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Fall 2009 An assessment of stress in Acer saccharum as a possible response to climate change Martha Carlson University of New Hampshire, Durham
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This Thesis is brought to you for free and open access by the Student Scholarship at University of New Hampshire Scholars' Repository. It has been accepted for inclusion in Master's Theses and Capstones by an authorized administrator of University of New Hampshire Scholars' Repository. For more information, please contact [email protected]. AN ASSESSMENT OF STRESS IN ACER SACCHARUM AS A POSSIBLE RESPONSE TO CLIMATE CHANGE
BY
MARTHA CARLSON BA, MOUNT HOLYOKE COLLEGE, 1968
THESIS
Submitted to the University of New Hampshire in Partial Fullfillment of the Requirements for the degree of
Master of Science in Natural Resources: Environmental Conservation
September 2009 UMI Number: 1472053
Copyright 2009 by Carlson, Martha
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ProQuest LLC 789 East Eisenhower Parkway P.O. Box 1346 Ann Arbor, Ml 48106-1346 ALL RIGHTS RESERVED ©2009 Martha Carlson This thesis has been examined and approved.
Thesis Director, Barrett N. Rock Professor of Natural Resources and Earth, Oceans and Space
Jdimes^E. Pollard, Professor of Plant Biologyj(Physiology)
Kevin T. Smith, Affiliate Professor, USDA Forest Service For my husband, Rudy Carlson
iv ACKNOWLEDGEMENTS
I wish to thank my graduate committee members: Dr. Barry Rock,
Dr. Jim Pollard and Dr. Kevin Smith. You set high standards. You taught the fine details of academic research. You answered the smallest question.
You enthusiastically supported this research.
This project had support from my family, Rudy Carlson, David and
Rosamond Carlson, Anne Raver, the late Kathleen Raver. They know how much their gift of learning means to me. Many old friends encouraged me to pursue this project. Thank you.
I also wish to thank the landowners and sugar producers who assisted with this study, particularly Jackie Hunter Rollins, Lori and David
Burrows, Janet Bickford and Charlie Johnston, and members of the New
Hampshire Maple Producers Association.
Many people at the University of New Hampshire, members of Dr.
Rock's graduate research team, staff members in both Natural Resources and Complex Systems Research Center, members of other departments and students assisted me in this research. I especially appreciate the help and friendship offered by Mike Gagnon, Erica Lingren, Danielle Haddad, and Brett Clark.
I also wish to thank the University of New Hampshire which welcomed a non-traditional student to all the wonders of a fine university.
v TABLE OF CONTENTS
DEDICATION iv
ACKNOWLEDGEMENTS v
LIST OF TABLES viii
LIST OF FIGURES x
ABSTRACT xiii
CHAPTER PAGE
I. INTRODUCTION AND LITERATURE REVIEW 1
Climate Change 1
Approach 11
Hypotheses and Objectives 16
II. METHODS AND SITE DATA 17
10 Study Plots 19
Plot Surveys 22
III. SPECTRAL STUDIES 27
Abstract 27
Introduction 28
Methods 32
Results 38
Discussion 43
Conclusion 55
IV. LEAF AND BUD ANATOMY 56 vi Abstract 56
Introduction 57
Methods 61
Results 63
Discussion 67
Conclusion 75
V. TRENDS IN SUGAR CONTENT AND WOOD GROWTH 77
Abstract 77
Introduction 79
Methods 83
Results 86
Discussion 91
Conclusion 102
VI. CONCLUSION 104
Hypotheses 104
Objectives 106
Recommendations for further study 108
LIST OF REFERENCES 109
APPENDICES 119
A. Tables 120
B. Figures 155
C. IRB #4136 202
vii LIST OF TABLES
2.1 Precipitation and temperature, 2008 121
2.2 Collection dates of buds and leaves 122
2.3 Plot data for 10 sites 123
2.4 Soils found on 10 plots 124
2.5 Plot soils and high quality site indicators 125
2.6 Individual tree measurements 126
2.7 Basal area by plot 127
3.1 Response-to-stress definitions 128
3.2 Ranking of Munsell Color Chart values 129
3.3 Days of season and growing days 130
3.4 Measured values for all trees 131
3.5 Indices values for Tree 826 136
3.6 Indices values for Tree 822 137
3.7 Correlations of all spectral indices measures 138
3.8 Comparison of grow days 139
3.9 Percent of season by index and grow days 140
3.10 Summary of analysis of means and grow days 141
3.11 Stress levels by each measure, 1-2, all trees 142
3.12 Stress levels by each measure, 102, all plots 143
4.1. Fall bud health defined 144
4.2. VIRIS scans suggesting SEM of pollen 145
viii 4.3 Spring bud size and growth 146
4.4 Fall bud quality 147
4.5 Leaf area of all trees 148
4.6 Comparison of spring bud and fall bud quality 149
4.7 Stress levels by all test 150
5.1 Decadal temperature change in NH 151
5.2 Sap sugar content, 1900 to 2000 152
5.3 Average decadal growth of one tree in each plot 153
5.4 Estimated age of trees by wood counts 154
IX LIST OF FIGURES
2.1 Map of study area 156
2.2 Range View Farm, Plots 1 and 2 157
2.3 Googin Farm, Plots 3 and 4 158
2.4 Hunter Farm, Plots 5 and 6 159
2.5 Bickford Farm, Plots 7 and 8 160
2.6 Burrows Farm, Plots 9 and 10 161
2.7 Sample plot 162
3.1 Sample VIRIS scan 163
3.2 Calculation of first derivative for a REIP 164
3.2 Sample from Munsell Color Chart with Leaf from Tree 837 165
3.4 VIRIS scan of Trees 832 and 833, April and May 166
3.5 May 30 VIRIS of Trees 835, 836, 837 167
3.6 May 30 VIRIS of Trees 820, 821 and 822 168
3.7 Seasonal VIRIS scan and photos, Tree 826 169
3.8 Seasonal VIRIS scan and photos, Tree 822 170
3.9 Chart of REIP and NDVI by plot and sample date 171
3.10 Chart of NIR3/1 and TM5/4 by plot and sample date 172
3.11 ANOVA, all REIPs by plot and time series of REIPs 173
3.12 ANOVA of TM 5/4 by plot 174
3.13 Comparison of two time series analyses of TM 5/4 grow days 175
3.14 ANOVA of NIR 3/1 by plot and time series of NIR 3/1 176 3.15 ANOVA of Munsell by plot and time series of Munsell 177
3.16 Correlations of all indices' values 178
4.1 Progress of bud development, spring 2008 179
4.2 Bud quality defined in photographs 180
4.3 ANOVA of good and excellent buds 181
4.4 ANOVA of excellent buds 182
4.5 Comparison of anthers 183
4.6 Comparison of pollen 184
4.7 Chart of changing leaf area by tree 185
4.8 ANOVA of leaf area by test 186
4.9 ANOVA of leaf area by plot 187
4.10 Correlations of leaf area with spectral measures 188
4.11 Scanning electron microscope (SEM) photos of bud 189
4.12 Arrangement of leaves from one bud 190
5.1 NH temperature change, 1835-2006 191
5.2 Hunter Farm sap to syrup ratio 192
5.3 Four New England states'sap to syrup ratio 193
5.4 Comparison of sap to syrup ratio trends and temperature trend 194
5.5 Hunter Farm first run days 195
5.6 Hunter Farm last run days 196
5.7 ANOVA of wood growth 197
5.8 Radial views of new wood and bark, Tree 816 and Tree 834 198
xi 5.9 Cambial zone. Tree 816 199
5.10 Cambial zone, Tree 834 200
5.11 Cells of cambial zone, Tree 834 201
xii ABSTRACT
AN ASSESSMENT OF STRESS IN ACER SACCHARUM AS A POSSIBLE RESPONSE TO CLIMATE CHANGE
by
Martha Carlson
University of New Hampshire, September 2009
Climate change is projected to extirpate Acer saccharum throughout its range in the United States. The current investigation evaluates the potential of spectral indices of foliar reflectance, measures of leaf area and bud quality, and historic trends in sap sugar and wood increments for detecting stress in sugar maple.
Thirty trees were examined in 10 plots on 5 sugar bushes in or near the Bearcamp Valley, New Hampshire, over the course of the 2008 growing season. The study found water stress in 100% of trees; reduced chlorophyll content in 60%; early abscission of leaves in 80%; reduced growing season in 70%; and poor fall foliage color in 80%. Drought in early summer and unusually heavy rain in mid-summer are likely factors. Despite stress, 73% of the trees produced high quality buds. Differences in stand management, site conditions, and prior stresses account for differences in response to stress.
XIII Chapter I
Introduction and Literature Review
Climate Change
Five global climate models (GCMs), recently released by the United
Nations' Intergovernmental Panel on Climate Change(IPCC), agree that annual minimum temperatures over the next century are likely to rise 3.2 to 5.4°C. (IPCC, 2007; UCS, 2007). Such warming and concomitant projected changes in precipitation regimes other climatologic factors predict the decline of the sugar maple, Acer sacchorum, in all but a few
Vermont and Wisconsin counties in the lower 48 United States (Iverson and
Prasad, 1998, Iverson and Prasad, 2002).
Even if reducing carbon in the atmosphere is addressed aggressively with public policies, temperatures in New England are likely to rise 1-2°C. (UCS, 2007; Hayhoe et a/., 2007), enough to change Boston's
"normal" temperature to that of Richmond, Virginia (NERA, 2001). Rising temperature will bring more frequent high day and night temperatures in spring and summer, earlier,snow melt and spring flowering, and an array of altered interactions within the ecosystem (IPCC, 2007, Hayhoe et a/.,
2007).
1 Climate change will mean more than increasing temperatures.
Precipitation patterns may change with more intense rainfall or snowfall, longer droughts between them, and more frequent heat waves (NERA,
2001; Malmsheimer ef a/., 2008). Northern latitudes may receive 20 to 40% more precipitation but the IPCC warns that the benefits of this may be outweighed by more intense storms and earlier snow melt (IPCC, 2007).
These unusual events may exacerbate pest infestations, change herbivory, fire and other stressors (Malmsheimer ef a/., 2008). In snow- dominated latitudes, which include New Hampshire, snow packs may melt earlier, causing drought in early spring, just when young maples are leafing out (Barnett, ef a/., 2005). 'There is high confidence that the ability of many ecosystems to adapt naturally will be exceeded this century"(IPCC, 2007).
Some researchers have hypothesized that more CO2 in the atmosphere will increase timber growth, photosynthetic rates and biomass production (Wullschleger ef a/., 2002). But these studies acknowledge that stress caused by increased acid deposition, higher temperatures, and changes in weather patterns may counteract any benefits that CO2 may afford (Norby ef a/., 1999; Wullschleger, ef a/., 2002; Nabuurs ef a/., 2002).
Other researchers have considered secondary factors which, as consequences of increasing temperature and changing weather patterns, may limit plant growth. For example, deposition of acidic
2 pollutants increases leaching of heavy metals in soil, blocking nutrient absorption by plant roots and interrupting normal growth (Shortle and
Smith, 1988). Alterations in the nitrogen cycle by human use of fertilizers and by increased emissions of nitrogen-based greenhouse gases also cause losses of calcium, potassium and other nutrients essential for plant growth (Vitousek, ef a/., 1997). Similarly, small water deficits can formation of chlorophylls (Bourque and Naylor, 1971). As precipitation patterns change, the availability of water will be a critical factor in how plants respond to a myriad of climate stressors (Wullschleger, ef a/., 2002).
Changes in species, biomes and regeneration rates may also have impacts on forest productivity and health that have not been studied
(Nabuurs ef a/., 2002). Climate change will influence so many factors in temperate zone growing conditions, new models of plant response are needed (Hanninen, 1995; Fisher and Mustard, 2007)
Economic Value of Acer saccharum
Sugar maples currently grow on a range of 12.5 million hectares (31 million acres) of land from Nova Scotia west to Manitoba, south through
New England and the Midwest to the southern Appalachians and west to
Minnesota and Iowa (Godman ef a/, 1990). While early records of the
North American forest show its greatest abundance was on the high carbonate till soils of northern Vermont, maples occur on a wide range of soil fertility and pH (Horsley et a/., 2002).
3 A warmer climate, with mild winters and long hot summers, would
be inhospitable to the sugar maple, quaking aspen, paper birch, northern
white cedar and many of the plants and animals that share this
ecosystem (Iverson and Prasad, 1998; NERA, 2001; Barnett et a/., 2005). The
loss of the sugar maple would have major ramifications for New England's
economy.
The greatest economic value of the maple is in the tree's foliage.
Each fall, after the first frost, sugar maple leaves turn golden yellow, orange and red. Travelers from around the world visit New England and
Canada to see this unique phenomenon. The foliage season accounts for as much as one-quarter of the tourist industry income, $2.5 billion annually in New Hampshire (Norris, 1999), equaling the total value of the agricultural industry in the State (NH Dept. of Agriculture, 2007).
Another economically important use of sugar maple is production of maple syrup. Canadian and American producers harvest 7.37 million gallons of syrup annually (Smith et a/., 2007). Maple syrup production in
2007 in the United States was 1.64 million gallons, with 85,000 gallons made in New Hampshire (Keough, 2008). In 2007, the harvest in New England was valued at $24.5 million. U.S. syrup production increased 30% in 2008, in part because of the excellent season, according to sugar producers reporting to USDA, "the best in 31 years," "the best in memory," (Keough,
2008). Aggressive marketing of syrup globally and governmental subsidies
4 of the maple industry in Canada have pushed the price of syrup to $60 per gallon or more for all Grade A syrup and account for the recent increase in sugar production (Bruce Bascom, 2008).
The golden color and high luster of polished maple "whitewood," makes it highly prized for veneer. Currently, in Carroll County, New
Hampshire, veneer grade sugar maple is valued at anywhere from $800 to
$3,000 per 1000 board feet (Rancourt, 2007). Most of the maple cut in
Carroll County, NH, is of pallet grade, sold for $60 to $80/1000 bf, not much higher than the price of pulpwood. A few good logs, and the upper log from a veneer log grade tree might be good for saw logs, valued at $400 to $500/1000 bf (Rancourt, 2007) Because of its low market value, maple is frequently used for firewood.
Beyond economics, the sugar maple is an iconic symbol of New
England's landscape and history. The sweet tree has been in New England for 8,000 years (Mann, 2002; Levine, 2007), a source of sugar since native
Americans first settled in the maple forest. Maple sugar, boiled into blocks, provided early white settlers with a cash crop, a preservative and sweetener that was more than a treat, particularly during war times. The author's family weathered World War II rationing of sugar by making their own maple sugar, just as many other New England families did. Images of sugar makers on snowshoes, yarns told around roaring sap pans, and the
5 fiery colors of maples in October connect New Englanders to a tree and a landscape that is difficult to imagine losing.
The sugar maple, grown in monocultures, offers a readily available laboratory for examining how its decline may be detected and understood.
Identifying Stress in Maples
Maple health is tied to many factors besides those accompanying climate change. The signal of distress that the maple may communicate as climate change imposes on New England is "buried" and has yet to be
"teased out" (Perkins, 2007, personal communication; Spencer et a/., 2001).
The maple is described as a "resilient" tree, one that can take the stress of annual 5/8-inch wide and 2-inch deep sap cores, two to four per tree without long term ill effects (Smith, 2009). Maples quickly seal off the sugarmaker's tap holes and continue growing, often for 300 to 400 years.
Even when trees had lost as much as half their crowns in the 1998 New
England ice storm, growth as measured in increment cores, continued at the same rate as in undamaged trees (Smith and Shortle, 2003).
Over the past 40 years, extensive studies of maples have investigated the decline of sugar maple throughout its range in the northeastern and midwestern United States and eastern Canada (Horsley et ol., 2002; Wood et a/., 2009). The North American Maple Decline
Project, now called the North American Maple Project, has fostered
6 numerous studies of individual stressors and complex analyses of combined stressors such as drought, pest defoliation, logging (Spencer et al., 2001; Horsley et a/.. 2002). Acid rain has been blamed for acidifying soils in maple forests, releasing metals such as aluminum and binding vital cat ions such as calcium (Ca) and magnesium (Mg) (Liu et al., 1997;
Vogelmann and Rock, 1988, Anatomy of red spruce). In both field and manipulative greenhouse studies of maples, trees with low foliar Ca, Mg, or manganese (Mn) show chlorosis in the leaves, accumulations of starch in the leaves, and abnormalities in the thylakoid membranes of chloroplasts (McQuattie et al., 1999).
Drought has played a key role in dieback and mortality in
Wisconsin, Massachusetts, Pennsylvania and Quebec (Horsley et al, 2002).
Maples in decline store more starch in their roots, causing not only foliar chlorosis but reduced annual basal area growth (Liu and Tyree, 1997).
Other research has studied affects of defoliation by pests such as tent caterpillars, herbivory, and competition from other plants (Wood et al.,
2009). No definitive cause of decline has been found and tree health has rebounded in some areas when good growing conditions returned and there were no secondary stressors.
However, these studies clarify that any stressor, natural or anthropogenic, will reduce vigor and predispose sugar maples to greater decline when another stress factor affects the trees. In decline, trees may
7 die when exposed to even minor stressors such as secondary pathogens
or adverse climate conditions (Hartmann and Messier, 2008). If the stressor,
such as defoliation by insects, occurs in late May to mid-July, the
remaining season is usually not long enough for the tree to replenish starch
reserves for the dormant season (Vogelmann and Rock, 1988, Anatomy of
red spruce; Vogelmann et a/., 1993; Horsley et a/., 2002; Polak ef a/., 2006).
Tree tissues are altered or even killed directly by the stress or by the tree's
response reactions to stress (Vogelmann and Rock, 1988, Anatomy of red
spruce; Moss et a/., 1998). In his study of maple decline in Wisconsin,
Houston (1999) found that when drought was followed by defoliating
insects which were then followed by fungal infestation, trees were unable
to resist this final stress because of biochemical changes in tissues (Horsley etai, 2002).
Climate change has only recently been added to the mix of factors in studies of maple decline. Tests of 1-year-old maple seedlings in pots in growth chambers exposed to elevated CO2 and higher temperatures show 40 to 80% increases in photosynthesis, earlier leaf break and later senescence (Norby, et ol. 1999). In a recent study in Ontario, near the
most northern latitude of the sugar maple's range, researchers found some correlations between rising temperature and improved maple basal growth but little correlation with precipitation (Goldblum and Rigg, 2005).
Noting a variety of factors such as warm late winter temperatures, terrain,
8 soils, and precipitation as rain rather than snow, this study (Goldblum and
Rigg, 2005) found evidence that climate change might initially encourage maple growth in Ontario yet ultimately extirpate the species even at this latitude. Such studies are the first investigations of potential impacts of climate change and associated stressors on decline in sugar maples.
Trees respond to stress with measurable changes in foliar pigments, canopy density, leaf water content, and leaf size (Rock et a/. 1986, 1988;
Liu etal., 1997; Martin and Aber, 1997; Entcheva Campbell etal., 2004).
Chlorophylls and carotenoids in the leaf decrease when trees are stressed
(Entcheva Campbell et a/., 2004).
Several studies have confirmed that sugar maple responds to seasonal stressors with changes in photosynthetic activity, carbohydrate production, and chlorophyll formation (Bourque and Naylor, 1971; Norby et a/., 1999; Carter and Knapp, 2001; Pontius et a/., 2008J. These changes can be used as indicators of tree vitality(Ellsworth et ol., 1994; Wong et a/.,
2003).
The current study approaches the question of sugar maple response to climate change, from a broad, inductive perspective. When a problem is new, when its symptoms are obscure or unknown, this author has found that general observation, simple measures of many kinds, may detect bits of evidence which later lead to deductive experimentation. Inductive
9 thinking welcomes chance, a mix of variables, something which is elemental to climate change.
The author is interested in determining whether scientific study can be conducted on privately owned lands where a multitude of variables including site characteristics and management history may confuse findings. The author is also interested in testing the use of simple tools which citizen scientists might use effectively to collect data that contributes to valid research.
10 Approach
The present study examined 30 trees on 10 plots, two each on five privately owned sugarbushes in central New Hampshire. Basic measurements taken in each plot are described in Chapter II. Local weather records of 2008 are also presented in Chapter II.
This study examined three features in sugar maples for their potential as indicators of stress. The findings of each study are presented as Chapters III, IV and V:
1. Reflectance spectra of leaves
2. Anatomy of buds, pollen and leaves.
3. Historic records as seen in sap sugar content and wood increment cores.
The first two measures were made throughout the growing season so that any indications of stress might be correlated with particular stressors during the 2008 growing season. Buds and wood cores were measured after leaf drop to account for growth over the entire year.
Measurements of these features have been quantified to allow for statistical analysis and comparison of findings. Definitions of stress and details of measures are given in each chapter.
Spectral Analysis, Chapter III
This study measures leaf reflectance through the visible spectrum and shortwave infrared spectrum (400-2400nm) using the GER 2600 Visible
11 Infrared Intelligent Spectroradiometer (VIRIS) (Spencer, 2001). Over the
past two decades, three spectral indices derived from VIRIS data have
been determined to be useful for evaluation of different components of
foliage health. These indices build on measurements of reflectance in the
near infrared plateau, NIR. When plants are stressed, there is reduced
reflectance from the NIR (Rock et a/., 1986). Healthy leaf cells refract light from cell membranes to water molecules to particles in intercellular spaces. Stress-induced change may close leaf stomates, reduce chlorophyll and other cell components, limit water content, or damage cell membranes. Leafs with such conditions will refract less light, reducing reflectance in the NIR (Rockef a/., 1986).
The red edge inflection point (REIP) compares light reflectance from the NIR with light reflectance in the red band of visible light. The REIP has been found to accurately measure total chlorophyll levels in both hardwoods and softwoods and thus is considered a indicator of tree health(Rockef a/., 1988; Moss and Rock, 1991; Vogelmann et a/., 1993).
The TM5/4 is named for the spectral bands of the Landsat Thematic
Mapper satellite, an orbital remote sensing instrument. The ratio compares reflectance in band 5, one of 3 bands of infrared light which
Thematic Mapper senses, with band 4, the first shoulder of the NIR plateau. The TM5/4 index is of particular interest in this study because it measures water stress.
12 The NIR3/1 examines a ratio of reflectance from the far right shoulder of the NIR plateau with reflectance from the first and left shoulder of the NIR plateau. Studies of how this ratio changes through growing season have proven valuable in assessing the rate of growth in plants (Albrectova et a/., 2001)
This study also uses a fourth indicator of plant stress, the Munsell
Color Charts for Plant Tissues developed by S.A. Wilde and K. Voigt of the
Soils Department, University of Wisconsin. The Munsell Color Charts are a tool used primarily in the field to evaluate soil and plant relationships with regard to nutrient deficits (MacBeth, 1977).
Pollen, Leaf and Bud Anatomy, Chapter IV
The second portion of this study characterized general bud health and foliar size on the study trees. These are relatively simple measurements which can be made by sugar producers as well as students or other citizens.
This study calculated leaf area to compare differences among trees and to determine when a tree lost leaves, particularly larger outermost leaves that form in the six-leaf set of each maple bud
(Niinemets et a/., 2006). Stressed trees have been observed to have small leaves, misshapen leaves, early fall coloration and dieback of fine twigs in the upper canopy (Horsley et a/., 2002).
13 Buds were measured to compare length and viability. A stressed tree is likely to produce smaller, less viable buds, buds that will produce smaller, less viable leaves in the following season, creating a cycle of stress in the tree.
In addition to field measures of leaves and buds, pollen from two trees which flowered in 2008 was examined in the scanning electron microscope (SEM) to see if any differences were apparent.
Increment Cores and Sugar Content, Chapter V
Thirdly this study examines the historic record of sugar maple health and growth as recorded in syrup production records and in increment cores of wood. These data were compared with temperature records since 1970 to determine if there is a correlation can be seen between increasing temperature and changes in potential indicators of stress in sugar maple.
This portion of the study looked at a possible inverse correlation between sap sweetness and rising temperatures. Anecdotally, sugar producers talk about a reduction in sap sweetness in recent years. This study looked for sugar production records which document sap sweetness and sap to syrup ratios. Sugar production in the maple may be a simple indicator of stress associated with increasing temperature.
