STRESS-MEDIATED RELATIONSHIPS BETWEEN INSECTS AND
FORESTS: EMPIRICAL AND MODELLING STUDIES
by JENNIFER J. BABIN-FENSKE
Thesis submitted as a partial requirement in the Doctor of Philosophy (Ph.D.) in Boreal Ecology
School of Graduate Studies Laurentian University Sudbury, Ontario
© Jennifer J. Babin-Fenske 2010 Library and Archives Biblioth&que et 1*1 Canada Archives Canada Published Heritage Direction du Branch Patrimoine de l'6dition
395 Wellington Street 395, rue Wellington Ottawa ON K1A 0N4 Ottawa ON K1A 0N4 Canada Canada
Your file Votre r6f6rence ISBN: 978-0-494-65842-0 Our file Notre reference ISBN: 978-0-494-65842-0
NOTICE: AVIS:
The author has granted a non- L'auteur a accorde une licence non exclusive exclusive license allowing Library and permettant a la Bibliotheque et Archives Archives Canada to reproduce, Canada de reproduce, publier, archiver, publish, archive, preserve, conserve, sauvegarder, conserver, transmettre au public communicate to the public by par telecommunication ou par Nnternet, preter, telecommunication or on the Internet, distribuer et vendre des theses partout dans le loan, distribute and sell theses monde, a des fins commerciales ou autres, sur worldwide, for commercial or non- support microforme, papier, electronique et/ou commercial purposes, in microform, autres formats. paper, electronic and/or any other formats.
The author retains copyright L'auteur conserve la propriete du droit d'auteur ownership and moral rights in this et des droits moraux qui protege cette these. Ni thesis. Neither the thesis nor la these ni des extraits substantiels de celle-ci substantial extracts from it may be ne doivent etre imprimes ou autrement printed or otherwise reproduced reproduits sans son autorisation. without the author's permission.
In compliance with the Canadian Conformement a la loi canadienne sur la Privacy Act some supporting forms protection de la vie privee, quelques may have been removed from this formulaires secondaires ont ete enleves de thesis. cette these.
While these forms may be included Bien que ces formulaires aient inclus dans in the document page count, their la pagination, il n'y aura aucun contenu removal does not represent any loss manquant. of content from the thesis. Canada
ABSTRACT
Insects are important contributors to environments in which they live and are essential for ecosystem processes such as soil nutrient cycling and pollination. Human activities such as agriculture, forestry, urban sprawl and discharge of pollution have severely altered habitats of insects in a variety of ways and studying how insects cope with these perturbations helps us understand how they function in natural habitats, along with roles they play in sustainability. It may be considered imperative to have a better understanding of the effects of stress on insect communities and their relationships with plants as stressors are anticipated to become more intense or frequent from various events such as increased pollution or climate change. In this study, I used both empirical and modelling techniques to understand how plant stress and insect stress from past events and future stress scenarios may alter insect population dynamics and community structure. The recovery of past pollution was also examined in sites under a restoration regime and sites recovering naturally. Using a stress gradient based on a decommissioned copper-nickel smelting complex, I examined the natural recovery of insects and the success of restoration techniques. Although almost forty years have passed after the decommissioning of the source of pollution, I found a significant impact on the composition of insect community in terms of diversity, richness and abundance for a number of taxa. There also remains distinct communities at the sites with the highest level of stress, which emphasizes the importance of thoroughly examining the unique landscape that results in severe disturbance events. Furthermore, I found that although certain taxonomic levels of insects had similar trends, insect communities have not recovered to the same degree as the plant communities in the physically assisted sites.
iii This suggests that restoration efforts, such as liming and seeding, may not be promoting the full recovery of an important ecosystem community. It also provides support for cross-taxon and higher taxon surrogacy within the insect community but not between insects and plants. With this new insight into how stress affects insect communities, I provided recommendations for future restoration techniques and forest defoliator management programs. Through examination of a specific forest defoliator along the stress gradient, I found the forest tent caterpillar (Malacosoma disstria Hiibner) (FTC), had an increased density with a decrease in distance from this decommissioned source of pollution. I suggest that the increased population density from stress may increase the magnitude and/or duration of an FTC outbreak. Using an individual-based model of the host-parasitoid dynamics of FTC and its primary parasitoid Arachnidomyia aldrichi
(Parker), I also found that a variety of stress scenarios can significantly alter the 10-year defoliation cycle of the FTC. I found that increasing FTC fecundity, dispersal or parasitoid mortality resulted in more severe outbreaks while a decrease in parasitoid fecundity or searching efficiency resulted in an overall elevation of defoliation. Since stress can alter such demographic parameters in a variety of ways, this gives us a better understanding of how future climate change and pollution scenarios may alter the outbreak cycle of major forest defoliators and how different management techniques may be implemented for such insects. Examining the effects of stress on population density, population dynamics and community composition shows a wide range of impact from stressors that are predicted to increase in various ecosystems.
IV ACKNOWLEDGEMENTS
I am indebted to my co-supervisor, Madhur Anand, for her guidance, patience and extremely speedy and thorough revisions. I would like to thank my other thesis committee members who were helpful and available whenever I needed them. I thank
Yves Alarie for being very accommodating co-supervisor and giving me his time and lab space. Joe Shorthouse made sure I was up-to-date with entomology news, events and fun facts. Charles Ramcharan always had encouraging words and great ideas. Jonathan
Newman gave me modeling guidance and was very patient as I learned the ropes.
Sincere and deep appreciation goes to the taxonomic experts who helped identify my insects, especially Patrice Bouchard, Henry Goulet, and Gary Umphrey. I am also very grateful for the short but extremely informative conversations I had with people in the
Ontario Ministry of Natural Resources and Canadian Forest Service of Natural Resources
Canada in Sault Ste-Marie. I would especially like to thank Barry Lyons, Lisa Venier,
Ron Fournier and Taylor Scarr.
I am very grateful for financial support from Ontario Graduate Scholarship Program,
Natural Sciences and Engineering Research Council, Entomological Society of Ontario,
Laurentian Graduate Studies and Laurentian Graduate Student's Association Travel
Grants. This project would not have been possible without the additional funding from grants to M. A. from the Natural Sciences and Engineering Research Council, the Canada
v Research Chairs program, the Canadian Foundation for Innovation, the University of
Guelph and Laurentian University.
Paul Larochelle, Cory Laurin, Wilder Leduc, Sarah Rintala, Jenna Pillarella, Natalie
Webster are acknowledged for their commendable job as field assistants. The weather was not always favourable while the lab work was not always exhilarating, although it
could be! I therefore appreciate their efforts and enthusiasm. I thank Leo Lariviere for
developing my site maps and I would also like to thank Aaron Langille for his
commitment to helping me develop my host-parasitoid model. His feedback was always
helpful while his computer programming and listening skills were invaluable. I thank all
my family and friends who were always understanding and encouraging.
This thesis is dedicated to my husband, Tom and daughter, Madeleine. Becoming a wife
and mother during the course of this thesis helped keep me grounded and motivated. My
frazzled moments were always soon defused. I thank you for your patience and
inspiration.
vi TABLE OF CONTENTS
Abstract iii
Acknowledgements v
Table of Contents vii
List of Figures x
List of Tables xv
(I) General Introduction 1
Defining stress with reference to plants and insects 3
Insect-forest interactions and stress 5
Forests, insects and stressors of the Boreal Shield landscape: Landscape scales. ..9
Forests, insects and stressors of the Boreal Shield landscape: The Case of
Sudbury, Ontario 10
Objectives and Hypotheses 11
References 14
(II) Terrestrial Insect Communities and the Restoration of an Industrially
Perturbed Landscape: Assessing Success and Surrogacy 24
Introduction 26
Methods 29
Results 35
Discussion 37
References 45
vii (III) Patterns of Insect Communities Along a Stress Gradient Following
Decommissioning of a Cu-Ni Smelter 65
Introduction 67
Methods 73
Results 76
Discussion 77
References 82
(IV) Forest Tent Caterpillar (Malacosoma disstria Hiibner) Population Density
Along a Stress Gradient in a Northern Ontario Forest 98
Introduction 100
Methods 102
Results 104
Discussion 105
References - 108
(V) Agent-based simulation model shows that stress may promote
forest tent caterpillar defoliation 117
Introduction 119
Methods 123
Results 131
Discussion 133
viii References 140
Final Conclusion and Future Endeavours 154
Final Conclusion 155
Future Endeavours 157
References 159
Appendix 162
ix LIST OF FIGURES
Figure 1.1. Map of Sudbury, Ontario with locations of smelters, decommissioned roastyards and research sites labeled 1 through 5. Site 1A and 2A have had assistance through liming, seeding and/or planting 23
Figure 2.1. Map showing the location of the four study sites and the decommissioned smelting complex near Sudbury, Ontario, Canada. Sites include Coniston unassisted (C),
Coniston assisted (CA), Daisy Lake unassisted (DL) and Daisy Lake assisted (DLA) ...55
Figure 2.2. Mean Shannon diversity values with standard error of the mean of ant genera
(A,B) and carabid beetle species (C,D). Significance of p<0.01 is denoted by ** 56
Figure 2.3. Mean Shannon diversity values with standard error of the mean of plant species (A,B) and plant families (C,D). Significance of p<0.05 is denoted by * and p<0.01 by ** 57
Figure 2.4. Coleman rarefaction of the ant community at the Coniston sites (A) and
Daisy Lake sites (B) and carabid beetle community at the Coniston Sites (C) and Daisy
Lake sites (D). Black lines represent unassisted sites and assisted sites are grey. Error bars represent one standard deviation 58
x Figure 2.5. Mean richness for plants (A,B), all insect morphotaxa (C,D), ants (E,F) and carabids (G,H) with standard error of the mean. Significance of p<0.05 is denoted by * and p<0.01 by** 59
Figure 2.6. Nonmetric multidimensional scaling plots showing differences between sampling stations (all sites) based on ant genera incidence. Circles represent Coniston sites while triangles represent Daisy Lake sites. Black symbols represent unassisted sites and white symbols represent assisted sites 60
Figure 2.7. Nonmetric multidimensional scaling plots showing differences between sampling stations (all sites) based on carabid species abundance. Circles represent
Coniston sites while triangles represent Daisy Lake sites. Black symbols represent unassisted sites and white symbols represent assisted sites 61
Figure 2.8. Nonmetric multidimensional scaling plots showing differences between sampling stations (all sites) based on plant species incidence. Circles represent Coniston sites while triangles represent Daisy Lake sites. Black symbols represent unassisted sites and white symbols represent assisted sites 62
Figure 3.1. Map showing the location of the five study sites and the decommissioned smelting complex near Sudbury, Ontario, Canada. Numbered circles indicate sites ....91
xi Figure 3.2. Rarefaction (A) and Shannon diversity (B) of ant genera along the stress gradient. The site numbers are located at the edge of each trend with increased numbers for an increase of distance from the smelting complex 92
Figure 3.3. Rarefaction (A) and Shannon diversity (B) of carabid beetle species along the stress gradient. Site numbers are located at the edge of each trend with increased numbers for an increase of distance from the smelting complex 93
Figure 3.4. Trends along a stress gradient for the abundance and Shannon diversity of predators (A), parasitoids (B), herbivores (C) and detritivores (D). Significance is denoted by * to represent p<0.05 and ** to represent p<0.01 94
Figure 4.1. Map showing the location of the five study sites and the decommissioned smelting complex near Sudbury, Ontario, Canada. Numbered circles indicate sites ....113
Figure 4.2. Distance from the smelting complex correlated with mean number of egg masses counted per branch for each tree (A) mean number of egg masses counted per branch for each site (B), tree density within 125 m (C) and tree Shannon diversity of all tree species (D) 114
Figure 4.3. Mean egg mass per branch for each site compared to total site tree diversity
(A) and density of trees in 500m2 (B) 115
xii Figure 5.1. Percent forest tent caterpillar defoliation in Ontario, Canada from observed data from Canadian Forest Service and Ministry of Natural Resources (black) and the simulation output (gray). Parameter values are given in Table 5.1 149
Figure 5.2. Changes in mean forest tent caterpillar defoliation through altering the parameter values with significance of p<0.05* and p<0.01**. Grey diamonds represent the base model value. CD = caterpillar dispersal, PD = parasitoid dispersal, CF = caterpillar fecundity, PM = parasitoid mortality, PF = Parasitoid fecundity, PE = parasitoid efficiency 150
Figure 5.3. Changes in forest tent caterpillar defoliation cycle from altering parameter values. CD = caterpillar dispersal, PD = parasitoid dispersal, CF = caterpillar fecundity, PM = parasitoid mortality, PF = Parasitoid fecundity, PE = parasitoid efficiency.* increased or t decreased length of outbreak (p<0.05); A increased frequency of defoliation peaks (p<0.05) 151
Figure 5.4 Screen shot of simulated defoliation (black squares) within FTC boundaries
(grey) of Ontario and the observed FTC defoliation (grey polygons) showing Sudbury,
Ontario (black dot) 152
Figure A.l. Initial setup of the simulation model showing the map of Ontario outline with the range of past FTC outbreaks (grey), caterpillars (dark grey squares) and parasitoids (black squares) 171
xiii Figure A.2. Netlogo interface showing how parameters may be altered by the user while the output may be monitored immediately on the lower graphs 172
xiv LIST OF TABLES
Table 2.1. Occurrence of insect morphotaxa at the four sites: Coniston (C), Coniston assisted (CA), Daisy Lake (DL), Daisy Lake assisted (DLA) 63
Table 2.2. Occurrence of ant and carabid taxa at the four sites: Coniston (C), Coniston assisted (CA), Daisy Lake (DL), Daisy Lake assisted (DLA) 64
Table 3.1. Abundance of taxa along the stress gradient. Guilds include predators (Pr), parasitoids (Pa), herbivores (H), detritivores (D) and unknown (U) 95
Table 3.2. Abundance of ant genera along the stress gradient. Note that analyses used incidence data instead of abundance 96
Table 3.3. Abundance of carabid species along the stress gradient 97
Table 4.1. Mean number of egg masses per branch for each species of tree examined and tree density for each site. Not applicable (na) denotes where tree samples were not found.
