions, high latitudes, or on northern exposures where opening on the forest floor. The increased amount soil temperatures may be too cold for germination of light caused by total canopy removal may stimu- (Bonan ; Balisky and Burton ). late the rate of germination of species such as pines (Li et al. ). For other species, partial canopy .. Moisture removal may be more favourable to germination The most usual immediate effect of canopy removal and early survival because retaining partial canopy is a rise in the water table; the loss of tree cover re- cover helps moderate the moisture and temperature duces transpiration and increases moisture in the of the seedbed. Protected microsites that maintain root zone. However, the removal of a tree canopy higher-than-ambient levels of humidity may not sup- exposes the soil surface to direct sun, to high surface port optimal seedling growth, but still are important temperatures, and to increased wind speed, and this for seed germination and emergence (Frenzen and can result in rapid drying of the surface layers that Franklin ; Battaglia and Reid ). Partial constitute the seedbed. These conditions often arise

 . Measured levels of photosynthetic active radiation (PAR) available to seedlings above and below the shrub layer in various partial cut systems at the Lucille Mountain Project, Prince George Forest Region, British Columbia (Jull et al. 1996). Results are shown for treatments illustrated in Figure 8.2d, e, and f.

136 field studies of seed biology • Is seed rain density significantly greater under a shelterwood system than a seed tree system? • Is tree seed germination more successful with or without some canopy cover? Does this vary by species and latitude? • What is the seed-to-seedling ratio under alternative stand treatments? • Can a given stand or stand treatment meet a desired level of stocking through natural regeneration? • What level of canopy retention significantly reduces (or increases) early seedling survival? • Does one tree species germinate and/or establish better than another under a particular canopy treatment (e.g., a shelterwood cut removing % basal area)? • Do canopy effects on germination depend on seedbed conditions? For example, is shade better for germination on all substrates, or just for seeds germinating in the duff layer?  . Growing-season soil temperatures (at 10 cm • What is the relation between canopy reduction, depth, 4-year means) on a north-facing slope understorey development, and the light and in clearcut, small patch cut, and group resource levels of the seedbed? selection treatments (Jull et al. 1996). Results are shown for treatments illustrated in Figure 8.2 a, c, and d. The objective of many studies is to correlate indi- cators of successful natural regeneration with various canopy openings. For example, tree seedling estab- after canopy removal in clearcuts, and historically, lishment has been correlated with canopy density, have been the major reason to develop silvicultural subcanopy irradiance levels (e.g., Burton and Mueller- systems that provide better protection to seedbeds Dombois ; Stewart ; Canham et al. ; and to newly established seedlings. Denslow and Hartshorn ), specific environ- mental variables (Geier-Hayes ; Oswald and .. Suggested questions and approaches Neuenschwander ; Denslow and Hartshorn Monitoring of tree seed germination and early seed- ), or site variables. Seedling establishment is usu- ling population dynamics is often part of evaluating ally enhanced in forest gaps or disturbances (Platt the effectiveness of silvicultural systems in promoting and Strong ; Coates and Burton []), but forest regeneration. Much of the incentive for choos- under extreme environmental conditions better ing one silvicultural system over another is the establishment may be found in protected, shaded expectation that one method is more effective in microsites (Frenzen and Franklin ). Evaluating producing seeds or creating better conditions for the success or failure of silvicultural treatments may germination and early seedling survival. In some depend on when the assessment is made (i.e., after stands, trees are retained to provide seeds or to pro- one growing season or after  years). Successful estab- tect young seedlings (such as seed tree, shelterwood, lishment of seedlings may depend more on the ability strip cut, and some patch-retention systems). Ques- of germinants to survive on a particular site than on tions that might be asked in regeneration silviculture the number of seeds that initially germinate (Burton field trials include the following: ). Optimal conditions for seed germination are not necessarily optimal for plant survival and growth • Is cone production per tree greater in partially of the same species (Parrish and Bazzaz ; Oswald girdled trees than in untreated trees? and Neuenschwander ; Schupp ).

section 8 silvicultural practices and tree seed biology 137 Once relationships are noted, more detailed ex- . Effects of Seedbed Manipulation periments may be undertaken to verify initial study results. This may be accomplished, for example, by The success of natural regeneration or direct seeding studying the effects of canopy shading on tree seed depends, in part, on how well seedbed environments germination in glasshouses or slathouses where shade meet the requirements for seed germination and levels can be controlled (e.g., Minore ; Alexander seedling establishment. The suitability of seedbeds is ). In this regard, note that “neutral shade” treat- determined by many factors, including their thick- ments created in slathouses are sometimes considered ness, water-holding capacity, hydraulic continuity, unrealistic because they do not mimic the spectral thermal properties, and chemistry. These factors are shift normally found under plant canopies. In neutral so inextricably linked that ecological and silvicultural shade treatments, light passes through a filter with no researchers have found it useful to characterize the change in the relative proportions of various wave- seedbed as a single (though complex) environmental lengths. Under plant canopies, the light spectrum has factor or metafactor, which is usually described as a proportionately less light in the red and blue wave- categorical variable. lengths and more in the green wavelengths (see Section ... and Figure .). Nevertheless, neutral .. Seedbed preferences shade is a useful experimental tool because it allows Microsites are sometimes evaluated as a way to researchers to vary the quantity of light while main- compare the suitability of seedbeds. In the following taining constant light quality. discussion, the term seedbed could include many Often, the next step after conducting controlled different types of microsites for seed germination, studies is to introduce pre-counted seeds into field such as different elevations or aspects of a mound or plots. Section . outlines some methods for how to berm, or different degrees of mixing of the forest study germination under field conditions. Treatments floor with the mineral soil. may consist of canopies comprising different species Typical seedbeds encountered in managed forests (Burton and Bazzaz ) or different degrees of include mineral soil (compacted or not compacted), canopy opening to test, for example, the effects of forest floor (possibly divided into undecomposed full shade, partial shade, and full sun on direct litter and decomposed humus layers), logs or rotting seeding spots (Smith and Clark ; Burton ). wood, and mats of mosses or lichens. Other substrates, Canopy cover effects can be measured within a stand, such as bare rock, standing water, or undecomposed or at different distances from a stand edge (Burton logging slash, are never considered as potential seed- ; Coates and Burton []). These two condi- beds. Combinations of materials are sometimes tions evaluate slightly different aspects of the recognized, such as moss on rotting wood versus influence of light and shade; different canopy thin- moss on mineral soil, or different (measured) thick- ning levels alter the size and duration of sunflecks, nesses of forest floor over mineral soil or rock. Most while plots placed at different distances from a stand of these materials are considered to be distinct when edge differ primarily in the daily duration of uninter- consumed or scorched by fire. rupted direct sunlight. Because of wide differences in physical character- When studying canopy treatment effects on seed istics, temperatures, and the availability of water and production, seed rain density, or seed dispersal, dif- mineral nutrients, seedling establishment varies ferences in the seed supply are of greater importance greatly in different natural seedbeds (see Table . and than differences in the amount or quality of light. example in Section ..). Mineral soil is a good seed- Seed trap arrays, either randomly distributed under bed because of its high infiltration capacity, adequate different canopy treatments or in transects away from aeration, and close contact between soil particles a stand edge, are one of the most common methods and seeds (Kramer and Kozlowski ). Although for monitoring the influence of forest canopies on mineral soils warm earlier and attain higher tempera- seed supply (Figure . and Section .). tures in the spring, in bright sunlight the surface

138 field studies of seed biology  . Comparative seedbed suitability of some northwestern tree species (from Minore 1979). Species in the upper groups are better suited to the seedbed than those in lower groups. Data are insufficient for species comparisons within the groups.

Organic seedbeds Mineral soil seedbeds Coastal Interior Coastal Interior Burned seedbeds

Tsuga heterophylla Picea glauca, Alnus rubra Larix occidentalis, Pseudotsuga menziesii, Thuja plicata Pseudotsuga Picea sitchensis Picea engelmannii Abies grandis, menziesii Pinus ponderosa Picea sitchensis Thuja plicata Pinus contorta, Abies lasiocarpa, Abies lasiocarpa Tsuga heterophylla, Alnus rubra Tsuga heterophylla Pinus contorta Pseudotsuga menziesii, Larix occidentalis, Larix occidentalis, Picea glauca Picea engelmannii, Picea engelmannii Pinus contorta Thuja plicata, Pinus monticola, Abies lasiocarpa

temperature of mineral soils and burned materials species can establish on both mineral soil and on can become so high as to be lethal to germinating moss and duff. If sufficient moisture is present, seeds. However, when moisture is adequate, most amabilis fir, subalpine fir, tamarack, Engelmann native British Columbia hardwoods and conifers ger- spruce, black spruce, Sitka spruce, Douglas-fir, minate best on mineral soil seedbeds. western hemlock, and mountain hemlock have Litter and duff are less suitable than mineral soil been found to germinate well on organic and because they warm slowly, inhibit root penetration, inorganic substrates (Fowells [compiler] ; prevent good seed–mineral soil contact, dry rapidly, McCaughey ). and shade small seedlings. Sphagnum moss often is a For some species, the properties of organic suitable seedbed because of its high water-holding substrates preclude seedling establishment. Western capacity, but it may subsequently smother young redcedar, because of its small seeds, germinates seedlings. Decayed wood is also an excellent natural poorly on duff (Fowells [compiler] ). Similarly, seedbed for seeds of forest trees, probably because of mineral soil and rotten logs are best for the germina- its capacity for water retention (Knapp and Smith tion and initial establishment of the very small seeds ; Harmon et al. ). However, although forest of paper birch. Newly germinated seedlings are ex- floor (or duff) and moss layers may be suitably moist tremely fragile; a paper birch seed that germinates on during the spring, they often dry out faster than a fallen hardwood leaf cannot push its radicle mineral soil and rotting wood. Therefore, organic through to the moist soil, and if it germinates under a materials usually form better seedbeds when they are leaf, the tiny seedling is almost always cut off from under partial shade. the light (Hutnik ). Duff seedbeds are better tolerated by large-seeded The relatively large seeds of bigleaf maple and species because these species can use their stored re- Garry oak have little problem penetrating leaf litter serves to subsidize radicle penetration to the mineral and organic substrates. Under field conditions, bigleaf soil. Thus, in boreal and subalpine forests, an organic maple germination often occurs on relatively undis- forest floor is an acceptable substrate for true fir turbed seedbeds in association with leaf litter and (Abies spp.) seeds (Alexander et al. ), but would other organic substrates (Tappeiner and Zasada not be suitable for the smaller seeds of spruce (Picea ). The best natural seedbed for Garry oak is moist spp.) (Noble and Ronco ; Klein et al. ). Some soil covered with  cm or more of leaf litter. After