Wood increment may be another. Increment cores were extracted from the 30 trees. Declining maples have been shown to exhibit reduced
14 basal area increment, possibly due to reduced leaf photosynthesis and reduced storage of carbohydrates (Liu, ef a/., 1997). Incremental cores may be a valuable tool in understanding the affects of past stressors on tree vigor (Hartmann et a/., 2008).
Two cores were also examined in the SEM to compare marginal parenchyma in the cambial zone.
15 Hypotheses and Objectives
The hypotheses of this study are:
• Stress is detectable in the sugar maple with measurements
reflectance spectra, anatomical features, sugar content and
wood increments.
• Data documenting stress will identify possible causes of stress.
• Indicators of stress will describe how the maple responds to
stress.
Objectives of this study are:
• Identify tools which may be useful as measures of climate
change and its attendant stress factors.
• Assess whether some of these tools could be used by students
or citizen scientists in collaborative study of sugar maples and
climate change.
16 CHAPTER II
METHODS AND SITE DATA
In March 2008, 10 study plots were established on 5 sugarbushes in the Bearcamp Valley, New Hampshire, 43° North, 71° West, as shown in
Figure 2.1.
The Bearcamp Valley lies on the south face of the White Mountain
National Forest. It is bounded on the north by the Sandwich Range, on the west by the Squam Range, on the south by Red Hill, Squam Lake and Lake
Winnipesaukee, and on the east by the Ossipee Mountains (Figure 2.1).
The valley is heavily forested with fewer than 500 hectares of open land in the 25,900 hectares which comprise the township of Sandwich. Similar land use is found in surrounding towns. Maple sugar is recorded as a major product in the Town of Sandwich's earliest records. During the Civil
War and the decades following the war, Sandwich produced 75 tons of hard maple sugar annually (Beckman, et a/., 1995). A seed tree on the author's sugarbush was cored and aged at approximately 320 years of age, a sprout in 1690.
The Bearcamp Valley lies in the northern New England snow belt
(Barnett, ef. a/., 2005), receiving an average of 252.5 mm of snow annually
17 (Weinberg, 2009). Snowfall in the winter of 2007-2008 was 397.8 mm, the snowiest season in 35 years (Weinberg, 2009). Annual precipitation in the
Bearcamp Valley is 1258 mm. The average annual temperature in the
Bearcamp Valley is 7.7°C (See Table 2.1).
Soils are granitic with heavy glaciation of hillsides and mountain slopes and deep outwash terraces of glacial sand in the valley floor
(USDA, 1977).
18 10 Study Plots
The 5 sugarbushes include the author's own sugarbush and 4 neighboring sites where sugar maples are regularly tapped for maple sugar. These stands of maple have been managed for sugar production for two decades or more. Seven are monocultures which could be easily identified with Landsat TM data. The other three are a blend of maple and conifers. The four farms were chosen for their proximity to the author's home, allowing for travel time and collection of data. On each farm, two plots were selected to study different elevations, basal area, age class and management conditions.
Figures 2.2-2.6 indicate the location of each sugarbush on U.S.
Geological Survey quadrant maps. Note that Plots 5 and 6 on the Hunter farm lie in Tuftonboro, a site 10 miles south on the northeast slope of Lake
Winnipesaukee. This site was selected because the Hunter family has sugared for over 100 years. Jackie Hunter Rollins was the first sugar producer to assist with this study. Weather, soils and mountain runoff from the Ossipee Mountains make this site similar in many ways to those in the
Bearcamp Valley on the west side of the Ossipees.
On each sugarbush, 2 study areas were selected. The areas differed in aspect, slope, age of stand, and openness of canopy. On some plots, soils and availability of water also differ moderately. Due to the large size of sugar maple canopies and their spacing, 30 meter by 30
19 meter plots were not always large enough. Instead, plots were sized so that 3 trees could be selected within that community of site features. Each plot is at least 60 x 60 meter but a few exceed that size (Figure 2.7).
Trees were not randomly selected. Rather, trees were selected because they appeared to be typical of trees on that site and because they had branches low enough to allow for repeated sampling of leaves.
Trees were tagged with aluminum identification numbers.
It should be noted that tree numbers are not consecutive. A dozen trees were numbered and studied in 2007 on Range View Farm. Those trees were numbered 801-812. In 2008, six of those trees (801, 803, and 804 in Plot 1, and 808, 811, and 812 in Plot 2) were selected for continued study. Numbers then run consecutively, excepting a Tree 819, omitted by mistake.
Collection dates were established as shown in Table 2.2. Buds were visited in the first week of April and on April 22 to observe change before bud break, which occurred on April 30. Dates of leaf collections were based on readings from the literature about different phenologic stages in leaf growth and sugar production and mobilization from the leaves
(Olmstead, 1951; Wong ef a/., 2003; Richardson et a/., 2006 ) A collection was made on May 30, when leaves were expected to have reached nearly full size. Another collection was made on July 30 at the end of the main growth of stems and wood when leaves are in full summer foliage.
20 August 28 was selected as a key time in production of carbohydrates for storage and when leaves might begin to show signs of stress. Collections were made on September 15 and September 29 to monitor the presence of any early senescence of leaves. The beginning of fall coloration of foliage was expected on October 4.
21 Plot Surveys
Plot surveys were performed at each tree rather than in the center of the plots, as shown in Table 2.3.
Slope was measured with an Abnay level. Aspect, or azimuth, was measured with a compass. Elevation and latitude and longitude were measured with a Garmin etrex hand-held global positioning unit. These measures were checked against the U.S. Geological Survey map, Mt.
Chocorua and Winnipesaukee quadrangles, 1958.
Assessment of each plot reveals some differences. As shown on
Table 2.3, aspect and slope vary. Elevation ranges from 186.5 m above sea level at the Bickford farm to 299.6 m at the Burrows farm. Six plots are open pasture or field where each maple has broad space for canopy.
Four plots are in sugarbushes where thinning has been minimal and competition from pine and other species may limit maple health.
The plots vary also in available water. Flat plots at Bickfords (Plots 7 and 8, and Hunters (Plots 5 and 6) are frequently wet during rain or snowmelt. Steeper slopes, while expected to drain more quickly, might actually show flowing water longer with snowmelt in the spring freshet.
Slopes are steep on two of the sugarbush areas, Plot 3 at Googins and
Plot 10 at the Burrows Farm. All lie in a valley where snowmelt from the
Sandwich Range and Ossipee mountains is heavy throughout the spring, generally keeping streams and groundwater high well into June.
22 Soils were identified using soil maps and descriptions in the Soil
Survey of Carroll County, New Hampshire (USDA, 1977). Soils range from very fine Ondawa which lies over glacial outwash sands to Berkshire and
Beckett bouldery dry loams found on rock-strewn mountainsides (Table
2.4). All are moderately well-drained soils where woodland production is generally fair (USDA, 1977). Many of these soils are relatively shallow and lie over hardpans which are impermeable. Snowmelt and rainwater running in these soils move laterally, just where shallow maple roots lie, rather than downward. The exception is the Ondawa soil which lies in the floodplain of the Bearcamp River where the river and groundwater frequently flood the root area of this sugarbush (USDA, 1977).
Understory plants and trees were inventoried in June, 2008.
Wildflowers that were blooming on other sampling days from late April through late September were also noted. Regeneration was estimated by counting sprouts in a 1 meter square with 20+ being called "dense," 10-20 called "moderate", 0-10 called "thin," (Table 2.5).
In studies of calcium deficiency in sugarbushes, Proctor Maple
Research Center has identified several wildflowers, ferns and trees which commonly grow in sugar maple understory and which indicate good availability of calcium and other nutrients as well as the pH which maples prefer (Wilmot and Perkins, 2004; Heiligmann ef a/., 2006). This list includes such plants as blue cohosh [Caulophyllum thalictroides), and basswood,
23 (Tilia Americano). The Proctor guide for landowners also identifies trees such as American beech (Fogus grandifolia), paper birch (Betula papyrifera), and eastern hemlock [Tsuga canadensis) which may indicate poor quality sites, acidic soils and fewer nutrients than maples prefer.
Use of the Proctor information proved somewhat helpful. The list is incomplete as it misses wild flowers such as purple trillium (Tritium erectum), which also favors rich woods (Peterson and McKenny, 1968) or witch hazel
(Hamamelis virginiana), and red oak [Quercus rubra), trees commonly found in the maple forest. Many sites contained both favorable indicators such as blue cohosh or white ash and also plants considered indicators of poor sites, hemlock [Tsuga canadensis) or red maple (Acer rubrum), particularly. Even the measure of regeneration, perhaps the best signal of site quality, was offset in those plots which were browsed by cows (Plots 6,
7, 8, 10) or mowed for lawns (Plots 4 and 9).
Individual trees were measured in July at peak foliage. Tree diameter at breast height and tree height were measured using an English
Biltmore stick. Canopy density was measured using a silhouette recommended by the North American Sugar Maple Decline Project
(Millers ef a/, 1991). Age of trees was estimated by measuring the average number of tree rings per inch as compared with dbh (See Table 2.6).
Basal area on each site was calculated using a basal area prism at each tree in each plot. The number of measurable trees counted
24 surrounding each tagged tree were averaged, dividing by 3. This was double checked by a count of all trees over 10 cm within a 10-meter circle around each tree, again averaged for the three trees. This number is multiplied by 10 to calculate the estimated basal area index per acre.
Desirable stand density, as measured by a basal area index, varies not only by species but by the age of trees (Wenger, 1984). Maximum desirable basal area for sugar maple stands of varying age is recommended by Ohio State University Extension and The North American
Maple Syrup Council (Heiligmann et a/., 2006). The North American Maple
Svrup Producers Manual (Heiliamann et al., 2006) instructs sugarbush owners and sugar producers in every aspect of management, technology, production, sale and scientific research regarding sugar maples and the maple syrup process.
To use this guideline, trees surrounding the tagged trees, within the
10 meter circle, were measured for exact dbh. An average dbh for trees in each plot was calculated. This allowed use of the Heiligmann (2006) recommendations for basal area.
Table 2.7 compares site biomass and average dbh in each plot with the recommended residual biomass per acre. "Residual" defines the number of trees left on a site after a planned thinning of trees
(Heiligmann, 2006). The biomass measures and comparisons provide key information as to the density of trees in each stand. Plots 5 and 6 stand out
25 as having much denser growth than is recommended. Other stands such as 7, 8, 9 and 10 show very low basal area, allowing each tree room to develop a full canopy and to obtain sunlight, water and nutrients with little competition.
Weather data for the 2008 growing season were gathered from Rod
Weinberg, a Sandwich weather observer for the last 35 years (Weinberg,
2009). Weinberg's monthly reports for the Bearcamp Valley are shown in
Table 2.1.
Total precipitation for 2008 was 1686.6 mm with higher than average rainfall in late June, July, August and September. May, however, with rainfall of 2.79 mm, was the driest recorded in 35 years of local observations (Weinberg, 2009). From leaf out at the end of April, the region at little or no rain until June 20. The warmest day measured was
33.8°C. on June 10 on Diamond Ledge which may be slightly cooler than high temperatures on the valley floor (Weinberg, 2009). The coldest winter temperature measured in 2008 was -22.7°C.
Data was analyzed using the JMP 8.0 software to detect significant differences in measures between sites and in tree response over the course of the growing season. P values were tested for a confidence level of 95% or p = <0.05.
26 CHAPTER III
SPECTRAL STUDIES
Abstract
Four spectral indices (REIP, TM 5/4, NIR 3/1 and Munsell Color rankings) were used to assess stress in 30 mature sugar maple at 10 plots in central New Hampshire.
Over the course of the 2008 growing season, 100% of the maples showed water stress; 50% of the maples showed low REIP, an indication of reduced chlorophyll; 80% of the trees showed early senescence; 60% of the trees showed colorimetric evidence of reduced chlorophyll content.
These indices correlate with drought as the primary stressor of the trees during the 2008 growing season with unusually heavy rains as a possible secondary stressor. Analysis of the data indicates differences among the 10 plots in response to stress. This variation in stress response suggests that stand management and elevation are factors which may protect maples from severe damage during and after stress.
27 Introduction
Light, as reflected from leaves, has been studied since 1873 (Carter and Knapp, 2001). By 1929, these studies noted that stressed leaves reflected light differently than non-stressed leaves. Stresses of any kind have a tendency to reduce leaf chlorophyll concentrations, changing leaf reflectance in visible light wavelengths (Carter and Knapp, 2001). In the 1980s, scientists determined that remote sensing of light reflectance from aircraft or satellite could record the same indicators of stress as measured in the laboratory (Goetz et a/., 1983; Horler et a/., 1983;
Vogelmann and Rock, 1988, Assessing forest damage; Rock etal., 1988).
Over the last 20 years, spectral indices of foliage and full canopies have proven highly effective in measuring damage to forest canopies, cellular damage, and physiologic change in plants (Rock, etal., 1986;
Rock et a/., 1988; Martin and Aber, 1997, Entcheva Campbell et a/., 2004,
Pontius et a/, 2005; Pontius et a/., 2008). This technique has been used to document landscape-scale effects of a range of plant stressors such as acid rain, ground-level ozone, nitrogen deposition, pest infestations and climate change. The research has refined spectral indices for plant stress from broadband thematic mapper data to hyperspectral data and fluorescence indices. Three indices consistently provide informative data about plant stress: Red Edge Inflection Point (REIP), Thematic Mapper 5/4
28 ratio (TM5/4), and Near Infrared 3/1 ratio (NIR3/1) (Definitions in Methods section).
The REIP is particularly sensitive for detecting differences in chlorophyll concentrations between non-stressed foliage and initially stressed foliage (Rock etal., 1988; Vogelmann, et a/., 1993; Gitelson &
Merslyak, 1996; Carter and Knapp, 2001; Entcheva Campbell etal., 2004).
The TM5/4 ratio is an indicator of water stress. Plant physiology studies of leaf development have found that plants need not only an adequate supply of water in the roots but also high humidity for young leaves to manufacture chlorophyll (Bourque and Naylor, 1971).
The NIR 3/1 ratio is an indicator of the rate of growth. Leaf senescence is expected in fall but early senescence may limit production of sugars and starches and synthesis of protectants such as anthocyanin.
While twig growth drops off after mid-summer (Gaucher et a/., 2005) and sugar concentrations in leaves drop (Wong et a/., 2003), photosynthesis in early fall builds starch that is then resynthesized as sugar and stored in roots and wood (Wong et a/., 2003; Gaurcher et a/., 2005). Sugar maples which held green leaf color and delayed abscission longer have higher photosynthate and greater translocation of carbohydrates to winter sinks
(Wilmot et a/., 1995). Reduction of the photosynthesis season results in carbohydrate deficiencies which may lead to longterm decline (Wilmot
29 etaL, 1995).
Photosynthesis in late fall, just before senescence of leaves, also provides sugars for production of phenolics and anthocyanin (Ishikura,
1976). These late-season protectants work with carotenoids (Gautheret,
1972), pigments already in the leaf, to protect leaf components from intense light and photoinhibition, allowing efficient resorption of foliar nutrients (Close and Beadle, 2003).
These three indices have been studied extensively at the University of New Hampshire in Forest Watch, a long term study of white pine and its response to ground-level ozone (CSRC, 2007).
Although it was developed for assessment of soil nutrients, the
Munsell Color Charts have been used for rapid estimation of pigment concentrations in tobacco leaves; values read from the charts correlate closely with laboratory measures of chlorophyll a and b (Kelley et al.,
1990). More recently, the Munsell system has been used to gauge changes in leaf color caused by soil acidification (Bo et al, 2008). Such studies suggest that the Munsell method may provide a handy tool for chlorophyll estimation when large numbers of observations must be taken quickly in the field and when access to laboratory tools is limited.
Hypotheses
The hypotheses for this portion of the study include the following:
30 • Stress can be detected in the sugar maple foliage by 4
spectral indices using VIRIS scans and Munsell Color Charts.
• Stress measures identified by the foliar spectral indices will
indicate a possible cause of stress during the 2008 growing
season.
• These spectral indices will indicate how sugar maple responds
to stress.
Objectives
The objectives of this study are:
• Use 4 spectral indices of light reflectance to measure leaf
stress.
• Document leaf stress as it changes during the growing season
(superimposed on natural senescence).
• Compare stress responses in different plots over time.
31 Methods
At least 7 leaves were collected from each tree 5 times during the growing season from May 30 to September 29, 2008 (Table 2.2). Leaves were taken from convenient positions at a height of 6-7 m above ground using a 4.8m pole pruner. Leaf collections were placed in sealable plastic bags with wet paper towels and put in a dark cooler with ice packs. A sample leaf from each tree was photographed and traced for area measurement. The sample leaf was ranked for color using a Munsell Color
Chart for Plant Tissue and returned to the plastic bag with other leaves from that tree. The leaves were then refrigerated overnight.
The next day 7 leaves from each tree were scanned using the VIRIS.
Following the Forest Watch protocol, the 7 leaves were randomly selected from those collected and were stacked on the VIRIS platform. Three scans were taken of each group. The 7 leaves were rotated 90° between each scan to compensate for differences in reflectance from different portions and angles of the leaves. VIRIS scans were evaluated with GER 2600 Data
Processing Program (Spencer, 2001). Each set of three scans was averaged, producing a data set of reflectance by wavelength. The data were then examined using Excel charts of the reflectance curve and statistically analyzed using JMP 8.0 (Figure 3.1).
32 Red Edge Inflection Point
The Red Edge Inflection Point, REIP, marks the transition from visible red light zone (680-750 nm) where absorption shows high chlorophyll content to the high reflectance near infrared (NIR) where non-stressed plants give strong reflectance (Rock et a/., 1988).
The REIP index provided by the GER 2600 calculates the first derivative of mean reflectances of light at each wavelength in this zone divided by mean wavelengths measured (Y2-Y1/X2-X1). Reflectance increases rapidly on a steep slope as the VIRIS scans into the NIR range of wavelengths. The REIP index for each VIRIS scan is the midpoint on this slope or change in inflection of the curve (Figure 3.2). The REIP has been used in Forest Watch studies of white pine to document needle and tree stress.
When trees are not stressed, VIRIS scans show that chlorophyll wells are deep and concave with much absorption in visible red light (680 nm) .
The REIP in non-stressed trees tends towards the longer wavelengths in the
NIR in what is called "the red shift." As chlorophyll levels decrease, the well narrows, becomes more V-shaped, and the NIR plateau shifts to a shorter wavelength, a "blue shift" (Goetz et a/., 1983; Horler et a/., 1983;
Rock et a/., 1988; Moss and Rock, 1991). Readings in a range of 685 nm to
726 nm give a precise reading of this change. For the purposes of this
33 study, a stress response will be considered a mean seasonal REIP less than
715 nm (Table 3.1).
In Figure 3.1, Tree 835 shows a deep, rounded chlorophyll well in the visible light zone. This tree's REIP measure of 723.9 nm indicates abundant chlorophyll. Tree 812 shows a narrow chlorophyll well. Its REIP measure of
705.4 nm, indicates severe stress and reduced chlorophyll.
TM5/4
TM 5/4 ratio considers the ratio of Landsat TM band 4, 760-900 nm, along the NIR plateau, with TM band 5, 1550 -1750 nm. Measures of reflectance in band 4, using satellite data sets, have proved useful in estimating biomass and growth in a range of vegetation conditions. Band
5 is also a reflectance plateau but it is related to the absorption wells at
1400 nm or 1900 nm, two features which show leaf water content and which do not reflect light. The deeper these wells and the lower the reflectance of the plateau between them, the more water in the foliage.
Thus the TM 5/4 ratio relates water absorption, data from band 5, with biomass, data from band 4. For this study, a response to stress was considered any value > 0.55 (Table 3.1).
Returning to Figure 3.1, a sample VIRIS curve, both trees have TM5/4 ratios which indicate water stress. Tree 835 measured 0.663 and Tree 816 measured 0.647 on September 15. These measures are considered normal
34 for September 15, a period late in the growing season when foliage is growing dry and beginning to senesce.
NIR 3/1
The NIR 3/1 ratio compares two regions in the near infrared spectrum, NIR 1, 800-900 nm, and NIR 3, 1250-1330 nm. These are two reflectance areas or humps on the NIR plateau. The difference in percent reflectance between them is generally less than 1.0 when the plant is growing.
Tree 835 shows a NIR 3/1 of 0.903 while Tree 812's NIR 3/1 is closer to a 1.0 ratio at 0.929 (Figure 3.1). Tree 835 reflects more than 80% of light in band 1 of the NIR. The plateau slopes to about 75%. Dividing band 3 by band 1, 75 by 82 produces a NIR3/1 of 0.903. Notice that the line of Tree
812 is flatter, with less difference between the left side of the NIR and the right, producing the NIR 3/1 of 0.929. On September 15, both trees demonstrate slowing growth, with Tree 812 more advanced to senescence than Tree 835.
NIR 3/1 index is an indicator of young rapid growth, slowing growth or senescence. In this study, the response to stress is defined as any NIR3/1
> 0.90, Table 3.1
Munsell Color Chart Ratings
Munsell Color Charts for Plant Tissues presents scales ordered by
35 chromatic color, primary hues and their combinations, such as the green- yellow used in this study. These hues are further divided into steps, 2.5 GY,
5.0 GY and 7.5 GY, more yellow at 2.5 and more green at 7.5.
Each category of hues presents color scales which are further divided. Value indicates the lightness of the hue on a 10 point scale as compared with a neutral gray scale ranging from 0 for black to 10 for pure white. Chroma, the second factor on the scale, indicates the strength or intensity of the hue. This is also compared with a neutral gray scale with colors intensifying as high as 14 in hue.
Figure 3.3 presents a sample page, 7.5GY, with a sample leaf taken from Tree 837 on July 30. This page presents color scales for the greenest hues, less yellow than 2.5 or 5.0 GY hues. This sample page shows values on the left from whitest at 8 to blackest at 3. Across the bottom of the page, chroma indicates intensity of hue from dullest at 2 to brightest at 10.
On July 30, 2008, Tree 837 was scaled at 7.5GY, 4/4.
In this study, leaves were photographed on the day on which they were collected. Leaves were then compared to Munsell Color Chart scales and rated. Later, when analysis of this data was done, the ratings were ranked 1 to 27. This rating list ordered Munsell samples from the greenest, darkest value, and brightest chroma, 27, measured in the study's
5 samples of leaves to hues tending to yellow hue, lighter value and duller
36 chroma, a 1 (Table 3.2). Colors at below 18 will be defined as stressed.
In summary, the VIRIS indices and the Munsell Color ranking will define a response to stress as shown in Table 3.1.
Spectral measures were analyzed by plot throughout the season.
Spectral measures were also analyzed by growing days between each collecting date (Table 3.3). April 22 is considered Day 1. Growing days were counted through September 29, 163 days. The days between samplings were counted as positive growth when a measure such as the
REIP increased or at least stayed at or better than the selected stress level,
> 715 nm for REIP. When REIP values stayed the same under 715 nm, or fell below 715, the growing days were not counted.
37 Results
Spectral indices and Munsell Color Chart values measured for each
tree on each of 5 sampling dates are presented in Table 3.4.
Growth between April and May
VIRIS scans for Tree 832 and 833, April 22 buds and May 30 leaves
are compared (Figure 3.4).
After 41 days of growth, REIP values show a shift from 697.6 nm to
723.9 nm in Tree 832 and from 700.7 nm to 728.5 nm in Tree 833, indicating
increases in chlorophyll. TM 5/4 ratios indicate initial water stress in Tree
833. NIR 3/1 ratios indicate rapid growth in both trees.
Condition of Three Trees in One Plot on May 30, 2008
For each tree in Plot 10, Tree 835, 836, and 837, VIRIS scans show
broad chlorophyll wells in the visible red band and high reflectance along the near infrared plateau (Figure 3.5). REIP values (722.4, 728.5 and 723.9
nm respectively) suggest trees have abundant chlorophyll. NIR 3/1, 0.853,
854, and 8.44 respectively, indicates all trees are growing rapidly. The
Munsell Color Chart, 5GY,4/6, 5GY, 4/6, and 5GY, 4/8 respectively, and
photos indicate leaves that are dark green.
TM 5/4 ratios above 0.55 indicate that the three trees are experiencing initial water stress.