Tree density expressed as number of trees per 500 m2 for all trees taller than 1.5m .... 116
Table 5.1. Parameter values for the base model of the forest tent caterpillar population dynamics 153
xv (I) General Introduction
1 This thesis is based on the following articles that will be referred to by their assigned roman numerals:
(II) Terrestrial insect communities and the restoration of an industrially perturbed landscape: assessing success and surrogacy. Jennifer J. Babin-Fenske and Madhur
Anand. In-press 2010 Restoration Ecology
(III) Patterns of Insect Communities Along a Stress Gradient Following
Decommissioning of a Cu-Ni Smelter. Jennifer J. Babin-Fenske and Madhur Anand.
Submitted to Biodiversity and Conservation
(IV) Forest tent caterpillar (Malacosoma disstria Hiibner) population density along a stress gradient in a northern Ontario forest. Jennifer J. Babin-Fenske and Madhur
Anand. In preparation for submission
(V) Agent-based simulation model shows that stress may promote Forest Tent
Caterpillar {Malacosoma disstria Hiibner) defoliation. Jennifer J. Babin-Fenske and
Madhur Anand. Submitted to Ecological Modelling
2 INTRODUCTION
Defining stress with reference to plants and insects
Stress ecology emerged as a field of science in the 1970's (Barrett et al. 1976) and aims to study effects of stress on all aspects of the ecosystem in order to aid future predictions and understand complex interactions. In this paper, Barrett et al. define stress as " a perturbation (stressor) applied to a system (a) which is foreign to that system or (b) which is natural to that system but applied at an excessive level (e.g., nitrogen, phosphorous, or water)". For a broad definition in ecology, Freedman (1995) considers stress as
"environmental influences that cause measurable ecological changes or that limit
ecological development". Natural stressors include fire, drought and volcano eruptions while anthropogenic stressors include pollution from smelter emissions, introduction of
exotic species and the lingering impact of human activities and disturbances such as
agricultural and forest harvesting and urban development (Rapport et al. 1985; Allen
2001). Different stressors at the individual level can often produce similar responses and this is especially true at the cellular level (Selye 1975). Effects of population level or
ecosystem level stress, on the other hand, can be quite variable with both positive and
negative changes in factors such as primary production, rate of decomposition, frequency
of disease, size of organisms and diversity (Odum 1985; Rapport et al. 1985; Gray 1989).
The positive effects of ecosystem stress on certain organisms include increased primary
productivity from a release of nutrients in pollutant discharge, increase in diversity after a
stressor removes a keystone species that once suppressed other species, and increased
3 nutrient availability and microbial activitiy from frass and leaf particles during outbreaks
of insect defoliators (Rapport et al. 1985; Hunter 2001).
The definition of stress may be different depending on the organism or ecosystem to which it refers. For example, stress in animals refers to alterations in the environment that
cause behavioural or physiological changes in the organism that may be costly for
metabolic processes (Buchanan 2000). In insects, stressors or combinations of stressors
such as food stress, non-lethal predator presence, and rearing density can reduce larval
growth rate, wing size at emergence, body size, asymmetry, fecundity, reproductive
investment and wing melanization (Stoks 2001; Talloen et al. 2004; Bauerfeind and
Fischer 2005). Plant stress may be defined as a mechanism that limits the rate of dry
matter production of vegetation (Grime 2001). This may be compared to a disturbance
where the biomass is not only limited, but there is partial or total destruction or death of
the plant material (Grime 2001). The lingering effects of a disturbance (such as fire and
floods) may subsequently create a stressed forest ecosystem if essential components for
plants, such as nutrients and shade, remain limited. I shall herein consider such
disturbances as sources of lingering stress. The resulting stress may cause changes in leaf
area, root surface area, leaf chemistry, resin flow and seed production (Grime 2001;
Kopper and Lindroth 2003; Knebel et al 2008).
Despite a great amount of work on the subject, a general theory of stress ecology is
lacking (Gray 1989). In addition, stress is generally expected to increase with both
human and natural perturbations in the next few decades. For example, two major
4 stressors in particular are anticipated to increase drastically in the coming years, climate change and pollution. Global mean annual temperatures are expected to increase 1-4 C° and greenhouse gas emissions will increase from 25-90% within the next 90 years while other catastrophic events such as flash floods, drought and fire may increase in frequency
(IPCC 2007). Other sources of pollution such as sulfur emissions are also expected to increase in the next 40 years, especially in rapidly developing areas like Southeast Asia that does not have emission control measures in place (Fowler et al. 1999) and industrial barrens may become more numerous (Zvereva and Kozlov 2010).
In this thesis I examine both specific and generalized stressors as well as both direct and indirect stressors. The specific ones include thin, acidic and contaminated soils (direct), loss of forest cover and reduced plant diversity (indirect). In one chapter, I examine a generalized stressor (modeled after climate change or pollution) in a model of forest-pest dynamics. I examine the response of insects to the stressor (direct affect of stress on insects) or their response to plants affected by stress (indirect affect of stress on insects from plant stress). Such responses include changes in composition, productivity, diversity, and susceptibility to pests or pathogens for plants and changes in feeding behaviour in insects. I examine how stress from past pollution and the loss of forest cover affects insect communities as well as how general stressors may alter herbivory and insect defoliator dynamics.
Insect-Forest Interactions and Stress
Despite their obvious and heralded contributions to ecosystems and our economy
5 (Scudder 2009), insects are often omitted from management programs to recover an
ecosystem from stress (Majer et al. 2007) or underrepresented in studies that examine the recovery of a terrestrial ecosystem (Dunn 2004). Recent theories in stress ecology such as
the Stress Gradient Hypothesis (Bertness and Callaway 1994; Callaway and Walker
1997) have only recently broadened their scope to include invertebrate herbivores
showing that positive (facilitative) relationships between plants and herbivores (crabs)
shift to negative (herbivorous) relationship as environmental stress decreases (Daleo and
Iribarne 2009). Furthermore, few studies have examined insect primary succession from
open-pit mining (Picaud and Petit 2007) and even fewer examine insect recovery in
industrial barrens (Kozlov and Zvereva 2007). Since stressed plants may be more
susceptible to insects (Plant Stress Hypothesis of White 1984) and insect herbivory
causes additional stress to plants, there can be a significant impact on the growth and
survivability of a recovering forest. We must enhance our understanding of how plant
stress affects the insect community and what techniques may be useful to aid the recovery
of certain taxa or reduce the destructive stress-induced behaviours of others.
It is clear that insects and plants have an intimate relationship in which stress plays an
important role. Both plant and insect responses to stress may affect pollination, gall
formation, seed dispersal, herbivory and other symbiotic relationships between insects
and plants. Pollination is not only essential for many plants to reproduce, but may also be
solely dependent on insect pollinators as in the obligate mutualism between figs (Ficus
spp. Moraceae) and their pollinator wasps (Hymenoptera: Agaonidae) (Ma et al. 2009).
Mineral stress, such as elevated levels of potassium, can reduce the attractiveness of
6 plants to bees and deters them from taking nectar (Waller et al. 1972). Gall inducing
insects may respond positively or negatively to water stress, depending on their resource requirements. For example, certain gall inducing cecidomyiids (Diptera: Cecidomyiidae) are more abundant on nonstressed plants, while others preferred water-stressed plants with more oviposition sites (meristematic terminals) from bushy architecture induced by
stress (Waring and Price 1990). The effects of stressed plants on herbivorous insects are numerous and include changes (both negative and positive) in adult weight, cocoon weight, larval survival, egg production and developmental time (Larsson 1989).
Although their intimate relationship may suggest a positive correlation between the stress
for the plant and stress for the insect, stressed plants may provide beneficial habitats for
insects as they can have altered and more palatable leaf chemistry and weakened
immunity to insect attack (Alstad et al. 1982; McLaughlin 1998; Kopper and Lindroth
2003). These support the Plant Stress Hypothesis (PSH) that suggests stressed host plants may have increased nutrients or decreased defensive compounds that promote insect herbivory (White 1984).
Direct and indirect effects of stress on insects also alter their relationships with plants
through changes in behaviour (Alstad et al. 1982; Filser et al. 2000), reproduction (Dale
1988; Heliovaara and Vaisanen 1993; Yang et al. 2007) and predation (Eeva et al. 2005).
Insect predators and parasitoids can respond to stress in ways that affects the relationship between their prey and the plant host. For example, natural enemies of herbivores have been shown to be more susceptible to the toxicity of pollution than herbivores (Alstad et
al. 1982, Zvereva and Kozlov 2000; Kramarz and Stark 2003). Enemy-free habitats may
7 also be created when predators or parasitoids have stronger adverse response to stressors such as pollution through toxicity, disturbance of habitat or changes in searching efficiency (Gate et al. 1995; Zvereva and Kozlov 2000; Zvereva and Kozlov 2006).
At the community level, stressors may affect richness, diversity, abundance and composition of both plant and insect communities (Alstad et al. 1982; Heliovaara and
Vaisanen 1993; Freedman 1995). Forests stressed by pollution from smelters, for example, have lower diversity (Anand et al. 2002) and this, in turn, may affect insect abundance (Bommarco and Banks 2003) and herbivory (Jactel and Brockerhoff 2007) through interactions with competitors, predators and chemical cues. For example,
Bommarco and Banks (2003) found that small plots with high diversity of plants had fewer herbivorous insects than plots with low diversity. This may be a result of a higher density of host plants with less diversity or an increase in generalist predators searching for diverse plots with alternate prey and resources. Species richness of herbivorous insects such as lepidopterans, hemipterans and orthopterans has been shown to be lower in stressed industrial areas (Heliovaara and Vaisanen 1993; Jana et al. 2006). Insect herbivore composition, and subsequent herbivory, may also be affected in polluted regions where food preference and subsequently breeding success of insectivorous birds was altered (Eeva et al. 2005).