section 8 silvicultural practices and tree seed biology 139 germination, the radicle quickly penetrates deep into .. Site preparation the moist mineral soil (Fowells [compiler] ). In Mechanical site preparation equipment was first used undisturbed forest, white spruce and western hem- to expose mineral soil for natural regeneration, not lock seedlings often are found on decayed wood, for planting (Smith ). Mechanical site prepara- which has several advantages over most other natural tion not only modifies the relative abundance of seedbeds. For these small seeds, decayed wood usually seedbed materials by increasing the exposure of min- provides more moisture, less chance of smothering eral soil, but also creates new microsites with raised conditions, and freedom from damping-off (Fowells or depressed elevations or changes in aspect. Site [compiler] ). preparation operations may remove, mix, or invert Very wet conditions are required by western white the organic layer and upper soil horizon to create pine and ponderosa pine seeds for germination and suitable microsites for seedling establishment (often seedling survival, and they are thus restricted more called planting spots) (McMinn and Hedin ). by water availability than by a specific substrate Some seedbed scarification methods, such as drag- (Fowells [compiler] ). Delayed germination and ging anchor chains or shark-fin barrels, remain the inability of Rocky Mountain juniper to establish common means to enhance natural regeneration on dry sites probably account for its generally sparse of lodgepole pine and western larch. natural regeneration. Juniper seedlings are found Prescribed burning is detrimental to natural most often in the moist soil of rocky crevices and in regeneration of conifers because conifer seeds are canyons near perennial water (Fowells [compiler] generally on or close to the surface of the forest floor, ). Under natural conditions, poplar and willow and are therefore vulnerable to even a low-severity seeds require a steady supply of water during germi- fire. However, fire creates seedbeds with better heat- nation and early seedling development. Seeds of both holding capacity and seed-substrate contact, and if species can germinate while floating in water or when some residual cover and seed trees remain in the sur- fully submerged (Wyckoff and Zasada []; Zasada rounding area, seeds dispersed after a fire are more et al. []). The high water requirements of these likely to establish greater numbers of seedlings. Pre- species is primarily due to their unique pattern of scribed burning releases nutrients more rapidly than epigeal germination (Figure .). In both poplars and through usual biological degradation processes; how- willows, the radicle does not emerge immediately, ever, depending on site factors, these may or may not but instead, a ring of fine hypocotyl hairs (the coro- be available to seedlings (Chapter  in Pritchett ). net) performs the dual function of water absorption and initial attachment of seeds to the substrate. .. Suggested questions for seedbed studies Seedlings often fail to survive because the root hairs Field seedbed research generally focuses on compar- dry too quickly or fail to securely attach seeds to ing different seedbed attributes (type, amount, or the soil. response to manipulation) and how they affect tree Seedbeds can be manipulated to favour establish- establishment. Substrate manipulation does not usu- ment by certain species. The rapid growth of ally affect seed availability on the ground, because hardwoods may pose serious competition problems natural seedfall is primarily related to the overstorey. for conifers. Red alder, which establishes quickly in Seed banks and seed predators could, however, be full sunlight on exposed mineral soil, is an aggressive influenced by site preparation. Site preparation can pioneer of avalanche paths, road cuts, log landings, influence the microtopography of the seedbed and, skid trails, or other areas where mineral soil has been for very small seeds such as willows and poplars, this freshly exposed to seedfall. To exclude red alder, some can be critical. A heterogeneous seedbed comprised forest managers try to reduce alder seed supplies by of particles of litter or soil prominences can strand removing seed trees in the vicinity, and by disturbing these seeds on rapidly drying surfaces where either the site as little as possible to avoid creating favour- seeds do not germinate, or root hair growth is insuffi- able seedbed conditions for red alder (Lousier and cient to make firm contact with the water-supplying Bancroft ). substrate (McDonough ).

140 field studies of seed biology Typical research questions associated with seedbed or retain moisture at the base. Seedbed trials are manipulation include the following: best conducted within frames (cylindrical or rec- tangular) that allow full hydraulic contact of the • Which seedbed type is best for conifer or hard- test material with the underlying soil. At the very wood germination and establishment? least, containers should be placed flush with the • Is there a critical thickness of forest floor material ground surface. above which germination or early seedling survival Another approach is to use removable germina- is inhibited? tion containers filled with intact substrate from the • Does site preparation (e.g., broadcast slash burn- study site. Haeussler et al. () constructed cylin- ing, mechanical site preparation) stimulate or ders ( cm diameter,  cm high) from pvc pipe and inhibit germination—from the seed bank? —of glued fine nylon mesh to the base. A core of forest fresh seeds deposited on the ground surface? floor or mineral soil was removed from the plot and • Is seedling recruitment density significantly greater placed intact into a container. The container was with or without seedbed scarification (e.g., drag- replaced into the core hole with its upper rim pro- ging anchor chains)? truding  cm. Seeds were sown into each container, • Is tree seed germination more successful on and a protective cage to exclude predators ( mm untreated forest floor or in scarified patches with plastic mesh measuring  ×  cm,  cm high) was exposed mineral soil? staked over each germination container. • What is the seed-to-seedling ratio under alternative The establishment of tree seedlings on a variety of site preparation treatments? substrates has been investigated for many ecosystems • Will seedbeds suffer greater predation in forested (Fisher ; Minore ). While controlled and rep- or in open conditions? licated experimental treatments are preferable, the • Does one tree species germinate and/or establish same information can be inferred from sample sur- better than another under a particular site prepara- veys comparing the observed abundance of seedlings tion treatment (e.g., a broadcast slashburn)? found on different seedbeds with the expected abun- • Does the influence of seedbeds on tree seed germi- dance of seedlings on those seedbeds (Christy and nation depend on canopy conditions? For example, Mack ; Geier-Hayes ). Only young or small is mineral soil significantly better than organic seedlings (less than  years old) should be counted substrates for germination under all canopy because the seedbeds from which they are derived conditions, or just in open areas? can deteriorate over time. This approach is dis- • How quickly do seedbeds “deteriorate” and how cussed in the following example and in Table .a does this affect seed-to-seedling ratios? and Table .b. • Can seedbeds be manipulated to enhance (or example reduce) hardwood regeneration relative to that (P. Burton and N. Daintith, unpublished data) of conifers? Objective. To determine whether naturally regen- erated subalpine fir, interior spruce, and Douglas-fir .. Methods for seedbed research seedlings exhibit any association with different seed- Some seedbed studies have used sieved materials in beds within a partially cut Douglas-fir stand. pots placed in growth chambers or greenhouses Hypothesis. If there is no difference between (Minore ; Ahlgren and Ahlgren ). Such substrates for germination and establishment of tree studies may be used to demonstrate allelopathic ef- seedlings, then the abundance of seedlings found on fects (such as Brown ; Yoder-Williams and Parker each substrate will be proportional to the abundance ), but do not replicate the thermal and moisture of that substrate. dynamics affecting seed germination in forest seed- Method. Seedbed abundance in an interior Doug- beds. Pots or trays containing experimental seedbeds, las-fir stand northeast of Williams Lake, B.C., was even when used in the field (though less so if buried measured by estimating percent cover along line in the ground), dry more rapidly along the edges, transects spaced at regular intervals (Table .a). All

section 8 silvicultural practices and tree seed biology 141  .(a) The relative abundance of seedbed substrates in an interior Douglas-fir stand (P. Burton and N. Daintith 1994, unpublished data)

Mineral Disturbed Undisturbed Rotten soil duff/moss duff/moss wood seedbed as % of total area 2.74 11.88 66.73 18.65

 .(b) Expected and observed seedling association with four forest floor substrates in an interior Douglas-fir stand

Total Chi- Mineral Disturbed Undisturbed Rotten observed square soil duff/moss duff/moss wood seedlings valuea

Exp Ob Exp Ob Exp Ob Exp Ob Subalpine fir 1.2056 0 5.2272 2 29.3612 22 8.2060 20 44 21.99 Interior spruce 0.5206 0 2.2572 1 12.6787 5 3.5435 13 19 31.11 Douglas-fir 3.7264 0 16.1568 1 90.7528 42 25.3640 93 136 224.49

Exp = expected number of seedlings (null hypothesis); Ob = observed number of seedlings (survey data). a See chi-square calculations below.

Calculations to determine the goodness-of-fit for different seedling and seedbed associations Subalpine fir: Chi-square = ∑ (observed - expected) / expected =(-.) / . + (-.) / . + (-.) / . + (-.) / . = . + . + . + . = . (exceeds the critical value .)

Interior spruce: Chi-square = ∑ (observed - expected) / expected =(-.) / . + (-.) / . + (-.) / . + (-.) / . = . + . + . + . = . (exceeds the critical value .)

Douglas-fir: Chi-square = ∑ (observed - expected) / expected =(-.) / . + (-.) / . + (-.) / . + (-.) /. = . + . + . + . = . (exceeds the critical value .)