Figure 3.6 presents a second example, May 30 data for Trees 820,
38 821 and 822 in Plot 5.
REIP measures indicate stress, 705, 702, and 703 nm respectively. The
chlorophyll wells of all three trees are narrow and v-shaped. Reflectance is
below 80% in the near infrared plateau. TM 5/4 values indicate initial water
stress in Tree 820, 0.555, Tree 821, 0.579, and 822, 0.572. The Munsell Color
Chart ratings vary. Tree 820 shows no stress, 5GY, 4/8; Tree 821 shows stress,
5GY, 7/10.
Comparison of Leaves on One Tree Through the Season
Figure 3.7 and Table 3.5 present a sample of data for one tree
throughout the season, Tree 826 in Plot 7. TM5/4 indicates water stress
throughout the season. Other measures indicate little or no other stress
until late September.
A second study (Figure 3.8 and Table 3.6) indicates Tree 822 may
have been stressed even at the beginning of the season. On April 20, the
TM5/4 value stands out as severely water stressed, 0.699. The TM5/4 ratio
never falls below 0.55 and was 0.572 even on May 30. Over the course of the season, REIP values rose into the healthy zone only in July, 727 nm, and then fell to 706.9, 30 days or more earlier than Tree 826.
Time Series Analysis Indicated
Figures 3.9 and 3.10, A and B present a time plot for each of the
VIRIS indices.
39 In Figure 3.9, trees in only two plots, 9 and 10, maintain no-stress measures through the full growing season. All others show stress in
September. Trees in two plots, 808-812 in Plot 2, and 820-822 in Plot 5, reach REIPs >715 nm only once in July and then fall back into stress levels.
By early September trees in six plots show rapid loss of productivity and the onset of senescence, as indicated by the NIR 3/1, Figure 3.9A.
Only trees in four plots, 3, 5, 9 and 10, maintain low NIR 3/1 through the full season.
In TM 5/4, Figure 3.1 OB, all trees in all plots, excepting those in Plot 10
(Trees 835, 836, 837) show initial or severe stress in May. For trees in all plots, water stress only grew more stressful as the season continued.
Comparison of Plots by Index
REIP. The mean of all REIP measures was 713.6 nm.
Analysis of variance shows a significant difference between plots for alpha 0.05 (p = >0.0238) (Figure 3.11 A).
Time series analyses of REIPs over the season(Figure 3.11B) found a mean of 120 growing days. A few trees maintained deep chlorophyll wells and high REIPs even in October just before leaf fall. In contrast, stressed trees lost chlorophyll and the REIP moved into lower wavelengths as early as July 28, marking a significant difference between days of growth (p =
>.0001).
40 TM5/4. The mean TM5/4 ratio for the season on all plots was 0.616
(Figure 3.12) with significant differences between plots (p = <0.0001).
Two methods of calculating growing days were tried: Days of no water stress, Figure 3.13A, and days with no stress or initial stress, Figure 3.13
B. The mean of days in which all 30 trees showed no stress was 31.6 days.
When initial or partial stress was included in growing days, the mean was
96.8 days.
NIR 3/1. The mean NIR 3/1 ratio was 0.909 with significant differences between plots (p = > 0.0244).
The mean number of growing days, all days producing NIR 3/1 ratios of 0.90 or less (Figure 14B) was 128.5 days with significant differences between plots (p=<0.0001).
Munsell Color Chart. Color rankings (Figure 3.15A) present a mean of 18.7 from late May through September, with significant differences between plots (p = 0.0158). Growing days of unstressed color present a mean response of 149 days (Figure 3.15B) with significant differences between plots (p=<0.0001).
Comparisons and Correlations. REIPs were positively correlated with
NDVI (r=0.7741) and with Munsell color rankings (r=0.7165). TM5/4 ratios were correlated positively with NIR3/1 (r=0.8059), Table 3.7 and Figure 3.17
A, B and C present these analyses.
41 Spearman's rank correlation coefficients indicate that there is also significant correlation (p=0.0001) for all indices excepting the Munsell color rankings with TM5/4 (p=0.4502) and NIR 3/1 (p=0.5754).
Table 3.8 was built following index analysis showing the marked difference in grow days plot to plot and as calculated for each index.
Table 3.9 presents a summary of findings, stress levels which were first set in
Table 3.1 compared with found means of each spectral indices, mean growing days and percentage of the season.
42 Discussion
Hypothesis One
• Stress can be detected in the sugar maples by 4 spectral
indicators measured by VIRIS scans and Munsell Color Charts
repeated through the growing season.
This study found clear evidence that various symptoms of stress
(chlorophyll loss, water stress, early senescence) can be detected through the use of 4 spectral indicators.
The statistical analyses detected significant divergence from the mean for all four of the indices. In some cases, the mean was exceedingly low. A REIP mean of 713.6 nm is below the stress level set by this study at
715 nm. The mean TM5/4 of 0.616 is well into the level which indicates full and increasing water stress. The NIR3/1 mean of 0.909 exceeds the 0.90 level set by this study as an indication of stress. The Munsell Color ratings also found a mean, 13, lower than healthy green.
The mean condition for these trees was one of stress: chlorophyll was less abundant than under ideal conditions, water stress was high, growth rates were reduced, and the onset of senescence occurred earlier.
Time series analysis of the spectral data also identified stress. The statistical analysis for the Munsell Color charts shows there was little
43 divergence from the mean of 149 days. This number of grow days is higher than mean growing days indicated by other indices. Yet any plot with 149 growing days failed to produce fall foliage color. Most trees maintained green color through the season until late September when a large number of leaves in 6 of the 10 plots showed dramatic loss of green hue.
The leaves which yellowed in mid to late September never reached peak color, even in Plot 1 which had a mean number of growing days at 153.
Instead, the leaves on 23 of the 30 trees continued to pale, turned brown and dropped off on or before October 4. In only 2 plots, Plots 9 and 10, leaves retained high values through late September into October. Leaves which maintained high color into October rapidly turned from green to red, orange or golden yellow and stayed on the tree until mid-October.
Data analysis supports hypothesis #1: Stress can be detected in the sugar maples through 4 spectral indicators measured by VIRIS scans and
Munsell Color Charts repeated through the growing season.
Hypothesis Two
• Stress indicators identified by the spectral methods will point
to a possible cause of stress during the 2008 growing season.
Drought, or the lack of uptake of available water, appears to be the likely initial stressor of these trees in the 2008 growing season. It may be that torrential rains which followed the spring drought further
44 contributed to stress and prevented some trees in some plots from recovering from the initial spring drought.
Drought early in the season is particularly stressful to plants (Horsley et al., 2002). The Bearcamp Valley experienced a drought in 2008 that began in mid-May and lasted through June. Unusually heavy rains followed in July. Measures of water stress showed significant initial stress as early as May and the majority of plots did not recover.
TM5/4 measures show initial and severe stress appeared even in
May, earlier than stress was apparent in any other spectral data. The high levels of TM5/4 stress increased during the season. All plots showed water stress for much if not all of the season.
Other indicators do not point so directly to one cause. Low chlorophyll and poor photosynthesis, low reflectance and disturbance of cell structures, a slowing of the pace of growth, and even the color of leaves may be associated with many stressors.
Rain and cloudy weather during the six weeks following the May-
June drought may have exacerbated the stress. Precipitation was higher than average and came in deluges. No trees recovered from the drought but some, in Plots 2 and 9, at least maintained TM5/4 stress levels at or near May levels through the season, Figure 3.11B. And, despite water stress, those trees showed increased development of chlorophyll as shown
45 in July REIP measures, Figure 3.1 OA. The more successful trees may have had ample access to oxygen, water and nutrients from the roots. Plots 2 and 9 may provide better drainage for trees.
Spring drought and unusually heavy rains are projected to become increasingly common in New England as a result of regional climate change (NERA, 2001; Wake, 2007; Hayhoe etoi, 2007). More detailed study of the weather in 2008 and of correlations with the spectral indices is needed to definitively determine if heavy rain was a stressor. However, it seems reasonable to conclude that the drought in May was the primary stress agent for sugar maples in the study. Hypothesis #2 is supported.
Hypothesis Three
• Stress identified by the spectral measures will suggest how the
sugar maple responds to stress.
Response varies from tree to tree and from plot to plot in ways which may help describe physiological characteristics of the tree or site.
Trees must not only cope with stress but repair damage caused by stress and make up for lost growing time. Trees with physiologically predisposed to cope with specific stressors, with exposure to fewer past stressors, or with better site conditions will maintain photosynthesis and cell growth during a stress period or at least rebound quickly.
Discussion of Hypothesis #3 is expanded in the following sections
46 and illustrated by 3 tables, Table 3.10 is a summary of analyses of spectral indicator means and growing days with p values. Table 3.11 presents mean spectral indicators rated on a 1 or 2 scale, 1 representing no stress and 2 representing stress. Table 3.12 summarizes both 3.10 and 3.11 by plot, allowing comparison of the 4 spectral measures and growing days for stress or no stress. Discussion of Hypothesis #3 is developed in the following sections, based on the three final tables.
Extremes. The three tables show that trees in Plot 3 scored stress levels in every index: a plot mean below 715 nm in REIP, a mean TM5/4 above 0.55 indicating water stress, a mean NIR3/1 indicating maturation or slower growth, and leaf color below the Munsell 18.7. Trees in Plots 3 and 4 showed no days without stress during the entire growing season. The site actually seeps with water but heavy growth of white pine and spruce may outcompete these sugar maples for water. Plot 3 is has a high basal area. Sugar maples must compete for sun and water with very large white pine, hemlock and dense young ash.
At the other extreme, Plots 9 and 10 repeatedly appear in the un stressed categories in Table 3.10. Plots 9 and 10 are managed as a graveyard/farmyard and as a pasture. Trees are spaciously located with room for full canopies. These trees do not have competition for water and nutrients. Moreover, these plots lie at the highest elevation in the study
47 area and are perhaps significantly cooler than other plots.
Stand density, as measured in basal area, seems to be the important factor in changing maple response at the extremes.
Review of Data for One Plot. When average responses are examined within one plot, details offer clues as to differences in individual tree response.
Plot 2 ranged across the indices, turning up in the stressed group of
REIPs and joining the unstressed plots on measures of NIR3/1, Table 3.10 and Table 3.11. Tree 811, for example, showed adequate water and no water stress for most of the growing season, 149 days, probably because it lies on a small seep of water, Table 3.11. This tree flowered and set seeds.
Its leaves retained high color through mid-September. Then 811 senesced rapidly and produced dull foliage color.
In the same plot, 812 had adequate water for only the first 41 days of the season. It had initial water stress for the remainder of the season but maintained TM5/4 ratios below 0.60 throughout that time. This tree showed low REIPs and high NIR3/1 by mid-September. Leaf color was low on the Munsell rating charts all season and, although leaves in the canopy turned a bright red-orange in September, leaves yellowed and dropped off before the normal foliage season, mid-October. Growing on the edge of a hayfield, 812 has no water other than rain and groundwater. This tree
48 may have also suffered compaction of soil during a recent timber harvest.
Tree 808 showed adequate water for 102 days, measures of initial stress for another 47 days and a final 14 days of stress. This growing season shows in the NIR 3/1 ratio, a mean of 0.87 for Tree 808, continued strong growth through the season.
All three of these trees might be expected to suffer much more severe stress response as Plot 2 was clearcut in 2006. Sudden exposure to sunlight and less competition sometimes shocks trees. Two of these trees, however, growing on a cool north-facing slope seem in relatively good health.
Comparing Plots Near the Mean. Comparison of responses between plots near the mean also offer information as seen in Table 3.12.
Trees in Plot 5 where water is abundant year-round showed stress throughout the season in every category. Overcrowding as seen in this site's biomass may have compounded the effects of 2008 seasonal stressors.
Stress as indicated by TM5/4 was also extreme in Plots 7 and 8, plots which lie along the Bearcamp River. However, these plots score no stress in REIP and Munsell scales. In this case, permeable gravel and sand soils and a falling water table played a role. So did site management as these trees are sited in a pasture with ample space for wide canopies.
49 Plots 7 and 8 recovered during the season and rated VIRIS scores frequently at the mean. These scores were almost identical to scores in
Plots 5 and 6. However, trees in Plots 7 and 8 retained their leaves through late September and showed some color in the foliage season. In Plots 4 and 5 colors faded quickly in mid-September. Leaves dropped with little color if any in Plot 5 and limited color in Plot 4.
In addition to pointing to difference in management which may assist a tree in coping with stress, this comparison also highlights how resilient the maple can be. A long-lived tree which lives among the elements at the top of the canopy has evolved as a species to adapt and acclimate to many stresses natural and anthropogenic (Witzell and
Martin, 2008). Given good management, the maple can rebound from severe stress. Given limited management or site difficulties, even resilient trees may suffer sustained damage.
Time Series Analysis of all Plots. Those trees which cope better with stress, growing despite it, continued their growth for the full season.
The Munsell Color Chart ratings, with accompanying photographs of the leaves, point out early senescence in 80% of the 30 trees studied.
These data are also present in the REIP and NIR3/1 records. Some research, however, may appear to consider those readings as normal.
Studies have found that growth of trees stops by mid-August and sugar
50 levels in leaves fall in September (Wong ef a/., 2003). The Forest Watch protocols combine the words "mature growth" with "senescence". One might assume, from these findings and treatment of VIRIS data that little or no production of sugar occurs in early autumn and that the tree is merely storing away the sugars produced earlier.
The green leaves tell a different story. Although leaves may stop expanding by July or even June, they are still conducting important photosynthesis, making the starch which is found in fall leaves (Wong et a/., 2003). Early senescence may be critical to the tree in lost production of sugar and starch needed for storage during the dormant season and for production of protectants such as anthocyanin (Gaucher et a/, 2005)
The high starch level measured in leaves in September changes back to sugar at senescence, allowing the leaf to mobilize sugar, nutrients, and phenolics for storage before abscission and leaf drop (Wong ef a/., 2003).
In studies of sugar maples in Vermont, researchers found that reduced photosynthesis equated to carbohydrate deficiencies which later led to decline of the trees (Wilmot ef a/., 1995).
The Munsell Color Chart readings force a reconsideration of these different views. Plots 9 and 10 are the only plots which showed no stress in this measure. The trees in Plots 9 and 10 show high REIPs even on
September 29, Table 3.4E, evidence that chlorophyll content is as high as
51 it was during the summer. They are capable of producing sugar. While they show some slowing of growth in the NIR3/1, they are not senescent; their leaves are metabolizing at a NIR 3/1 ratio of less than 0.90 or just above 0.90 for the entire season. These data suggest that fall metabolism may produce sugars which provide some vital product for the trees. Later examination of the wood and buds will pursue this question.
This question also suggests another look at the May measurements.
Healthy trees changed rapidly, registering no-stress values in REIPs, NIR3/1 and Munsell ratings by May 30, despite the drought that lasted from April
30 to June 20. Trees in plots which evidenced stress in those measures as early as August were the slowest to change in May. The rate of change in reflectance in young leaves may contain evidence of longterm strength and resilience in the tree. Trees which show rapid growth in the first month may have experienced fewer past stresses than trees which exhibited slow growth. This observation provides support for claims by many climate change researchers that stresses will be cumulative.
Measurements of leaf reflectance support Hypothesis Three: The spectral indices suggest how sugar maples respond to stress. Anatomical and physiological evidence and repeated seasonal spectral measures would provide fuller information as to how maples respond to drought, stressful site conditions or cumulative stresses.
52 Discussion of Objectives
The study met its objectives but numerous suggestions arise for improving the methodology and the analysis.
VIRIS. These 3 spectral indices appeared relevant and useful in measuring maple health. The index values provide information that supports and explores all three hypotheses.
This study sets rankings for the 3 indices which differ slightly from those used in Forest Watch: a clear division between stress and no stress for the REIP at 715 nm, the selection of 0.55 and 0.90 as limits in TM5/4 and
NIR3/1 ratios, respectively. These rankings appear to be useful for sugar maple and could be adopted if Forest Watch is expanded to include a maple component.
Studies of maples using the VIRIS should continue in order to compare findings on the ground with the same spectral indices as seen with remote sensing tools. Correlations of the two would allow monitoring of maple health with remote sensing tools. The study demonstrates clearly that spectral measures need to be taken across the growing season.
Munsell Color Charts. A continuous numerical rank of Munsell Chart values allowed for statistical analysis of data. The Munsell system does not provide such a ranking system. Creating an artificial ranking may be illegitimate. Munsell Color Charts should not be used in future studies.
53 However, it was the Munsell ratings which pointed up the significance of sustained REIP and NIR 3/1 values, questioning the literature which equates maturity with the onset of senescence.
Future studies should be done with digital photography and managed with a uniform computer analysis program.
Time Series Analysis. Time series analyses also raise the issue of uniformity in ranking data. The author experimented with a system for counting growing days. Such rating systems need testing if they are to be widely used by others, especially the public. This work should be done with statistical analysts such as the authors of JMP 8.0.
54 Conclusion
Four spectral measures were effective in detecting stress in sugar maple, in suggesting the main stressor, and in describing the maple's response to stress. The measures suggest that site and management differences may account for differences in tree and plot response to stress.
The key findings include:
• 100% of the trees showed water stress.
• 80% of the trees showed reduced growing days, early
senescence and loss of foliage color.
• 60% of the trees showed reduced chlorophyll.
These indices raise questions as to how trees differ anatomically and physiologically in response to stress.
55 CHAPTER IV
LEAF AND BUD ANATOMY
Abstract
Anatomical differences found among the 30 trees in this study are related to differences measured with spectral methods: Trees that showed high stress based on reflectance data also demonstrate smaller or fewer leaves, abscission of leaves during the summer, and misshapen and dull- colored buds. All trees showed water stress and all trees showed declining leaf area.
Stressed trees, however, produced large numbers of normal buds, pointing to differences in source-to-sink priorities or capacities in the trees as they respond to stress. Fifty percent of trees produced excellent buds.
Two trees studied in 2007, one stressed and one unstressed, also show differences in pollen morphology.
Simple measures of leaf area and bud quality may be useful in measuring stress in sugar maples. They may be ideal for use by citizen scientists.
56 Introduction
Stress early in the growing season may significantly impact plant anatomy (Bourque and Naylor, 1971). Chlorophyll levels in newly unfurled deciduous leaves are very low but increase rapidly; even when a leaf is only 9% of its eventual size, it will have produced near maximum amounts of chlorophyll (Gamon and Surfus, 1999). Even slight damage to young leaves by pear thrips can reduce CO2 assimilation by 4 to 20%, significantly reducing the seasonal carbon balance in sugar maples
(Ellsworth, et a/, 1994; Vogelmann and Rock, 1988, Anatomy of red spruce). Dry air associated with drought, imposed on young seedlings, can retard chlorophyll accumulation rates by up to 50% and, when severe, can impede leaf recovery (Bourque and Naylor, 1971).
In one of the earliest studies of maple leaves, University of Vermont scientists estimated the number of leaves on a "thrifty" maple (Jones et a/.,
1903). In 1899 the tree, 50 feet high with a dbh of 12 inches, had approximately 146,250 leaves in its canopy; the following year, the same tree had approximately 162,500 leaves in its canopy (Jones etoi, 1903).
Although they did not identify a cause for the difference, these scientists concluded that conditions were favorable for leaf development in one season and unfavorable in the other. The researchers calculated that the
"thrifty" tree carried about one-fifth of an acre of leaves in 1899 and one- third of an acre of leaves in 1900.
57 Early experiments with leaf abscission found that in maples the autumnal shortening in the length of the photoperiod is the trigger which changes the balance of auxins, which retard abscission, and ethylene, which accelerates aging (Olmstead, 1951). More recently, tests of sugar maple leaves showed a strong correlation between peak red foliage color and the presence of four sugars, glucose, sucrose, fructose and stachyose (Schaberg ef a/., 2002).
Such experiments have led scientists to conclude that any reduction in photosynthesis can cause carbohydrate deficiencies and change other physiological processes in the tree (Wilmot ef a/., 1995).
Numerous studies suggest that trees exposed to stress cannot grow large or long-lived leaves.
In studies of longterm decline of sugar maple forests, maples exposed to stress show reduced leaf area, foliar damage and sometimes irregular leaf shape or lobe damage whereas healthy trees had normal leaves (Liu ef a/, 1997). In addition to smaller than usual leaves, maples under stress can be recognized by early fall color and dieback of fine twigs (Horsley ef a/., 2002).
Another study suggests that large leaves may be a liability to a stressed tree. Large leaves must allocate significantly more energy, nitrogen and carbon to petiole and mid-rib support tissues than smaller leaves (Ninemets ef a/., 2006). This cost may reduce net photosynthetic
58 export by larger leaves, suggesting that trees under stress might abscise
such leaves in favor of retaining smaller, more efficient leaves.
In most cases^when decline has been noticed, as when trees lose
significant portions of leaf canopy or show large scale death of branches,
it is too late for the tree to reverse the damage; the tree is in such decline
it will die (Minocha, 1999). Early detection is critical for management or
mitigation of stress (Minocha, 1999).
The present study measured the size of leaves throughout the
season, compared leaves among trees and plots, and investigated loss of
leaf size over the growing season due to abscission of larger leaves.
Spring and fall buds were also studied. When trees are stressed and
carbohydrate supplies are reduced, trees may select which carbon sink
to supply. Research in red spruce forests of central New Hampshire (Moss et a/, 1991) and in the Czech Republic (Entcheva Campbell et a/., 2004)
has shown that production of buds and seeds may be the last priority for a
highly stressed tree.
This study also compared pollen from two trees to examine
differences in this component of reproductive anatomy.
Hypotheses
The hypotheses for this portion of the study are:
• Stress will be reflected in anatomical structures including
leaves and buds.
59 • Anatomical effects of stress will suggest how the sugar maple
responds to stress.
Objectives
The objectives of this study are :
• Observe and record measures of leaf health during the
growing season.
• Observe and record anatomical structures such as buds.
• Identify what measures and observations would be useful in
detecting and quantifying the effects of stress.
• Identify measures and observations easily replicated by
citizen scientists.
60 Methods
Buds
Terminal buds were sampled in on April 2 and April 22, and again after leaf drop, October 2008.
Spring buds were photographed on graph paper to allow comparison of size and rate of growth. The number of lateral buds was counted. Width and length of the terminal bud from the apical collar were measured. Laterals were described as small and not swelling, swelling or rapidly swelling as shown in Figure 4.1 A, B, C, and D.
The Czech method was used to rate bud health on fall samples
(Polak ef a/., 2006). Buds were sliced in half from distal to proximal end and inventoried on a 1-3 scale, excellent, good, dead or deformed, and missing, as described in Figure 4.2A, B, C and D and Table 4.1.
Spring and fall buds were then compared to provide an overall stress rating, 1 as unstressed and 2 as stressed. This rating system allowed comparison of buds with leaves and spectral data.
Pollen
Flowers and pollen, harvested on April 8, 2008, were selected from
Tree 801 and Tree 811. In a preliminary trial in September 2007, VIRIS scans showed loss of chlorophyll, water stress and early senescence in Tree 801 while Tree 811 maintained chlorophyll, showed only initial water stress and maintained growth until September 24, 2007(Table 4.2). Flowers produced 61 in 2008 by both trees offered an opportunity investigate whether differences in stress might produce differences in the trees' reproductive organs. Anthers were mounted on metal stubs and prepared for study with the SEM following standard procedures (Rock, 2009).
Leaves
Leaves harvested for VIRIS analysis (Chapter III) were also characterized by size. One leaf was randomly selected from each Tree on each collection date and traced onto graph paper. A square centimeter of the same paper was weighed. The graph paper tracing of the leaf was cut out and weighed. Leaf area (cm2) was calculated as the weight of the leaf tracing divided by the weight of the 1 cm2 piece of graph paper
(Jones et a/., 1903). While other more modern tools, planimeter and computer software, can do this job, this method was chosen to determine its usefulness in the K-l 2 classroom. The JMP 8.0 program was used to analyze the data.
62 Results
Spring Buds
Spring buds generally doubled in length between the first measures on April 2 or 8 and the second measure on April 22. Some buds increased in width more than two-fold. Trees at lower elevations showed earlier and greater growth with swelling of lateral as well as apical buds. The most advanced buds showed increased red color and some green in the bud scales.