In this thesis I examine the following insect-plant relationships: the influence of plant stress on the abundance and diversity of the insect community and the effects of both plant and insect stress on the tri-trophic relationship between trees, their defoliators and
8 parasitoids. More specifically, I examine how a plant stress gradient influences the
insects community (III), how recovery and assisted recovery of the plant community
from stress does not represent the recovery of the insect community (II), how a plant
stress gradient may affect the density of a major forest defoliator (IV) and how various plant and insect stressors may affect the population dynamics and outbreak cycle of a
forest defolialor through changes in demographic parameters such as dispersal and
searching efficiency of its parasitoid (V).
Forests, insects and stressors of the Boreal Shield landscape
Landscape scales
This project is set mainly within the boundaries of the Boreal Shield of Canada,
containing a large swath of the boreal forest's mixed forest ecotone and northern
coniferous forest, as outlined by Scott (1995). The ecological and economic wealth found
in the Boreal Shield includes vast continuous forests, peatlands and sugar maple stands.
Harvesting of such products is not considered one of the major sources of disturbance
(causing lingering stress) for boreal forests, which are fire (mainly due to lightning),
insects, disease and acid precipitation (Allen 2001; Stocks et al. 2002). Other sources of
stress are numerous, including droughts, floods and climate change. Furthermore, climate
change alone is expected to increase the frequency of various types of stress and
disturbance including fire, drought, species introduction, and defoliator outbreaks (Dukes
and Mooney 1999; Flannigan et al. 2000; Dale et al. 2001; IPCC 2007; Logan et al.
2010). With climate change and industrial emissions becoming increasing concerns, such
9 sources of stress can become more prevalent and intense while multiple stressors complicate responses (Paoletti et al. 2010).
At the landscape scale, stressors can affect large spans of forest. For example, changes in moisture and temperature from climate change are expected to increase forest insect outbreaks (Dale et al. 2001; Logan et al. 2003; Carroll et al. 2004; Logan et al. 2010).
Outbreaks of defoliators, such as the forest tent caterpillar {Malacosoma disstria Hiibner)
(FTC), can cause reduction in productivity and dieback, costing industries such as the lumber and sugar maple industries millions of dollars (Howse 1995; Wood et al. 2009). I will examine how stress affects the defoliation dynamics of the FTC at such a landscape scale (both provincial and regional) as well as how it affects demographic parameters for both the FTC and its parasitoid at the local scale.
The Case of Sudbury, Ontario
I emphasize that many sources of stress may occur in forest ecosystems; however, the model ecosystem for this study was chosen in Sudbury, Ontario due to its stress gradient and restoration regime (Figure 1.1). Mining and smelting practices in this area once released SO2 into the air and heavy metals and contaminants into the soil of surrounding areas creating what was once the most ecologically disturbed region in Canada (Amiro and Courtin 1981; Gunn et al. 1995; Winterhalder 1995). Indeed, this region is one of the
36 industrial barrens found around the world (Kozlov and Zvereva 2007). The point source of stress I examine is a smelting complex in the region of Sudbury that was
10 decommissioned in 1972 (Gunn et al. 1995). Other regional mining activities have remained in production; however, have improved their technology and facilities to reduce
SO2 emissions by approximately 90% over the past 30 years (Potvin and Negusanti
1995). Heavy metal concentrations are significantly higher in the soils closest to the
smelter (Anand et al. 2003) and have negatively affected root growth, biomass and reproduction of various plant species (Gundermann and Hutchinson 1995; Anand et al.
2003; Ryser and Sauder 2006). Recovery from such devastated land may be considered primary succession (Picaud and Petit 2007) or anthropogenic succession (Bagatto and
Shorthouse 1999) as opposed to secondary succession observed after most stand- replacing disturbances in forest ecosystems such as fire and windfall. Few studies have
examined insect primary succession from post-mining events (Picaud and Petit 2007) and
even fewer examine the insect recovery in industrial barrens as examined here (Kozlov
and Zvereva 2007). In this thesis, I add to our understanding of insect recovery and
dynamics in ecosystems with post-mining and smelting stress. My results also provide an
initial investigation of the insect community in primary and anthropogenic succession of
industrial barrens. This information is not only beneficial to the continued monitoring of
the recovery of the Sudbury region, but is applicable to the distinct industrial barren
ecosystems currently found in over ten countries worldwide (Kozlov and Zvereva 2007)
Objectives and Hypotheses
My general objectives are to examine how stress-mediated changes within a forest
ecosystem may alter specific population dynamics and the broader community
11 composition of terrestrial insects. I also examine the subsequent recovery from a
decommissioned copper-nickel smelting complex of the Greater City of Sudbury, Ontario
in the Boreal Shield to assess the lingering stress of past pollution and the success of restoration efforts on the stressed environment. I examine both direct effects of stress on
insect communities and the indirect effects through stress on plant communities. Chapters
II, III, and IV specifically explore a region devastated by mining and smelting pollution.
Chapter IV uses a generalized stressor while focusing on a specific insect population
density, the forest tent caterpillar (FTC) {Malacosoma disstria Hiibner). Chapters II and
III examine a variety of insect taxa at different taxonomic resolution to examine
community composition and changes in diversity, abundance and richness.
The empirical field-based studies of this project focus around Sudbury, Ontario, a
"natural laboratory" for examining effects of past pollution, recovery and restoration. I
also examine a theoretical source of stress to examine how generalized stressors can
affect the outbreak cycle population dynamics of a major forest defoliator, FTC. Both
empirical and theoretical approaches are important and have been considered priority
areas for research in emerging issues landscape ecology (Wu and Hobbs 2002).
The following are my hypotheses: I hypothesize that stressors can alter vegetation in
ways that benefit insect herbivores like FTC. For example, decreased diversity from the
soil contaminants (Anand et al. 2002) may increase herbivory through reduced non-host
interference (both physically and chemically) (Jactel and Brockerhoff 2007). When
examining the stress gradient extending from the decommissioned smelting complex, I
12 expect that although plant diversity has increased with an increase in distance from the smelting complex (Anand et al. 2002) and with aid of restoration efforts (Rayfield et al.
2005), the insect community will not have recovered to the same degree. Insects may have different patterns of diversity and abundance than plants since they have numerous interactions with predators and competitors (Bommarco and Banks 2003). I also expect that within insect communities, there will also be differences between trophic levels, within the same trophic guild and between taxa. Herbivores have different and sometimes opposite response to air pollution than predators that may suffer from higher levels of toxins through biomagnification along trophic levels or decline of preferred habitat
(Zvereva and Kozlov 2010). I also hypothesize that predators will further have intraguild differences in diversity or abundance partly due to habitat preferences. My simulation model of the FTC is anticipated to provide more insight into the demographic parameters such as dispersal, fecundity, searching efficiency and mortality that may alter the cycle of this defoliating insect in stressed environments. I expect that searching efficiency of the parasitoid will have a strong influence on the dynamics of FTC compared to the other demographic parameters.
13 REFERENCES
Allen E. 2001. Forest health assessment in Canada. Ecosystem Health 7:28-34.
Alstad D. N., G. F. J. Edmunds, and L. H. Weinstein. 1982. Effects of air pollutants on
insect populations. Annual Review of Entomology 27:369-384.
Amiro B. D., G. M. Courtin. 1981. Patterns of vegetation in the vicinity of an industrially
disturbed ecosystem, Sudbury, Ontario. Canadian Journal of Botany 59:1623-1639.
Anand M., B. C. Tucker, and R. Desrochers. 2002. Ecological monitoring of terrestrial
ecosystem recovery from man-made perturbation: assessing community complexity.
Pages 341-351 In C. A. Brebbia and J. F. Martin-Duque, editors. Air Pollution X.
WIT Press, Southampton, United Kingdom.
Anand M., K. Ma, A. Okonski, S. Levin, and D. McCreath. 2003. Characterising
biocomplexity and soil microbial dynamics along a smelter-damaged landscape
gradient. Science of The Total Environment 311:247-259.
Bagatto G., J. D. Shorthouse. 1999. Biotic and abiotic characteristics of ecosystems on
acid metalliferous mine tailings near Sudbury, Ontario. Canadian Journal of Botany
77:410-425.
Barrett G. W., G. M. van Dyne, and E. P. Odum. 1976. Stress ecology. Bioscience
26:192-194.
14 Bauerfeind S. S., K. Fischer. 2005. Effects of food stress and density in different life
stages on reproduction in a butterfly. Oikos 111:514-524.
Bertness M. D., R. Callaway. 1994. Positive interactions in communities. Trends in
Ecology and Evolution 9:191-193.
Bommarco R., J. E. Banks. 2003. Scale as modifier in vegetation diversity experiments:
Effects on herbivores and predators. Oikos 102:440-448.
Buchanan K. L. 2000. Stress and the evolution of condition-dependent signals. Trends in
Ecology and Evolution 15:156-162.
Callaway R. M., L. R. Walker. 1997. Competition and facilitation: A synthetic approach
to interactions in plant communities. Ecology 78:1958-1965.
Carroll A. L., S. W. Taylor, J. Regniere, and L. Safranyik. 2004. Effects of climate
change on range expansion by the mountain pine beetle in British Columbia. Pages
223-232 In T. L. Shore, J. E. Brooks, and J. E. Stone, editors. Mountain pine beetle
symposium: challenges and solutions. October 30-31, 2003, Kelowna, British
Columbia, Natural Resources Canada, Canadian Forest Service, Pacific Forestry
Centre, Information Report BC-X-399, Victoria,B.C.
Cobbold C. A., M. A. Lewis, F. Lutscher, and J. Roland. 2005. How parasitism affects
critical patch-size in a host-parasitoid model: Application to the forest tent
caterpillar. Theoretical Population Biology 67:109-125.
15 Dale D. 1988. Plant-mediated effects of soil mineral stresses on insects. Pages 35-110 In
E. A. Heinrichs, editor. Plant Stress-Insect Interactions, Wiley, New York.
Dale V. H., L. A. Joyce, S. McNulty, R. P. Neilson, M. P. Ayres, M. D. Flannigan, P. J.
Hanson, L. C. Irland, A. E. Lugo, C. J. Peterson, D. Simberloff, F. J. Swanson, B. J.
Stocks, and M. Wotton. 2001. Climate change and forest disturbances. Bioscience
51:723-734.
Daleo P., O. Iribarne. 2009. Beyond competition: The stress-gradient hypothesis tested in
plant-herbivore interactions. Ecology 90:2368-2374.
Dukes J. S., H. A. Mooney. 1999. Does global change increase the success of biological
invaders? Trends in Ecology and Evolution 14:135-139.
Dunn R. R. 2004. Recovery of faunal communities during tropical forest regeneration.
Conservation Biology 18:302-309.
Eeva T., M. Ryoma, and J. Riihimaki. 2005. Pollution-related changes in diets of two
insectivorous passerines. Oecologia 145:629-639.
Filser J., R. Wittmann, and A. Lang. 2000. Response types in Collembola towards copper
in the microenvironment. Environmental Pollution 107:71-78.
Flannigan M. D., B. J. Stocks, and B. M. Wotton. 2000. Climate change and forest fires.
The Science of the Total Environment 262:221-229.
16 Fowler D., J. N. Cape, M. Coyle, C. Flechard, J. Kuylenstierna, K. Hicks, D. Derwent, C.
Johnson, and D. Stevenson. 1999. The global exposure of forests to air pollutants.
Water, Air, and Soil Pollution 116:5-32.
Freedman B. 1995. Environmental Ecology: The Ecological Effects of Pollution,
Disturbance, and Other Stresses. Academic Press, San Diego.
Gate I. M., S. McNeill, and M. R. Ashmore. 1995. Effects of air pollution on the
searching behaviour of an insect parasitoid. Water, Air, and Soil Pollution 85:1425-
1430.
Gray J. S. 1989. Effects of environmental stress on species rich assemblages. Biological
Journal of the Linnean Society 37:19-32.
Grime J. P. 2001. Plant Strategies, Vegetation Processes, and Ecosystem Properties.
Wiley, New York.
Gundermann D. G., T. C. Hutchinson. 1995. Changes in soil chemistry 20 years after the
closure of a nickel-copper smelter near Sudbury, Ontario, Canada. Journal of
Geochemical Exploration 52:231-236.
Gunn J. M., W. Keller, J. Negusanti, R. Potvin, P. Beckett, and K. Winterhalder. 1995.