142 field studies of seed biology the seedlings encountered in separate regeneration Comparisons of expected and observed seedling survey plots were classified according to the seedbed and seedbed associations indicate that seedlings of all in which they were found (observed values, Table .b). three species were found more frequently on rotten The expected value in each cell (seedbed/species wood, and that Douglas-fir seedlings did not estab- category) is derived from the percentage of the seed- lish well on duff/moss substrates. It is not known bed area multiplied by the total number of seedlings whether Douglas-fir seeds were unable to germinate of the species encountered (e.g., .% mineral soil on moss/duff substrates, or whether the seedlings ×  subalpine fir seedlings = .). emerged, but did not survive. Chi-square values are calculated separately for each species based upon observed and expected values, Cautions on use of the chi-square statistic: as shown below. Values are calculated for each seed- The use of the chi-square test statistic is conditional ling and seedbed association, then summed to create upon achieving expected values greater than .. An a chi-square test statistic for the species. expected value greater than . must be obtained for If the chi-square test statistic for a species exceeds the test statistic to be chi-square distributed (Lesper- the critical value (determined from published tables ance ). In this example, all of the expected values of the chi-square distribution), then seedbeds—in for mineral substrates were less than ., as were the general—have a significant effect on seedling estab- expected values for interior spruce on disturbed duff/ lishment. In addition, if one value of the sum exceeds moss and rotten wood. the critical value, then that individual value is If this situation occurs, there are several alterna- significantly different. tives to employ: Null hypothesis. In Table .a, the null hypothesis . Increase the sample size. To calculate the sample of random association of seedlings and seedbeds is size required, divide the expected value needed rejected for α = . and degrees of freedom =  (.) by the percentage of the least abundant (number of seedbed categories, minus one). substrate. In this example, mineral soil represents .% of the total seedbed area. Thus, the mini- Results: mum number of seedlings required for each . The calculated chi-square test statistic exceeded species would be . ÷ . = . seedlings. the critical value (.) for each species, indicating . Combine the data in different columns. Observa- that the observed seedling/seedbed associations tions for mineral soil could be combined with the were non-random. observations for disturbed duff/moss or rotten . A comparison of chi-square test statistics for dif- wood. In this case, combining data is probably ferent seedbeds shows that values contributed by not a viable option because mineral soil is very rotten wood exceeded the critical value (.) for different from the other substrates. all three species: subalpine fir (.), interior . Rather than assume the chi-square distribution, spruce (.), Douglas-fir (.). use a random procedure to determine the empiri- . In addition, for Douglas-fir, the calculated chi- cal distribution. Refer to Manly () for further square test statistic exceeded the critical value information on this topic. (.) for disturbed duff/moss (.) and for undisturbed duff/moss (.). Therefore, the Inferring substrate suitability from a one-time lack of seedling establishment on those seedbeds survey (as in the example above) may be adequate could not be attributed merely to chance. for some purposes, but understanding the actual constraints to natural regeneration requires establish- Conclusions: ing controlled treatment plots and evaluating tree Calculated chi-square test statistics for all three tree seedling emergence and survival over time. In this species confirmed that different seedbeds within a way, the effects of seed rain, seed predation, seed partially cut interior Douglas-fir stand significantly germination, and germinant survival may be affected seedling establishment. evaluated separately.

section 8 silvicultural practices and tree seed biology 143 For example, seeds may germinate in a wide range Because young seedlings usually require some of microsites, but may fail to survive as a result of protection during the first growing season, the drought conditions over the summer (Potts ; interactions between site preparation and shade Burton ). Better-than-average survival is often treatments are often evaluated. For example, Alexan- noted in cohorts of seedlings that germinate earlier, der () found that germination and survival of rather than later, in the spring (Zasada et al. ). Engelmann spruce in Colorado was poorer on sites Low seedling densities may not be due to the seed- that were left unscarified and/or unshaded. Cain bed, but rather to the limited availability of seeds, () noted that seedbed preparation resulted in the seed-shedding behaviour of associated vegetation, better survival of understorey loblolly (Pinus taeda) or local activity and habitat preferences of seed and shortleaf pine (Pinus echinata); however, the predators. Conversely, high numbers of seedlings in chemical removal of hardwoods in the canopy (with a particular microsite may be due to the capture of or without seedbed scarification) was even more seeds drifting on a crusted snow surface, to microsites important than seedbed treatments in promoting of exposed mineral soil, or to unusually abundant pine survival. soil water during the growing season (Matlack ). The Engelmann Spruce–Subalpine Fir (essf) If the factors (and their interactions) promoting biogeoclimatic zone is one of the most extensive for- good regeneration are not understood, site est zones in British Columbia, but it is also one the preparation methods cannot be successfully applied province’s most severe climates for forest growth. To to other locations. determine the best conditions in this area for the natural regeneration of subalpine fir and Engelmann . Combined Studies spruce, germination plots received a number of seed- ing and silvicultural treatments: screefed and seeded Studies of seed germination and seedling establish- (ds), screefed and not seeded (dn), undisturbed and ment can be combined with seed rain monitoring to seeded (us), or undisturbed and not seeded (un) select the optimal width for patch cuts and strip cuts (Jull et al. ). Disturbed forest floor, created either for natural regeneration (see Noble and Ronco ; by screefing or logging disturbance, dramatically im- McDonald and Abbott ). By coupling seed rain proved the germination of both spruce and subalpine with seedling survival, estimates can be made of the fir seeds (Figure .). Direct seeding of the plots with seed-to-seedling ratios required to establish a single undisturbed forest floor only slightly improved the seedling that survives to a given age (e.g.,  years) total number of germinants relative to unseeded (see Alexander ; Walker et al. ). plots. Very small numbers of germinants were ob- Seed-to-seedling estimates help us understand served in clearcut areas when additional seeds were the dynamics of major factors influencing successful not supplied, even though  (the year in which reforestation of a site. Even with good seed supplies the study was conducted) was a year of relatively and high emergence, seedling survival can differ high seed production in the surrounding stands. significantly among sites and seedbeds, in different These results indicate that natural seed supplies years, and between clearcut and forest conditions. cannot be relied on for the reforestation of clearcuts For example, in the first growing season, heat and in this area. drought accounted for % of red alder seedling mortality in clearcuts compared to only % of red . Summary alder mortality in forests (Haeussler et al. ). Later other factors became more important. Dur- Seeds, by virtue of their small size, respond to the ing the first winter, soil erosion, frost heaving, and environmental conditions prevailing within a freezing together caused over % of mortality in relatively small microsite. Much of the research and clearcuts; during the second growing season, crush- documentation of seed germination ecology under ing under litter or vegetation (%) was the primary natural conditions thus involves the classification, mortality factor. modification, or monitoring of microsites and the

144 field studies of seed biology behaviour of seeds and seedlings within them. evaluated by a single factor isolated from other envi- Farmer () provides a useful summary of forest ronmental or site variables. Even though canopy and microsites as regeneration niches, and how these seedbed influences are, in themselves, complex meta- microsites might be studied and manipulated. factors, careful consideration must also be given to a Even the simplest field investigations of seedbed range of other influences, including local climate, the and canopy effects (whether natural or manipulated) silvics of different tree species, the microsite attributes constitute a challenging exercise in ecosystem ecology. of vegetation and soil, and many of the other factors The potential of a site to support natural regeneration that comprise the physical and biological matrix or successful regeneration by direct seeding cannot be upon which successful natural regeneration depends.

a)

b) Number of germinants per hectare (in thousands)

 . Number of (a) subalpine fir and (b) Engelmann spruce germinants per hectare within three silvicultural treat- ments at the Lucille Mountain Project, Prince George Forest Region, British Columbia (Jull et al. 1996). Results are shown for treatments illustrated in Figure 8.2a, b, and e. DS = screefed and seeded, DN = screefed and not seeded, US = undisturbed and seeded, UN = undisturbed and not seeded.

section 8 silvicultural practices and tree seed biology 145 APPENDIX A Tree Species Occurring in British Columbia

Gymnosperms Scientific name/authority Common name

Abies amabilis (Dougl. ex Loud.) Forbes amabilis fir Abies grandis (Dougl. ex D.Don in Lamb.) Lindl. grand fir Abies lasiocarpa (Hook.) Nutt. subalpine fir Chamaecyparis nootkatensis (D.Don in Lamb.) Spach yellow-cedar Juniperus scopulorum Sarg. Rocky Mountain juniper Larix laricina (Du Roi) K.Koch tamarack Larix lyallii Parl. in DC. subalpine larch Larix occidentalis Nutt. western larch Picea engelmannii (Parry ex Engelm.) Engelmann spruce Picea glauca (Moench) Voss white spruce Picea mariana (P.Mill.) B.S.P. black spruce Picea sitchensis (Bong.) Carr. Sitka spruce Pinus albicaulis Engelm. whitebark pine Pinus banksiana Lamb. jack pine Pinus contorta Dougl. ex Loud. var. contorta shore pine Pinus contorta Dougl. ex Loud. var. latifolia Engelm. lodgepole pine Pinus flexilis James limber pine Pinus monticola Dougl. ex D.Don in Lamb. western white pine Pinus ponderosa Dougl. P. & C. Lawson ponderosa pine Pseudotsuga menziesii (Mirb.) Franco Rocky Mountain (interior) Douglas-fir var. glauca (Beissn.) Franco Pseudotsuga menziesii (Mirb.) Franco var. menziesii coastal Douglas-fir Taxus brevifolia Nutt. Pacific yew Thuja plicata Donn ex D.Don in Lamb. western redcedar Tsuga heterophylla (Raf.) Sarg. western hemlock Tsuga mertensiana (Bong.) Carr. mountain hemlock

147 APPENDIX A Continued

Angiosperms

Scientific name/authority Common name

Acer macrophyllum Pursh bigleaf maple Alnus rubra Bong. red alder Arbutus menziesii Pursh arbutus Betula papyrifera Marsh. paper birch Betula papyrifera var. neoalaskana (Sarg.) Raup. Alaska paper birch Cornus nuttallii Aud. ex T. & G. Pacific dogwood Fraxinus latifolia Benth. Oregon ash Malus fusca (Raf.) Schneid. Pacific crab apple Populus balsamifera L. ssp. balsamifera balsam poplar Populus balsamifera L. ssp. trichocarpa black cottonwood (T. & G.) Brayshaw Populus tremuloides Michx. trembling aspen Prunus emarginata (Dougl.) Walp. bitter cherry Prunus pensylvanica L. pin cherry Quercus garryana Dougl. Garry oak Rhamnus purshiana DC. cascara Salix amygdaloides Anderss. peach-leaf willow Salix bebbiana Sarg. Bebb’s willow Salix discolor Muhlenb. pussy willow Salix exigua Nutt. sandbar willow Salix lucida Muhl. ssp. lasiandra (Benth.) E. Murray Pacific willow Salix scouleriana Barratt ex Hook. Scouler’s willow

Standard species names and codes for British Columbia can be found in both  . and  . files at the B.C. Ministry of Forests Research Branch FTP site (...) (anonymous login) in the directory /pub/ provspp. They are regularly revised and updated.