On a scale of 1 to 3, excellent buds, Scale 1, terminal buds doubled in size with an almost equal swelling of lateral buds. Scale 2 buds showed growth of the apical bud and some swelling of laterals. Scale 3 buds showed less than two-fold growth of the apical bud and no swelling of laterals (Table 4.3).
Leaves opened from apical buds on April 30. In some cases, the first lateral buds opened leaves at the same time. The opening buds were approximately 4.0 cm in length, a 10-fold increase in length from April 2.
These buds had a strong rose color in the unfolding bud scales.
Fall Buds
During the fall, the percent of viable buds ranked excellent or good was compared with non-viable buds, dead, deformed and missing (Table
4.4). An overall rating was awarded each tree: Scale 1 = 75% or more of buds ranked excellent; Scale 2 = 60% or more of buds ranked excellent
63 and/or good; Scale 3 = 40% or more were dead, deformed or missing. All
three trees in Plot 10 (835, 836, and 837) had 85 to 97% excellent buds with
no good buds and a few dead, deformed or missing buds. In contrast, all three trees in Plot 3 (813, 814, and 815) had more than 50% missing buds
and high percentages of dead and deformed buds.
Bud data were analyzed with ANOVA (Figure 4.3). When both good and excellent buds were measured together, only buds from Plot 3
(Trees 813, 814, and 815) were significantly poorer than those from any other plot (r=4.97, p=0.0014). Trees in Plots 1, 2, 5, 9 and 10 had much better buds and a greater number of viable buds. Trees in Plots 4, 6, 7 and
8 were not significantly behind the mean of 70% of buds ranked good and excellent buds.
When only excellent buds were analyzed (Figure 4.4), the mean dropped from 70% to 54%. Plots 3, 4, 7, and 8 fell significantly below the mean. Plot 9, just below the mean, showed significant differences
(pO.0001) from buds in Plots 1,5, and 10, the three best plots for bud production.
Plots in which bud health was lower (Plots 4, 7, 8 and 9) had large numbers of "good" buds as compared to "excellent" buds. Trees in Plot 9, one of the two plots that showed little stress in the spectral scans, had 52 good buds and 93 excellent buds on its three trees.
64 Pollen
Anthers on Tree 801 were empty of all but a few grains of pollen
(Figure 4.5 A). On the same date, anthers on 811 were robust (Figure 4.5B).
Pollen grains from anthers on Tree 811 appeared deflated, some were split, others were squashed (Figure 4.6A) In the 811 anthers, pollen grains were fat, round, and thickly clustered (Figure 4.6B).
Leaves
Leaf area as measured five times throughout the season (Table 4.5).
All trees shed leaves, showing a decrease in leaf size throughout the season (Figure 4.7). Trees lost leaves at the height of the growing season, before the July measure, in August, and September. The declining area indicates that larger basal leaves were shed. In some cases, trees showed two major declines in leaf size, an indication they also shed medial leaves.
An Anova of leaf area by sampling date, Figure 4.8, shows the general decline of size with greatest losses in August and September.
Mean leaf size on May 30 was 103 cm2 and on July 30 was 103 cm2, indicating that from bud break at the end of April to May 30, leaves quickly attained maximum size and maintained that size through July.
However, ten trees had losses of 10% to 38% in leaf size between May and
July 30 (Table 4.5). Rapid growth in the size of other leaves hides these losses in the Anova mean.
65 By the end of August, mean leaf size decreased to 85 cm2, a 17%
loss of leaf area. The mean decreased again to 74 cm2 by mid-
September, a 28% loss, with a small increase by September 30 to 76 cm2
(Figure 4.8). Leaf area for all trees decreased (Table 4.5). The mean leaf
size for the season is 88 cm2, 15 % less area than the spring mean of 102
cm2. May and July leaf areas are significantly higher than later than areas
measured later in the season (p=<0.0001).
A second ANOVA was performed to evaluate leaf area by plot
(Figure 4.9). The mean leaf area for the season is 87 cm2, a 15 % decrease
from the May mean area. Trees in Plot 4 and Plot 6 had significantly
greater mean leaf area for the season. However, leaf area in trees in
these plots decreased as much or more than leaf areas of trees in other
plots (Table 4.5). These trees had a very wide variation in leaf size with a
few extremely large leaf areas measured in May.
Leaf area varied from tree to tree on each sampling date. The range, for example, spread from 173 cm2 to 62 cm2 in May. The widest
range of differences was measured in May (Figure 4.8).
Multivariate analyses were done to determine if leaf areas are correlated with spectral indicators of stress. Spearman's rank correlation coefficients indicate that there was slight positive correlation of leaf area with REIP values (p=0.0001). TM5/4, NIR 3/1, NDVI and Munsell Color rankings were not significantly correlated with leaf area (Figure 4.10).
66 Discussion
Discussion of Buds and Leaves
Each sugar maple bud contains an apical meristem and the
primordia of 6 leaves. The SEM photo at 21.2x shows the six leaves developing within the bud (Figure 4.11). The apical meristem becomes oval, producing two leaf primordia at either pole of the oval. The
meristem then swells as two more primordia emerge at 90 degrees to the first two. As the lower photo shows, these second leaves are abaxial to the first leaf primordia.
When the bud opens, the leaves emerge and expand in pairs, each pair at 90 degrees to the pair above (Figure 4.12). Leaf size varies with 2 larger outer or basal leaves, 2 large medial leaves, and 2 smaller central or distal leaves. The base of each leaf petiole encloses a primordial bud for the next season.
Once leaves begin to expand, the shoot elongates rapidly. Within a month, a shoot may be six inches or more in length with green internodes between the bud scale scar of the previous year and the basal leaves, between those and the medial set, and between the medial set and the distal pair. The distal pair of leaf petioles shelters not only 2 primordial buds but also the apical meristem which will develop a new terminal or apical bud. A single bud in 2008 will produce 6 leaves which may produce 7 buds for the 2009 season. 67 These observations lead to two conclusions about the buds studied here. Some twigs collected in the spring and in the fall carried fewer than
7 buds. The basal and medial leaves which sheltered those buds during primordial development may have been abscised in the 2007 season.
Secondly, the terminal bud and distal lateral buds are of greater importance than other pairs of buds. As the distal leaves have two tasks- sheltering the apical meristem and protecting developing lateral buds- their dual role may explain why the tree maintains them and allows larger outer leaves to abscise during stress.
Discussion of Spring Buds
Terminal buds were generally quite similar. They doubled in size in the first three weeks of April. The chief difference was seen in development of the laterals, their presences or absence and whether they swelled or not. Flowering trees, such as Tree 811, produced lateral buds as large as the apical bud. In some trees which show stress in spectral measures, such as Tree 812 and 813, laterals failed to swell. Other trees, such as Tree 833 and 837, had poor spring buds yet show little or no stress in spectral measures. Their higher elevation may merely have delayed their growth.
Discussion of Fall Buds
Although only 20% of the trees in the study retained leaves throughout the season, 70% of the trees produced good or excellent buds
68 with few dead or missing buds and little shoot damage. Trees in Plots 1, 2,
5,6 and 10 produced predominantly excellent buds.
Buds, rated from 1 to 3 on a scale from excellent to poor, are compared for Spring and Fall 2008 (Table 4.6). Change is shown with + for improved quality, 0 for no change, and - for declining quality. Trees are graded for vegetative production on a 1-2 scale as used for spectral data, 1 indicated no stress, 2 indicating stress.
Sixteen trees showed improved bud quality. Five other trees maintained good or excellent bud quality. Five trees maintained Level 3, poor quality, and 4 trees showed a decline in quality. Most trees may experience stress and yet recover, investing in the next year's buds. Some of the trees which showed improvement in bud quality (Trees 817, 820,
821, 831, 833, and 837) had no lateral buds in the spring. They may have suffered stress in 2007, losing leaves which produce lateral buds, yet they produced good or even excellent buds in 2008.
Other trees may have experienced greater stress, prolonged stress or numerous stresses, reaching a tipping point at which they lack the sugar or energy to produce buds. Trees which maintain grade 3 poor buds (812, 813, 815, 825, 827) had no lateral buds in the spring of 2008, an indication they suffered stress in 2007 as well as 2008. Trees which declined from good spring condition to poor fall bud quality (814, 816,
69 816, 830) all had laterals with visible swelling in the spring of 2008. These trees may not have been previously stressed.
Recording bud quality may provide a benchmark for future study of stress effects on bud development. Despite common stress from drought and heavy rain in 2008, and despite site differences, the sugar maples are able to develop buds and prepare for the next season. Most of the trees with poor buds are located in Plots 3 and 4, the Googin farm, and Plots 7 and 8, the Bickford farm. As discussed in Chapter III, dense growth in Plots
3 and 4 and glacial till soil in Plots 7 and 8 may account for the stress shown in these trees' productive capacity. The latter site is also the lowest in elevation and is more subject to late frosts in spring, early frosts in fall and the greatest heat in summer.
These very simple anatomical measures could easily be used by students to gauge the health and resilience of sugar maples. Over time, such studies may reflect changing conditions and stresses in a tree's environment. Bud studies of individual trees and sugarbush stands might also guide landowners as they make decisions about which trees to remove and which to retain, which stands to thin and improve or which stands to clearcut.
Discussion of Pollen
Pollen differed markedly between Tree 801 and Tree 811. Poor quality of pollen may relate to greater stress seen in spectral measures
70 (Table 4.2). Two samples are too few from which to draw conclusions.
Flowers on Tree 801 might simply have opened a day or two earlier than flowers on Tree 811. Further study of pollen could be useful in defining differences in bud anatomy and tree response to longterm stress.
Discussion of Leaf Area
Leaf area varies widely within a species (Ninemets et a/., 2006). In a study of maple leaves and their response to pear thrips defoliation, control leaves had an average area of 110.4 cm2 in June and maintained that size for the season (Ellsworth et a/., 1994). This study found all leaves averaging 103 cm2 at the end of May, a similar size, perhaps a bit smaller because of the earlier date.
While larger leaf area might seem an advantage in allowing for greater photosynthesis area, added area carries high costs in stem and interior leaf support structures, both architectural and physiological
(Ninemets et a/., 2006). Smaller leaves might be advantageous in net energy production, protection of chlorophyll from high heat, intense light and other stressors (Ninemets ef a/., 2006).
Difference in leaf area at any one sampling time is not necessarily an indicator of stress. Trees which flowered in 2008, Tree 801, Tree 811 and
Tree 834, had very small leaves in May, 59 cm2, 79 cm2 and 87 cm2 respectively, suggesting that they invested energy in producing flowers and pollen rather than in larger leaves. On the other hand, trees in Plots 3
71 and 4, that were highly stressed according to spectral indicators (Table
3.11) began the 2008 season with leaves at or above the mean area. One exception was Tree 815 which, as noted in Chapter III, demonstrated severe, longterm stress.
It is the change in leaf area over the season that demonstrates stress. All trees shed leaves and showed a significant reduction in leaf area over the season. All trees were stressed.
Comparison of Anatomical and Spectral Measures
All trees were assigned a stress index on a scale of 1 to 2 to compare leaf area and bud quality with spectral measures (Table 4.7).
Trees, typically, showed reduced leaf area by August (Table 4.5).
Leaf area declined again in September. This would indicate that the trees shed large basal leaves in August. Some trees continued to shed leaves, dropping the slightly smaller medial leaves in September. Internodes which shed leaves would not develop buds.
Much of the decline seen in VIRIS scans and color was not measured until September. Leaf area measurements indicate that trees were experiencing stress at least a month earlier, shedding leaves to reduce transpiration loss of water, maintain chlorophyll content, and protect apical buds in August.
72 The only correlation seen between leaf area and spectral measures was with REIP. The higher the REIP, the higher the mean leaf area (Figure
4.10).
No correlation with other spectral measures is seen. The JMP 8 regressions show leaf areas clustered at mean spectral measures. As discussed in Chapter III, the mean is not a measure of health. Leaf area varied widely, with no correlation to stress in trees. Indeed, unstressed trees selectively reduced mean leaf size as readily as did stressed trees. Anova analysis of leaf area by plot showed some of the highest mean leaf areas in Plots 4 and 6, two of the more stressed sites.
Water stress and loss in leaf area are seen in all 10 plots (Table 4.7).
In this perspective, the TM5/4 ratio appears to have a clear connection between the retention or shedding of leaves during the season.
Any stress might cause leaf abscission. The 6 leaves produced by each bud can potentially produce 7 new buds for the following year.
Recalling the 1903 counts of leaf numbers (Jones et a/., 1903), 160,000 leaves on a tree might theoretically produce 1.1 million leaves in the next season. Healthy maple trees produce more than the minimal number of buds and pollen granules to favor growth and survival under adverse conditions of light, temperature, climate and many other factors in the environment. Abscission of leaves was a principal means to reduce water stress during 2008.
73 For example, trees in Plots 1, 2, and 3 showed very low mean REIPs and other signs of stress in spectral measures yet they produced high quality buds that show no effects from stress. Leaves in all of these plots lost color and abscised before the normal end of these season. Yet they produced excellent buds in high numbers and showed relatively little bud death or damage. In response to stress, these trees favored growth in the next season through bud production rather than leaf production in the current season.
74 Conclusion
This study accepts the hypotheses:
• Stress will be reflected in leaf area and bud quality.
• The effects of stress indicated in the anatomy suggest how
sugar maple responds to stress.
Key findings include:
• 100% of trees abscised leaves during the growing season.
• 73% of trees produced good or excellent buds.
Comparisons of leaf size and bud quality with spectral measures indicate trees manage stress by leaf abscission while favoring bud production. Simple measures of leaf abscission and bud quality can detect stress at an early stage when better management of the stand might aid trees in coping with stress.
Continued testing of the 30 trees, comparing 2009 leaves with the
2008 bud quality, might find a measurable difference between outcomes in leaf health, an indication of cumulative stress or resilience from stress.
The study met its objectives but methods could be improved. Leaf area measures would be improved with sampling higher in the canopy. A standard selection protocol, sampling from two or three sides of each
75 tree, might improve accuracy of the data. Wet weight/dry weight measures should also be made of the leaves.
The bud studies might be improved by a more systematic categorizing of excellent, good, dead or missing. Calipers could be used for finer measures and measures of bud thickness. Measurements of stems and numbers of lateral buds might be included. More numbers of buds may be needed to see a statistical significance. Field protocols should be clarified as to how to deal with or count entirely dead twigs.
76 CHAPTER V
TRENDS IN SUGAR CONTENT AND WOOD GROWTH
Abstract
Records from the Hunter Farm, Tuftonboro, NH, sugar maker and the
New England Agricultural Statistics Service for 4 states show a steady loss of sap sweetness since 1970. The sap season on the Hunter farm now begins 5 to 10 days earlier than it did 40 years ago and ends 2 to 3 days earlier. During the same period, average annual temperature in New
Hampshire, as reported by the United States Historical Climatology
Network for Hanover, New Hampshire, substation 273850 (USHCN), has risen 4.75°C.
These parallel trends support projections of climate change in New
England by numerous scientific authorities (NERA, 2001; Hayhoe ef a/.,
2006; Perkins, 2007, Statement to House; Wake, 2007).
Records indicate that sugar content in maple sap has decreased from annual averages of 3.13-3.44% in 1900 and 2.93% in 1950 to 1.98-
2.02% in this decade. The decline may indicate a response to longterm and ubiquitous stress. 77 Increment cores from the 30 maples in this study were unable to substantiate a connection between trends in annual ring production and changing temperatures. Rather, wood growth offers a record of timber stand management and longterm health, information that may provide an important baseline for understanding any future change in maple health. Investigation of marginal parenchyma in two trees, one stressed, the other unstressed, indicates further study of wood and its response to stress might be warranted.
78 Introduction
Sugar maples provide two historic records of their health. One,
sugar production records maintained annually by sugar producers are
unique to this species. Maple syrup is produced more efficiently from
sweeter sap. Sweeter sap has traditionally been considered an indicator
of genetic superiority and lack of stress in the maple. The other historic
record is wood production determined by measuring growth rings, a
record frequently used by foresters and dendrochronologists as an
indicator of growth response to known stressors.
Less than a decade ago, the New England Regional Assessment
(NERA) presented two models of climate change and its potential impacts for the region (NERA, 2001). One model, the Canadian Global
Coupled Model (CGCM1) projected a dramatic increase in temperature for New England, 5.4°C in minimum annual average temperatures by 2100
(NERA 2001). The second model, by the Hadley Centre for Climate
Modeling and Analysis (HadCM2), was interpreted by NERA (2001) to project a less dramatic increase in minimum annual average temperatures, 3.2°C over the 21st century, but a 30% increase in regional precipitation (NERA., 2001).
Average annual temperature in New England has risen steadily in the last 150 years, increasing 2.91°C (5.23°F) since 1840. The rate of warming has increased since 1970 as average annual temperatures have
79 warmed 1.47°C (2.64°F), more than half the 150 year increase in 36 years
(Hayhoe et a/., 2006; Williams et a/., 2009).
Rising temperatures are projected to be accompanied by more rain, an increase in heavy precipitation, and periods of drought at times of the year when water shortages may significantly impact water supplies and agriculture(Hayhoe et a/., 2006). Climate change will also affect the timing of seasons with earlier bloom dates and leaf flush (Hayhoe et a/.,
2006).
This study explores whether such rapid change or new patterns in weather and climate have any affect on annual production of sugar and wood in maple.
The sweetness of maple sap is recognized by both sugar makers and scientists as an indicator of the tree's value and quality (Jones ef a/.,
1903; Taylor, 1956; Heiligmann ef a/., 2006). In the first studies of sap at the
University of Vermont, sugar maples produced sap that was 3.14% sugar and 3.44% sugar in 1900 and 1901, respectively (Jones et a/., 1903). The differences between sugar content from the same trees measured over two years was attributed then to differences in the growing season prior to the sap season. Sugar makers have understood, probably since the first native Americans boiled sap, that sweeter sap means more syrup or sugar in less boiling time. By the mid-1950s, Dr. Fred Taylor at UVM quantified this concept with his "Rule of 86" (Taylor, 1956). Taylor's rule states that 86
80 gallons of 1% sap evaporate down to 1 gallon of syrup. Sap of 2% sugar requires 43 gallons and 3% sap needs only 28.6 gallons of sap to make 1 gallon of syrup.
A number of indicators of change in the New England climate have already been identified. Ice out in northern New England now occurs 8 days earlier than it did in 1970 (Wake, 2007). The sap season begins approximately 8.2 days earlier and ends 11.4 days earlier than it did in
1970 (Perkins, 2007, Statement to House). Thus the season is approximately
3.2 days or 10% shorter (Perkins, 2007, Statement to House).
Increment wood cores are another historic record which may contain information about how trees respond to environmental conditions. Sugar maple growth, as measured in annual wood increments or ring widths, was first measured at UVM in 1900 (Jones ef a/., 1903).
Cores of 11 trees showed a range of tree ring width from 2.2 mm to 4.2 mm. Today researchers are investigating whether such growth will change as trees are stressed by climate conditions. Following the 1998 ice storm, as mentioned in Chapter IV, trees showed no change in average growth even when they lost as much as 50% of their crowns (Smith and
Shortle, 2003) In another study, however, reduced growth in tree rings was interpreted as a result of drought which caused shoot dieback in maples in Quebec (Payette et a/., 1996). Most recently, changes in tree ring size from 1900 and projected through 2080 are modeled to consider whether
81 trees will grow more wood with rising temperatures and increasing CO2 or grow less wood as weather patterns change (Goldblum and Rigg, 2005).
The hypotheses for this portion of the study include:
• Rising temperatures since 1970, will correlate with in a
decrease in sugar content of maple sap.
• Rising temperatures since 1970, will correlate with records of
start and end of sugar season.
• Stresses associated with climate change will correlate with a
reduction in average annual wood growth in maples.
Objectives
The objectives of this portion of the study include:
• Locate reliable and comparable sugar production records
from 1970 to present.
• Examine sugar production records and increment cores from
1970 to the present.
• Identify useful and practical measures for monitoring of
climate change by citizen scientists.
82 Methods
Temperature data
Data for the last four decades was obtained as a subset of the
United States Historical Climatology Network for Hanover, NH, station
273850 (Williams ef a/., 2009). These data are drawn from daily observations collected by the National Climatic Data Center's network of monitoring stations. Data are reviewed for accuracy, consistency and completeness and have been used by climate change scientists to monitor changes in temperature and precipitation since 1900 (Wake,
2007).
Sugar production data
Data was obtained from three sources.
The Hunter family of Tuftonboro, NH, has sugared for the past 150 years. They record sap volumes and syrup production annually. Records of production dating to 1972 include daily number of barrels of sap collected, gallons of syrup produced, first run dates and last run dates.
The Hunter records are of particular interest because this family continues to collect sap and make syrup in the same way they have for
150 years: they use buckets. Sap is poured from buckets into 30-gallon barrels. Volume from each of four sugarbushes is measured daily.
A second set of data was collected from Bascom Maple Farms,
Alstead, NH., the largest producer of maple syrup products in New
83 England. These data include number of taps, gallons of sap, sap per tap,
gallons of syrup produced and average sugar content for the last 9 years.
Third, sap to syrup ratios calculated by reports from producers in
New Hampshire, Vermont, Maine and Massachusetts were obtained from
the New England Agricultural Statistical Service. NEASS is a field office of
the National Agricultural Statistics Service, U.S. Department of Agriculture.
Reports are required by producers each April. Analysis of their reports as well as county by county and state anecdotal comments are reported each June by NEASS (Keough, 2009, Summary).
These data were analyzed in both Excel and JMP 8.0. Syrup figures are reported in gallons, the standard U.S. measure.
Wood Cores
In the late fall, each tree was cored with 16" 5.15 mm Suunto increment borer at breast height. Because of the density and hardness of sugar maples, the borer was assisted by a Jim-Gem Increment borer bit starter. Cores were glued and dried in wooden troughs. They were sanded with sandpaper ranging from 60 to 600 grade and buffed. Rings were measured to a precision of 0.001 mm using a binocular microscope and a measuring stage (Smith and Shortle, 2003).
Numerous problems were encountered in counting rings and initial counts of rings were set aside as inaccurate. In many cores, marginal parenchyma, which generally distinguish one year from the next, were
84 difficult or impossible to see. In other cores, so many marginal parenchyma lines, false rings, were present, it was impossible to identify false from true ring demarcations.
Ten cores, one from each plot, were selected for a recount. These cores were stained with iodine, an indicator of starch, to bring out marginal parenchyma. Cores for this recount were selected for strong evidence of marginal parenchyma. The remaining cores were saved for
SEM work or for chemical analysis in the future. Core measures were reevaluated and averaged in 10-year sections.
Because marginal parenchyma seemed to cause the problem in counting increments, SEM samples were made for examination of these cells. Samples were prepared from one healthy tree and one stressed tree on the hypothesis that healthy wood would show strong marginal parenchyma while stressed wood would not. The most recent wood was taken from cores. The wood was split laterally to provide radial views.
Wood samples were mounted on steel stubs and submitted to the SEM lab for preparation (Rock, 2009).
85 Results
Temperature
New Hampshire's annual mean temperatures have climbed steadily since 1840 (Williams etal., 2009) to an average temperature 2.91°C warmer today than the 5.14°C recorded 150 years ago (Table 5.1).
Temperatures warmed 1.1°C per decade in the 1800s, 0.34°C per decade between 1900 and 1970, 1.47°C per decade from 1970 to 2006. More than half of the increase since 1835 has occurred in the last 36 years.
Sugar Content
The sap-to-syrup ratio has changed significantly on the Hunter Farm since the 1970s when an average of 36 gallons of sap produced 1 gallon of syrup. In this decade an average of 44 gallons of sap are needed to produce 1 gallon of syrup with over 50 gallons needed in 2002, 2004, 2008, and 2009 (Figure 5.2), a significant trend (p=0.0038).
The Hunter sap-to-syrup ratio translates into less sugar. The percentage of sugar in sap was 2.39% in the 1970s, 2.37% in the 1980s,
2.13% in the 1990s, and 2.02% in this decade. These sugar content percentages are one-third to one-half the sugar content recorded at the
Proctor Maple Research Center (PRMC) in 1900 and the early 1950s (Table
5.2).