Ecosystem recovery after emission reductions: Sudbury, Canada. Water, Air, and
Soil Pollution 85:1783-1788.
Heliovaara K., R. Vaisanen. 1993. Insects and Pollution. CRC Press, Boca Raton.
17 Howse G. M. 1995. Forest Insect Pests in the Ontario Region. Pages 41-57 In J. A.
Armstrong and W. G. H. Ives, editors. Forest Insect Pests in Canada, Natural
Resources Canada, Canadian Forest Service, Ottawa, Ontario.
Hunter M. D. 2001. Insect population dynamics meets ecosystem ecology: effects of
herbivory on soil nutrient dynamics. Agricultural and Forest Entomology 3:77-84.
IPCC. 2007. Climate Change 2007: Synthesis Report. Contribution of Working Groups I,
II and III to the Fourth Assessment Report of the Intergovernmental Panel on
Climate Change [Core Writing Team, Pachauri, R.K and Reisinger, A. (eds.)].
IPCC, Geneva, Switzerland.
Jactel H., E. G. Brockerhoff. 2007. Tree diversity reduces herbivory by forest insects.
Ecology Letters 10:835-848.
Jana G., K. Misra, and T. Bhattacharya. 2006. Diversity of some insect fauna in industrial
and non-industrial areas of West Bengal, India. Journal of Insect Conservation
10:249-260.
Knebel L., D. J. Robison, T. R. Wentworth, and K. D. Klepzig. 2008. Resin flow
responses to fertilization, wounding and fungal inoculation in loblolly pine (Pinus
taeda) in North Carolina. Tree Physiology 28:847-853.
Kopper B. J., R. L. Lindroth. 2003. Effects of elevated carbon dioxide and ozone on the
phytochemistry of aspen and performance of an herbivore. Oecologia 134:95-103.
18 Kozlov M. V., E. L. Zvereva. 2007. Industrial barrens: Extreme habitats created by non-
ferrous metallurgy. Reviews in Environmental Science and Biotechnology 6:231-
259.
Kramarz P., J. D. Stark. 2003. Population level effects of cadmium and the insecticide
imidacloprid to the parasitoid, Aphidius ervi after exposure through its host, the pea
aphid, Acyrthosiphon pisum (Harris). Biological Control 27:310-314.
Larsson S. 1989. Stressful times for the plant stress: Insect performance hypothesis.
Oikos 56:277-283.
Logan J. A., W. W. Macfarlane, and L. Willcox. 2010. Whitebark pine vulnerability to
climate change induced mountain pine beetle disturbance in the Greater Yellowstone
Ecosystem. Ecological Applications e-View. doi: 10.1890/09-0655.
Logan J. A., J. Regniere, and J. A. Powell. 2003. Assessing the impacts of global
warming on forest pest dynamics. Frontiers in Ecology and the Environment 1:130-
137.
Ma W., Y. Peng, D. Yang, and J. Guan. 2009. Coevolution of reproductive characteristics
in three dioecious fig species and their pollinator wasps. Symbiosis 49:87-94.
Majer J. D., K. E. C. Brennan, and M. L. Moir. 2007. Invertebrates and the restoration of
a forest ecosystem: 30 years of research following bauxite mining in Western
Australia. Restoration Ecology 15:S104-S115.
19 McLaughlin D. 1998. A decade of forest tree monitoring in Canada: Evidence of air
pollution effects. Environmental Reviews 6:151-171.
Odum E. P. 1985. Trends expected in stressed ecosystems. Bioscience 35:419-422.
Paoletti E., M. Schaub, R. Matyssek, G. Wieser, A. Augustaitis, A. Bastrup-Birk, A.
Bytnerowicz, M. S. Gunthardt-Goerg, G. Muller-Starck, and Y. Serengil. 2010.
Advances of air pollution science: From forest decline to multiple-stress effects on
forest ecosystem services. Environmental Pollution 158:1986-1989.
Picaud F., D. P. Petit. 2007. Primary succession of Orthoptera on mine tailings: Role of
vegetation. Annales de la Societe Entomologique de France 43:69-79.
Potvin R., J. Negusanti. 1995. Declining industrial emissions, improving air quality and
reduced damage to vegetation. Pages 51-65 In J. Gunn, editor. Environmental
Restoration and Recovery of an Industrial region, Springer-Verlag, New York.
Rapport D. J., H. A. Regier, and T. C. Hutchinson. 1985. Ecosystem behavior under
stress. The American Naturalist 125:617-640.
Rayfield B., M. Anand, and S. Laurence. 2005. Assessing simple versus complex
restoration strategies for industrially disturbed forests. Restoration Ecology 13:639-
650.
Ryser P., W. R. Sauder. 2006. Effects of heavy-metal-contaminated soil on growth,
phenology and biomass turnover of Hieracium piloselloides. Environmental
Pollution 140:52-61.
20 Scott G. A. J. 1995. Canada's Vegetation : A World Perspective. McGill-Queen's
University Press, Montreal.
Scudder G. G. E. 2009. The importance of insects. Pages 7-32 In R. Foottit and P. H.
Adler, editors. Insect Biodiversity: Science and Society. Wiley-Blackwell, Hoboken,
NJ.
Selye H. 1975. Stress Without Distress. Signet, New York.
Stocks B. J., J. A. Mason, J. B. Todd, E. M. Bosch, B. M. Wotton, B. D. Amiro, M. D.
Flannigan, K. G. Hirsch, K. A. Logan, D. L. Martell, and W. R. Skinner. 2002.
Large forest fires in Canada, 1959-1997. Journal of Geophysical Research 108:1-12.
Stoks R. 2001. Food stress and predator-induced stress shape developmental performance
in a damselfly. Oecologia 127:222-229.
Talloen W., H. V. Dyck, and L. Lens. 2004. The cost of melanization: Butterfly wing
coloration under environmental stress. Evolution 58:360-366.
Waller G. D., E. W. Carpenter, and O. A. Ziehl. 1972. Potassium in onion nectar and its
probable effect on attractiveness of onion flowers to honey bees. Journal of the
American Society for Horticultural Science 97:535-539.
Waring G. L., P. W. Price. 1990. Plant water stress and gall formation (Cecidomyiidae:
Asphondylia spp.) on creosote bush. Ecological Entomology 15:87-95.
21 White T. C. R. 1984. The abundance of invertebrate herbivores in relation to the
availability of nitrogen in stressed food plants. Oecologia 63:90-105.
Winterhalder K. 1995. Early history of human activities in the Sudbury area and
ecological damage to the landscape. Pages 17-31 In J. Gunn, editor. Environmental
Restoration and Recovery of an Industrial region, Springer-Verlag, New York.
Wood D., R. Yanai, D. Allen, and S. Wilmot. 2009. Sugar maple decline after defoliation
by forest tent caterpillar. Journal of Forestry 107:29-37.
Wu J., R. Hobbs. 2002. Key issues and research priorities in landscape ecology: An
idiosyncratic synthesis. Landscape Ecology 17:355-365.
Yang S., T. Ruuhola, and M. J. Rantala. 2007. Impact of starvation on immune defense
and other life-history traits of an outbreaking geometrid, Epirrita autumnata: A
possible causal trigger for the crash phase of population cycle. Annales Zoologici
Fennici 44:89-96.
Zvereva E. L., M. V. Kozlov. 2010. Responses of terrestrial arthropods to air pollution: A
meta-analysis. Environmental Science and Pollution Research 17:297-311.
Zvereva E. L., M. V. Kozlov. 2006. Top-down effects on population dynamics of
Eriocrania miners (Lepidoptera) under pollution impact: does an enemy-free space
exist? Oikos 115:413-426.
Zvereva E. L., M. V. Kozlov. 2000. Effects of air pollution on natural enemies of the leaf
beetle Melasoma lapponica. Journal of Applied Ecology 37:298-308.
22 Figure 1.1. Map of Sudbury, Ontario with locations of smelters, decommissioned roastyards and research sites labeled 1 through 5. Site 1A and 2A have had assistance through liming, seeding and/or planting.
23 (II) Terrestrial Insect Communities and the Restoration of an Industrially
Perturbed Landscape: Assessing Success and Surrogacy
24 ABSTRACT
Restoration is a common method by which humans can repair damaged ecosystems. Most of the work to date on terrestrial systems has focused on restoring plant communities, with an assumption that the conditions that lead to more diverse plant communities will also lead to a restoration of insect communities. This is not often the case. Here, we examine the recovery of terrestrial insect communities in naturally recovering and restored sites in response to severe past pollution caused by metal smelters in the region of Sudbury, Ontario. Although plant communities have often been used to represent the success of the restoration efforts, we find that insect communities have not recovered to the same degree as the vegetation. Insect diversity and richness did not reflect the patterns found in the plant diversity or richness and therefore, the use of plant diversity or richness for restoration success should be cautionary in landscapes devastated by copper- nickel smelting operations. Furthermore, we present directions on how cross-taxa surrogacy can be useful to further aid the use of insects as indicators of restoration success.
25 INTRODUCTION
Industrial barrens from the long-term smelting of copper and nickel are found in many regions around the world (e.g., Canada, Finland, Russia) and span thousands of hectares
(Kozlov and Zvereva 2007). The resulting derelict land has relatively low levels of diversity and abundance in many taxa, including plants (Hutchinson and Whitby 1977;
Winterhalder 1996), biting insects (Kozlov et al. 2005), and vertebrates (Kataev et al.
1994). Despite reduced pollution levels (or the removal of the pollution source entirely), recovery of these ecosystems may be slow due to legacy effects such as lingering
concentrations of heavy metals and hydrogen ions (acidity) in the soil (Gundermann and
Hutchinson 1995), and the persistence of thin soil layers susceptible to erosion
(Hutchinson and Whitby 1977; Winterhalder 1996).
Initial restoration efforts in various industrial barrens have focused on liming, seeding
and tree planting and have been successful at increasing the plant diversity of these
ecosystems (Lautenbach et al. 1995; Winterhalder 1996; Kiikkila 2003 and references therein; Rayfield et al. 2005). Recent studies have shown that the arthropod community
diversity has lagged behind restoration of plant community diversity (Longcore 2003;
Majer et al. 2007). As a result, restored sites have been called "depauperate imitations",
as they superficially resemble the undisturbed sites in some ways but do not have the
same arthropod diversity or composition (Longcore 2003). Although some studies have
suggested that insect communities may be correlated to plant species richness and plant
complexity (Brose 2003; Pearce et al. 2003), restoration of the diversity of the plant
26 community does not always imply restoration of the full range of fauna and biological processes. An increase in plant diversity or abundance does not necessarily result in an increase in insect diversity or abundance due to interactions with competitors, predators and parasitoids. For example, plant richness can influence insect herbivores while the insects predators may have stronger relationships with the herbivores and detritivores than with the plants (Perner et al. 2003). For certain size plots, generalist predators have been found to be more abundant in plots with higher plant diversity where more diverse prey and alternate prey may inhabit. In turn, there was a decrease in abundance of insect herbivores in diverse plots due to increased predator pressure (Bommarco and Banks
2003). Furthermore, Anand et al. (2005) found that although vascular plant diversity correlated with the bryophyte community diversity in unassisted sites of the Sudbury region, restored sites showed no relationship between the two taxonomic groups, possibly due to the introduction of non-native plant species.
Restoring insect communities is important due to the roles that various insect groups play in ecosystem structure and function. The presence of certain insect species can reveal particular aspects of ecosystem dynamics. Ants (Hymenoptera: Formicidae) can significantly affect soil nutrients, temperature and aeration, and seed dispersal, which in turn may alter the soil and vegetation of the area (Lyford 1963; MacMahon et al. 2000;
Majer et al. 2007). In stressed ecosystems with thin or nutrient-poor soils, ants may therefore be essential for soil composition and revegetation. In the temperate North
American forests, ants are predators of forest defoliators like the spruce budworm
(Choristoneura fumiferana Clemens) (Sanders and Pang 1992) and are dispersers of
27 forest herb seeds like Viola sp. and Trillium sp. (Beattie and Culver 1981). Carabid beetles (Coleoptera: Carabidae) are primarily predators (Ball and Bousquet 2001), although other feeding guilds (phytophages and omnivores) within the family are often overlooked (Harvey et al. 2008). Certain carnivorous species may indicate the presence of particular prey items or act as surrogates for the biodiversity of other beetle families.