148 field studies of seed biology APPENDIX B Conversion Factors

Imperial units SI equivalents Approximate conversion factors for light

Length Daylight, full sun*

 chain =  feet = . m (exactly), or  W m-2 = . cal cm-2 min-1 ≅ , lux a  or  m nylon tape of this  (– nm) is:  µmol photons m-2 s-1  foot = . m (exactly) ≅  W m-2 = . cal cm-2 min-1 = % of total.  inch = . cm (exactly) ∴  W m-2 (total) ≅ . µmol photons m-2 s-1 ()  mile = . km  yard = . m (exactly) Blue sky light*

Area  W m-2 = . cal cm-2 min-1 ≅  lux of this  is:  µmol photons m-2 s-1  acre = . hectare ≅  W m-2 = . cal cm-2 min-1 = % of total.  square foot = . m2 ∴  W m-2 (total) ≅ . µmol photons m-2 s-1 ()  square inch = . cm2 (exactly)  square mile = . km2 *Data from Coombs et al. ().  square yard = . m2

Mass

 ounce = . g  pound = . g  ton (, lb.) = . t

Volume or Capacity (dry measure)

 US bushel = . cu. in. = approx. . L  UK bushel (liq & dry) = approx. . L =  imp gal  US peck = (¼ US bushel) = . L  UK peck =  gals. or = . L  imp qts.  imp gal = . L (exactly)  U.S. gal = . L . US bushels =  L or  hectolitre

149 150 field studies of seed biology APPENDIX C Resources for Tree Seed Studies

Cone and Seed Analysis Companies and Computer Programs Suppliers The computer programs mentioned in the text are For a current list of cone and seed analysis familiar to the authors, but this does not imply companies and suppliers, please refer to Portlock endorsement or that they are the only programs (compiler, ). available for the task. Further information about each program is available from the contacts and references provided below. Internet Resources Sit (a) lists the code of a  program for Solar noon estimates computing tree shadow lengths for different http://www.crhnwscr.noaa.gov/grr/sunlat.htm times of day and year.

B.C. Ministry of Forests Internet resources  homepage: http://www.for.gov.bc.ca/ Dr. Charles Canham, Institute of Ecosystem Studies, Box R, Millbrook ny - usa Glossary of terms: http://www.for.gov.bc.ca/pab/ Reference: Canham () publctns/glossary/glossary.htm Publication catalogue: http://www.for.gov.bc.ca/hfd/ + (Professional Geostatistics for the PC, Version pubs/search/index.htm . (). Gamma Design Software, P.O. Box , Plainwell mi Forest Practices Code homepage: http://  usa www.for.gov.bc.ca/tasb/legregs/fpc/fpc.htm Current species lists: Res. Br.  site (...),  in directory /pub/provspp. The Tropenbos Foundation, P.O. Box ,  AE Wageningen, The Netherlands Research Branch  site: address of the Cowichan Reference: ter Steege () server is ... The directory will depend on your enquiry.  (Statistical Analysis System) Nursery and Seed Operations Branch Homepage  Institute Inc., Box , Cary nc - usa http://www.for.gov.bc.ca/nursery/branch.htm SiteTools Software  homepage (for estimating site series from species and height) http://www.for.gov.bc.ca/nursery/headqtrs/spar.htm B.C. Ministry of Forests, Research Branch, P.O. Box , Stn. Prov. Govt., Victoria, bc vw c - (radiometer) homepage http://www.licor.com  Dr. Robin Chazdon, Department of Ecology and Evolutionary Biology, University of Connecticut, Box U-, Storrs ct - usa Reference: Chazdon and Field ()

151 APPENDIX C Continued

Computer Programs (continued) Internet: spar homepage at http:// www.for.gov.bc.ca/nursery/headqtrs/spar.htm  Mr. W. Rick Smith, Research Forester, USDA Forest Biogeoclimatic Ecosystem Classification System Service, Southern Forest Experiment Station,  The biogeoclimatic ecosystem classification () Loyola Ave., New Orleans la  usa is a hierarchical land classification system used in Reference: Smith and Somers () British Columbia that delineates ecological units based on vegetation, soils, and climate.  inform- / ation for specific regions in British Columbia can be SPSS Inc.,  North Michigan Avenue, Chicago il found in the following publications: – usa Forest region References  Cariboo Steen et al. []  is a computer data entry and reporting tool Kamloops Lloyd et al. () for describing site data (soil, mensuration, vegeta-  tion), and is based on the FS forms available from Nelson Braumandl and Curran ( ) B.C. Ministry of Forests Sales. The program is Prince George DeLong (a) available from the B.C. Ministry of Forests Research DeLong (b) Branch  site (address: ...) in directory / Delong et al. () pub/venus. For further information, contact the Delong et al. () Ecology Data Analyst (Greg Britton): MacKinnon et al. () Meidinger et al. () B.C. Ministry of Forests, Research Branch, P.O. Box  , Stn. Prov. Govt., Victoria, bc vw c Prince Rupert Banner et al. ( ) Vancouver Green and Klinka ()  Other Resources The climate summary database is not yet available on the Internet. For information, contact -  David Spittlehouse, Research Branch, B.C. Ministry of Forests, P.O. Box , Stn. Prov. Govt., Victoria, LI-COR Inc.,  Superior St., P.O. Box  bc vw c Lincoln ne , usa Telephone --- (U.S. and Canada) Forest Practices Code Guidebooks or --; fax: -- Information about the B.C. Forest Practices Code and email: [email protected] a list of current guidebooks is available on the Forest Practices Code homepage. Guidebooks can be or- () Seedling Planning and Registry System dered through the Guidebook page or by telephone,  is an on-line registry, intended for use by B.C. fax, or mail from the address below. Ministry of Forests staff, licensee, and nursery staff whose job responsibilities require it. The registry Forest Practices Code homepage: http:// facilitates entering Seedling Requests, managing the www.for.gov.bc.ca/tasb/legregs/fpc/fpc.htm Tree Seed Register for seedlots and the Cutting Forest Practices Code Guidebooks, Public Affairs Registry for cutting lots, and monitoring Seedling Branch, B.C. Ministry of Forests, P.O. Box  Stn. and other Cone and Seed Service Requests. Services Prov. Govt., Victoria, bc vw c also include electronic access for all Ministry and Telephone: --- or -- non-Ministry clients and data entry of seedling fax: -- request and seedlot provenance information at the forest district level.

152 field studies of seed biology GLOSSARY

Felix que potuit rerum cognoscere causes. —Happy he who can understand the causes of things. (Virgil)

abscission The separation of an appendage (petiole, anemometer An instrument for measuring wind fruit stalk, etc.) as a result of the programmed death speed, which may give direct or recorded readings. of a specialized zone of cells (the abscission layer) found at the base of the appendage. angiosperms Flowering plants, distinguished from gymnosperms by having the ovules enclosed within achene A dry, indehiscent (non-opening) one- the ovary; after fertilization the ovary becomes a fruit, seeded fruit (e.g., fruit of Betula). enclosing one or more seeds. Compare gymnosperms. accuracy The closeness of a set of estimates to the aril Exterior covering or appendage that develops true population parameter, considered together with after fertilization as an outgrowth from the point of how closely they are grouped together (their preci- attachment of the ovule (e.g., fleshy fruit of yew sion). Compare precision. containing a single seed). acorn The one-seeded fruit of oaks; consists of a artificial regeneration Establishing a new forest by cup-like base and the nut (e.g., fruit of Quercus planting seedlings or by direct seeding. Compare garryana). natural regeneration. adjusted coefficient of determination See coefficient aspect The direction toward which a slope faces, of determination. expressed in degrees azimuth (clockwise from north), or categorized according to  (n, s, e, or w), , or  allometric Refers to the study and measurement of the compass points. growth of part of an organism relative to the whole. auger A tool used to bore into wood or soil to retrieve analysis of covariance () A statistical tool a cylindrical sample or core. that combines both  and regression. The treat- ment means of the dependent variable are adjusted autocorrelation The correlation between a point in by using a covariate which controls error and in- a set and other points within the same set. creases precision. See , regression, precision. berry A pulpy fruit developed from a single pistil analysis of variance () A statistical tool used and containing one or more immersed seeds, but no to analyze differences observed in the means of true stone (e.g., fruit of Arbutus menziesii). treated samples, to determine whether the differences in the means are due to the treatment or to random biogeoclimatic ecosystem classification () A variation in the population. hierarchical land classification system used in British

glossary 153 Columbia that delineates ecological units based on capsule A dry, many-seeded fruit composed of two vegetation, soils, and climate. or more fused carpels that split at maturity to release their seeds (e.g., fruit of Alnus, Betula, Populus). biogeoclimatic site series within the  system all sites capable of producing the same mature or categorical variable See variable. climax plant communities within a biogeoclimatic subzone or variant. Site series are described by the catkin In gymnosperms, a male strobilus which site and soil conditions as well as the vegetation produces pollen. In angiosperms, a spike-like inflo- community. rescence, usually pendulous, of unisexual flowers (either staminate or pistillate) (e.g., Alnus, Betula, biogeoclimatic subzone geographic areas influenced Populus, Salix). by one regional climate. Subzones are divided into variants and site series. central tendency A measure of the “middle” of a distribution. Common measures of central tendency biogeoclimatic variant subzones are sometimes are mean (the average), the median (the middle value further divided into areas called variants which re- of an ordered set), and the mode (the value with flect variations in climate (e.g., drier, wetter, snowier, highest frequency). warmer, or colder) within the subzone. chi-square test A statistical test for analyzing cat- biogeoclimatic zone within the  system, general- egorical variables measured for two or more ized units representing extensive areas of broad, populations. See variable - categorical. homogeneous macroclimates. Zones are divided into subzones. chord An aeronautics term: an imaginary straight line between the leading and trailing edges of an airfoil. biological diversity (biodiversity) The diversity of plants, animals, and other living organisms in all chromosome The genetic material of organisms; their forms and levels of organization, including composed of  and proteins. genes, species, ecosystems, and the evolutionary and functional processes that link them. clearcut (n. or adj.) An area of forest land from which all trees have been harvested. clear-cut (v.) Bonferroni technique A statistical method for mak- A timber harvesting method and an even-aged silvi- ing several non-independent pairwise comparisons, cultural system in which all trees (typically > m tall) usually performed after . are removed to maximize the recovery of fibre and to provide growing space for the next crop. bract In gymnosperms, a modified leaf that extends underneath a scale in a female cone. closed canopy Describes a stand in which the crowns of the main level of trees forming the canopy breast height age The number of annual growth are touching and intermingled so that light cannot rings measured on a tree at breast height, . m above reach the forest floor directly. See canopy. high side ground level. See also dbh. codominant In stands with a closed canopy, those trees canopy () The cover of branches and foliage formed whose crowns form the general level of the canopy by tree crowns. () The branches and foliage of any and receive full light from above, but comparatively vegetation. little from the sides. In young stands, those trees with above-average height growth. See canopy, crown class. canopy bank All seeds retained in cones or fruits on the tree, as opposed to seeds being retained in the coefficient of determination (r2) A statistic that soil. Compare soil seed bank. assesses how clearly a regression model describes the