The sap-to-syrup ratio is also increasing in Vermont, New Hampshire,
Maine and Massachusetts, according to New England Agricultural Service
86 Statistics (Keough, 2009, Summary). Vermont showed a significant trend
from a mean of 39.2 gallons in the 1970s to a mean of 42.4 in this decade
(p= 0.0216) (Figure 5.3) Massachusetts and New Hampshire show some
increase but not enough to be statistically significant. Maine's sap to syrup
ratio has changed little since 1970. The 2009 season average regionwide was 44 gallons to one (Keough, 2009).
The Bascom Maple Farms provided data from 2000. Over the past 9 years, the sap has averaged 1.835% in sugar content, equating to 46.82 gallons of sap needed to produce 1 gallon of syrup (Bascom, 2008). The
Bascom average is 9% lower than the Hunter average for the decade,
2.02% sugar.
When sugar content and temperature are compared, both show a trend over the last four decades with a slightly steeper trend in average annual temperature (Figure 5.4). Temperature and sap ratios follow similar peaks and valleys in many recent years.
Other Historic Data
The first run of sap on the Hunter Farm of the season is occurring 5 to
10 days earlier than it did in 1970 (Figure 5.5). The Hunter Farm last day of the season occurs 2 or 3 days earlier than it did in the past(Figure 5.6).
Wood Cores
Core measures for each three years were averaged and very unusual outliers were removed, as done in Polak et al, 2006 and Smith and
87 Shortle, 2003. An ANOVA of these means by plot showed mean growth of
2.02 mm with no significant difference among growth in different plots
(p=>0.1006) (Figure 5.7). The ANOVA recalls plot analyses of spectral measures and leaf health. Trees in Plot 10, for example, which repeatedly show no stress here show the highest average wood production. Much older trees in Plot 9 show much smaller growth, a likely condition with great age. The ANOVA shows questionable figures for Plot 3 wood production. The highly stressed trees (813, 814, and 815) show a very high wood production.
A closer look at the tree ring measures showed many inaccuracies in measurement. The counts could not be correlated with dbh to estimate the age of the trees. Annual ring counts ranged from lows of less than
1.000 mm, exceedingly low, to highs of over 9.000 mm.
A century ago, sugar maple growth rings ranged from 2.2 to 4.5 mm with an average of 2.7 mm (Jones et a/., 1903). The 3-year averages of recent growth match that number. In some cases, this study's count of total cores also seemed appropriate, knowing the history of the sites. Ages calculated for Plot 2, Plot 3, Plot 6 and 7 met estimations of dbh and landowners' memory. Counts in other plots were too young or too old. A second count was done.
The iodine staining clarified marginal parenchyma, marking ring widths slightly. The rings were recounted and average annual growth was
88 calculated for each decade (Table 5.3). Annual growth ranged from a
low of 0.8 mm on Tree 811 in the 1970s to a high of 7.25 mm on Tree 826 in
the same decade. Tree growth increased on some trees decade to
decade. Growth declined in others. And one tree, Tree 833 maintained a
rate of 2.7 to 2.9 mm each decade.
Tree 815 continued to confound counting with innumerable false
growth rings and apparent growth rings. Annual growth was estimated
from the core length and the tree's dbh.
The new counts allowed for apparently accurate estimations of age
for these trees (Table 5.4). These ages agree with landowner recollections
and observations of land use in the plots.
The tree rings from Plot 3 (813, 814, and 815) and one tree in Plot 4,
Tree 818, showed similar staining across the years approximately 1973 to
1986. The stains indicate wounding, possible insect damage from a bark
borer which would have damaged the wood.
Parenchyma
Samples were taken from core 816, a tree which showed stress in
Chapter III, and from core 834, a tree which showed robust growth through the season in spectral measures (Figure 5.8).
Parenchyma cells and cambial tissue are approximately 15 pm wide at 855x (Figure 5.9). The cambial zone was torn and fibrous. Cells in the wood inside the parenchyma were crushed and torn even though the
89 sample appeared to have a smooth conjunction with bark when viewed with no magnification. Still, a fairly accurate measure of the width of the zone can be made. Details of the cells are not visible.
The band of parenchyma and vascular cambium tissue on Tree 834 was approximately 35 |jm wide with numerous pores, 850x (Figure 5.10). A closer look at Tree 834(Figure 5.11), at 520x, shows differences between the cells in the cambial zone. Cells in the cambial zone include vascular cambium cells, fusiform initials and ray initials (Figure 5.10, A and B). The longer rectangular cells to the left side of the cambial zone might be called the marginal parenchyma (Figure 5.11,D), adding another 10 |jm to the width of the band, the cambial zone (Evert, 2006).
90 Discussion
Temperature Increase
In the last 36 years, the mean average temperature has climbed
1.47°C (2.64°F). This increase matches or slightly exceeds the Hadley model for climate change in New England (Hurtt et a/., 2001).
The rapid increase in the 1800s might record the wide scale timbering in New Hampshire and heavy industrial development along the
Merrimack River during the 1800s. By 1900, records maintained by the
Society for the Protection of New Hampshire Forests show the state was denuded of all but 2 or 3% of its forests (Carlson and Ober, 2001). Since
1900, the forest has returned to New Hampshire. The forest might explain the slowing in the warming trend between 1900 and 1970. However, New
Hampshire's warming trend continued and grew steeper in the last four decades (Figure 5.1).
Sugar Content
The three modern records from the Hunter Farm, Bascom, and NASS show a clear drop in sap sugar content since 1950(Table 5.2). By those measures, the sap-to-syrup ratio a century ago was below 30 gallons to one. Sap averaged 3.13-3.44% sugar content in 1900 and 2.93% in 1950.
Today, sap sugar levels have dropped to 1.83% and 2.02%. The levels of sugar, those measured in buckets and those in vacuum tubing systems, are not that far apart.
91 Sugar concentration in maple sap varies tremendously from tree to tree, from day to day, and from year to year (Taylor, 1956). Percentages of sugar ranged from 1.8% on poor sites in northern Vermont to an occasional high of 8.4% in a study of 3400 trees on 10 sites conducted from 1944 to 1951 by the University of Vermont; year after year, the same trees consistently held the lead as top sugar producers (Taylor, 1956).
Such findings led maple researchers to conclude that trees could be selected for high sugar content and reproduced for plantings in sugar orchards (Taylor, 1956; Marvin, 1969; Staats et a/., 2008). Tests of sugar content in offspring of these experiments have shown a diminution in sap content over time even though test orchards vary significantly in soil and latitude (Baribault, 2009).
Some recent studies have dismissed sugar content as an indicator of tree health. Sweetness or a loss of sugar concentration might vary according to management practices in a sugarbush, and to crown size, crowding of trees or shading (Perkins, 2007). In a study of maple dieback in 1990-1992, researchers at PRMC found no correlation between damage to crowns and canopy transparency and sugar concentration in sap
(Wilmot, et a/, 1995).
Sugar making technologies make sugar content almost irrelevant to the sugar producer. Sap flows from the tree when atmospheric pressure is less than pressure within the tree. Vacuum pumps now allow sugar makers
92 to draw sap from trees even at night when the pressure gradient ordinarily stops sap flow. Sugar content below 2.0%, collected at night, is mixed with higher percent sugars from the day's run. The Bascom Maple Farms drew sap of 1.0% in the latter part of the 2009 season (Bascom, 2009).
Reverse osmosis technology also makes concern for low sugar content less important to the large scale commercial producer. Reverse osmosis forces sap through a filter system which retains sugar molecules and filters out smaller water molecules. The resulting concentrate of sap boils to syrup density in approximately half the time of untreated sap.
Such technologies, introduced and constantly upgraded in the past
20 years, make comparisons of current sap sugar content with historic sap sugar content difficult (Bascom, 2008). Measures of sap sugar content also are difficult to compare year to year because producers annually vary the number and type of taps they use, change tubing, add new young trees or retire old trees (Bascom, 2008).
Bascom Maple Farms does maintain careful records of the number of taps on each of 16 to 21 sugarbushes they own or lease, the number of gallons of sap collected from each orchard, and a consequent sap-to- tap ratio. The number provides Bascom with an annual sap sugar content average. Compared to early measures of sugar content, 3.14% sugar in
1900, and 3.44% sugar in 1901 (Jones et a/., 1903), the Bascom number,
1.835%, appears extremely low.
93 Bascom and other commercial producers use such information to manage their sugarbushes. Rather than compare one year to the past, they use the sap to syrup ratio to show that one sugarbush is producing more than another. In 2008, for example, a sugarbush identified in Bascom records as the Glenn's Tank sugar bush produced 23.69 gallons of sap per tap over the season compared with only 12.19 gallons from a sugarbush called Camp Good News. Such information guides the Bascoms in thinning sugarbushes, fertilizing, or cutting out old trees (Bascom, 2008). Or it may indicate that equipment used on the Glenn's Tank sugar bush is more effective.
The New England Field Office of the National Agricultural Statistics
Service has collected data on the number of taps sugar producers set and the gallons of syrup produced since 1918. These data produce a yield per tap figure similar to the Bascom's figures. From this, the NEASS office calculates an annual sap to syrup ratio and estimate of sugar content.
Because of the increasing use of vacuum pump systems, these longterm figures show a reduction in sugar content just as the Bascom data shows: sap of lower sugar content is deliberately being extracted from the trees.
All four states reported in these statistics show a slight trend toward lower sugar content.
The conflict which technology gives to the accuracy of records may be great enough to contradict modern sugar content measures. It is
94 possible that maple trees contain as much sugar as they did 60 years ago.
Only the Hunter record, collected by the same method as in the past and comparing volume of sap to volume of syrup, provides a clear trend. One sample is insufficient for any conclusion.
The change in sugar content would be a major one for a maple producer. When the sap-to-syrup ratio was 30, to produce one gallon of syrup, the sugar maker boiled away 29 gallons of water. Today, the
Hunters must evaporate more than 44 gallons of water to produce the same gallons of syrup. That increase means longer boiling times, more wood fuel in the evaporator, more hours of labor and a more costly product. Longer boiling time generally reduces the grade of sugar, darkening syrup color and value, (Heiligmann, 2006).
The decrease would also be significant for sugar maples. If the sap is less sweet and more watery, the trees may be using more sugar to drive metabolism or they may be producing less sugar due to changes in photosynthesis rates. In the first studies of sugar maples at Proctor, Jones et al. (1903) estimated that a tree carrying 135 pounds of sap on a spring day would carry 35 pounds of sugar, if it were 3% sap. Today, the Hunters'
2% trees may carry only two-thirds that much sugar. This means a significant loss of glucose and sucrose for growth and metabolism..
The decrease in sugar content, if present, parallels rising temperatures in New England. However, without more accurate
95 measurements of sugar content, the hypothesis cannot be supported.
While it may not be correlated with climate change, a loss of sugar content would indicate the presence of a ubiquitous longterm stressor.
Seasonal Change
The hypothesis is supported. The earlier first run at the Hunters matches the 8 day shift in seasons noted at PRMC (Perkins, 2007,
Statement to House). The earlier ending of the season noted by the
Hunters, though less than 11 days noted by Perkins (2007, Statement to
House), points to the same trend. The Hunter Farm sets its dates as much by custom as by weather. Even if the weather is warm enough for the sap to run in February, the Hunters have historically waited to tap until Town
Meeting, in the first week of March (Rollins, 2007). If this farm followed seasonal temperatures rather than the calendar, the change in sap season might be even greater.
The NEASS also records start and end dates of the season. In 2008, the sap season began January 6 on one farm in Connecticut and ended as late as May 4 in Vermont. The annual reports include anecdotal comments from producers such as one Carroll County, NH, sugar maker's comment: "Too cool in the beginning and then later it was too hot
(Keough, 2008). These data, an archive that begins in 1918, though skewed by latitude and human custom, provide phenological data which might be useful in studies of climate change.
96 Wood Cores
The wood cores reflect changes in growing conditions, decade to
decade (Table 5.3). But rising temperatures cannot be identified as the causal agent for those changes. Farm management is much more evidenced in the ring measures. The hypothesis is not supported.
Tree 811, for example, shows vigorous growth in the 1950s with an average ring width of 3.6 mm (Table 5.3). Ring widths decreased to 0.9 mm in the 1960s and 0.8 mm in the 1970s. Growth was 2.7 mm in the 1990s and then declined this decade to 1.4 mm.
Plot 2 on Range View Farm was not managed as a sugarbush until logging occurred in 2006. During the 1960s and 1970s, the lot was densely stocked with white pine which grew rapidly and exceeded the height of
Tree 81 l's canopy in the 1960s. The pines were logged off in the late 1970s and Christmas trees were planted. Dense mature fir did not shade Tree
811 but probably did compete with it for water and nutrients. Growth of this tree rebounded to 2.7 mm in 2008, an indication that the tree is responding to the thinning and clearing of the plot (Table 5.2).
Management can also be seen in Plot 10. Tree 835 (Table 5.2) showed decadal growth of 3.8 mm in the 1950s and similar 3.35 mm in the
1990s and 3.5 mm in the 2000s. Growth dropped to 1.93 mm in the 1970s.
This plot, a mountain pasture, grew densely in the 1950s and 1960s, each
97 tree competing with its neighbors. The plot was thinned in the late 1970s
and growth rebounded.
A lack of thinning in the forest is the probable cause of slowing growth in Plot 1, Tree 801, Plot 4, Tree 817 and Plot 6, Tree 824.
Consistent growth occurred decade after decade in Tree 826, Plot
7, and Tree 833, Plot 9. Plot 7, a pasture, has been regularly thinned by its owner, giving trees here full canopy space. Plot 9 includes trees in an historic family graveyard and on a farmyard stone wall. These trees also have room for full canopy development and have had such space consistently for decades.
This study of increment cores taken from different landowner plots demonstrates that experimental forests, such as those at PRMC, have the advantage in any study of one factor and its effect on tree health. Tying climate change to wood growth would require tests in experimental plots where all other conditions are the same.
Iodine staining was of little value in this study. The cores in this study were taken in late October and early November when starch reserves would have been resynthesized as sugars (Wong ef a/., 2003). Instead of using iodine as a stain for identifying wood parenchyma tissue, a future study using differential stains that identify soluble sugars, applied in the field as cores are removed from the trees, is recommended.
98 Discussion of Parenchyma.
The difficulty in reading the rings, however, opened a new chapter on parenchyma. The marginal parenchyma cells are formed at the end of the growing season just inside the vascular cambium. In the fall, as the vascular cambium becomes dormant, partially formed fusiform initials will become marginal parenchyma (Shortle, 2009).
These cells form a sheath around the stem of the tree where starch and sugars are stored for export to the growing cambium early in the spring. They may also provide sugars to xylem vessels, creating an osmotic gradient to aid in early transport of water to the leaves (Carlquist et a/.,
1985). Starch to sugar hydrolysis may also assist in protecting the cambium from freeze damage during dormancy (Evert, 2006). Thus, more parenchyma cells are advantageous for coping with future stress.
Release of sugar into the xylem of sugar maples in spring depends on the respiratory enzymes and activity of axial and radial parenchyma in surrounding the vessel elements (Sauter, et a/., 1973). A recent study of parenchyma measured the respiration rates of these cells in conifers and hardwoods (Spicer and Holbrook, 2007) finding that in sugar maple, parenchyma cells in rings 35 years old had the same respiration rate of younger cells. These cells synthesize complex polyphenolics, produce cellulose, secrete gums, and deposit lignins in wood as it transitions from sapwood to heartwood which no longer transports water (Spicer and
99 Holbrook, 2007). The parenchyma cells are the site of exchange between symplast and apoplast of woody tissue, storage of carbohydrates, transport of sugars and wound response (Spicer and Holbrook, 2007).
Trees which consistently measure higher sugar content in sap had significantly higher volume of vascular rays in twigs (Morselli etai, 1978). A subsequent analysis found no correlation between sap sweetness and volume of ray tissue in sugar maple wood (Garrett and Dudzik, 1989).
Further study might clarify whether axial parenchyma shows the same differences in volume as the Morselli study found in twigs.
Cambial growth is controlled in part by auxin which increases in concentration in spring and decreases in autumn (Evert, 2006). Leaf abscission is also controlled in part by auxin. Eighty percent of the trees in this study lost their leaves 2 to 3 weeks before the normal end of the season. If auxin levels dropped enough for leaves to abscise earlier, then cambial cell division would also have slowed or stopped two to three weeks earlier. The growth of wood would be limited in those trees compared with growth in healthy trees still in leaf. Limited trees will still develop marginal parenchyma, out of the last dividing cells in the cambial zone (Shortle, 2009). SEM photos indicate, however, that the zone and hence the width of marginal parenchyma may be limited in stressed trees.
100 While the width of the annual wood increment may or may not have been changed by stresses seen in the spectral scans, the marginal parenchyma and cambial zone might have been affected. A loss of volume in parenchyma would have consequences for continued healthy function and spring flow of sugars in these trees.
Like the pollen analysis in Chapter IV, this examination of two wood cores is too limited to draw any conclusions.
101 Conclusion
Historic records of sugar content and wood increment cores in sugar maples cannot be correlated with climate change. The rejection of these hypotheses indicates that climate change is subtle, consisting of impacts beyond temperature alone, and that evidence of its effects on trees lie in more sophisticated measures.
Key findings include:
• Sugar content appears to have declined from 3.1-3.4% in the
early 1900s to 1.98-2.02% currently. Such a trend would
suggest a ubiquitous longterm stressor affects sugar maples at
many different latitudes on varying sites managed in multiple
ways. New technologies in sugar production, however, make
verification of such a trend difficult.
• Records of beginning and end of sap season parallel
projections of phenologic changes in New England which
have been projected for climate change.
• Changes in wood increment cores are likely the result of
differences in management history of sites rather than climate
change.
The objectives of this portion of the study were not met. Accurate and consistent records were not found. Historic measures of sugar
102 content in maple sap and wood increments do not appear useful in
monitoring climate change, at least using current methods.
Continued monitoring of sap sugar could develop a useful measure of stress in maple. Further declines in sugar content would suggest the continued presence of a regionwide stress factor. To obtain useful data, sugar producers would need a standardized protocol for collection of sap at midday, when normal negative pressure allows natural flows of sap.
Increment cores collection would not appear to be technique that is practical for citizen scientists. Cores are difficult to obtain and difficult to read. It might be more instructive to students to examine whole wood disks which sugar producers might provide schools as they cull maples from their sugarbushes.
103 CHAPTER VI
CONCLUSION
Hypotheses
This study concludes the following about its 3 hypotheses:
• Stress can be detected in Acer saccharum with simple
measures.
Spectral measures find that 80% of trees in 5 different sugar bushes in the Bearcamp Valley of New Hampshire were stressed in the summer of
2008 by some factor, perhaps drought in early spring, perhaps heavy rains in mid-summer, perhaps both.
Anatomical studies of leaves confirm spectral measures of stress but found that despite high stress, 73% of trees produced excellent buds.
Historic records indicate that sap may be less sweet than it was 40 years ago or a century ago. This change, if accurately measured, parallels rising temperatures in New Hampshire. Study of the maple's history in incremental cores did not find environmental stress.
• Indicators of stress identify possible causes of stress.
104 Spectral measures of leaves and anatomical study of leaves and
buds suggest drought and possibly unusually heavy rains in the 2008 growing season as possible causes of stress.
These stresses may be cumulative with other stresses in tree history such as limited management, poor site conditions and pest infection.
Study of increment cores were particularly telling of sugarbush management.
• Indications of stress describe how the maple responds to
stress.
During the 2008 growing season, stressed trees abscised leaves to reduce seasonal stress. All trees produced at least some viable buds and half of the trees produced only buds of the highest quality.
105 Objectives
• Numerous tools were assessed as to their usefulness in
measuring stress which may attend climate change.
Three spectral measures by VIRIS are useful tools for measuring stress which may attend climate change.
The Munsell Color Charts are not useful.
Anatomical measures of buds and leaves are useful.
Study of pollen and wood parenchyma might prove useful, with further study, as tools for measuring climate change stress in maples.
Study of sap sugar content may prove useful.
Study of increment cores, while instructive of tree history, would not be useful as a tool for investigate climate change in this sort of study.
This study indicates in several ways that the sugar maple is an ideal species for study of climate change. Acer saccharum buds, six-leafed shoots, and high fall foliage color offer baseline spectral, anatomical and physiological features against which stress can be measured. In addition, this species is managed in monocultural stands by sugar producers across the tree's entire range. Even small sugarbushes such as Range View grow sugar maples in large enough plots to monitor with Landsat 30 x 30m resolution.
• Many of the measures and data collection practices used in
this study would be useful to citizens, students and teachers,
106 maple sugar producers and other members of the public who
wish to monitor and study climate change.
Measurements of bud quality, leaf size and color, and recording of
change in leaf health are simple yet useful measures of stress in sugar
maple. Both children and adults could easily use these measures, record and report their findings. These citizen scientists might also collect samples of buds, leaves, and sap, photographs and historic records of sugar production for analysis at the university level. A collaborative of citizens and scientists might obtain valuable data about sugar maple health and its response to climate change. Such a program would educate many citizens about climate change and how a major species in this community is responding to climate change and its concomitant stresses.
107 Recommendations
Continue Monitoring
Monitoring of the 30 trees on the 5 Bearcamp Valley sugarbushes should continue.
Improve Laboratory Protocols
Laboratory measures of spectral properties of leaves, size of leaves, and bud health should be continued. Wet weight/dry weight of leaves should be added to these measures. Thin sections of leaves and buds should be made to examine cells for damage by stressors. Protocols for archiving samples, slides, photographs, data, wood cores and statistical analyses must be developed. Digital photography should replace the
Munsell Color Charts. Statistical analysis should be improved, especially for change over time in biological indicators.
Expand Study
Additional sites should be identified for the study. A statewide selection of sugar bushes would offer trees on different soils, aspects, and elevations, trees of varying age and management history. A dozen members of the New Hampshire Maple Producers Association have volunteered their maple stands for study. On these farms, a standardized measure of sugar content could be developed. Curriculum for involving schools should be developed.
108 LIST OF REFERENCES
109 LIST OF REFERENCES
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118 APPENDICES
119 APPENDIX A
TABLES
120 Table 2.1: Precipitation and temperatures for 2008 in the Bearcamp Valley compared with the norm as measured for 35 years by local weather obser ver Rod Weinberg (Weinberg, 2009). Starred* items were drawn from 2007 archives. Temperatures are given in inches and degrees F as provided by the source. Conversion of annual totals were added.
Month Precip. Normal High Low Avg Normal (in.) Precip. Temp. Temp. Temp. Temp (°F.) (°F.) January 2.76 4.1" 30.7 15.2 27.9 23.2 February 8.13 3.14* 31.2 15.6 27.9 26.3 March 5.75 4.02 37.5 20.5 29.0 31.0 April 4.34 3.98 55.7 34.0 44.8 43.1 May 1.10 4.33* 67.2 42.3 54.7 53.9 June 5.19 4.13 76.8 56.5 66.6 63.9 July 6.54 4.34 80.7 59.7 70.2 68.4 August 7.94 4.33 74.4 56.4 65.4 66.6 September 7.94 4.12 68.4 50.6 59.5 57.4 October 3.97 4.48 55.3 36.8 46.0 46.0 November 6.57 4.37 41.9 29.8 35.8 35.7 December 6.17 4.19 31.7 16.4 24.0 24.0 Year 66.40 49.53 45.98 45.9 Conversion 1686.6 1258.1 7.8° C. 7.7° C. mm mm
121 Collection Date Expectation April 2-April 8 Spring buds coming out of dormancy April 22 Buds swelling May 30 Near-full leaf extension July 30 Height of canopy density August 28 Near end of growing season September 15 First signs of senescence September 29 Early abscission October 4 Expected first color of fall Late Oct.-Nov. Wood cores and fall buds
Table 2.2. Collecting dates of buds and leaves were selected based on the literature (Olmstead, 1951; Wong ef a/., 2003; Richardson ef a/., 2006) to see different phenologic points in the growing season. Wood cores and fall buds were harvested after the growing season and before dormancy.