Both carabids and ants have been used as bioindicators of stress and disturbances such as clearcutting, fire, and mining practices (Majer 1983; Jennings et al. 1986; Heliola et al.
2001; Rainio and Niemela 2003; Teixeira et al. 2005; da Silva et al. 2008).
Insects are considered one of the most feasible taxa to work with for a range of ecological studies (Lawes et al. 2005), and ants and carabid beetles in particular are further considered the most useful study organisms within terrestrial insects (Beaudry et al.
1997; Majer et al. 2004). This is due to factors such as their abundance, diversity of guilds or species and quick response to environmental change (Majer 1983; Beaudry et al. 1997; Rainio and Niemela 2003). Despite their importance, biodiversity assessment and monitoring of insects is often not feasible for short-term studies due to the intensive taxonomic identification and research costs. Surrogacy may therefore be explored. The two common approaches of surrogacy for insects are cross-taxon surrogacy (using one taxonomic group to represent others) and using higher taxa (family, genus, etc) as surrogates for lower taxa (species). Studies have suggested that using higher taxa is a better form of surrogacy for invertebrates (more congruency or correlation) than cross- taxon, allowing for more rapid evaluation by parataxonomists (Lovell et al. 2007). If cross-taxon surrogacy is used; however, it should only be used to represent taxa within
28 the same trophic guild and a multi-taxa approach should be used to cover a broad range of guilds (Lovell et al. 2007; Majer et al. 2007).
In this paper we compare the plant and insect communities of sites recovering naturally
(unassisted) from past pollution with sites under a restoration (assisted) regime near
Sudbury, Ontario, Canada. Our objective is to determine if restoration efforts are affecting the terrestrial insect community and at what taxonomic level these effects can be observed. We address the potential of the surrogacy approach by comparing the results of the various taxa,. Although cross-taxon surrogacy and higher taxon surrogacy have been in much debate, a multi-taxa approach may prove to be useful for rapid assessment of restoration success (Lovell et al. 2007; Majer et al. 2007).
METHODS
Site description
The focus of this paper is the region of Sudbury, Ontario, Canada, which was once considered one of the most ecologically disturbed regions in Canada due to mining and smelting practices of the late 1800s and early 1900s that decimated practically all woody plants in the region and resulted in the contamination and erosion of the soil (Amiro and
Courtin 1981; Winterhalder 1995). The restoration techniques used in the Sudbury area include liming, seeding and planting trees and have been successful in the recovery of plants in many areas (Winterhalder 1996; Rayfield et al. 2005). The ecological impact of
29 such pollution has been documented for various taxa, including plants (Backor and
Fahselt 2004; Anand et al. 2005; Rayfield et al. 2005), aquatic invertebrates (Yan et al.
2004), fish (Pyle et al. 2005) and mites (St. John et al. 2002). The few studies that have focused on terrestrial insects in this area aimed to examine the effects of fragmentation on herbivore outbreaks (Roland 1993) and the accumulation of metals in the insect herbivores (Bagatto and Shorthouse 1996). To our knowledge, no studies have used ants or carabids as the primary study organisms in assessing restoration success in this region.
Four study sites were selected from the Sudbury region (46°27.5'N to 46°28.6'N and
80°51.0'W to 80°53.1'W) in Ontario. Canada. The area is part of the Boreal Shield of
Canada in the Great Lakes-St. Lawrence forest ecotone region surrounding Sudbury,
Ontario. The Great Lakes-St. Lawrence forest is a climatically transitional forest between the Boreal forest to the north and the temperate deciduous forest to the south, often dominated by white pine (Pinus strobus L.), white birch (Betula papyrifera Marshall) and red pine (Pinus resinosa Aiton) (Scott 1995). With a temperate climate, the summer temperature in the Sudbury region reaches over 30°C and winter temperatures fall below
-30°C. Although the soils are mainly podzol or gleysol, years of acidification and erosion have left many areas with a thin acidic soil layer.
The sites are located near a smelting complex that was decommissioned in 1972. There are two localities, Coniston and Daisy Lake, with two sites within each locality, an unassisted site and an assisted site (Figure 2.1). Both unassisted sites are naturally recovering and are characterized by a thin or absent soil layer and a pH ranging from 3.7
30 to 4.6. The Coniston unassisted site is located approximately 1.7 km from the smelter and the vegetation is composed mainly of grasses, mosses and white birch where it is not bare ground or rock. The Daisy Lake unassisted site is approximately 4.2 km from the smelting complex and has distinctly more soil, plant species and ground cover than
Coniston but remains relatively open with few trees.
The assisted sites have had various restoration techniques applied to them. The Coniston assisted site is approximately 0.7 km from the smelting complex and has undergone over
23 years of rehabilitation through liming, fertilizing and seeding. Jack pine {Pinus banksiana Lambert), red pine (Pinus resinosa Aiton), white pine {Pinus strobus L.) and red oak (Quercus rubra L.) were also planted at this site within 30 m of our transect. The
Daisy Lake assisted site is 3.6 km from the smelting complex and has had over 12 years of rehabilitation from aerial-liming, seeding and planting of jack pine.
We use previously manipulated sites on the landscape, which we believe have allowed a sufficient time for insect communities to recover. The selected assisted sites have obviously not received the same restoration regimes. Our objective here is not to compare different restoration regimes, but to compare assisted with unassisted sites. These sites represent the best opportunities to study assisted along with unassisted sites in the same relative position from the decommissioned smelter.
31 Sampling Procedure
Insects were collected using ramp pitfall traps following methods based on Bouchard et
al. (2000) and Pearce et al. (2005). Traps consisted of 473 mL, 115 mm top diameter
covered food containers with two side holes for entry of ramp and insects. Anti-slip
granulated paint was used on the surface of the ramps and a combination of propylene
glycol (RV plumbing antifreeze), water and soap acted as the trap mixture. Three stations
were marked at each site and distributed at 25-metre intervals along a linear transect to
avoid sampling bias (Ward et al. 2001). Each station was associated with four pitfall
traps. This resulted in 12 traps per site within three stations along a 75-metre transect
perpendicular to the slope of the hill.
Trap samples were collected every week for five weeks in June and July of 2006. The ant
community and higher insect taxa were sampled for one week in 2007, while the beetle
community was further sampled for five weeks in 2007 to increase its sample size. Plant
community data were collected in 2006 using 1 x 1 m quadrats along a 100-m transect
parallel to the pitfall trap transect, except at the Coniston assisted site where we needed a
50-m transect. Identification of plant species within each quadrat was determined on-site.
Preliminary results from data collected on these sites over the past four years (J.J. Babin-
Fenske and M. Anand, unpublished data) suggest that the plant community does not
change significantly in time on a yearly basis.
Sorting, Preserving and Identifying
32 Only adults were selected for further study, while adult male ants and queen ants were also excluded for genera analyses as they do not necessarily represent the presence of a colony and most taxonomic research is based on the workers (Longino et al. 2002).
Specimens were identified to various taxonomic levels and were either housed in 75% ethanol or pinned. We identified all specimens to family or morphofamily using Borror et al. (1989). Ants and carabids were then sorted and sent to specialists for further identification. Ants were identified to genus while carabids were identified to species.
Data Analysis
Ants often present a problem for quantitative studies as their social behaviour promotes a clumping of individuals within samples. Two common methods to address this issue are to use incidence (presence/absence) data (Longino et al. 2002) or to transform abundance to an ordinal scale (Hoffman et al. 2000). For this study, we use incidence data for the analyses comparing ant communities with those of plants. Higher insect taxa and carabid species were examined by their abundance. Ants were removed from the higher taxa analyses due to their ubiquitous presence and high abundance.
Estimated richness was calculated using Estimates version 7.5.2 for Mac (Colwell 2005).
Each sample (trap or quadrat) was iterated 50 times to obtain standard deviations for
Coleman rarefaction (Colwell and Coddington 1994; Colwell et al. 2004). Although past studies using incidence data of ants have had successful results using Incidence-based
33 Coverage Estimate (ICE) compared to other richness estimators (Longino et al. 2002),
individual-based Coleman rarefaction allows for a comparison of estimates species richness curves between sites of unequal sampling efforts (Gotelli and Colwell 2001).
Shannon diversity and richness values were determined for the samples within each site
and compared by Wilcoxon signed-rank test. Patterns in community structure (relative
abundance and taxa identity) were further examined for select taxa through Nonmetric
Multidimensional Scaling (NMDS) using Statistica 6 (Statsoft Inc., 2001). For NMDS
analyses, insect data were pooled into their three stations for each year resulting in six
stations for each site. For the vegetation NMDS analyses, quadrats were grouped every
10 m along the 100-m transect to provide 10 data points for each site. The Coniston
assisted site only had 50-m transects, resulting in fewer data points. Bray-Curtis
similarity matrices were calculated on non-transformed data for ants and plants because
the data were already transformed into incidence data while carabid abundance data was
log(x+l) transformed (Clarke and Gorley 2006). Stress of the analyses were determined
based on two- or three-dimensional analyses established with 100 iterations of the data.
Two dimensions were deemed sufficient if stress was less than 0.1 (Clarke and Warwick
2001). The significance of the community differences between sites was determined with
permutational multivariate ANO VA through the PERMANOVA+ add-on for PRIMER 6
(Clarke & Gorley 2006).
34 RESULTS
A total of 7912 individuals of 115 morphotaxa were examined for the higher taxa analyses, excluding the ants (Formicidae) (Table 2.1). For the higher resolution taxa analyses, there were 12 genera of ants that were analysed and 23 carabid species (Table
2.2).
The Shannon diversity index of the ant community was significantly higher at the
Coniston assisted site than at the Coniston unassisted site (p<0.001, Z = -5.7) while there were no significant differences found at the Daisy Lake sites (Figures 2.2a, 2.2b). The
Shannon diversity of the carabid community revealed no significant differences (Figures
2.2c, 2.2d). In comparison, there was a significant increase in the plant species at both the
Coniston (p<0.01, Z=2.94) and Daisy Lake sites (p<0.01, Z=3.62) (Figures 2.3a, 2.3b).
This trend was also observed at the family level for the plants at both the Coniston
(p<0.01, Z=2.94) and Daisy Lake sites (p<0.05, Z=2.51) (Figures 2.3c, 2.3d).
The Coleman rarefaction suggests that our sampling effort was sufficient when examining ant genera (Figures 2.4a and 2.4b). Once again, the Coniston assisted site exhibited a higher estimated richness than the unassisted site. The Daisy Lake sites did not show a significant change in estimated richness between assisted and unassisted sites.
The sampling effort of the carabids appears to be not as robust, as the rarefaction does not reach an asymptote. Nevertheless, the rarefaction graph shows the estimated carabid
35 richness of both assisted sites would be larger than the unassisted sites (Figures 2.4c and
2.4d).
In terms of species richness, the plant species showed a significant increase in assisted
sites for both the Coniston sites (p<0.01, Z=10.11) and the Daisy Lake sites (p<0.01,
Z=7.42) (Figures 2.5a and 2.5b). Furthermore, the Coniston unassisted site exhibited
significantly lower plant richness than the Daisy Lake unassisted sites (p<0.05, Z = 2.5) while the Coniston assisted site exhibited significantly higher plant richness than the
Daisy Lake assisted site (p<0.01, Z = 8.0) The insect morphofamilies exhibited a
significant increase in richness in the Coniston assisted site (p<0.05, Z=-2.20) but no
difference was observed in the Daisy Lake site (P>0.05) (Figures 2.5c and 2.5d). The ant
genera exhibited a significant increase in richness in the Coniston assisted site (p<0.01,
Z=-5.84) but no difference in the Daisy Lake site (P>0.05) (Figures 2.5e and 2.5f). The
carabid species exhibited no significant difference between any of the sites (P>0.05)
(Figures 2.5g and 2.5h).