154 field studies of seed biology relationship between the dependent and independent crown The live branches and foliage of a tree. variables. Adjusted r2 is the coefficient of determina- tion adjusted by the model degrees of freedom, and is crown class A group of trees in a forest having crowns more appropriate than r2 for comparing several mod- of similar development and occupying a similar posi- els using the same data. tion in the canopy. See canopy, dominant, codominant. coefficient of variation () A measure of variation cutting test A method to determine seed maturity; relative to the mean; the ratio of standard deviation the seed is bisected longitudinally and the morpho- to the mean. logical development of the embryo and the storage tissue are assessed. cohort A group of organisms of more or less the same age (e.g., all seedlings that germinated in the datalogger A portable, rugged simple computer, month of May). typically used in the field to automatically record data from environmental sensors over a period of cone The dry multiple fruit of conifers. A female cone time. The data can then be transferred to a computer consists of a central axis supporting scales which bear and returned to the lab for analysis. naked seeds. A male cone consists of a central axis supporting spirally arranged microsporophylls bear- dbh Diameter at breast height; a standard forestry ing pollen sacs that contain pollen grains. Syn. measurement used to indicate stem diameter . m strobilus. See conelet, microsporophyll. above ground level. conelet In gymnosperms, the immature stages of detection limit The resolution or finest distinction development of a female flower following pollination. that can be measured with a particular instrument or See cone, female flower. methodology. confidence interval A range of possible values above dioecious (Literally two houses). Describes plants in and below an estimate of some population param- which the male (staminate) and female (pistillate) eter, expressing the likelihood (e.g., %) that the flowers are borne on different plants. Compare true value lies between the bounds of that range. The monoecious. confidence level is the probability that a confidence interval will enclose the true value of the parameter; direct count A method for determining the number  – confidence level = level of significance. Compare and species of seeds found in a soil seed bank by level of significance. separating seeds from the soil, then counting and identifying them directly. Compare sample germina- continuous (of data or a variable). See variable. tion. See elutriation. coppice A silvicultural system that takes advantage direct seeding The practice of sowing seeds in or on of the tendency of some trees to produce many the soil, rather than planting seedlings to reforest a shoots when the main stem is removed and the root harvested area. See artificial regeneration. system is left intact. discrete See variable. cotyledon The first leaf produced by the embryo of a seed plant. In conifers, cotyledons appear needle-like. dispersal Movement of individuals away from a source, as in the spread of seeds away from a parent plant. cover The vertical projection of the crown or stem of a plant onto the ground surface; usually expressed dispersal curve The frequency distribution of dis- as a percentage of the total ground area being persed seed versus the distance that seeds are found considered. from the seed source.

glossary 155 dispersion The spatial arrangement of objects, often even-aged Describes a forest, stand, or forest type in described as random, clumped, or regular. which relatively small age differences (– years) exist between individual trees which could be consid- dominant Trees with crowns extending above the ered members of a single cohort. Compare uneven-aged. general level of the canopy and receiving full light from above and partly from the side; taller than the excised embryo test: A quick test for evaluating the average trees in the stand and with well-developed growth potential of an embryo that has been crowns. See canopy, crown class, codominant. removed from the seed. dormancy Physical or physiological condition of a exclosure A cage placed around a field plot to viable seed that prevents germination even in the exclude predators of seeds or seedlings, or other presence of otherwise favourable germination animal activity. conditions. experimental unit. The smallest collection of the drupe Fleshy indehiscent fruit, usually one-seeded, experimental material to which one level of a factor containing a seed enclosed in a hard, bony endocarp or some combination of factor levels is applied. (pericarp), (e.g., fruit of Cornus, Prunus). Syn. stone fruit. factor Some influence that is thought to cause a response (e.g., soil moisture or soil type may affect elutriation The process of separating soil and parti- germination rate). Often used as a synonym for cles from seeds. See root elutriator. “treatment.” A factor may be either fixed or random. The levels of a fixed factor (e.g., soil moisture) are embryo The rudimentary plant within the seed; that chosen by the experimenter, and replication of the part of a seed that develops from the union of the egg experiment would involve those same factor levels. cell and sperm cell, which after germination becomes The levels of a random factor (e.g., soil type) are cho- the young plant. sen in a random manner from the population of all possible levels, and replication of the experiment emergence () Protrusion of the radicle through the would (possibly) involve a new random set of levels. seed coat, or () under nursery or field conditions, protrusion of the hypocotyl and cotyledon above the female flowers () The female strobili of conifers soil surface. before and during pollination. () The flowers of angiosperms that contain female structures (ovary emittance The radiant flux emitted per unit area of a and style), but not male structures. See cone, conelet, surface. Compare irradiance. strobilus. empty seed A seed that does not contain all the tis- fertilization Penetration of a pollen tube into the sues essential for germination. Compare filled seed. ovule; the male sperm nucleus is discharged into the ovule to unite with the egg nucleus. endosperm Nutritive tissue (N) of an angiosperm seed, which surrounds and nourishes the embryo. filled seed A seed that contains both storage tissue Compare megagametophyte. and an embryo, as opposed to being empty or par- tially empty. Compare empty seed. epicotyl That portion of the seedling stem above the cotyledons. fixed factor See factor. epigeal Seed germination in which there is consider- flora The plant life characteristic of a particular able elongation of the hypocotyl so that the cotyledons geographic area. are raised above the surface of the ground to form the first green leaves of the plant. Compare hypogeal. frugivore (adj. frugivorous): An animal that eats fruit.

156 field studies of seed biology gamma radiation High-energy electromagnetic ra- system designed to regenerate an uneven-aged stand diation emitted by excited atomic nuclei passing to a by removing trees in small groups. See silvicultural lower excitation state; a useful tag for retrieving seeds. system, uneven-aged. See radioactive. growing degree-days () A cumulative sum of gap The space left in the canopy when one or more the degrees of temperature above a threshold (gener- trees die or are removed. See canopy. ally °C) counted on each day that the daily mean temperature exceeds that threshold. genotype The hereditary constitution of an indi- vidual organism, which may or may not be expressed gymnosperms Conifers and their allies; distin- as observable features. Compare phenotype. guished from angiosperms by having unprotected ovules (not enclosed in a fruit). Compare geostatistics A branch of applied statistics that angiosperms. focuses on the detection, modelling, and estimation of spatial patterns. half-face The cut surface of one side of a cone that has been bisected longitudinally. germinant A young seedling, just after emergence from the seed, but before full establishment as an hybrid The offspring produced by crossing indi- independent plant. viduals of different species or unrelated genetic lines. Usually refers to crossing of two true-breeding indi- germination Resumption of active growth in the viduals (homozygous) with different forms of a trait embryo, which results in emergence of the embryo (e.g., green or yellow seeds); the offspring are hetero- from the seed and development of the embryo into zygous hybrids. an independent plant. hydration (of seeds) Uptake of water by seed tissues. germination pecentage An expression of how many seeds germinated as a percentage of the total number hypocotyl Part of the axis of an embryo or stem of a of seeds sown; = number of seeds germinated ÷ seedling between the cotyledons and the radicle; usu- number of seeds sown × . ally identifiable as the region between the root collar and the base of the cotyledons. germination rate (R) The number of days it takes for % of the total number of sown seeds to germinate. hypogeal Seed germination in which the cotyledons remain below the ground. Compare epigeal. germination speed (R') The number of days it takes for % of the germinating seeds to germinate. in situ Literally, in place; to describe experiments con- ducted in the field or in their natural environment germination value () An expression that com- (in vivo), as opposed to in the laboratory (in vitro). bines the speed and completeness of germination into a single number;  = peak value () × mean independent variable See variable. daily germination ().  = maximum quotient obtained by dividing the number of accumulated insect-species complex A group of different insect daily germination by the corresponding number of species that feed on a single tree species. days.  = total germination divided by the number of days in the test. Compare germination integument The outer cell layer or layers that sur- rate, germination speed. round the ovule and give rise to the seed coat. global radiation See solar radiation. irradiance The electromagnetic radiant energy received per unit area of a plane surface. Compare group selection system A harvesting and silvicultural emittance.

glossary 157 isopleth A line joining points of equal value; for meristem Undifferentiated tissue that is capable of example, a contour map consists of isopleths of el- undergoing cell division; located in root and shoot evation. tips where growth in length occurs in axillary buds of male and female cones, or in the secondary meristem level of significance A statistical term expressing the tissue (cambium) where growth in girth occurs. probability that an apparently significant difference is not real but simply due to chance; the level is pre-set metafactor A complex factor or a set of independent for an experiment, typically at % or %. variables which are tightly associated, and hence of- ten treated as a single factor. See factor. LFH layers Litter, fermentation, and humus layers of the soil profile, consisting of the surface organic lay- microclimate The small-scale climates of hill and ers (forest floor or duff in forest soils). hollow, field and forest; the physical environment of plant communities, insects, fish, and wildlife; may life table A tabulation of mortality and survivorship differ significantly from the general climate of the of a population; static, time-specific, or vertical life region. See microsite. tables are based on a cross-section of a population at a given time; dynamic, cohort, or horizontal life micropyle A minute opening into an ovule of an tables are based on a cohort of organisms followed angiosperm plant through which the pollen grain nor- throughout life. mally passes to reach the egg cell; usually closed in the mature seed to form a superficial scar. See ovule. linear regression See regression. microsite The specific spot or local habitat occupied longwave radiation Electromagnetic radiation by an organism; the environmental conditions sensed with wavelength .– µm; also known as thermal by an individual organism. radiation. microsporophyll. The spore-producing structure of male flowers () The male strobili of conifers that plants; in angiosperms, the stamen. See male flowers. produce pollen. () The flowers of angiosperms that contain no female structures, only male (anthers). moisture content (mc) A measure of the amount of water present in a seed; can be expressed as a percent-  See multivariate analysis of variance. age of either fresh or dry weight. mast year A year of unusually good seed production; monoecious Literally, one house. Describes plants in generally applied to hardwoods. which both male (staminate) and female (pistillate) flowers are borne on the same plant. Compare dioecious. maturation Final stage of seed development charac- terized by dehydration of seed tissues and, usually, multistage sampling Experimental design where the induction of dormancy. samples are taken at successive layers of random- ization. For example, two-stage sampling involves mechanical site preparation The use of machines selection of a sample of secondary units from the to prepare a site for reforestation; may consist primary units; three-stage sampling involves of dragging anchor chains or shark-fin barrels, selection of a third level of samples from the disc trenching, plowing, or mounding. See secondary units; higher-order multistage designs site preparation. are also possible. megagametophyte The nutritive tissue (N) of gym- multivariate analysis of variance () An nosperm seeds, which surrounds and nourishes the extension of  with comparisons made on a embryo. Often incorrectly called endosperm. group of dependent variables.