122 Plot Trees Farm Lat./Long. Slope Aspect Elev. Owner 1 801,803,804 Carlson 43°48,546771°2r53" 4% South 750'
2 808,811,812 Carlson 43°48'652771°2r57" 4% North 740'
3 813,814,815 Googin 43°57'62771°23'57" 10% East 775'
4 816,817,818 Googin 43°57'62771°23'52" 8% East 722' 5 820,821,822 Hunter 43°43,57"71°17'96" 2% SW 670 6 823, 824, 825 Hunter 43°4376771°18'10" 2% SW 696' 7 826, 827, 828 Bickford 43°50,n771°20'93" 0% South 615' 8 829, 830, 831 Bickford 43°50'15771o20'99" 0% South 615' 9 832, 833, 834 Burrows 43o44'52771°2r74' 5% West 830" 10 835, 836, 837 Burrows 43°44'48771°2r6r 10% West 955'
Table 2.3: Plot data for the 10 sites studied.
123 Plots Description 1,2,3,6, Hermon, very stony, fine sandy 7,9 loam
4 Berkshire, very rocky fine sandy loams 5 Hinckley, excessively drained, glacial outwash
5 Scituate, moderately well- drained 7 Ondawa, floodplain, sandy and gravel 8 Colton, fine gravelly loam 10 Beckett, very stony
Table 2.4: Soils found on the 10 plots (USGS, 1977).
124 Plot Regeneration Groundcover Tree Indicator Indicator Species Species 1 Dense purple trillium 2 Moderate purple trillium white ash 3 Moderate basswood 4 Moderate blue cohosh basswood 5 Thin white ash 6 Moderate blue cohosh 7 Thin 8 Moderate wood nettle 9 Thin 10 Dense
Table 2.5. Plot Soils and High Quality Site Indicators.
125 Plot Tree DBH DBH Hgt. Hgt. Canopy Estimated Tag In. Cm Ft. M % Age of 1 No. Density Selected Tree 1 801 20" 50 65' 19.8 50% 66 1 803 20" 50 75' 22.9 50% 1 804 15" 38 74' 22.6 50% 2 808 17" 43 65' 19.8 80% 2 811 25" 63 72 21.9 60% 105 2 812 16" 41 61' 18.6 60% 3 813 35" 89 92' 28.0 50% 3 814 24" 61 86' 26.2 70% 3 815 24" 61 84' 25.6 60% 146-205 4 816 18" 46 78' 23.8 70% 4 817 11.5" 29 70' 21.3 70% 61 4 818 23" 58 68' 20.7 60% 5 820 14" 36 64' 19.5 60% 5 821 22" 56 52' 15.8 70% 65 5 822 16" 41 60' 18.3 60% 6 823 10" 25 80' 24.4 70% 6 824 16.5" 42 72' 21.9 80% 83 6 825 24" 61 72' 21.9 5% 7 826 23" 58 72' 21.9 85% 45 7 827 23" 58 80" 24.4 80% 7 828 20" 51 72' 21.9 80% 8 829 47" 119 96' 29.3 60% 8 830 25" 64 96' 29.3 70% 103 8 831 17" 43 76' 23.2 70% 9 832 25" 64 94' 28.6 50% 9 833 28" 71 80' 24.4 60% 105 9 834 40" 102 80' 24.4 60% 10 835 24" 61 88' 26.8 80% 86 10 836 14" 36 68' 20.7 70% 10 837 16" 50 68' 20.7 70%
Table 2.6: Individual Tree Measurements
126 Plot Avg. Basal Rec.Max. Avg. Basal Rec.Max. dbh Area Basal dbh Area Basal (inch) (ftVac) Area (cm) m2/ha Area ftVac m2/ha 2 6 26 38 15.2 5.97 8.7 5 9 73 58 22.9 16.75 11.7 1 11 56 70 27.9 12.85 16.1 6 11 130 70 27.9 29.84 16.1 4 12 60 75 30.5 13.77 17.3 3 13 76 82 33 17.44 18.8 10 14 16 96 35.6 3.67 20.5 7 18 40 103 45.7 9.18 23.7 8 18 40 103 45.7 9.18 23.7 9 26 30 110+ 66 6.89 25.2
Table 2.7: Basal area by plot compared by average dbh and maximum desireable basal area in square feet/acre as recommended by North American Maple Syrup Producers Manual (Heiligmann et al., 2006). The figures show that trees in Plots 5 and 6 are overcrowded. Trees in Plots 1 and 3 are due for thinning. Trees on other plots have ample room to develop full canopies.
127 Unstressed = 1 Stressed =2 REIP > 715.00 < 715.00 TM5/4 <0.55 >0;55 NIR3/1 <0.90 >0.90 Munsell Color >18 <18
Table 3.1. Stress levels are selected for this study to allow for comparison of trees and different measures on a 1 to 2 scale. 1 will represent no stress. 2 will represent stress. Each spectral measure is defined above at the threshold when stress is identified.
128 Munsell Color Rank Health 2.5Y, 7/10 1 2 2.5GY, 8/8 2 2 2.5GY,8/10 3 2 2.5GY, 7/8 4 2 2.5GY, 7/10 5 2 5GY.7/10 6 2 2.5GY,6/6 7 2 2.5GY,6/10 8 2 2.5GY/6/8 9 2 5GY,6/10 10 2 2.5GY,5/8 11 2 2.5GY,5/6 12 2 2.5GY, 5/4 13 2 5GY,5/10 14 2 5GY, 5/8 15 2 5/GY, 5/6 16 2 5GY, 5/4 17 2 5GY, 4/8 18 5GY, 4/6 19 5GY, 4/4 20 5GY, 3/4 21 7.5GY, 5/4 22 7.5GY, 4/6 23 7.5GY, 4/4 24 7.5GY, 4/2 25 7.5GY, 3/4 26 7.5GY, 3/2 27
Table 3.2. Ranking Munsell Color Chart values found in this study. From top to bottom, the colors show darker hues of green-yellow, 2.5 to 5 to 7.5. Secondary numbers indicate lighter to darker values and dull to brighter chroma. This study found 27 different values. These were assigned a 2 for stressed, pale or fading colors, and a 1 for rich and dark green colors which indicate no stress.
129 Sampling Day of Growing Date Season Days Between Samplings April 20 1 0
May 30 41 41
July 30 102 61
Aug. 28 131 29
Sept. 15 149 18
Sept. 29 163 14
Sept. 30 163 14
Table 3.3: Days of season and growing days between each sampling date. Grow days for different VIRIS readings were calculated as follows: If a tree showed an improvement or at least maintained a measure, such as REIP, in the no-stress level (above 715 nm for REIP), the days between samplings are counted. If a tree's measures fell into the stress zone, below 715 nm for REIP, those days between samplings were not counted. Each VIRIS measure and the Munsell Color rankings were assessed for grow days. Figure 3.11 B presents the first of these time series analyses.
130 TM5 4 TM5 4 TM5 4 Septe m Auaus t Munsel l Munsel l Munsel l REI P Leave s NIR3 1 REI P Leave s NIR3 1 REI P NIR3 1 oo Z =} 70 CD c 5SQ3 0 c_ s- - < m C- TO ft — Q c 3 CO <£ "0 CD < Cn < co £ -o CD" co __. -N CO D CD CO CO 3 CD o o CD to I— cr cr i- oo CD CD CD CD Q —^ —^ (— Q tO . CD < NO Cn Q CD < 5GY,4 / Cn Cn < Cn co Cn CD to
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5GY, 4 Cn Cn Cn V| O O o O VI o O O O VI TO O O ON O VJ -< -< O O IO '•o Cn 00 oo V bo p Cn oo bo Cn oo bo J^. \*J yji i\ o***Jo ON 00 Cn £ 00 •^ IO 00 V| Cn •N bo Ln —• Ln —> -^ to —' IO NO *«. ON Cn •I** 00 K> !N VI CO VI ON NQ IO 4*. —' 00 NQ NQ 'ji. —• 00 CN NQ ON -J
tI.5GY5 / o IO Cn Cn 10 Cn O to Ln Cn ON VJ V| O _-< o O O o O O 0. 5 O vi vi 70 ON O O -< ON 0 r" P -< bo In 00 NO ON O bo P Cn g 00 Cn ON ^ 00 C-n< oo oo Cn 1 O ON NO V| IO Cn oo to 00 Cn y — 00 to Cn 00 VI 2 00 Cn S3 —• tO CN NO VI IO •N VI CO ON VJ Ji. -K IO O -N bo co to CN VJ *> oo to IO ON IO Table 3.3B: Measured Values for Trees in Plots 3 and 4
April Buds Plot 3 Plot 4 813 814 815 816 817 818 REIP 697.6 696.1 696.1 696.1 696.1 697.6 TM54 0.521 0.613 0.626 0.651 0.639 0.566 NIR31 0.873 0.943 0.931 0.965 0.947 0.96 Munsell 2.5R,4/6 2.5R,4/4 2.5R,4/6 2.5R4/6 2.5R/4.6 2.5R,4/6 May 30 Leaves 813 814 815 816 817 818 REIP 725.4 723.9 703.8 703.8 723.9 725.4 TM54 0.635 0.626 0.605 0.556 0.629 0.569 NIR31 0.884 0.875 0.88 0.841 0.893 0.856 Munsell 5GY,4/8 5GY,4/8 5GY,5/6 5GY,5/6 5GY,4/6 5GY,4/6 July 30 Leaves 813 814 815 816 817 818 REIP 723.2 725.4 727 719.3 725.4 728.5 TM54 0.66 0.626 0.619 0.574 0.607 0.583 NIR31 0.913 0.881 0.888 0.865 0.885 0.887 Munsell 7.5GY4/6 7.5GY4/6 7.5GY4/6 5GY,5/8 7.5GY4/4 7.5GY4/4 Auaust 28 Leaves 813 814 815 816 817 818 REIP 722.4 723.9 723.9 702.3 723.9 722.4 TM54 0.685 0.692 0.62 0.606 0.644 0.605 NIR31 0.941 0.95 0.894 0.926 0.89 0.897 Munsell 7.5GY4/4 7.5GY4/4 7.5GY4/4 2.5GY5/6 5GY,4/6 5GY,4/6 September 15 Leaves 813 814 815 816 817 818 REIP 706.9 703.8 705.4 700.7 708.5 719.3 TM54 0.746 0.778 0.699 0.626 0.699 0.694 NIR31 0.966 1.016 0.964 0.909 0.959 0.968 Munsell 7.5GY4/4 5GY.4/6 5GY.4/6 5GY.5/6 5GY.4/6 7.5GY4/6 September 29 Leaves 813 814 815 816 817 818 REIP 693 694.6 694.6 691.5 694.6 700.7 TM54 0.59 0.806 0.729 0.686 0.716 0.709 NIR31 0.976 1.035 0.991 0.974 0.996 0.995 Munsell 2.5Y8/10 5GY.5/6 5GY.5/6 2.5Y8/10 2.5GY6/8 5GY.5/6
132 Table 3.3C: Measured Values for Trees in Plots 5 and 6
April Buds Plot5 Plot 6 820 821 822 823 824 825 REIP 696.1 696.1 697.6 697.6 703.8 696.1 TM54 0.671 0.742 0.699 0.635 0.554 0.646 NIR31 0.988 1.037 1.026 0.906 0.907 0.968 Munsell 2.5R,4/4 2.5R,4/8 2.5R4/6 2.5R,4/8 2.5R,4/6 2.5R,4/6 Mav 30 Leaves 820 821 822 823 824 825 REIP 705.4 702.3 703.8 725.4 727 722.4 TM54 0.555 0.579 0.572 0.623 0.581 0.552 NIR31 0.844 0.845 0.854 0.89 0.861 0.844 Munsell 5GY,4/8 5GY7/10 5GY,5/6 5GY,5/8 5GY,4/8 5GY,4/6 July 30 Leaves 820 821 822 823 824 825 REIP 725.4 703.8 727 725.4 728.5 723.9 TM54 0.569 0.546 0.59 0.518 0.589 0.644 NIR31 0.887 0.887 0.881 0.816 0.871 0.886 Munsell 7.5GY4.4 2.5GY5/8 7.5GY4/6 7.5GY3/4 7.5GY3/4 7.5GY4/6 Auaust 28 Leaves 820 821 822 823 824 825 REIP 720.8 703.8 706.9 723.9 730.1 723.9 TM54 0.583 0.615 0.592 0.538 0.604 0.664 NIR31 0.868 0.88 0.878 0.87 0.878 0.895 Munsell 5GY,4/8 5GY,5/6 5GY,4/8 5GY,3/4 5GY,3/4 5GY,4/6 September 15 Leaves 820 821 822 823 824 825 REIP 723.9 702.3 708.5 725.4 723.9 723.9 TM54 0.665 0.625 0.599 0.632 0.637 0.71 NIR31 0.927 0.917 0.897 0.926 0.935 0.923 Munsell 7.5GY5/4 5GY.5/6 5GY.5/4 7.5GY3/4 7.5GY3/2 5GY.4/8 September 29 Leaves 820 821 822G 823 824 825 REIP 702.3 700.7 700.7 699.2 700.7 700.7 TM54 0.602 0.573 0.615 0.712 0.735 0.662 NIR31 0.88 0.896 0.916 1.001 0.989 0.902 Munsell 5GY.4/8 2.5GY6/8 2.5GY5/8 5GY.4/8 5GY.6/10 2.5GY6/10
133 Table 3.3D: Measured Values for Trees in Plots 7 and 8 April Buds Plot 7 Plot 8 826 827 828 829 830 831 REIP 700.7 696.1 702.3 696.1 702.3 697.6 TM54 0.553 0.775 0.682 0.642 0.663 0.632 NIR31 0.958 1.101 1.027 1.066 1.023 0.988 Munsell 2.5R,4/6 2.5R,4/6 2.5R.4/8 2.5R/4/8 2.5R,4/6 2.5R,4/8 Mav 30 Leaves 826 827 828 829 830 831 REIP 730.1 722.4 705.4 719.3 722.4 705.4 TM54 0.612 0.546 0.591 0.592 0.621 0.591 NIR31 0.887 0.853 0.876 0.867 0.863 0.873 Munsell 5GY,4/4 5GY,4/6 5GY,5/4 5GY,4/8 5GY,4/6 5GY,4/8 July 30 Leaves 826 827 828 829 830 831 REIP 725.4 724.7 725.4 725.4 724.7 725.4 TM54 0.565 0.567 0.588 0.599 0.579 0.629 NIR31 0.874 0.866 0.867 0.877 0.876 0.891 Munsell 7.5GY3/4 7.5GY4/4 7.5GY4/4 7.5GY3/4 7.5GY4/4 7.5GY4/4 Auaust 28 Leaves 826 827 828 829 830 831 REIP 730.1 725.4 722.4 725.4 719.3 722.4 TM54 0.573 0.597 0.6 0.621 0.621 0.645 NIR31 0.886 0.872 0.885 0.888 0.904 0.926 Munsell 5GY,3/4 5GY,3/4 5GY,4/4 7.5GY4/4 7.4GY4/4 7.5GY4.4 September 15 Leaves 826 827 828 829 830 831 REIP 730.1 719.3 708.5 727 723.9 725.4 TM54 0.672 0.665 0.667 0.642 0.675 0.68 NIR31 0.932 0.956 0.948 0.917 0.925 0.947 Munsell 7.5GY3/4 7.5GY4/4 7.5GY4/4 7.5GY4/4 7.5GY3/4 7.5GY4/4 September 29 Leaves 826 827 828 829 830 831 REIP 723.9 702.3 697.6 705.4 705.4 700.7 TM54 0.65 0.756 0.601 0.667 0.686 0.744 NIR31 0.937 1.03 0.92 0.932 0.952 0.975 Munsell 5GY.3/4 5GY.4/8 2.5GY5/8 5GY.4/8 5GY.4/6 5GY.4/8
134 Table 3.3E: Measured Values for Trees in Plots 9 and 10 April Buds Plot 9 Plot 10 832 833 834 835 836 837 REIP 697.6 700.7 697.6 694.6 696.1 696.1 TM54 0.506 0.543 0.616 0.661 0.631 0.604 NIR31 0.906 0.889 0.965 1.05 0.946 0.934 Munsell 2.5R.4/10 2.5R,5/8 2.5R,4/6 2.5R,4/4 2.5R,4/6 2.5R,4/6 May 30 Leaves 832 833 834 835 836 837 REIP 723.9 728.5 725.4 722.4 728.5 723.9 TM54 0.529 0.576 0.538 0.583 0.595 0.589 NIR31 0.839 0.83 0.831 0.853 0.854 0.844 Munsell 5GY,4/8 5GY,4/6 5GY,4/8 5GY,4/6 5GY,4/6 5GY,4/8 July 30 Leaves 832 833 834 835 836 837 REIP 722.4 725.4 722.4 723.9 722.4 731.6 TM54 0.564 0.558 0.592 0.639 0.616 0.589 NIR31 0.861 0.857 0.876 0.886 0.878 0.874 Munsell 5GY4/6 7.5GY3/4 7.5GY4/4 7.5GY4/4 7.5GY4/6 7.5GY4/4 Auaust 28 Leaves 832 833 834 835 836 837 REIP 722.4 727 723.9 730.1 727 703.8 TM54 0.597 0.541 0.621 0.626 0.608 0.575 NIR31 0.871 0.862 0.89 0.909 0.885 0.87 Munsell 5GY,4/8 5GY,4/4 7.5GY4/4 7.5GY4.4 7.5GY4/4 5GY,4/6 September 15 Leaves 832 833 834 835 836 837 REIP 716.2 730.1 723.9 723.9 719.3 722.4 TM54 0.545 0.591 0.643 0.663 0.647 0.597 NIR31 0.885 0.918 0.913 0.903 0.921 0.867 Munsell 7.5GY4/4 7.5GY3/4 7.5GY4/4 7.5GY4/4 7.5GY4/4 7.5GY4/4 September 29 Leaves 832 833 834 835 836 837 REIP 723.9 730.1 725.4 720.8 723.9 706.9 TM54 0.538 0.586 0.553 0.647 0.596 0.646 NIR31 0.871 0.88 0.868 0.905 0.892 0.907 Munsell 5GY.4/6 5GY.3/4 5GY.3/4 5GY.4/8 5GY.4/6 5GY.4/8
135 Table 3.5: VIRIS indices and Munsell Color ratings for Tree 826 throughout 2008.
April May July August Sept. 15 Sept. 29 Oct. 4 REIP 700.7 730.1 725.4 730.1 730.1 723.9 702.3 TM5/4 0.553 0.612 0.565 0.573 0.672 0.65 0.729 NIR3/1 0.958 0.887 0.874 0.886 0.932 0.937 0.989 Munsell 5GY,4/4 7.5GY,3/4 5GY,3/4 7.5GY,3/4 5GY,3/4
136 Table 3.6: VIRIS and Munsell Color ratings for Tree 822. Note that readings were taken on a green leaf and a red leaf on September 29. All leaves had dropped or were red by October 4 and no readings were done.
April May July August Sept. 15 Sept. 29 Sept. 29 Green Red REIP 697.6 703.8 727 706.9 708.5 700.7 691.5 TM5/4 0.699 0.572 0.59 0.592 0.599 0.615 0.56 NIR3/1 1.026 0.854 0.881 0.878 0.897 0.916 0.909 Munsell 5GY,5/6 7.5GY,4/6 5GY,4/8 5GY,4/4 2.5GY,5/8 10R.5/10
137 REIP TM5/4 NIR 3/1 Munsell
REIP -0.2960 r=-0.5555 r=0.8082
TM5/4 -0.2960 r=0.8059 -0.1854
NIR3/1 r=-0.5555 r=0.8059 -0.4148
Munsell r=0.8082 -0.1854 r=-0.4148
Table 3.7: Correlations of all spectral indices values show positive correlations between REIP and Munsell Color and between NIR3/1 and TM5/4. REIP shows an inverse correlation with TM5/4 and NIR 3/1, as it should.
138 REIP TM5/4* NIR3/1 Munsell 1 113 91 131 153 2 76 152 152 118 3 117 18 77 149 4 107 77 121 144 5 56 136 146 134 6 149 77 131 149 7 134 117 131 158 8 135 68 111 158 9 163 147 151 158 10 149 81 132 163
Table 3.8: Comparison of Growing Days. *TM5/4 uses the combined No Water Stress and Some Water Stress measure.
139 Stress Level Found Grow %of Set by Mean Days Season Study Mean REIP <715 713.6 120 73.6% TM5/4 >0.55 0.616 96.8 59.4% NIR3/1 0.90 0.909 128.5 78.8% Munsell 18 18.7 149 91.4% Color
Table 3.9: Percent of season by index and growing days with calculation of percentage of growing season when trees showed no stress. Notice that trees registered no water stress for less than 60% of the season.
140 Me Me Mea P Grow Grow p value an an < n> valu Days < Days > Hea Healt e Mean Mean Ithy hy REIP 713. 1,2, 6,7,8, >0.0 1,2,3,4, 6,7,8,9, >0.0001 6 3,4, 9,10 238 5, 10 5 NDVI 0.78 3 9, 10 0.52 3 5,9, 10 >0.0001 2
TM5/ 0.61 3 2,9 <0.0 3 2,5,9 O.0001 4 6 001
NIR3/ 0.90 2,9, 0.024 3,8 2,5,9 <0.0001 1 9 10 4
Muns 18.7 2,3, 1,6,7, 0.015 2,5 7, <0.0001 ell 4,5 8,9,10 8 8,9,10
Table 3.10: Summary of Analyses of Means and Growing Days for all plots for all spectral indices. This chart opens discussion of Hypothesis #3.
141 Tree Plot Mean REIP Mean TM5/ Mean NIR3/1 Munsell Munsell Reip TM5/4 4 NIR3/1 Mean 801 1 708.9 2 0.63 2 0.92 2 18.4 1 803 1 715.2 1 0.61 2 0.90 2 17.0 2 804 1 713.1 2 0.63 2 0.90 2 17.6 2 808 2 710.0 2 0.57 2 0.87 1 17.6 2 811 2 717.2 1 0.53 1 0.86 1 20.2 1 812 2 701.5 2 0.59 2 0.91 2 12.0 2 813 3 711.4 2 0.64 2 0.93 2 18.2 1 814 3 711.2 2 0.69 2 0.95 2 17.2 2 815 3 708.5 2 0.65 2 0.91 2 16.8 2 816 4 702.2 2 0.62 2 0.91 2 12.4 2 817 4 712.0 2 0.66 2 0.93 2 16.4 2 818 4 717.3 1 0.62 2 0.93 2 20.2 1 820 5 712.3 2 0.61 2 0.90 2 20.0 1 821 5 701.5 2 0.61 2 0.91 2 11.6 2 822 5 707.4 2 0.61 2 0.91 2 17.0 2 823 6 716.1 0.61 2 0.90 2 17.8 2 824 6 719.0 0.62 2 0.91 2 18.6 1 825 6 715.1 0.65 2 0.90 2 16.6 2 826 7 723.3 0.60 2 0.91 2 23.0 1 827 7 715.0 0.65 2 0.95 2 21.2 1 828 7 710.2 2 0.62 2 0.92 2 19.4 1 829 8 716.4 0.63 2 0.92 2 22.0 1 830 8 716.3 0.64 2 0.92 2 22.4 1 831 8 712.8 2 0.65 2 0.93 2 18.4 1 832 9 717.7 0.55 2 0.87 1 20.4 1 833 9 723.6 0.57 2 0.87 1 22.4 1 834 9 719.6 0.59 2 0.89 1 22.2 1 835 10 719.3 0.64 2 0.92 2 21.8 1 836 10 719.6 0.62 2 0.90 2 21.8 1 837 10 714.1 2 0.60 2 0.88 1 20.6 1
Table 3.11: Stress levels by each measure, 1 indicating no stress, 2 indicating stress, are assigned to each tree. Values for spectral measures are means calculated for the 2008 season.
142 Plot Trees REIP TM5/4 NIR Munsell Grow 3/1 Days 1 801- 2 2 2 2 2 804 2 808- 2 2 1 2 2 812 3 813- 2 2 2 2 2 815 4 816- 2 2 2 2 2 818 5 820- 2 2 2 2 2 822 6 823- 2 2 2 2 825 7 826- 2 2 1 2 828 8 829- 2 2 1 2 831 9 832- 2 1 1 1 834 10 835- 2 1 1 1 837
Table 3.12: Stress levels, 1 indicating no stress, 2 indicating stress, are assigned to each plot by measure. If two trees showed a stress level, the entire plot was given a stress rating. If two trees showed a no-stress level, the entire plot was given a no-stress rating.