When examining the ant community structure data using NMDS, there was distinct
clustering of stations at the Coniston sites (2-D Stress = 0.04) but not the Daisy Lake sites
(3-D stress = 0.04), and a separation between the Coniston assisted site and the other sites
(3-D Stress = 0.08) (Figures 2.6). The ants showed a significant difference between the
two Coniston sites through PERMANOVA analyses (p<0.01, Pseudo-F=9.15), a slight
difference between the Daisy Lake sites (p=0.03, Pseudo-F=2.79) and no interaction
between years or stations (p>0.05). The carabid data, once again, did not reveal a
36 distinguishing pattern between sites for either Coniston or Daisy Lake in the graphical
NMDS (Figure 2.7) or PERMANOVA (p>0.05, Pseudo-F=1.23 and 0.67 respectively).
The NMDS for the vegetation reveals that there are community differences between the
two Coniston sites (2-D Stress = 0.03), between the two Daisy Lake sites (2-D Stress =
0.09), and between the Coniston assisted site and all other sites (3-D Stress = 0.07)
(Figures 2.8). PERMANOVA revealed significant difference between both the Coniston
(p<0.01, Pseudo-F=28.10) and Daisy Lake (p<0.01, Pseudo-F=9.34) sites.
DISCUSSION
We found that while plant (species and family) diversity increased significantly in
assisted areas compared to unassisted ones, insect (various taxa) diversity did not.
Restoration efforts were thus only moderately successful for reestablishing the terrestrial
insect community at the Coniston site compared to the recovery of the plant community.
The Daisy Lake site did not show successful restoration for the terrestrial insects in any
of the examined taxa. Thus, we conclude that restoration of plant communities, in terms
of plant diversity, may not be sufficient for bringing about ecosystem-level changes,
including the restoration of insect communities at least in the 13 years of restored
recovery observed at the Daisy Lake site. The NMDS results indicate that restoration
efforts at the Coniston site are indeed changing ant and vegetation community
composition at this site. This trend may also be observed by examining the insect taxa of
the sites (Tables 2.1 and 2.2). There were more taxa unique to the Coniston site and
included two saprovore taxa: Dermaptera (earwigs) and Eucinetidae (plate-thigh beetles).
37 Only two taxa exhibited more than one individual and were uniquely found at the Daisy
Lake assisted site and both are primarily considered predators: Cleridae (Checkered beetles) and Calosoma frigidum Kirby (Caterpillar hunter) (Borror et al. 1989, Majka et al. 2006). This suggests more availability of leaf litter (humus layer) at the Coniston site than the Daisy Lake site to support saprovore insects. We therefore found that the
Coniston assisted site has been moderately successful in reestablishing some insect taxa but the Daisy Lake site has not.
The differences between the technique and timing of restoration of the two assisted sites may account for the differences observed between the sites. Future studies may reveal whether or not aerial liming used at the Daisy Lake site is less effective than the manual liming used at the Coniston site or if Coniston's extra decade of restoration would result in significant changes. Indeed, studies show that the rehabilitation of insect species assemblages from a disturbed state to the expected original state may only take several years; however, the trend is not always linear or observed across different taxa due to successional changes in the habitat (Davis et al. 2002, Davis et al. 2003, Wassenaar et al.
2005). The discrepancies between Coniston and Daisy Lake do not explain why there is only a marginal improvement in certain aspects of the insect community for either site.
We therefore suggest reasons why either of the restoration techniques may not be successful for the insect community.
The taxa found exclusively on assisted sites tended to be phytophages. There were at least seven families of Hemiptera/Homoptera, two Orthoptera, one Thysanoptera, one
38 Dermaptera and two Coleoptera that are deemed herbivores (Borror et al. 1989) at these restored sites. The ant genus Temnothorax is often associated with aphid honeydew
(requiring a plant component) (Coovert 2005) and all members of carabid tribe Harpalini
(Bradycellus and Harpalus sp.) are considered phytophages (Lovei and Sunderland
1996).
While restoration efforts provide suitable habitat and food for certain herbivorous insects,
they may not enhance the forest structural complexity, which includes attributes such as
foliage arrangement, tree height and volume of large woody debris (McElhinny et al.
2005). The structural heterogeneity hypothesis specifies that the structural complexity of
the plant community may be more important in determining the richness of the insects (or
other higher trophic groups) than the number of plant species (Brose 2003, Harvey et al.
2008). Industrially disturbed sites, such as the ones studied here, are often devoid of any
woody debris or even a humus layer preferred by, or required for, many scavengers,
detritivores, predaceous species or other feeding guilds. Such aspects of the structural
complexity are not easily reestablished with the traditional restoration techniques used for
these sites.
The presence of herbivorous carabids (Bradycellus and Harpalus sp.) at both assisted
sites may also affect the success of restoration efforts. Studies have shown that other
seed-eating carabid species are effective granivores that may limit herbaceous weed
populations (Honek et al. 2009). Such granivores may hinder the rehabilitation process or
perhaps aid it by removing some non-native species preferentially. Another reason for the
39 lack of response of the insect community could simply be the fact that we could not capture the entire spectrum of insects. Our study focused on ground-dwelling insects that are found in severely affected landscapes and that are susceptible to pitfall trapping. The community captured by pitfall traps is an important one (Pearce et al. 2005) and thus we believe provides a reasonable baseline study, the first, to our knowledge, to examine restoration effects on insects in this area.
We found that plant diversity, both at the species and family levels, increased in both assisted sites while certain insect taxa diversity increased at the Coniston site but not for the Daisy Lake site. We therefore reject the idea that plant diversity may be used as surrogate for insect diversity in this region. Within the insect community itself, cross- taxon surrogacy is not always appropriate or reliable because insects of different guilds have such a diversity of environmental and nutritional requirements (Negi and Gadgil
2002; Lovell et al. 2007). A multi-taxa approach may provide different surrogates for groups of insects that share habitat, feeding strategies or guilds (Lovell et al. 2007).
Using higher taxa as surrogates for the species level has been more successful where there is stronger congruency between the groups (Negi and Gadgil 2002; Cardoso et al.
2008; Lovell et al. 2007). Rapid biodiversity assessments performed by using higher taxa may still provide useful information for conservation and biodiversity studies.
In this study, we showed that both the insect family level and ant genus level had a marginal improvement and change in composition from the restoration efforts at the
Coniston site but not at the Daisy Lake sites. There were no significant differences for the
40 carabid species (primarily predators). We suggest that if there are large changes in the community, such as those found at the Coniston sites, higher taxa surrogates would be sufficient to detect them. In addition, the restoration efforts may not be as effective for predators, such as most carabids, compared to generalists like ants (Spalding and Haes
1995). The differences between the family and genera analyses and the carabid species analyses, shows the value of examining different guilds in such a study. Insect families and ant genera exhibited similar results, showing larger diversity changes in the Coniston sites than in the Daisy Lake sites. Thus, we conclude that these insect taxa can be used as surrogates for other insects, increasing the feasibility of future studies of insect biodiversity in the area. At a broad level, family level analyses may provide insight into the success of restoration techniques if significant differences occur. For example, changes in family composition at an assisted site compared to an unassisted site can signify changes at the species level as well.
The lack of significant results for the carabid species is also an important component of this study as it examines the effects of restoration on predatory insects. Restoration techniques change the structure of the habitat by adding a herbaceous layer to barren rock that makes it suboptimal for visual predators such as many carabids (Spalding and Haes
1995; Harvey et al. 2008). In fact, there are arguments that degraded landscapes of industrial perturbation may be considered unique habitats that should be protected:
Benefits of the barren land include sun exposure for basking insects like butterflies and grasshoppers and space for fast-running predators (Spalding and Haes 1995, Kozlov and
41 Zvereva 2007). Therefore, it is not surprising that a generalist group like ants would benefit from restoration efforts while the carabids do not.
Restoration techniques in this area could be further adapted to help accelerate the recovery of both plants and insects. Recently, Eranen and Kozlov (2006) found that physical sheltering by wooden fences or natural rock can increase the survival and performance of some tree species such as mountain birch seedlings [Betula pubescens
ssp. czerepanovii (Orlova) Hamet-Ahti] in Monchegorsk, Russia. Another important area
of research relates to enhancing the humus layer to increase the natural recolonization of pioneer species and increase the survival of planted seedlings/shrubs, which has been
examined in Harjavalta, Finland by adding mulch to the soil (Helmisaari et al. 2007).
These and other methods of restoring forest floor complexity (by adding woody debris)
can provide areas for fauna to escape predators and the elements and may help to
accelerate insect diversity. Majer (1989) gives a list of various wildlife rehabilitation
techniques that may provide habitat and shelter for fauna of reclaimed land. These
techniques include adding direct-haul topsoil, creating large boulder and rock piles,
creating large brush piles, and implanting dead trees or large woody debris. Only a
handful of mining companies have taken the invertebrate fauna into consideration in
restoration efforts (Majer et al. 2007) but we suggest that it should become of increasing
importance.
We realize that the ultimate goal of restoration is not always simply the increase in
species biodiversity. Other factors must be taken into consideration such as ecosystem
42 functioning (e.g., nutrient cycling, soil formation) and ecosystem services (e.g., pollination, wood production) (Ehrenfeld 2000; Ruiz-Jaen and Aide 2005). Although there is a relationship between diversity and ecosystem function, the strength of the relationship is often under debate (Srivastava and Vellend 2005). Further studies could examine more explicitly the roles of both plant and insect communities in ecosystem function in the context of restoration.
Implications for Practice
• Insect diversity and richness does not mirror the plant diversity or richness and therefore, the use of plant diversity or richness as an indictor for restoration success should be cautionary in landscapes devastated by copper-nickel smelting operations
• Terrestrial insect fauna should be incorporated as an important indicator of restoration success for landscapes devastated by copper-nickel smelting operations
• Rapid assessment using the most abundant insect families may be sufficient for certain aspects of restoration in such landscapes
• More detailed analyses may use ants (Hymenoptera: Formicidae) and carabid beetles
(Coleoptera: Carabidae) as useful and feasible insect taxa as surrogates for generalist and predatory insect guilds, respectively.
43 ACKNOWLEDGEMENTS
We thank Gary Umphrey and Matthius Buck (University of Guelph); and the National
Identification Service, Canada, especially Patrice Bouchard and Henri Goulet for their insect identification. We thank Sarah Maki, Jenna Pillarella, Cory Laurin, and Tom
Fenske for their field and lab assistance. The site map was created by Leo Lariviere,
Laurentian University. This research was funded by the Natural Sciences and
Engineering Research Council, the Canada Research Chairs program, the Canadian
Foundation for Innovation, the University of Guelph and Laurentian University grants to
M. A.
44 REFERENCES
Amiro B. D., G. M. Courtin. 1981. Patterns of vegetation in the vicinity of an industrially
disturbed ecosystem, Sudbury, Ontario. Canadian Journal of Botany 59:1623-1639.
Anand M., S. Laurence, and B. Rayfield. 2005. Diversity relationships among taxonomic
groups in recovering and restored forests. Conservation Biology 19:955-962.
Backor M., D. Fahselt. 2004. Physiological attributes of the lichen Cladonia pleurota in
heavy metal-rich and control sites near Sudbury (Ont., Canada). Environmental and
Experimental Botany 52:149-159.
Bagatto G., J. D. Shorthouse. 1996. Accumulation of Cu and Ni in successive stages of
Lymantria dispar L. (Lymantriidae, Lepidoptera) near ore smelters at Sudbury,
Ontario, Canada. Environmental Pollution 92:7-12.
Ball G. E., Y. Bousquet. 2001. Carabidae Latreille, 1810. Pages 32-132 In R. H. J. Arnett
and M. C. Thomas, editors. American Beetles: Archostemata, Myxophaga,
Adephaga, Polyphaga: Staphyliniformia. Vol. 1. CRC Press, Boca Raton, FL.
Beattie A. J., D. C. Culver. 1981. The guild of myrmecochores in the herbaceous flora of
West Virginia forests. Ecology 62:107-115.
Beaudry S., L. C. Duchesne, and B. Cote. 1997. Short-term effects of three forestry
practices on carabid assemblages in a jack pine forest. Canadian Journal of Forest
Research 27:2065-2071.