158 field studies of seed biology natural regeneration The renewal of a forested area Pearson product-moment correlation coefficient by natural as opposed to human means (e.g., by seeds A statistic that characterizes the strength of the linear derived from adjacent stands, or by seeds transported relationship between two variables; its square is by wind, birds, or animals). equivalent to r2 for simple linear regression. nonlinear regression See regression. percentile (e.g., p-th percentile) A value such that when data are ordered from smallest to largest, at least nonparametric Statistical methods for analyzing p% of the observations are at or below this value. data when a “classical” or specified distribution is inappropriate. See normal distribution. Compare periodicity A cycle of time over which a phenomenon parametric. repeats itself. For example, many conifers do not produce collectable crops every year, but depending normal distribution A symmetrical, bell-shaped on the species, may only produce cones at – year distribution curve, with the mean, median, and mode intervals. coinciding (see central tendency for definitions). Such data fulfills the requirements for analysis using para- phenology Study of the relationship between sea- metric statistics. sonal climatic changes and periodic biological phenomena such as flowering, fruiting, leafing, normal probability plot A diagnostic plot used to growth flushing, and dormancy. check whether data (or residuals) are normally dis- tributed. The plot is a graph of the cumulative phenotype All characteristics—morphological, ana- distribution of the data (or residuals) on normal tomical, and physiological—of an organism, probability paper (paper scaled in such a way that the determined by the interaction between the genotype cumulative normal distribution plots as a straight and the environment. Compare genotype. line). See normal distribution. photoinhibition A reversible loss of photosynthetic nut Dry, indehiscent, one-seed fruit with a hard wall capacity that occurs when a plant is exposed to exces- (e.g., fruit of Quercus). sive sunlight. Compare sun scald. nutlet A small nut or nut-like fruit (e.g., fruit of photosynthetically active radiation () Elec- Betula). tromagnetic radiation in the wavelength band – nm, which contains the wavelengths orthodox A term to describe seeds that can be stored absorbed by plants for photosynthesis. for long periods at low moisture content (–%) and below zero temperatures; this group includes all Brit- phytochrome Protein-based plant pigment that ex- ish Columbia conifer seeds, and many hardwoods. ists in two interconvertible forms; it changes from Compare recalcitrant. one form to the other by absorption of red ( nm) or far-red ( nm) light. ovule A female organ surrounded by integument, within which an egg cell (N) is produced, and which, pollination Process by which pollen in transferred following fertilization, matures into a seed (N). from the male structure where it is produced to the female structure. In gymnosperms, pollen parametric Statistical methods for analyzing data from is dispersed by wind from male to female cones. a specified distribution. Compare nonparametric. In angiosperms, pollen may be wind dispersed, or carried by animals from the male to female flowers. partial cutting Logging practices in which only certain individuals are removed from a stand of pome Many-seeded fruit of the apple family consist- harvestable trees. Compare clearcutting. ing of an enlarged fleshy receptacle surrounding the

glossary 159 pericarp; in Malus the pericarp is papery and fleshy; radioactive Capable of giving off high-energy parti- in Crataegus it is hard and stony. cles or waves, such as the alpha, beta, and gamma rays produced by disintegration of atomic nuclei; can be post-dispersal To describe events occurring after used as a tag to identify an object, such as a seed, for dispersal of seeds from the mother tree. Compare later recovery. pre-dispersal. radioisotope (also radioactive isotope). An unstable power A statistical term, expressing the probability of isotope which, upon decay, can be detected with a detecting a difference when in fact there is a difference. scintillometer. precision The degree to which a set of estimates is random factor See factor. closely grouped together. Compare accuracy. randomization In experimental design, the assign- pre-dispersal To describe events occurring while the ment of treatments to the experimental material in seeds are still attached to the mother tree. Compare an unbiased manner. post-dispersal. recalcitrant A term to describe seeds that will not provenance (of seeds) The geographical area (latitude, germinate unless they are stored at relatively high longitude, and elevation) and environment to which moisture content (>%). Seeds of this type cannot the parent trees are native, and within which their be stored successfully for long periods (generally only genetic constitution has evolved through natural several weeks to several months). Compare orthodox. selection; their genetic origin. Compare seed source. recruitment The successful transition or graduation pseudoreplication When subsamples are statistically of an organism from one age class or stage to another treated as experimental units, when, in fact, they are (as from seed to seedling, or from seedling to sapling), not. Compare replication. See experimental unit. or the organisms that have made this transition. quantum An indivisible unit or discrete packet reforestation Actions taken to re-establish continu- of energy. ous tree cover after mature trees have been harvested or otherwise lost. quartiles The three values of a variable dividing a set of ordered data into quarters: the th, th, and th regression A statistical technique for modelling the percentiles. See percentile. relationship between two or more variables; linear regression assesses the relationship between variables r2 and adjusted r2 See coefficient of determination. that can be depicted by a straight line; nonlinear re- gression assesses the relationship between variables  R See germination rate. without assuming a linear relationship between them. See stepwise regression. R' See germination speed. remay Lightweight, nonwoven white fabric, often radiation or radiant energy Energy transferred used as a horticultural row cover. The material allows through space in the form of electromagnetic waves air, water, and –% of light to pass through. or photons. repeated measures analysis A special  tech- radicle Portion of the axis of an embryo from which nique applicable to data that consist of measurements the root develops. collected on the same experimental unit(s) at more

160 field studies of seed biology than one time. That is, experimental units measured secondary dispersal Movement of seeds (by wind, at different times cannot be treated as replicates be- water, or animals) after they have already fallen from cause they are not independent—in fact, they are the parent plant. likely autocorrelated. See autocorrelation. seed bank See canopy bank; soil seed bank. replication In experimental design, the independent application of treatment levels to an experimental seedbed In natural regeneration, the surface or unit. Compare pseudoreplication. substrate on which seeds falls; in nursery practice, a prepared area over which seeds are sown. residuals In statistical analysis, the difference be- tween the observed and predicted values after a seed coat The protective outer layer of a seed derived model has been fitted. from the integument of the ovule. root elutriator Tool designed to separate roots from seedlot A quantity of seeds of the same species, soil and which can be adapted to separate seeds from provenance, date of collection, and handling history, soil. which is identified by a single number. samara A dry, indehiscent, winged fruit, one-seeded seed orchard A plantation of specially selected trees as in Fraxinus and most conifers, or two-seeded as in that is managed for seed production, usually for the Acer. purpose of genetic improvement. sample germination A method for determining the seed production stand A forest stand reserved and number and species of seeds found in a soil seed managed as a source of seeds. bank by counting germinants that emerge from soil samples placed in a controlled environment. Com- seed rain The overall input of seeds on a surface per pare direct count. unit area per unit time.

Satterthwaite’s approximation A method of con- seed shadow The area of ground with a high structing approximate F-tests. density of dispersed seeds, centred on (or down- wind from) a seed-producing individual or stand. scarification () of seeds, the process of abrading a See dispersal. seed coat to make it more permeable to water, either by mechanical means or by brief exposure to hot wa- seed source The place (latitude, longitude, and ter or to strong acids such as sulphuric acid; () of elevation) from which seeds are collected; their physi- seedbeds, a method of seedbed preparation in which cal source. The source of a seed collection may not be patches of mineral soil are exposed through mechani- identical to its provenance. cal action. seed trap A device designed to collect all the seeds scintillometer An instrument for measuring gamma landing in a defined area. radiation emitted by a radioactive substance. Can be   used to locate seeds previously tagged with a seed tree ( ) A seed-bearing tree. ( ) An even- radioisotope. aged silvicultural system in which a forest stand is regenerated by removing all trees from an area screefing Removing weeds and small plants together except for a small number of seed-bearing trees left with most of their roots from the area immediately singly or in small groups. See silvicultural system; surrounding the planting hole. partial cutting.

glossary 161 selection system A method of harvesting and regen- solar radiation Electromagnetic energy from the sun erating a forest stand, which maintains an in the – nm wavelengths, of which the – uneven-aged structure by removing some trees in all  nm range reaches the earth’s surface. It has size classes, either singly or in small groups. See direct and diffuse components. The former is radia- silvicultural system; partial cutting. tion directly from the solar disc, and the latter radiation that has been scattered by the atmosphere. serotiny (adj. serotinous) A term to describe cones Syn. global radiation, shortwave radiation. that remain closed on the tree (often for several years after maturity); some require heat (fire) to disperse spatial statistics A branch of statistics for studying their seeds. the spatial variation of positional (x-y coordinate) data. Many of the methods stem from or overlap with shelterwood An even-aged silvicultural system de- geostatistics. signed to establish a new crop under the protection (overhead or side) of the old. See silvicultural system, Spearman’s rank order correlation A correlation partial cutting. technique that measures the relationship between two variables, based on the rank order of the data. It significance level See level of significance. assesses whether two variables have a strictly increas- ing or strictly decreasing relationship. silvicultural system A process whereby forests are tended, (thinning, pruning, etc.) harvested, and re- standard deviation A statistic that assesses the placed to produce a crop of timber and other forest spread or variability of data about the mean; the products. The particular system is typically named by square root of variance. the cutting method used for regeneration. stepwise regression A statistical procedure for sys- single-tree selection harvesting See selection system. tematically reducing the number of independent variables required to model the dependent variable. site index The measure of the relative productive capacity of a site for a particular crop or stand, gener- stocking A measure of the area occupied by trees, ally based on tree height at a given age. usually measured in terms of well-spaced trees per hectare, or basal area per hectare, relative to an opti- site preparation A treatment, either mechanical, fire, mum or desired level. chemical, or manual, to modify a site to provide fa- vourable conditions for natural or artificial stratification A dormancy-breaking treatment in regeneration of the desired tree species. which seeds are exposed to moist, cold (–°C) con- ditions for several weeks (or months, depending on site series See biogeoclimatic ecosystem classification. the species). Compare warm stratification. slope The angle of the ground relative to horizontal, stressing Attempts to induce tree seedling dormancy expressed in degrees or as a percentage of the run to or enhanced seed production through the application the rise. of some kind of physiological stress (e.g., drought) or mechanical stress (e.g., partial girdling). soil seed bank All viable seeds present on or under the surface of the soil. strobile (pl. strobiles) Spiky pistillate inflorescence of angiosperms or the resulting fruit. Syn. female solar noon The time of day at which the sun is at its catkin. highest point. For a specific location and date the information is available from website http:// strobilus (pl. strobili) The male and female repro- www.crhnwscr.noaa.gov/grr/sunlat.htm ductive structures of gymnosperms. Syn. cone.