143 Table 4.1: Fall Bud Health Defined.
Scale Scale Name Size Exterior Color Interior Color Lateral Buds 1 Excellent 4-6mm, plump Rich red-brown White apical meristem, 2-6 green ground tissue, red/green in bud scales and epidermal walls 2 Good 2-4 mm, thin Dull, dark brown No green or red. 2-0 3 Dead/Deformed 2-4 mm Dark brown, Apical meristem 2-0 or Missing black discolored or dead. No red or green. Bud scales may be black and crumbly. Table 4.2: VIRIS scans of Tree 801 and Tree 811 in September 2007 and September 2008 suggested SEM of pollen. Tree 801 showed loss of chlorophyll, high water stress and early senescence in both years, with slightly more stress shown in 2007. Tree 811 showed little stress by any measure in 2007 and moderate stress, as indicated by the lower REIP, in late September 2008.
9/4/2007 9/24/2007 8/28/2008 9/28/2008 801 801 801 801 REIP 722.4 693 717.7 702.3 TM54 0.668 0.788 0.624 0.665 NIR31 0.919 1.009 0.898 0.956
9/4/2007 9/24/2007 8/28/2008 9/28/2008 811 811 811 811 REIP 725.4 722.4 727 708.5 TM54 0.577 0.584 0.543 0.581 NIR31 0.902 0.895 0.857 0.926
145 Table 4.3: Spring Bud Size and Growth.
Scale Tree April 2-8, April 22, size (mm), size(mm), # swelling ot laterals laterals 2 801 2x6,6 4x10, swelling 2 803 2x6,4 4x12, swelling 2 804 2x6,6 4x12, swelling 2 808 3x6,2 4x12, major swell 1 811 2x6,6 6x16, major swell 3 812 3x6,4 4x10, none 3 813 2x6,2 3x12, none 2 814 3x6,4 5x14, swelling 3 815 2x6, 4 tiny 4x12, none 2 816 2x6,4 4x12, swelling 3 817 3x8,4 4x14, none 2 818 2x6,4 5x12, swelling 3 820 2x6,4 4x8, none 3 821 3x8,4 4x12, none 3 822 3x6,2 4x10, swelling 2 823 3x6,4 4x12, swelling 2 824 3x6, 6 swelling 4x14, swelling 3 825 3x6,4 4x12, none 1 826 2x6,4 5x10, major swell 3 827 2x4, 4 tiny 3x8, none 2 828 3x6, 6 tiny 4x12, swelling 2 829 2x6, 6 tiny 4x10, swelling 2 830 3x8, 6 swelling 4x16, swelling 3 831 2x6,6 4x12, none 2 832 3x6, 6 swelling 4x10, swelling 3 833 3x6,6 5x10, none 2 834 3x6, 6 swelling 4x10, swelling 2 835 2x6,4 5x10, swelling 2 836 2x8,4 5x12, swelling 3 837 3x6,6 4x14, none Table 4, 4: Fall Bud Quality. Buds collected after leaf drop in late October were assessed as described in Table 4. 1 and counted. An overall rating was awarded each tree: Scale 1 = 75% or more, excellent buds; Scale 2 = 60% or more of buds are excellent and/or good; Scale 3 = 40% or more are dead, deformed or missing Scale Plot Tree Excellent Good Dead/Dying Missing %Excellent %Good %D/D %Missing 1 801 37 0 0 8 82 0 0 18 1 803 25 0 i 7 76 0 3 21 1 804 30 2 0 3 86 5 0 9 2 808 35 0 l 0 97 0 0 3 2 811 36 0 0 5 88 0 0 12 3 2 812 24 0 25 0 49 0 0 51 3 3 813 0 6 0 36 0 14 0 86 3 3 814 7 14 4 36 11 23 7 59 3 3 815 0 0 18 36 0 0 33 66 3 4 816 24 10 1 32 36 15 1 48 2 4 817 16 17 1 13 34 36 2 28 2 4 818 30 21 7 11 43 30 10 16 2 5 820 15 1 8 1 60 4 32 4 1 5 821 37 0 1 0 97 0 3 0 1 5 822 46 0 1 6 87 0 2 11 1 6 823 29 0 3 5 78 0 8 14 1 6 824 28 0 1 4 85 0 3 12 3 6 825 13 0 18 5 36 0 50 14 2 7 826 21 19 4 3 45 40 9 6 3 7 827 24 33 20 54 18 25 15 41 2 7 828 18 52 8 18 19 54 8 19 2 8 829 18 21 5 8 35 40 10 15 3 8 830 19 16 4 20 32 27 7 34 2 8 831 0 32 3 11 0 70 6 24 2 9 832 34 15 3 4 61 27 5 7 2 9 833 32 16 12 15 43 21 16 20 2 9 834 27 21 4 51 40 2 7 1 10 835 44 0 7 85 0 2 13 1 10 836 37 0 2 93 0 3 5 1 10 837 31 0 0 97 0 3 0 IV CK CK — CO — IV CM CM CO 00 Iv CO 00 NO CK NO — 00 ON CM IV -Nt CK IV LO "Nt IVl 00 CM -o CM ' CO -* to "NT — CM CM CM LO CO — — LO "5. CD CK CO CM
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a WON O Iv CO 00 -O CO LO 00 CM •- o N* CK — O LO "fr Iv O "Nt — ON ON CM — 001 o O 148 Table 4.6: Comparison of Spring Bud and Fall Bud Quality. Buds, rated on a scale of 1 to 3, excellent to poor, are compared for Spring and Fall 2008. Change is shown with + for improved quality, 0 for no change, and - for declining quality. This chart allows trees now to be graded for vegetative reproductive capacity on a 1-2 scale as used for spectral data, 1 indicated no stress, 2 indicating stress. Tree Plot Spring Bud Fall Change Stress Bud 801 1 2 + 803 1 2 + 804 1 2 + 808 2 2 + 811 2 1 0 812 2 3 3 0 2 813 3 3 3 0 1 814 3 2 3 - 2 815 3 3 3 0 2 816 4 2 3 - 2 817 4 3 2 + 818 4 2 2 0 820 5 3 2 + 821 5 3 1 ++ 822 5 3 1 ++ 823 6 2 1 + 824 6 2 1 + 825 6 3 3 0 2 826 7 1 2 - 2 827 7 3 3 0 2 828 7 2 2 0 829 8 2 2 0 830 8 2 3 - 2 831 8 3 2 + 832 9 2 2 0 833 9 2 2 0 834 9 2 2 0 835 10 2 1 + 836 10 2 1 + 837 10 3 1 ++ 149 Table 4.7: Stress Levels by All Tests. Comparison of all measures on all plots. A level 1 indicates no stress. A level 2 indicates stress at or above the minimal level. Plot Trees REIP TM5/4 NIR Munsell Grow Leaf Buds 3/1 Days Area 1 801- 2 2 2 2 2 2 1 804 2 808- 2 2 1 2 2 2 1 812 3 813- 2 2 2 2 2 2 2 815 4 816- 2 2 2 2 2 2 2 818 5 820- 2 2 2 2 2 2 1 822 6 823- 2 2 2 2 2 2 825 7 826- 2 2 1 2 2 2 828 8 829- 2 2 1 2 2 2 831 9 832- 2 1 1 1 2 1 834 10 835- 2 1 1 1 2 1 837 For Table 4.7, values of 1 represent the following: REIP Mean season-long REIP greater than 715. TM5/4 Mean season-long TM5/4 less than 0.55. NIR3/1 Mean season-long NIR 3/1 less than 0.90. Munsell Season-long color greater than mean, 18.7 ranking, 5GY,4/8. Grow Days Season-long growth for 163 days Leaf Retention Leaf size maintained throughout season Buds Production of more than 75% excellent buds. 150 Decade Avg. Avg. Degrees Degrees Major Annual Annual of Change, of Change Temp. F. Temp. F. Change, °C C. 1840 41.26 5.14 1850 42.47 5.82 1.01 0.68 1860 41.91 5.5 -0.36 -0.32 1870 43.32 6.29 1.41 0.79 1880 42.81 6.0 -0.51 -0.29 1890 42.60 5.89 -0.21 -0.11 1900 43.24 6.24 0.64 0.35 1840-1900, +1.98°F/1.1°C 1910 42.91 6.06 -0.33 -0.18 1920 43.32 6.29 0.41 0.23 1930 43.67 6.48 0.35 0.19 1940 43.96 6.64 0.29 0.16 1950 43.92 6.62 -0.04 -0.02 1960 44.72 7.06 0.80 0.44 1970 43.85 6.58 -0.87 -0.48 1900-1970, 0.61°F/0.34°C 1980 44.30 6.8 0.45 0.22 1990 45.47 7.48 1.17 0.68 2000 45.70 7.61 0.23 0.13 2006 46.49 8.05 0.79 0.44 1970-2006, 2.64°F/1.47°C 1840-2006, 5.23°F/2.91°C Table 5.1: Decadal temperature change in New Hampshire since 1840 shows a 2.91°C (5.23°F) change. The fastest increase has occurred since 1970, 1.47°C (2.64°F). (Based on annual average temperatures, NH, Williams ef a/., 2009). Data were reported in Fahrenheit and converted here to Celsius. 151 Proctor Hunter Farm Bascom NASS Maple 1900-1901 3.1-3.4% 1949-1953 2.9% 1970s 2.39% 1.8% 1980s 2.37% 1.915 1990s 2.13% 1.93% 2000s 2.02% 1.98% 1.96% Table 5.2: Change in sugar content of sap, 1900-present. Comparison of sap sugar content is made difficult by modern technologies and by different data collection methods. However, all modern records show a marked decrease in sap sugar content compared with those measured a century ago (Jones etai, 1903) and in the 1950s (Taylor, 1956). 152 801 811 815 817 821 824 826 830 833 835 2000-08 2.38 1.4 1.77 1.6 3.8 1.1 6.1 3.2 2.7 3.5 1990-99 2.28 2.7 1.38 2.1 3.4 1.7 6.8 2.65 2.8 3.35 1980-89 3.66 1.5 1.88 1.9 4.6 2.9 5.8 2.4 2.7 3.03 1970-79 4.05 0.8 1.41 2.4 4.9 4.0 7.25 4.3 2.9 1.93 1960-69 2.4 0.9 1.57 3.4 2.5 2.82 1950-59 3.6 1.06 2.2 3.8 Table 5.3: Average annual growth in cm, by decade, one tree in each plot, was calculated after staining wood cores with iodine. 153 Plot Tree DBH Hgt. Estimated Tag No. cm. m Age 1 801 50.8 19.8 66 2 811 63.5 21.9 105 3 815 60.9 25.6 146-202* 4 817 29.2 21.3 61 5 821 55.8 15.8 65 6 824 41.9 21.9 83 7 826 58.4 21.9 45 8 830 63.5 29.3 103 9 833 71.1 24.4 105 10 835 60.9 26.8 86 Table 5.4: Estimated ages of selected trees in each plot after recount with iodine. The * indicates a range of ages for Tree 811 which had numerous false growth rings and was difficult to count accurately. 154 APPENDIX B FIGURES 155 Figure 2.1: Acer saccharum study area, Bearcamp Valley and Northeast portion of Lake Winnipesaukee, Carroll County, New Hampshire, 43° North, 71° West,. Numbers identify Plots 1 and 2 on the Carlson farm, Plots 3 and 4 on the Googin sugarbush, Plots 5 and 6 on the Hunter Farm, Plots 7 and 8 on the Bickford Farm, and Plots 9 and 10 on the Burrows Farm. 156 Figure 2.2: Carlson Farm, Vittum Hill Road, Sandwich, NH. Location of Plots 1 and 2. Chocorua Quadrangle (USGS, 1972). Plot 1 is a managed sugarbush of trees 60 to 70 years of age with 2 to 3 older seed trees. Marlow soils. Good regeneration. Biomass is still within recommended standards at 12.85 m2/ha. Plot 2 is a newly opened sugarbush, recently dominated by white pine and a small Christmas tree plantation. Logged in 2006, trees range in age from 40 to 105, Tree 811, the oldest tree in this plot. Soils are Marlow with a small drainage on the northern portion of the plot and sheep pasture on the south side. Biomass at 5.95 m2/ha is below recommended maximum. Range View Farm has been managed by the Carlsons for sugar production and high quality timber since 1930. 157 Figure 2.3: Googin Farm, Route 113A, North Sandwich, NH. Location of Plots 3 and 4. Chocorua Quadrangle. (USGS, 1972). Plot 3: Mature sugar maple, Marlow soils, good regeneration. Trees crowded by white pines and ash have a biomass index of 17.44 m2/ha, close to the maximum of 18.8 m2/ha plot 4: Mature and young sugar maples, Berkshire soil, edge of field and yard. Trees crowded on forest side have a biomass index of 13.77m2/ha, below the recommended maximum. Property used as second home. The sugarbush is leased and has had little or no timber management for many years. 158 Figure 2.4: Hunter Farm, Route 171, Tuftonboro, NH. Location of Plots 5 and 6. Winnipesaukee Quadrangle. (USGS, 1972). Plot 5, mixed age sugar maples in very wet site. Trees are crowded by competing white pines with a biomass index of 16.75 m2/ha, well above the recommended 11.7 m2/ha. Hinckley and Scituate soils. In Plot 6, sugar maples, 60 to 85 years old, grow on Hermon soil. Although this stand appears open, trees have very narrow crowns and need thinning as seen in a biomass index of 29.84 m2/ha, over the recommended 16.1 m2/ha. Briefly pastured by cows, manured. The Hunter family has sugared continuously for 6 generations. 159 Figure 2.5: Janet and Fred Bickford Farm, Route 113 and Cold River, Sandwich, NH. Location of Plots 7 and 8. Chocorua Quadrangle (USGS, 1972). Plot 7, young sugar maples on glacial outwash, Colton soils, are widely spaced, pastured, manured. Plot 8, mature sugar maples on Ondawa soil, widely spaced, pastured, manured. On both plots, the biomass index of 9.18 m2/ha is well below the recommended 23.7 m2/ha maximum. The Bickford farm has been continuously managed for three generations. Plot 8 trees were allowed to grow in the pasture during World War II. 160 Figure 2.6: Lori Burrows Farm, Ossipee Mountain Rd., Moultonboro, NH. Location of Plots 9 and 10. Chocorua Quadrangle. (USGS, 1972) Plot 9: Mature sugar maples on Marlow soils, widely spaced with a biomass index of 3.67 m2/ha in graveyard and along stonewall in farm yard. Plot 10: Mixed age sugar maples on Beckett soils, widely spaced with a biomass of 6.89 m2/ha, pastured, manured. Farm continuously managed for three generations. 161 Drainage,/ 0 811 *$ K> S...fc##.ft.&. 0 Pasture n 812 North Figure 2.7: Sample plot, Range View, Plot 2. Trees identified by number. All plots were aligned north-south. This plot is typical in size, measuring 70 x 70 meters in size. Site measures such as groundcover, canopy density, and slope were examined at each tree. 162 Sample VIRIS, September IS, 2008 90 835 812 RF-IP 723.9 705.4 NDVI 0.876 0.856 TM54 0.663 0.647 NIR3I 0.903 0.929 -Tree 835 -Tree 812 CN CO Blue Green Red 4TOT "BDTT 800 1000 1200 1400 1600 1800 2000 2200 2400 Wavelength (nm) Figure 3.1: A sample of spectral curves taken from two trees on September 15, 2008. Based on the spectral indices. Tree 835 would be considered healthier than Tree 812. Tree 835 has a deep chlorophyll well, a high REIP. Plotting 1st Derivative of 814 726.21 : ' ;. . . . ';.. : \,rJ-:" v \ y"1 • \ v> 0.80 A Y I 1 '• / ^ S 0.60 "'/ : ": ;"•/.: rv\/ , 710 720 Mean Wavelength on Red Edge Figure 3.2: Calculation of the first derivative for Tree 814, July 30, finds the peak at 726.21 nm. The GER 2600 rounded this to a REIP of 727.00 nm 164 Figure 3.3: The Munsell Color Chart for Plant Tissues. Page 7.5 GY presents color scales for the greenest hues, less yellow than 2.5 or 5.0 GY hues. This sample page shows values on the left from whitest at 8 to blackest at 3. Across the bottom of the page, chroma indicates intensity of hue from dullest at 2 to brightest at 10. On July 30, 2008, Tree 837 was scaled at 7.5GY, 4/4. 165 April Buds and May Leaves Burrows 832 and 833 832April 833April 832May 833May 1200 1400 1600 Wavelengths (nm) Figure 3.4: VIRIS scan of leaves from Tree 832 and 833 in April and May indicate rapid growth from bud stage, as photographed, to leaf stage. The blue line, Tree 832 shows very little reflectance in April. By May 30, the blue line has jumped to a NIR reflecting 80% of light with a deep chlorophyll well. The red lines represent Tree 833, just a bit behind Tree 832 in spring development. 166 May 30 Burrows 835-837 835 836 837 REIP 7224 728 5 723 9 80 l*~—"v« \ NDVI 0 877 0 867 0 871 TMS4 0 583 0 595 0 589 f \^^\\^^ NIR31 0 853 0 854 0 844 50 l \ — -835 836 1 I / "X -837 30 \ f \ \y •* \J\J^u 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 Wavelengths (nm) • k ;••< 1A' . . * • f* «*.,;., > s£ * 835 836 837 Figure 3.5: May Sampling of Trees 835, 836, 837 in Plot 10. Munsell Color Chart ratings were 5GY, 4/6 for 835 and 836; 5GY, 4/8 for 837. 167 May 30 Hunters 820-822 820 821 •"•'"•"822 400 600 1000 1200 1400 1600 1800 2000 2200 2400 Wavelengths (nm) - - I * •_"-"•* --«•" * *, 820 821 822 Figure 3.6: May sampling of Trees 820, 821, and 822 in Plot 5. Munsell Color Chart ratings of 5GY, 4/8; 5GY, 7/10 (with fringed polygala, Polygala paucifolia); and 5GY, 5/6 respectively. 168 826 V1RIS Scans, 2008 April Buds 30-May 30-Jul 28-Aug 15-Sep Sept. 29 Oct 4 o-l , , , ^ ;! -•• <•••., ," - • i • —^-, ^-r- 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 Wavelength (nm) Figure 3.7: Seasonal VIRIS scans and Munsell Color Ratings for Tree 826. Photos of the leaves show colors a rich green May 30, July 30, August 29. Color begins to fade in September. Note the high reflectance of the NIR plateaus in May and deep chlorophyll well. By late fall, the well is steep and narrow and the plateaus have fallen. Table 3.4 presents data for these five dates, Tree 826. 169 Hunters' 822 20-Apr 30-May 30-Jul 28-Aug 15-Sep Sept. 29 Green Sept. 29 Red 400 600 800 1000 1200 1400 1600 1800 2000 2200 2400 Wavelength (nm) i "v -: .•W , .V JL # Figure 3.8: VIRIS curves and photographs of leaves, Tree 822, throughout 2008. Photos left to right show the progress of color May 30 through September. Spectral measures are shown on Table 3.5. 170 NDVI Averaged by Plot 0.950 ! 5 0.850 »• •'"5-, r o 0.750 • ••« Plot! •, o —*•' Plot 2 « •• Plot 3 I 0.650 K Plot 4 i // O" "Plot 5 *•> / / --•—Bote 5 0.550 A Plot 7 X Plot 8 M —•> Hot 9 r 1 —•• Plot 10 0.450 0.350 X 0.250 April May July August Sept. 15 30-Sep Sampling Time Figure 3.19 A and B. REIP and NDVI by Plot. Recall that health or lack of stress is measured as a REIP above 715 nm and NDVI (in the field of view, FOV) of more than 0.75. The progress of health is dramatic. Trees in only two plots, 9 and 10, maintain high measures through the full growing season. All others tumble precipitously into stress in September. Notice that trees in two plots, 808-812 in Plot 2, and 820-822 in Plot 5, reach healthy REIPs only once in July and then fall back into stress levels. Their leaves appear to mature to full photosynthetic power more slowly than other trees and then to lose chlorophyll more rapidly. Notice that the trees in Plot 3, 813-815, lose biomass rapidly in early September. 171 NIR3/1 -m~ 801-804 • - 808-812 8 0 950 J 813-815 * -816-818 -*- 820422 -•— 823-825 -O-826-828 • 829-831 -*-832-834 -*- 835-837 0.800 -P 30-May Aug. 28 Sampling Time TM 5/4 Water Stress All Plots 0.80 0.75 • -•-Ptotl 0.70 ~e~ Plot 2 I Plot 3 •• v Plot 4 -*-Plot5 i|o, - "* f S -«-Plot6 & -*—Plot 7 Rati o —^ Plot 8 .. •»-Plot 9 0.60 1"* " " & Plot 10 V • • • 0.55- "" — •• MayLvs July Lvs Aug. Lvs Sept 15 Sept 29 Sampling Dates Figure 3.10A and B. NIR 3/1 and TM5/4 VIRIS measures over time. Recall that in these scans lower numbers indicate health: <0.90 for NIR 3/1 and <0.55 for TM5/4. By early September trees in six plots show rapid loss of productivity and the onset of senescence, as measured by the NIR 3/1. Only trees in four plots, 3, 5, 9 and 10, maintain low NIR 3/1 through the full season. TM 5/4 presents the most alarming VIRIS data: All trees in all plots, excepting those in Plot 10 (Trees 835, 836,837) show initial or severe stress in May, the most vulnerable time for young leaves. Trees in Plots 8 and 9 are borderline in May but then show water stress. Even trees in Plot 10 show initial stress late in the season. 172 [Oneway Analysis of Alt Relps By Plot One way Analysis of No. Grow Days By Plot 730- — -t- • :" .. A> ^ 725- ^AA <3 ._^_ f 715- A^-A-A z..M^v v^A • H 5—T^ /"%A/ "S A V ^Y w -fcj - ! Oneway Anova !Oneway Anova j Summary of Fit I Analysis of Variance Rsquare 0.468979 Sum of Ad) Rsquare 0.440866 Source DT- Squares Mean Square f Ratio Proh > F Root Mean Square Error 34.88131 Plot 9 2892.645 321.405 2.2067 0.0238" Mean of Response 120.0333 Error 170 24759.951 145.647 Observations (or Sum Wgts) 180 0. Total 179 27652.596 : Analysis of Variance ^1 j Means for Oneway Anova GO Sum of level Number Mean Strt Error Lower 9Sa« Upper 95% Source OF Squares Meroi Square F Ratio ProafcF 1 18 712.422 2.8446 706.81 718.04 Plot 9 182673.80 20297.1 16.6820 «.OO01* 10 18 717.650 2.8446 712.03 723.27 Enor 170 206840.00 1216.7 2 18 709.583 2.8446 703.97 715.20 C. Total 179 389513.80 3 18 710.389 2.8446 704.77 716.00 ; Means for Oneway Anova 4 18 710.556 2.8446 704.94 716.17 5 18 707.078 2.8446 701.46 712.69 Level Number Wean Std ftror Lower 95*/* Upper 95*/* 6 18 716.767 2.8446 711.15 722.38 1 18 113.667 8.2216 97.44 129.90 7 16 716.228 2.8446 710.61 721.84 10 18 148.667 8.2216 132 44 164.90 8 18 715.194 2.8446 709.58 720.81 2 18 76.000 B.2216 59.77 92.23 9 18 720.322 2.8446 714.71 725.94 3 16 117.333 8.2216 101.10 133.56 18 107.000 8.2216 90.77 123.23 18 56.333 8.2216 40.10 72.56 18 149.000 8.2216 132.77 165.23 18 134.000 6.2216 117.77 150.23 18 135.333 8.2216 119.10 151.56 18 163.000 8.2216 146.77 179.23 StdEnor uses a pooled estimate of errorvariance Figure 3.11A and B. JMP analysis of REIP by A. Plot and B. Grow Days. The mean REIP, as shown in A., is 713.6 nm for the entire season, a number below the level signalling stress. Trees in Plots 6, 7,8,9 and 10 are not stressed with high mean REIPs for all five test dates. When grow days, detailed in Table 3.6, are analyzed, the mean response is 120 days, 43 fewer days than the full season. Trees in Plots 2 and 5 fall far short of even that mean number of growing days. Oneway Analysis of TM54 By Plot 0.8- 0.75- 0.7- 0.65- 4J^_ .v^I^AA^.... 