45 Bommarco R., J. E. Banks. 2003. Scale as modifier in vegetation diversity experiments:
Effects on herbivores and predators. Oikos 102:440-448.
Borror D. J., C. A. Triplehorn, and N. F. Johnson. 1989. An Introduction to the Study of
Insects. Saunders College Pub, Philadelphia.
Bouchard P., T. A. Wheeler, and H. Goulet. 2000. Design for a low-cost, covered, ramp
pitfall trap. Canadian Entomologist 132:387-389.
Brose U. 2003. Bottom-up control of carabid beetle communities in early successional
wetlands: mediated by vegetation structure or plant diversity? Oecologia 135:407-
413.
Cardoso P., N. Scharff, C. Gaspar, S. S. Henriques, R. Carvalho, P. H. Castro, J. B.
Schmidt, I. Silva, T. Sziits, A. Castro, and L. C. Crespo. 2008. Rapid biodiversity
assessment of spiders (Araneae) using semi-quantitative sampling: A case study in a
Mediterranean forest. Insect Conservation and Diversity 1:71-84.
Clarke K. R., R. N. Gorley. 2006. PRIMER v6: User Manual/Tutorial. PRIMER-E,
Plymouth.
Clarke K. R., R. M. Warwick. 2001. Change in marine communities: An approach to
statistical analysis and interpretation. PRIMER-E, Plymouth.
Colwell R. K. 2005. EstimateS: Statistical Estimation of Species Richness and Shared
Species from Samples. Version 7.5. User's Guide and Application. Published at:
http://purl.oclc.org.librweb. laurentian. c a/estimates.
46 Colwell R. K., J. A. Coddington. 1994. Estimating terrestrial biodiversity through
extrapolation. Philosophical Transactions: Biological Sciences 345:101-118.
Colwell R. K., C. X. Mao, and J. Chang. 2004. Interpolating, extrapolating, and
comparing incidence-based species accumulation curves. Ecology 85:2717-2727.
Coovert G. A. 2005. The ants of Ohio (Hymenoptera: Formicidae). Bulletin of the Ohio
Biological Survey 15:1-196. da Silva P. M., C. A. S. Aguiar, J. Niemela, J. P. Sousa, and A. R. M. Serrano. 2008.
Diversity patterns of ground-beetles (Coleoptera: Carabidae) along a gradient of
land-use disturbance. Agriculture, Ecosystems & Environment 124:270-274.
Davis A. L. V., R. J. van Aarde, C. H. Scholtz, and J. H. Delport. 2002. Increasing
representation of localized dung beetles across a chronosequence of regenerating
vegetation and natural dune forest in South Africa. Global Ecology & Biogeography
11:191-209.
Davis A. L. V., R. J. van Aarde, C. H. Scholtz, and J. H. Delport. 2003. Convergence
between dung beetle assemblages of a post-mining vegetational chronosequence and
unmined dune forest. Restoration Ecology 11:29-42.
Ehrenfeld J. G. 2000. Defining the limits of restoration: the need for realistic goals.
Restoration Ecology 8:2-9.
47 Eranen J. K., M. V. Kozlov. 2006. Physical sheltering and liming improve survival and
performance of Mountain Birch seedlings: A 5-Year study in a heavily polluted
industrial barren. Restoration Ecology 14:77-86.
Gotelli N. J., R. K. Colwell. 2001. Quantifying biodiversity: Procedures and pitfalls in the
measurement and comparison of species richness. Ecology Letters 4:379-391.
Gundermann D. G., T. C. Hutchinson. 1995. Changes in soil chemistry 20 years after the
closure of a nickel-copper smelter near Sudbury, Ontario, Canada. Journal of
Geochemical Exploration 52:231-236.
Harvey J. A., W. H. van der Putten, H. Turin, R. Wagenaar, and T. M. Bezemer. 2008.
Effects of changes in plant species richness and community traits on carabid
assemblages and feeding guilds. Agriculture, Ecosystems and Environment 127:100-
106.
Heliola J., M. Koivula, and J. Niemela. 2001. Distribution of carabid beetles (Coleoptera,
Carabidae) across a boreal forest-clearcut ecotone. Conservation Biology 15:370-
377.
Helmisaari H.-S., M. Salemaa, J. Derome, O. Kiikkila, C. Uhlig, and T. M. Nieminen.
2007. Remediation of heavy metal-contaminated forest soil using recycled organic
matter and native woody plants. Journal of Environmental Quality 36:1145-1153.
Hoffmann B. D., A. D. Griffiths, and A. N. Andersen. 2000. Responses of ant
communities to dry sulfur deposition from mining emissions in semi-arid tropical
48 Australia, with implications for the use of functional groups. Austral Ecology
25:653-663.
Honek A., Z. Martinkova, P. Saska, and S. Koprdova. 2009. Role of post-dispersal seed
and seedling predation in establishment of dandelion (Taraxacum agg.) plants.
Agriculture, Ecosystems and Environment 134:126-135.
Hutchinson T. C., L. M. Whitby. 1977. Effects of acid rainfall and heavy-metal
particulates on a boreal forest ecosystem near Sudbury smelting region of canada.
Water, Air, and Soil Pollution 7:421-438.
Jennings D. T., M. W. Houseweart, and A. Francoeur. 1986. Ants (Hymenoptera:
Formicidae) associated with strip-clearcut and dense spruce-fir forests of Maine.
Canadian Entomologist 118:43-50.
Kataev G. D., J. Suomela, and P. Palokangas. 1994. Densities of microtine rodents along
a pollution gradient from a copper-nickel smelter. Oecologia 97:491-498.
Kiikkila O. 2003. Heavy-metal pollution and remediation of forest soil around the
Harjavalta Cu-Ni smelter, in SW Finland. Silva Fennica 37:399-415.
Kozlov M. V., E. L. Zvereva. 2007. Industrial barrens: Extreme habitats created by non-
ferrous metallurgy. Reviews in Environmental Science and Biotechnology 6:231-
259.
Kozlov M. V., N. K. Brodskaya, A. Haarto, K. Kuusela, A. Schafer, and V. Zverev. 2005.
Abundance and diversity of human-biting flies (Diptera : Ceratopogonidae,
49 Culicidae, Tabanidae, Simuliidae) around a nickel-copper smelter at Monchegorsk,
northwestern Russia. Journal of Vector Ecology 30:263-271.
Lautenbach W. E., J. Miller, P. J. Beckett, J. J. Negusanti, and E. K. Winterhalder. 1995.
Municipal land restoration program: The greening process. Pages 109-122 In J. M.
Gunn, editor. Restoration and Recovery of an Industrial Region: Progress in
Restoring the Smelter-Damaged Landscape Near Sudbury, Canada, Springer Verlag,
New York.
Lawes M. J., D. J. Kotze, S. L. Bourquin, and C. Morris. 2005. Epigaeic invertebrates as
potential ecological indicators of afromontane forest condition in South Africa.
Biotropica 37:109-118.
Longcore T. 2003. Terrestrial arthropods as indicators of ecological restoration success in
coastal sage scrub (California, U.S.A.). Restoration Ecology 11:397-409.
Longino J. T., J. Coddington, and R. K. Colwell. 2002. The ant fauna of a tropical rain
forest: Estimating species richness three different ways. Ecology 83:689-702.
Lovei G. L., K. D. Sunderland. 1996. Ecology and behavior of ground beetles
(Coleoptera: Carabidae). Annual Review of Entomology 41:231-256.
Lovell S., M. Hamer, R. Slotow, and D. Herbert. 2007. Assessment of congruency across
invertebrate taxa and taxonomic levels to identify potential surrogates. Biological
Conservation 139:113-125.
50 Lyford W. H. 1963. Importance of ants to brown podzolic soil genesis in New England.
No. 7. Harvard Forest Paper, Petersham, MA.
MacMahon J. A., J. F. Mull, and T. O Crist. 2000. Harvester ants {Pogonomyrmex spp.):
Their community and ecosystem influences. Annual Review of Ecology &
Systematics 31:265-291.
Majer J. D. 1983. Ants: Bio-Indicators of minesite rehabilitation, land-use, and land
conservation. Environmental Management 7:375-383.
Majer J. D. 1989. Animals in primary succession: the role of fauna in reclaimed lands.
Cambridge University Press, Cambridge, UK.
Majer J. D., S. O. Shattuck, A. N. Andersen, and A. J. Beattie. 2004. Australian ant
research: fabulous fauna, functional groups, pharmaceuticals, and the fatherhood.
Australian Journal of Entomology 43:235-247.
Majer J. D., K. E. C. Brennan, and M. L. Moir. 2007. Invertebrates and the restoration of
a forest ecosystem: 30 years of research following bauxite mining in Western
Australia. Restoration Ecology 15:S104-S115.
Majka C. G., R. S. Anderson, and D. B. McCorquodale. 2007. The weevils (Coleoptera:
Curculionoidea) of the Maritime provinces of Canada, II: New records from Nova
Scotia and Prince Edward Island and regional zoogeography. Canadian Entomologist
139:397-442.
51 McElhinny C., P. Gibbons, C. Brack, and J. Bauhus. 2005. Forest and woodland stand
structural complexity: Its definition and measurement. Forest Ecology and
Management 218:1-24.
Negi H. R., M. Gadgil. 2002. Cross-taxon surrogacy of biodiversity in the Indian
Garhwal Himalaya. Biological Conservation 105:143-155.
Pearce J. L., L. A. Venier, J. McKee, J. Pedlar, and D. McKenney. 2003. Influence of
habitat and microhabitat on carabid (Coleoptera: Carabidae) assemblages in four
stand types. The Canadian Entomologist 135:337-357.
Pearce J. L., D. Schuurman, K. N. Barber, M. Larrivee, L. A. Venier, J. McKee, and D.
McKenney. 2005. Pitfall trap designs to maximize invertebrate captures and
minimize captures of nontarget vertebrates. Canadian Entomologist 137:233-250.
Perner J., W. Voigt, R. Bahrmann, W. Heinrich, R. Marstaller, B. Fabian, K. Gregor, D.
Lichter, F. W. Sander, and T. H. Jones. 2003. Responses of arthropods to plant
diversity: changes after pollution cessation. Ecography 26:788-800.
Pyle G. G., J. W. Rajotte, and P. Couture. 2005. Effects of industrial metals on wild fish
populations along a metal contamination gradient. Ecotoxicology and Environmental
Safety 61:287-312.
Rainio J., J. Niemela. 2003. Ground beetles (Coleoptera: Carabidae) as bioindicators.
Biodiversity and Conservation 12:487-506.
52 Rayfield B., M. Anand, and S. Laurence. 2005. Assessing simple versus complex
restoration strategies for industrially disturbed forests. Restoration Ecology 13:639-
650.
Roland J. 1993. Large-scale forest fragmentation increases the duration of tent caterpillar
outbreaks. Oecologia 93:25-30.
Ruiz-Jaen M. C., T. Mitchell Aide. 2005. Restoration success: How is it being measured?
Restoration Ecology 13:569-577.
Sanders C. J., A. Pang. 1992. Carpenter ants as predators of spruce budworm in the
boreal forest of northwestern Ontario. The Canadian Entomologist 124:1093-1100.
Scott G. A. J. 1995. Canada's Vegetation : A World Perspective. McGill-Queen's
University Press, Montreal.
Spalding A., E. C. M. Haes. 1995. Contaminated land - A resource for wildlife: A review
and survey of insects on metalliferous mine sites in Cornwall. Land Contamination
and Reclamation 3:24-29.
Srivastava D. S., M. Vellend. 2005. Biodiversity-Ecosystem function research: Is it
relevant to conservation? Annual Review of Ecology, Evolution, & Systematics
36:267-294.
St. John M. G., G. Bagatto, V. Behan-Pelletier, E. E. Lindquist, J. D. Shorthouse, and I.
M. Smith. 2002. Mite (Acari) colonization of vegetated mine tailings near Sudbury,
Ontario, Canada. Plant and Soil 245:295-305.