162 field studies of seed biology Student’s t-test See t-test. Type II error In statistical analysis, the error of not rejecting the null hypothesis (the hypothesis subsample Units within an experimental unit to be that the treatment has no effect) when in fact it is sampled for measurements. For example, if the ex- false; the probability of avoiding which is the power perimental unit is a tree, the seeds from that tree of the test. could be a subsample. See experimental unit. ultraviolet () radiation Radiation in the sunfleck A relatively small area of forest floor that waveband – nm. Since - (– nm) receives direct-beam solar radiation through the in- is filtered out by the atmosphere,  radiation terstices of overstorey foliage and branches in an received at the earth’s surface is in the – nm otherwise closed forest canopy. range. sun scald Damage to foliage and destruction of uneven-aged Describes a forest, stand, or forest chlorophyll incurred through exposure to high light type in which relatively large age differences (>– intensities when the plant is not acclimated to such  years) exist between individual trees within a conditions, also called photodamage. Compare stand; these age differences usually denote multiple photoinhibition. cohorts. Compare even-aged. t-distribution Distribution of the Student’s t-test variable An expression that can be assigned any of a statistic; similar in shape to a normal distribution; set of values. A variable can be independent (causal) useful for small samples. with levels set by the experimenter, or dependent (response) and responding to changes in the inde- t-test or Student’s t-test A statistical test that as- pendent variable. The terms discrete, continuous, sesses the differences between two groups by and categorical are used to describe data or a vari- comparing the means. able: discrete—having a distinct value, sometimes expressed in whole numbers (e.g., number of terminal velocity The maximum velocity of a falling filled seeds); as opposed to continuous—able object, determined by the force of gravity and the to take a continuum of values (e.g., percent shape of the object. germination, seed weight). Categorical describes information that has been grouped (e.g., age class, top height trees The largest dominant or colour, species). codominant trees of the same species that are healthy, undamaged, and unsuppressed. variance A statistic that measures the spread in the data; the square of standard deviation. transformation A mathematical procedure for con- verting data to a different scale using one or more viable Alive; with respect to seeds, capable of germi- mathematical functions (e.g., square root, sine, natu- nation and subsequent growth and development of ral log, exponential); often used to make the data the seedling. more appropriate for a statistical test. vigour The combination of properties which enables transpiration Release of water vapour from the seeds to germinate quickly under a wide range of aerial parts of a plant, primarily through the stomata. environmental conditions, and which endows germinants with the ability to establish quickly and Type I error In statistical analysis, the error of reject- resist disease. Seeds that perform well under a wide ing the null hypothesis (the hypothesis that the range of environmental conditions are termed high treatment has no effect) when it is in fact true; the vigour seeds and those that perform poorly are called probability is usually preset as the level of significance low vigour seeds. of the test.

glossary 163 warm stratification A dormancy-breaking treat- z-test (z-score) The z-test and the z-score are ment of seeds in which moist seeds are held at warm examples of Wald statistics. They are computed temperatures (usually –°C) for several weeks. by taking the estimated parameter, subtracting The warm incubation period is usually followed by from it the parameter value under the null an incubation period at –°C. See stratification. hypothesis, and then dividing this entire quan- tity by the approximated standard error of the wing loading A measure of the weight-to-area ratio estimated parameter. Under certain conditions, of an airborne or falling object; equal to its mass this statistic is asymptotically (i.e., large sample times gravitational acceleration divided by its sizes) distributed with a standard normal planform (projected, one-sided area). distribution.

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The researches of many commentators have already thrown much darkness on this subject, and it is probable that, if they continue, we shall soon know nothing at all about it. (Mark Twain)

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Zobel, D.B. . Seed production in forests of Chamaecyparis lawsoniana. Can. J. For. Res. :–.

186 field studies of seed biology INDEX

A B Abies mariesii banking, seed. See seed banks predicting seed production,  berries, collecting and processing,  Abies spp. bigleaf maple collecting, processing, storage,  collecting, processing, storage,  germination under snow,  pre-dispersal germination, ,  predicting seed production,  seed exclosures,  pre-dispersal germination,  seed traps,  seedbed,  seedbed,  stratification,  stratification,  abortion biogeoclimatic ecosystem classification, vi, , ,  insect attack,  biogeoclimatic zone, ,  self-incompatibility,  birch self-pollination,  collecting, processing, storage,  abscission, , , ,  predicting seed production,  accuracy, , , ,  seedbed,  administration of site,  birds allometric relationships,  as dispersers,  anemometer,  as pollinators,  angiosperms,  as predators, ,  animals exclosures for,  as dispersers,  exclusion of,  as pollinators,  patterns of dispersal,  as predators, ,  role in dormancy release,  exclosures for,  bitter cherry role in dormancy release, ,  collecting, processing, storage,  , , ,  black spruce in dispersal studies,  collecting, processing, storage,  in germination studies, ,  predicting seed production, , , , ,  in seed bank studies,  seedbed,  arbutus serotiny,  collecting, processing, storage,  blocking, , ,  artificial seeds randomized, , , ,  in dispersal studies,  two-factor randomized,  artificially introduced seeds,  Bonferroni technique, ,  ash breast height age,  collecting, processing, storage,  bud counts stratification,  predicting seed production using,  viability tests,  burial experiments aspect, , , , ,  in seed bank studies, ,  in site selection,  augers, soil,  C autogyroscopic seeds,  caches, , , , ,  collecting cones,  germination in,  mapping locations, 

index 187 canopy,  codominant trees,  and light levels, , ,  coefficient of determination,  and wind effects,  coefficient of variation,  closed,  collecting and processing seeds,  gaps, , ,  conifers,  canopy banks,  hardwoods,  canopy cover, measuring,  colour, seed,  canopy analyzer,  combined studies,  densiometer,  comparison studies leaf area index (),  in production studies,  line-intercept method,  seed bank studies,  moosehorn,  comparitive analysis photographic,  in dispersal studies,  point-intercept method,  comparitive studies spherical densiometer,  analysis of,  canopy manipulation, ,  computer programs indicators,  for geostatistical analysis,  light effects,  ,  moisture effects,  , ,  objectives,  ,  openings,  ,  partial removal,  ,  retention of,  ,  temperature effects,  cone and seed analysis cascara for conifers,  collecting, processing, storage,  for hardwoods,  case studies cone crop rating scales,  in seed production,  cone half-face, , , ,  categorical data,  confidence intervals, , , , , ,  categorical data analysis,  conifers catkins, , ,  collecting seeds,  collecting and processing,  extracting seeds,  chemical poisons, .  monitoring cones,  chi-square test,  reproductive cycle,  cautions,  reproductive structures,  in germination studies, ,  contingency table,  in predation studies,  continuous data,  in seedbed studies,  coppicing, ,  chitting,  coronet,  clearcut system, effects of,  cotyledon,  climate length, ,  and serotiny,  number,  effect on dispersal,  cotyledons effect on seed production,  and meristematic growth,  climate monitoring colour and viability,  macroclimate,  in epigeal germination,  microclimate,  in germination criteria,  site climate,  in hypogeal germination,  tree weather,  cutting test, ,  wind speed and direction, 

188 field studies of seed biology D gravity, ,  data snow, , ,  analyzing and interpreting,  water, , ,  categorical,  wind, , , , ,  coding,  dispersal patterns,  continuous,  animal-dispersed,  management,  secondary,  planning for collection,  wind-dispersed,  recording,  dispersal studies,  data analysis data analysis,  in dispersal studies,  experimental design,  in germination studies,  mapping resting spots,  in predation studies,  mechanistic modelling,  in production studies,  spatial analysis,  in seed bank studies,  dogwood data management,  collecting, processing, storage,  dataloggers,  gravity dispersal,  in environmental monitoring, ,  dominant trees, ,  in germination studies,  dormancy in plant temperature,  and seed bank studies,  in snowfall,  breaking procedures,  in soil temperature,  factors affecting,  in wind monitoring,  in fall-dispersed seeds,  daylength, .  in reproductive cycle,  densiometer,  of buds,  descriptive analysis release,  in dispersal studies,  role of animals in release, ,  desiccation,  role of light in release,  dewinging, , ,  role of mc in release,  dioecious, ,  variable,  direct counts dormancy-breaking procedures,  in seed bank studies, ,  clipping,  direct seeding, , , , ,  plant growth regulators,  diseases, seed, , , , ,  scarification,  dispersal stratification,  distance,  Douglas-fir mechanisms,  predicting seed production, ,  primary,  seedbed, ,  secondary,  stratification,  seed morphology,  drupes, collecting and processing,  seed quality,  Duncan’s multiple range test,  seed quantity,  Dunnett’s test,  temperature, effects on,  . See seed weight, dry timing of,  weather, effects on,  E dispersal agents,  ecosystem management,  animals,  efficiencies birds,  cone, seed, extraction, germination, 

index 189 elutriation,  field germination studies,  embryo development,  delimiting the site,  emergence, , , ,  excluding other seeds,  criteria,  excluding predators,  factors affecting,  experimental design,  speed and timing,  marking germinants,  Engelmann spruce preparing seeds,  predicting seed production,  using stratified seeds,  regeneration,  using unstratified seeds,  seedbed,  filled seeds environmental monitoring,  and pollen abundance, ,  designing a program,  and position in crown,  soil moisture,  determining, , , ,  soil temperature,  in cone and seed analysis,  solar radiation,  in cone half-face, ,  epigeal germination, ,  in germination percentage,  estimation studies per cone,  analysis of,  foliar analysis,  design of,  frugivores, ,  even-aged stand,  F-test, ,  excised embryo test,  . See seed weight, fresh exclosures, ,  choices,  G in field germination studies,  Garry oak in predation studies, ,  collecting, processing, storage,  excluding predators,  dormancy levels,  experimental design,  gravity dispersal,  dispersal studies,  recalcitrant seeds,  field germination studies,  seed exclosures,  germination studies,  seed traps,  multiple factors,  seedbed,  pseudoreplication,  Gaussian plume model,  randomization,  . See growing degree-days,  replication,  geostatistics,  seed bank studies,  germination single factor,  containers for,  split plot,  epigeal,  extracting seeds hypogeal,  conifers,  in seed bank studies,  hardwoods,  in water,  media,  F pre-dispersal, ,  Fagus sylvatica germination criteria,  stratification,  germination measures fanning mill,  germination percentage, , , , ,  field germination germination rate, , , , ,  in seed bank studies, ,  germination speed, ,  germination value, 