0.6- T -r /*V Ttp 0.55- 4i 0.5- 9 Each Pair Student's t 0 05 ! Oneway Artoya: } Summary °f Fit RsquaiB 0 209855 Adj Rsquare 0.168024 Root Mean Square Error 0-056719 Mean of Response 0.616672 Observations (or Sum Wgts) 180 [ Analysis oryjrnsnce _ _. _ Sitmtf Source DF- Squares Mean Square F Ratio Proti>F Plot 9 0.14017349 0.015575 5.0167 «.0001* Error 170 0.52778017 0.003105 C. Total 179 0.66795366 [Means for Oneway Anova Level Number Mean SM Error Lower 95% Upper 95% 1 18 0.623556 0.01313 0.59763 0.64948 10 18 0.617333 0.01313 0.59141 0.64326 2 18 0.565333 0.01313 0.53941 0.59126 3 18 0.659778 0.01313 0.63385 0.68570 4 18 0.631056 0.01313 0.60513 0.65698 5 18 0 610667 0.01313 0.58474 0.63659 6 18 0.624222 0.01313 0.59830 0.65015 7 18 0.625556 0.01313 0.59963 0.65148 8 18 0.640500 0.01313 0.61458 0.66642 9 18 0.568722 0.01313 0.54280 0.59465 Bill Frrnr ncaaa nnnlpH agtlmata nf prrnrvarianr-a Figure 3.12: A TM5/4 analysis by plot found the mean response at 0.61, a measure considered as demonstrating stress by Forest Watch and well beyond initial stress. Only trees in Plots 2 and 9 show lower TM5/4 ratios which still lie in the level indicating initial stress. 174 [ Oneway Analysis of TrVtSK Some or No Stress Pays By Plot Oneway Analysis of TM54 No-Stress Days By Ptot $ is 0 . <€> | Q 100- f-S *^> ? 8 9 Each Pair ( ' » ' 2 ' 3 ' 6 ' 9 Each Pair Students t Student's t 0.05 0.05 Oneway Anova Oneway Anova ; Summary of Fit i Summary of Fit Rsquare 0.609392 Rsquare 0.622768 Adj Rsquare 0.588712 Adj Rsquare 0 602797 Roo1 Mean Square Error 32.56559 Root Mean Square Error 27.06767 Mean of Response 96.83333 Mean of Response 31.63333 Observations (or SumWgts) 160 Observations (or SumWgts) 160 \ Analysis of Variance Analysis of Variance Sum ot Sunt ot Souice Of- Snnates Uemt Stiuate t'Rstfio Preb»f Source D¥ Senates Meatt Senate t-Ratio Plot 9 281269.00 31252.1 29.4687 "0001* Plot S 205621.80 22846.9 31.1835 «.ooor Error 170 180288.00 1060.5 Error 170 124552.00 732.7 C. Total 179 461557.00 C. Total 179 330173.60 Means for Oneway Anova __ ___ j Means for Oneway Anova I. evel N&nber fiteao Std Error lower 35** Upper 9S«> Level Nuiniiet Wvsn Sttt tit BT Lower S5H Upper 95% 68.000 6.3799 55.41 80.59 1 16 91333 7.6758 76.18 106.49 0.000 6.3799 -12.59 12.59 81.667 7.6758 66 51 96.82 102.000 6.3799 89.41 114.59 152.333 7.675B 137.18 167.49 13.667 6.3799 1.07 26.26 18.333 7.6758 3.10 33.49 0.000 6.3799 -12.59 12.59 77.667 7,6758 62.51 92.82 20.333 6.3799 7.74 32.93 136.667 7,6758 121.51 151.82 30000 6.3799 17.41 42.59 77.667 7,6758 62.51 92.82 13.667 6.3799 1.07 26.26 117.333 7.675B 102.18 132.49 0.000 6.3799 -12.59 12.59 68.000 7.6758 52.85 83.15 68.687 6.3799 58.07 81.26 147.333 7.6759 132.18 162.49 Std Error uses a pooled estimate of errorvariance Std Error uses a pooled estimate of errorvariance Means Comparisons Figure 3.13 A and B. Two different time series analyses were done, one showing growing days when no stress, no measures above 0.55, were found, Figure 3.13A. The second analysis counted growing days when trees showed no stress or initial stress, measures below 0.60. The mean number of days when no stress was measured is only 31.6, a dramatically low number. When initial stress is included, Figure 3.13B, the number climbs to a mean of 96.8, still low compared to a full growing season of 163 days. Oneway Analysis of NIR31 By Piot [OnewayAnalysis of NIR31 Grow Days By Plat | 1.1- 1B0- 1.05- S> 140- 1- " 0 0.95- o 100- «F> 0.9- *£t «F-.4^- > & T'W | 80- O 0.85- ff^T 60- S Each Pair 1'10'2'3'4'5'8'7'8'9 Student's t Plot 0.05 OnewayAnova j Oneway Anoya Summary of Fit ; Summary of Fit Rsquare 0.639242 Rsquate 0.104218 Adj Rsquare 0.056794 Adi Rsquare 0.620143 Root Mean Square Error 0.054572 Root Mean Square Error 16.10773 Mean ofResponse 0.908756 Mean of Response 128.5333 ObservarJons(orSumWgts) 180 Observations (or SumWgts) 180 i Analysis of Variance (Analysis of Variance 1 Sum of Sum of Source UF Squares Mean Square f Ratio Proti>F Sotcrce DF Squares Mean Square F Ratio Preb > f Plot 9 0.05890302 0.006545 2.1976 0.0244* Plot 9 78166.80 8684.09 33.4700 «.0001* Error 170 0.50628622 0.002978 Error 170 44108.00 259:46 C. Total 179 0.56518924 C. Total 179 122264.80 ; Means for Oneway Artova (Means for Oneway Anova Level Number Mean Sid Error Lower H5% Upper 95% Level Number Mean Std Error Lower 95% Upper 95% 1 18 0.909444 0.01286 0.88405 0.93484 1 18 131.000 3.7966 123.51 138.49 10 16 0.898778 0.01286 0.87339 0.92417 10 18 132.000 3.7966 124.51 139.49 2 18 0.881167 0.01296 0.85578 0.90656 2 18 152.333 3.7966 144.84 159.83 3 18 0.933389 0.01286 0.90800 0.95878 3 18 77.667 3.7966 70.17 85.16 4 18 0.922944 0.01286 0.89755 0.94834 4 18 121.333 3.7966 113.84 128.83 5 16 0.906000 0.01296 0.86061 0.93139 5 18 146.333 3.7966 138.84 163.83 6 18 0.903778 0.01286 0.87839 0 92917 6 18 131.000 3.7966 123.51 138.49 7 19 0.926389 0.01286 0.90100 0.95176 7 18 131.000 3.7966 123.51 138.49 8 16 0.927222 0.01286 0.90183 0.95261 8 18 111.667 3.7966 104.17 119.16 9 18 0.878444 0.01286 0.85305 0.90384 9 18 151.000 3.7966 143.51 158.49 Sid Error usos a pooled estimate oferrorvartance Std Error uses a pooled estimate oferrorvariance Figure 3.14 A and B. NIR 3/1 ratios for each plot found a mean for the season at 0.908, 3.14A, indicating that trees hovered at or just above the level of maturity and initial senescence for the whole season. Only Plots 2, 9 and 10 fall below the mean and show vigorous growth as their mean for the season. In 3.14B, analysis of growing days finds a mean at 128.5 days. Only Plots 2, 5 and 9 had significantly longer growing seasons above the level of stress, 0.90. Oneway Analysis of Munzell Color Rank By Plot ; Oneway Analysis of Munsell Green Days By Plot 26- 160- 4^ " ^\ k • /\0*?¥^ 20- 140" ^ 4—? ' _ £ -^ m v If 15 V ^Ki>v r. Figure 3.16A, B and C: Correlations of spectral measures by multivariate analysis finds positive correlation in 316A between REIP and Munsell Color; in 316B, between NIR 3/1 and TM5/4, and in 316C, between REIP and NDVI. *•*"#- u^w $ tt;i . » ,--. v. ^ i; ''*•'• i 13 I -Sr 6> «ss* '• • • "•*£ %L- & ' te. - "' '. 'A .•"""'•" : sl I f m 1 1 • ••!. 1.I." I ! HM . V t . a. 1 / ••••«.s- fc - *£• ;.. Figure 4.1: Progress of Bud Development, Spring 2008. At upper left, Tree 836 shows typical buds, 2x8 mm with 4 laterals on April 6. At upper right, Tree 825 shows Scale 3, buds which doubled in size yet had no swelling of laterals, on April 22. At lower left, Tree 836 shows Scale 2, buds doubling in width with swelling of laterals on April 22. At right. Tree 811, shows buds nearly triple in length with almost equal swelling of laterals, Scale 1, April 22. Tree 811 produced flowers in these large terminal buds. 179 A and B Cand D Figure 4.2: Viable buds photographed above, A and B, show 4-6 mm size, healthy lateral buds, rich color both externally and internally, classifying both of these on Scale 1, Excellent. Dead and deformed buds, C and D, represent Scale 3. At left, dead bud shows brown meristematic tissue and dry papery bud scales. At right, deformed buds appear twisted and missing the distal tip. A missing apical bud, shown in E. 180 Oneway Analysis of %:<*eodto; Total Buds By Plot i • 0.9- £\ A M A A A \Y^^ 0.8- yv 0.7- \7x-i H\ I 1 AV7AA\ T-( i U ¥ A'• \ S ? 0.6- v m V / • \ * \ A A . / ° ~ n0- 5c - a? £ 0.4- • y vyv A 0.3- 0.2- / A \ 0.1- 0 1 ' 2 ' 3 ' 4 ' 5 ' 6 ' 7 ' 8 ' 9 ' 10 Plot : I Oneway Aneva : Summary of Fit . Rsquare 0.691067 Adj Rsquare 0.552047 Root Mean Square Error 0.168147 Mean of Response 0.700667 Observations (or Sum Wgts) 30 (Analysis of Variance ] Sum of Source DF Squares Mean Square F Ratio Prob>F Plot 9 1.2649200 0.140547 4.9710 0.0014* Error 20 0.5654667 0.028273 C. Total 29 1.8303867 Means for Oneway Anova Level Number Mean Std Error Lower S5% Upper 95% 1 3 0.830000 0.09708 0.6275 1.0325 2 3 0.780000 0.09708 0.5775 0.9825 3 3 0.166667 0.09708 -0.0358 0.3692 4 3 0.583333 0.09708 0.3808 0.7858 5 3 0.826667 0.09708 0.6242 1.0292 6 3 0.663333 0.09708 0.4608 0.8658 7 3 0.673333 0.09708 0.4708 0.8758 8 3 0.680000 0.09708 0.4775 0.8825 9 3 0.886667 0.09708 0.6842 1.0892 10 3 0.916667 0.09708 0.7142 1.1192 Std Error uses a pooled estimate of errorvariance Figure 4.3. ANOVA of Good and Excellent buds 181 i Oneway Analysis of % Excellent buds By Plot .] 1- •g 0.8- /7\A /A A 3 £2 vv vA £ 0.6- v v y { } A m -f S 0.4- • A * X AA^ LU # 0.2- vy o- V 1 ' 2 ' 3 ' 4 ' 5 ' 6 ' 7 ' 8 ' 9 1 10 Plot Oneway Anova | Summary of Fit Rsquare 0.820139 Adj Rsquare 0.739202 Root Mean Square Error 0.162645 Mean of Response 0.542333 Observations (or Sum Wgts) 30 [Analysis of Variance Sum of Source DF Squares Mean Square F Ratio Profo>F Plot 9 2.4124700 0.268052 10.1330 <.0001* Error 20 0.5290667 0.026453 C. Total 29 2.9415367 Weansfer Oneway Anova Level Number Mean Std Error Lower 95% Upper 95% 1 3 0.813333 0.09390 0.6175 1.0092 2 3 0.780000 0.09390 0.5841 0.9759 3 3 0.040000 0.09390 -0.1559 0.2359 4 3 0.360000 0.09390 0.1641 0.5559 5 3 0.813333 0.09390 0,6175 1.0092 6 3 0.663333 0.09390 0.4675 0.8592 7 3 0.273333 0.09390 0.0775 0.4692 8 3 0.246667 0.09390 0.0508 0.4425 9 3 0.516667 0.09390 0.3208 0.7125 10 3 0.916667 0.09390 0.7208 1.1125 Std Error uses a pooled estimate of errorvariance Figure 4.4: ANOVA of % Excellence of Buds by Plot. 182 Figure 4.5: Comparison of anthers, Tree 801, top, and 811, collected on the same day, shows very different structures. Tree 801 's anthers are almost empty and accompanying flower structures appear wilted. Tree's 811 anthers are bursting with pollen granules and flower structures appear stout. 183 Figure 4.6: Comparison of Pollen, 801, top, and 811. Tree 81 Ts anther contains many more pollen granules and granules appear round and robust. Tree 801 granules are few in number and many look deflated or misshapen. 184 Figure 4.7: Changing Leaf Area of All Trees. Throughout the season, all trees in the study showed reduced size. The one line, Tree 835, can be dismissed as an error or outlier. 185 Oneway7Ari3ly$is of Leaf Areacm2 By Test Oneway Ahova Summary ef Fit Rsquare 0.181003 AdjRsquare 0.158409 Root Mean Square Error 27.21578 Mean ofResponse 87.989 Observations (or Sum Wgts) 150 Anaiysis of Variance Sum of Source OF Squares Mean Square F Ratio Profo > F Test 4 23736.22 5934.06 8.0114 <.0001* Error 145 107401.31 740.70 Figure 4.8: Leaf area by Test. 186 [Oneway Analysis of ieafAreacmZ By Plot iUU" 180- " 160- £ 140- | 120- - S 100- 3 80- "**" Ti / I \ \tjT •'. / ^• V • T ^z4i^z\ly^ "f \ 60- i • ^ . ^ : : Y r 40- » • JU 1 ' 10 ' 2 ' 3 ' 4 ' 5 ' 6 ' 7 ' 8 ' 9 Plot I Oneway An ova : ! Summary of Fit Rsquare 0.254325 Adj Rsquare 0.206389 Root Mean Square Error 26.4286 Mean ofResponse 87.989 Observations (or Sum Wgts) 150 | Analysis of Variance Sum of Source DF Squares Mean Square F Ratio Pro»>F Plot 9 33351.58 3705.73 5.3055 <.0001* Error 140 97785.96 698.47 C. Total 149 131137.53 Means for Oneway Ansva Level Number Mean Std Error Lower 95% Upper 95% 1 15 94.202 6.8238 80.71 107.69 10 15 98.927 6.8238 85.44 112.42 2 15 68.019 6.8238 54.53 81.51 3 15 87.182 6.8238 73.69 100.67 4 15 104.989 6.8238 91.50 118.48 5 15 68.925 6.8238 55.43 82.42 6 15 116.051 6.8238 102.56 129.54 7 15 86.762 6.8238 73.27 100.25 8 15 78.033 6.8238 64.54 91.52 9 15 76.799 6.8238 63.31 90.29 Std Error uses a pooled estimate of errorvariance Figure 4.9. ANOVA of leaf area by plot. 187 AHReips 1 Leverage Plot ro 200- . CN 3 E y * I 8 150- m CC :*- -.-" . • < (V . .**."-. o Lea f evera g z-zm&P* 50- 1 i i i i i i i i 690695700 705710715720725730735 All Reips Leverage. P«.0001 M54 i NIIR31 ) Leverage Plot | Leverage Plot ___ » 180- . 18 o, °- r, I 160- ; „ 1 160- " 1 ? 140- »• i 1 I 140- «* •*. S S. 120- — ..* • • ,-•• a) Q- 120 • . \ • * < g, 100- - $.:-c •-" I-.,-..-—• *>*%&'- «-•••-••-•••• -Hfet .-•• -- LeafA r S 60- C D 0 O Leverag e <*?>£ ~ 40- 40- --. •• • . • i ' i • i • i 0.50 0.55 0.60 0.65 0.70 0.75 0.80 0.80 0.85 0.90 0.95 1.00 1.05 TM54 Leverage. P=0.0202 NIR31 Leverage. P=0.0467 NDVI Munzell Color Rank Leverage Plot I Leverage Plot __- 200- 18 180- 160- „ 1«, 160°- 1 § 140- 140- S S 120- • . . .-','-" 120- < g ioo- 100- ;~n&j S| 80- Ia) I 80- S 60- -•^p^. 60- 40- 40- . i i i i i i ( i i i i 20" -i—i—i—i—i—i—i—r 0 5 10 15 20 25 30 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Munzell Color Rank NDVI Leverage, P=0.5365 Leverage, P=0.1091 Figure 4.10: Correlations of Leaf Area with spectral data. REIPs and leaf area show a small positive correlation (r=0.36, p=<0.0001). Although p values generated by the JMP 8.0 test shows significance, r values reject any correlation. TM5/4 (r=0.0476, p=0.0202) and NIR3/1 (r=0.1627,p=0.0467). As the linear plots show, all leaf area measures clustered at the mean forTM5/4, 0.62 (Figure 3.15) and NIR 3/1, 0.90 (figure 3.17). Munzell Color rank and NDVI were not significant. 188 mm •E \" \ ^ • v-.\ ' • ' *-i>iSv- >.. B .•.••V ••&,;. ~'*i • :V- ••• \--V*V.* 1 "••••- i .'•".sllli'--.' . V-:V^> \ . • •:,/. Figure 4.11: Six leaves in a sugar maple bud. Notice the five veins forming in the leaf at far right. 189 Figure 4.12: Six leaves on the stem of a twig from 811, July 2008. The six leaves which emerge from one bud lie in pairs, each pair at 90 degrees from the next so that the smaller central leaves emerge at the same angle as the largest and lowest leaves. 190 Annual Average Temperature (F.) 49 — Annual Average (F) r2=0.4232 — Linear (Annual Average (F)l 39 r2=0.4754 Williams ef 37 a/., 2009) 35 1835 1855 1875 1895 1915 1935 1995 Year Figure 5.1: New Hampshire Temperature Change, 1835-2006. Since 1840, decadal average temperature in New Hampshire has risen 2.91°C (5.23°F). The trend grows even steeper in the last 40 years when more than half of the increase occurred. Average annual temperature rose from 6.58°C (43.85°F) in 1970 to 8.05°C (46.49°F) in 2006, an increase of 1.47°C (2.64°F) (Williams ef a/., 2009). 191 Hunter Farm, Sap to Syrup Ratio —•—Hunter Farm Linear (Hunter Farm) 1970 1975 1980 1985 1990 1995 2000 2005 2010 Years Figure 5.2. Hunter Farm Sap to Syrup ratio shows a steady trend over the last 40 years towards less sweet sap. An average of 36 gallons of sap boiled down to 1 gallon of syrup in the 1970s. More recently, an average of 44 gallons is needed (Rollins, 2007; Rollins, 2009). 192 Figure 5.3. Four states reporting maple syrup production to the National Agricultural Statistical Service and the Hunter Farm records show a steady rise in the sap to syrup ratio excepting in Maine (Keough, 2009; Rollins, 2007,2009). 193 Sap to Syrup Ratios & Temperature 49 r [-60 48 50 47 7\ » 1 \ * , i •' i A • / / \ ''A- H / -A- u;46 40 d. \ .... v-w--. o E —a—Hunter Farm •- 45 1 ' :.x.' \A, ,' \ Q. —•—Vermont State «3 C 30 1 Avg. Annual Temp. C \ " \ Linear (Avg. Annual Temp.) a 44 s a Linear (Hunter Farm) E a (0 *I 43 20 42 - 10 41 40 - < — - 1979 1989 1999 2009 Year Figure 5.4. Comparison of sap to syrup ratios with average annual temperature since 1970 demonstrate the trend in both measures. The trend in temperature is a bit steeper than sap to syrup ratios. Temperature and Hunter records show some similar change in peaks and valleys. 194 Hunter First Run Days 29-Mar 24-Marl 19-Mar - Hunter First Run Days 14-Mar •Linear (Hunter First Run Days) 9-Mar R2=0.0836 4-Mar 27-Feb 1970 1975 1980 1985 1990 1995 2000 2005 2010 Figure 5.5: Hunter Farm First Run Days, 5 to 10 days earlier today than in 1970. 195 Hunter Farm Last Run Days - Last Run Days -Linear (Last Run Days) 29-Mar £ •Linear (Last Run Days) a a 24-Mar r2=0.018 19-Mar 14-Mar W- 9-Mar N Figure 5.6: Last Run Days of Sap Season, 1970-2007. The sugar season ends 2-3 days earlier than it did in the early 1970s. 196 Oneway-AhfKlx$fc;6f Mean 3-¥r Wood: Growth By Plot 3.5H 3-^ • c o Plot Missing Rows Oneway Artova Summary :pf Fit Rsquare 0.517301 Adj Rsquare 0.261754 Root Mean Square Error 0.622626 Mean ofResponse 2.025926 Observations (or Sum Wgts) 27 .Analysis of Variance; Sum of Source DF Squares Sean Square F Ratio Prob > F Plot 9 7.062701 0.784745 2.0243 0.1006 Error 17 6.590281 0.387664 C. Total 26 13.652982 Figure 5.7. ANOVA of mean wood growth by 3-year averages shows a mean of 2.02 cm for all trees in 10 plots. 197 : • ,-i - •-*.'* - - • •••.i—~ -, •S . / XjHPB***^ . \ '/•hdflHP r •**"•' • ,?": • •^ *' ,"" "' - ^ / afMlsB^-1*--* - •>.• * -. . v.: . ~^€3S&:- - .-:•• * ^ms^^r- ••* • - '.V s~ j Figure 5.8. Radial views of wood from Tree 816, at top, 80x, shows bark on the left. The cambial zone and marginal parenchyma will lie just inside the bark. Below, wood from Tree 834, 85.5x, shows bark to the right, cambial zone just to the left of the bark. 198 SMI 1-16-01 Figure 5.9: Tree 816, at 855x, shows a cambial zone just under the bark. (See black arrow.). The zone of living cells, vascular cambium and the marginal parenchyma are approximately 15 pm in width. 199 Figure 5.10: Tree 834 at 850x shows a band of living cells that is approximately 35 urn wide. The marginal parenchyma lie just to the left side of this band, a vessel element with spiral thickenings is visible to the left. Bark tissue lies to the right of the cambial zone. 200 Figure 5.11: Another view of cambial zone cells and possible parenchyma in Tree 834 at 520x shows the bowl-shaped cells typical of ray parenchyma, A. These cells run perpendicularly to the smoother parenchyma cells above, B. To the left of these cambial zone cells, between them and the vessel element, C, a single line of slightly longer parenchyma cells, D, may be the marginal parenchyma which form the visible line between growth rings. 201 APPENDIX C IRB #4136 202 University of New Hampshire Research Conduct and Compliance Services, Office of Sponsored Research Service Building, 51 College Road, Durham, NH 03824-3585 Fax: 603-862-3564 20-Dec-2007 Carlson, Martha Natural Resources, James Hall 342 Vittum Hill Road Center Sandwich, NH 03227 IRB#:4136 Study: Maple Watch: An assessment of sugar concentrations in Acer saccharum as a stress response to climate change Approval Date: 20-Dec-2007 The Institutional Review Board for the Protection of Human Subjects in Research (IRB) has reviewed and approved the protocol for your study as Exempt as described in Title 45, Code of Federal Regulations (CFR), Part 46, Subsection 101(b). Approval is granted to conduct your study as described in your protocol. Researchers who conduct studies involving human subjects have responsibilities as outlined in the attached document, Responsibilities of Directors of Research Studies Involving Human Subjects. (This document is also available at http://www.unh.edu/osr/compliance/irb.html.) Please read this document carefully before commencing your work involving human subjects. Upon completion of your study, please complete the enclosed pink Exempt Study Final Report form and return it to this office along with a report of your findings. If you have questions or concerns about your study or this approval, please feel free to contact me at 603-862-2003 or [email protected]. Please refer to the IRB # above in all correspondence related to this study. The IRB wishes you success with your research. For the IRB, cc: File Rock, Barrett