190 field studies of seed biology germination rate hydration. See also moisture content, seed and daylength,  and light response,  and dormancy release,  in stratification redry,  and paints,  in variable dormancy,  and seedling establishment,  of cones,  and stratification,  of seeds, , , , germination requirements hydrogen peroxide test,  light,  hygrothermograph,  moisture content,  hypogeal germination,  oxygen,  seedbed,  I soil conditions,  incubation,  temperature,  insects germination speed, ,  and other studies,  germination studies,  as predators, , , ,  data analysis,  chemical poisons,  experimental design,  damaged capsules,  field tests,  effect on viability,  light,  exclosures for,  germination tests marks on seeds,  cutting test,  seed damage,  excised embryo test,  species complexes,  hydrogen peroxide test,  isozymes in dispersal studies,  in field,  in laboratory,  J quality,  jack pine quick tests,  collecting, processing, storage,  respiration measures,  cone and seed size,  sampling methods for,  serotiny,  tetrazolium chloride test,  X-rays,  L germination value,  leaf area index (),  germination, field. See field germination  soil layers gibberellins. See plant growth regulators,  in seed bank studies,  Gompertz function,  life tables,  goodness of fit,  in predation studies,  gravimetric sampling,  in production studies,  gravity dispersal, , ,  light growing degree-days (), ,  and canopy,  canopy manipulation,  H in germination studies,  hardwoods monitoring,  collecting and processing seeds,  quality,  description of seeds,  requirements for germination,  recalcitrant seeds, , , ,  lodgepole pine reproductive structures,  cone and seed size,  ,  predicting seed production,  hormones. See plant growth regulators serotiny, ,  humidity, monitoring air, 

index 191 M N maceration,  nonparametric analysis, , ,  mammals nuts, collecting and processing,  as dispersers,  as pollinators,  O as predators,  orthodox. See storage exclosures for,  oxygen exclusion of,  in dormancy release,  ,  levels, in soil,  in germination studies,  requirements for germination,  in seed bank studies,  use, in germination studies,  marking germinants,  in field germination studies,  P in seed bank studies,  Pacific crab apple marking plots,  collecting, processing, storage,  marking seeds viability tests,  by predators,  Pacific yew in predation studies,  collecting, processing, storage, ,  with paint,  painting seeds,  with radioisotopes, ,   (photosynthetically active radiation), ,  maturity parametric analysis,  cone dimensions,  Pearson product-moment correlation, ,  embryo development,  periodicity fruit and seed,  in conifers,  seed colour,  in seed production,  seed dimensions,  of seed rain,  mc. See moisture content, seed permanent file measurement, types,  creating,  megagametophyte, ,  site and plot location,  meristem,  . See plant growth regulators metafactors, ,  photoinhibition,  microtopography,  phytochrome, , ,  modelling Picea abies in dispersal studies,  predicting seed production,  in production studies, ,  Pinus resinosa moisture content (mc), seed,  predicting seed production,  definition and formula,  Pinus sylvestris in germination studies,  predicting seed production,  moisture, soil plane-winged seeds,  and canopy manipulation,  planning field studies,  monitoring,  designing study,  Monte Carlo method,  experimental design,  moosehorn,  marking and installing plots,  mortality obtaining approvals,  of cones, ,  permanent file,  of germinants, , ,  selecting factors,  of seeds, ,  selecting study site,  mountain hemlock site administration,  seedbed,  plant growth regulators (), , 

192 field studies of seed biology plant temperature predicting seed production monitoring,  using aspect and slope,  planting spots,  using bud counts,  plots using cone crop scales,  describing,  using crown characteristics,  marking and installing,  using weather variables,  size and shape,  pregermination temporary or permanent,  for seedling production,  pollen,  pre-dispersal, ,  and wind,  primary dispersal,  identification,  production studies,  monitoring,  case studies,  sampling for, ,  data analysis,  traps,  experimental design,  pomes, collecting and processing,  plot description,  ponderosa pine sample size determination,  cone and seed size,  Prunus sativum dispersal,  stratification,  predicting seed production,  pseudoreplication, , , ,  seedbed,  purity tests,  poplar pyranometer,  collecting, processing, storage,  cone and seed size,  Q seedbed,  quantum sensor,  wind dispersal, ,  quick tests,  power,  power analysis,  R precipitation, monitoring,  radiant flux density,  precision, ,  radiation frosts,  predation studies,  radicle, , , ,  data analysis,  length,  distributing seeds,  radiometer,  excluding predators,  radiotagging, ,  marking and recovering seeds,  rainfall, monitoring,  on artificially introduced seeds, ,  randomization, , ,  on seeds and cones,  in germination tests,  post-dispersal,  in seed bank studies,  pre-dispersal, , ,  recalcitrant. See storage quantifying predation,  red alder timing of monitoring,  collecting, processing, storage,  using unmarked/unmarked seeds,  predicting seed production,  predators regeneration,  and painted seeds,  seed traps,  birds,  seedbed,  exclusion devices,  regression,  insects,  regression analysis,  mammals,  in dispersal studies,  marks on seeds,  in germination studies,  in seed bank studies, 

index 193 replication, , , , , , , ,  field germination, ,  in field germination,  inventories,  in germination studies,  marking germinants,  in seed bank studies,  sample germination, ,  in seed sampling, ,  seed separation,  of seed traps,  soil samples,  over time,  vertical distribution, ,  reproductive structures, ,  seed banks. See also canopy banking resin bond rupture,  seed coat,  respiration, seed, ,  seed collections, permits,  respiration test,  seed counts Rocky Mountain juniper in predation studies, ,  collecting, processing, storage, ,  in seed bank studies,  seedbed,  seed dispersal. See dispersal rodents seed predation. See predation exclusion, , ,  seed production. See production root elutriator,  seed separation in seed bank studies,  S seed traps safety,  as exclosures,  samaras, , ,  design,  collecting and processing,  designs,  sample germination for area source,  in seed bank studies, ,  for point source,  sampling number, distribution,  coding,  total trap area,  determining sample size,  using water,  in production studies,  seed tree system,  over time, , ,  seed weight, ,  planning for collection,  dry weight (), ,  randomized,  fresh weight (), ,  sampling methods seedbeds,  for germination tests,  comparison study,  modified halving method,  in field germination studies,  random cups method,  manipulation,  spoon method,  preferences,  , ,  seedbed studies,  Satterthwaite’s approximation,  site preparation,  scarification,  serotiny, , ,  scattergrams,  estimating cone volume,  Scheffé’s method,  extraction,  scintillometers,  weathering of cones in,  secondary dispersal,  shelterwood system,  patterns,  significance level, ,  security at site,  silvicultural practices seed bank studies,  principles,  burial experiments, ,  systems,  data analysis,  site direct counts, ,  administration,  experimental design,  description, 

194 field studies of seed biology site index,  subalpine larch site preparation, v, , , ,  cone and seed size,  Sitka spruce predicting seed production,  seedbed,  stratification,  slope, ,  sun scalding,  in site selection,  sunflecks,  snow, dispersal across, , ,  ,  snowfall, monitoring,  ,  soil augers,  T conditions for germination,  tagging. See marking  layers,  tamarack, seedbed,  moisture monitoring,   (time-domain reflectometry),  monitoring variables,  temperature nutrient levels,  canopy manipulation,  oxygen in,  effect on dispersal,  oxygen in flooded,  monitoring air,  pH levels,  monitoring plant,  seedbed preferences,  requirements for germination,  temperature monitoring,  soil,  soil samples tensiometer,  in seed bank studies,  terminal velocity, , , ,  pooling,  tetrazolium chloride () test,  processing in seed bank studies,  thermocouples,  soil seed banks. See seed banks thermoperiod,  solar noon, determining,  Thuja occidentalis solar radiation. See also light cone and seed size,  ,  predicting seed production,   (Seedling Planning and Registry),  top height tree,  spatial analysis traps. See seed traps, pollen traps in dispersal studies,  traps, pollen,  Spearman’s rank order correlation,  true firs. See Abies spp. spherical densiometer,  t-test,  sterilization, of seeds,  tumbling,  storage. See also collecting and processing Type II error,  in soil,  of orthodox seeds, ,  U of recalcitrant seeds, , ,  uneven-aged stands,  stratification unmarked seeds combined,  in predation studies,  conifers,  unstratified seeds conventional, ,  in field germination studies,  hardwoods,  redry,  V variable dormancy,  ,  strobile (strobiles), , , ,  viability tests strobilus (strobili), ,  cotyledon colour,  Student-Newman-Keuls () test,  cutting test,  subalpine fir excised embryo,  seedbed, ,  tetrazolium chloride,  X-rays, 

index 195 W X water. See also moisture content, humidity X-rays as dispersal agent,  in germination studies,   regulations, ,  of plant structures,  weather. See climate to determine causes of loss,  weathering, of serotinous cones,  to determine filled seeds,  weight. See seed weight to measure seeds,  western hemlock using Polaroid film,  pre-dispersal germination,  seedbed, ,  Y western larch yellow-cedar cone and seed size,  stratification,  predicting seed production,  western redcedar Z seedbed,  z-test stratification, ,  in cone crop estimation,  western white pine in predation studies,  predicting seed production, ,  seedbed,  stratification,  white spruce cone and seed size, ,  predicting seed production, , ,  seedbed,  wind dispersal,  whitebark pine predicting seed production,  Wilcoxon tests,  willow collecting, processing, storage,  cone and seed size,  germination,  seed traps,  seedbed,  wind dispersal, ,  wind and abscission, ,  dispersal,  dispersal patterns,  dispersal, by species,  dispersal, modelling,  dispersal, traps for, ,  effect of canopy manipulation,  monitoring,  winged seeds dewinging, , ,  dispersal, 

196 field studies of seed biology