53 Statsoft Inc. 2001. STATISTICA: Data analysis software system, Version 6.
Teixeira M. C., J. H. Schoereder, J. T. Nascimento, and J. Louzada N.C . 2005. Response
of ant communities to sand dune vegetation burning in Brazil (Hymenoptera:
Formicidae). Sociobiology 45:631-641.
Ward D. F., T. R. New, and A. L. Yen. 2001. Effects of pitfall trap spacing on the
abundance, richness and composition of invertebrate catches. Journal of Insect
Conservation 5:47-53.
Wassenaar T. D., R. J. van Aarde, S. L. Pimm, and S. M. Ferreira. 2005. Community
convergence in disturbed subtropical dune forests. Ecology 86:655-666.
Winterhalder K. 1996. Environmental degradation and rehabilitation of the landscape
around Sudbury, a major mining and smelting area. Environmental Reviews 4:185-
224.
Winterhalder K. 1995. Early history of human activities in the Sudbury area and
ecological damage to the landscape. Pages 17-31 In J. Gunn, editor. Environmental
Restoration and Recovery of an Industrial region, Springer-Verlag, New York.
Yan N. D., R. Girard, J. H. Heneberry, W. B. Keller, J. M. Gunn, and P. J. Dillon. 2004.
Recovery of copepod, but not cladoceran, zooplankton from severe and chronic
effects of multiple stressors. Ecology letters 7:452-460.
54 Figure 2.1. Map showing the location of the four study sites and the decommissioned smelting complex near Sudbury, Ontario, Canada. Sites include Coniston unassisted (C),
Coniston assisted (CA), Daisy Lake unassisted (DL) and Daisy Lake assisted (DLA).
55 1.2 e 1.2 B A** 0 1 »-8 a (*•S3 sJSc 5 0.4 - 53 a § o Coniston Coniston Daisy Lake Daisy Lake Assisted assisted
04 0.4 o* D O8 S 0.3 ag 0-3 xn 0.2 0.2 e 5 o.i
Coniston Coniston Daisy Lake Daisy Lake Assisted assisted
Figure 2.2. Mean Shannon diversity values with standard error of the mean of ant genera
(A,B) and carabid beetle species (C,D). Significance of p<0.01 is denoted by ** .
56 32 B 3.2 A** d a e ** o § 2.4 s§ " « £ 16 £ 1-6 2 0.8 I 8 0.8 0 Coniston Coniston Daisy Lake Daisy Lake Assisted assisted
2.4 2.4 c D 0S ** 1.8 18 * a1 c« 1.2 5 « s | 0.6 8 0.6 0 Coniston Coniston Daisy Lake Daisy Lake Assisted assisted
Figure 2.3. Mean Shannon diversity values with standard error of the mean of plant species (A,B) and plant families (C,D). Significance of p<0.05 is denoted by * and p<0.01 by **.
57 12
AO B « I 8 I«6 E4 v> •f 0 20 40 60 0 Sample number Sample4&umber 1
D
1« E
20 40 20 40 Sample number Sample number
Figure 2.4. Coleman rarefaction of the ant community at the Coniston sites (A) and
Daisy Lake sites (B) and carabid beetle community at the Coniston Sites (C) and Daisy
Lake sites (D). Black lines represent unassisted sites and assisted sites are grey. Error bars represent one standard deviation.
58 B **
2 « 2 < e c 86 « V u S 2 S 2
Coniston Coniston Daisv Lake Daisy Lake assisted assisted
10 D
8
s
s Daisy Lake Daisy Lake 02 Coniston Coniston assisted assisted
E ** 2 s> JSi 3
Daisy Lake Daisy Lake Coniston Coniston assisted assisted
2.5 H 2 • s JS 1.5 • I I 2 2 8S1 1 • e S S 0.5 • 2. 0 Coniston Coniston assisted Daisy Lake Daisy Lake assisted
Figure 2.5. Mean richness for plants (A,B), all insect morphotaxa (C,D), ants (E,F) and carabids (G,H) with standard error of the mean. Significance of p<0.05 is denoted by * and p<0.01 by**.
59 2- D Stress = 0.04
r* s 12
oS £ -J o
-2 -2-10 1 2 Dimension 1
3-D Stress = 0.04
e .2 si «s
-2 P
Dimension 1
3-D Stress = 0.08
= .2 "3e! £
-2 -p -2-10 1 Dimension 1
Figure 2.6. Nonmetric multidimensional scaling plots showing differences between sampling stations (all sites) based on ant genera incidence. Circles represent Coniston sites while triangles represent Daisy Lake sites. Black symbols represent unassisted sites and white symbols represent assisted sites.
60 2-D Stress = 0.03
s O o O a o a> o . °o -1
-2 -1 0 1 Dimension 1
2-D Stress = 0.06
e V #o V e a> E
-r 7 ^ -2 -1
2-D Stress = 0.09
^0 « 1 0 a> -1
-2-10 1 2 3 Dimension 1
Figure 2.7. Nonmetric multidimensional scaling plots showing differences between sampling stations (all sites) based on carabid species abundance. Circles represent
Coniston sites while triangles represent Daisy Lake sites. Black symbols represent unassisted sites and white symbols represent assisted sites.
61 ' 2-D Stress = 0.03 o • mt o Z 0 Q -2 -1 0 l Dimension 1 oS 2-D Stress = 0.09 S3 -10 12 Dimension 1 3-D Stress = 0.07 a #o "5*1 a 0i r4 -1 •A 0 % -2 -1 0 1 2 Dimension 1 Figure 2.8. Nonmetric multidimensional scaling plots showing differences between sampling stations (all sites) based on plant species incidence. Circles represent Coniston sites while triangles represent Daisy Lake sites. Black symbols represent unassisted sites and white symbols represent assisted sites. 62 Table 2.1. Occurrence of insect morphotaxa at the four sites: Coniston (C), Coniston assisted (CA), Daisy Lake (DL), Daisy Lake assisted (DLA). Taxa C CA DL DLA c CA DL DLA Blattodea X X X X Diptera Tachinidae X X X Coleoptera A* X Diptera Tipulidae* X Coleoptera B* X Diptera Unknown X X X Coleoptera C x X X Hemiptera Aradidae* X Coleoptera D x X X X Hemiptera Coreidae X X Coleoptera Anthicidae X Hemiptera Lygaeidae X X X X Coleoptera Byrrhidae X X X X Hemiptera Miridae X X X Coleoptera Cantharidae* X Hemiptera Nabidae X X X X Coleoptera Carabidae X X X X Hemiptera Pentatomidae X X Coleoptera Cerambicidae* X Hemiptera Rhopalidae* X Coleoptera Chrysomelidae X X X X Hemiptera Tingidae X X X X Coleoptera Ciidae* X Hemiptera Unknown X X Coleoptera Cleridae X X Homoptera Aphididae X X X X Coleoptera Coccinellidae X X X Homoptera Cercopidae X X X Coleoptera Cucujidae* X Homoptera Cicadellidae X X X X Coleoptera Curculionidae X X X X Homoptera Cixiidae X X X X Coleoptera Elateridae X X X X Homoptera Coceidae X X Coleoptera Eucinetidae X Homoptera Delphacidae* X Coleoptera Hydrophilidae X X Homoptera Dictyopharidae* X Coleoptera Lathridiidae X X X X Homoptera Eriosomatidae X X X X Coleoptera Leiodidae X X X Homoptera Issidae X X Coleoptera Melandryidae X X Homoptera unknown X X X Coleoptera Mordellidae X X X X Hymenoptera A X X Coleoptera Nitidulidae X X X Hymenoptera B X Coleoptera Pselaphidae X X X X Hymenoptera C* X Coleoptera Ptilidae* X Hymenoptera D* X Coleoptera Scarabidae X X X X Hymenoptera E X X Coleoptera Scolytidae* X Hymenoptera Apidae X X Coleoptera Scydmaenidae X X X X Hymenoptera Braconidae X X X X Coleoptera Staphylinidae X X X X Hymenoptera Chalcoidea X X X X Coleoptera Tenebrionidae* X Hymenoptera Colletidae X X Coleoptera Throscidae X X Hymenoptera Diapriidae X X X X Coleoptera unknown X X X Hymenoptera Halictidae X X X Dermaptera X Hymenoptera Ichneumonidae X X X X Diptera A X X Hymenoptera Megachilidae X X X Diptera B X X Hymenoptera Mutillidae* X Diptera C* X Hymenoptera Myrmaridae* X Diptera D* X Hymenoptera Pompilidae X X X X Diptera Anisopodidae X X X Hymenoptera Scelionid X X X X Diptera Anthomyiidae X X X X Hymenoptera Sphecidae X X Diptera Asilidae* X Hymenoptera unknown X X X X Diptera Ceratopogonidae X X X X Hymenoptera Vespidae X X X X Diptera Chloropidae X X X X Lepidoptera X X X X Diptera Culicidae X X X X Neuroptera* X Diptera Dolichopodidae X X X Odonata* X Diptera Drosphilidae X X X X Orthoptera A X X Diptera Empididae X Orthoptera B X X X X Diptera Heleomyzidae X X X X Orthoptera Acrididae X Diptera Lauxaniidae X X Orthoptera Gryllacrididae X X Diptera Muscidae X X X X Orthoptera Gryllidae X X X X Diptera Mycetophilidae X X X X Orthoptera Tetrigidae X X X Diptera Nematocera X X X X Orthoptera unknown X X Diptera Phoridae X X X X Psocoptera X X X X Diptera Psychodidae X X Thysanoptera Aeolothripidae* X Diptera Sarcophagidae X X X X Thysanoptera Phlaeothripidae X X X X Diptera Scathophagidae* X Thysanoptera Thripidae X X X X Diptera Sphaeroceridae X X X X Trichoptera X Diptera Syrphidae* x Total richness 77 88 66 74 * Denotes taxa represented by one specimen 63 Table 2.2. Occurrence of ant and carabid taxa at the four sites: Coniston (C), Coniston assisted (CA), Daisy Lake (DL), Daisy Lake assisted (DLA). Taxa C CA DL DLA C CA DL DLA Ants (Formicidae) Carabids (Carabidae) Formica X X X X Agonum cupripenne X Myrmica X X X X Amara angustata X X X Lasius X X X Amara obesa* X Ponera X X Apristus subsulcatus X X X Aphaenogaster X Bradycellus nigrinus* X A canthomyops * X Calathus ingratus X Camponotus X X X X Calosoma calidum X X Crematogaster X X X X Calosoma frigidum X Dolichoderus X X X Cicindela longilabris X Temnothorax X X Cicindela sexguttata X X X Brachymyrmex X X X Cymindis cribricollis X X X Tapinoma X X X X Cymindis neglecta X X X Diplocheila obtuse X Total ant richness 6 9 10 10 Dyschirius sphaericollis* X Harpalus opacipennis X Harpalus somnulentus X X Lebia moesta* X Lebia pumila* X Microlestes linearis* X Miscodera arctics X Poecilus lucublandus X X Pterostichus mutus X X X X Synuchus impimctatus X X X * Denotes taxa represented by one specimen Total carabid richness 8 14 9 10 64 (Ill) Patterns of Insect Communities Along a Stress Gradient Following Decommissioning of a Cu-Ni Smelter 65 ABSTRACT The diversity, estimated richness and abundance of terrestrial insect communities were examined along a gradient of past pollution in the region of Sudbury. Ontario, Canada. This gradient represents the natural recovery and lingering effects of a decommissioned copper-nickel smelting complex that once destroyed the flora and fauna in its immediate vicinity. Ant genera and sixteen higher taxonomic groups (family and order) had the highest abundance at the sites with intermediate stress. Eight families increased in abundance with distance from the decommissioned source of pollution and eleven families decreased. Carabid beetles show a distinct increase in diversity further from the smelter; however, examination of the species composition reveals a distinct carabid community closest to the smelter, emphasizing the unique habitat created by severe disturbance in a landscape. Although almost forty years have passed after the decommissioning of the smelting complex, the terrestrial insect community remains significantly altered along the stress gradient. The industrial barrens at the sites closest to the smelting complex also provide an opportunity to examine primary succession of insects in a post-smelting environment. 66 INTRODUCTION Industrial barrens surrounding point sources of pollution are defined as unique habitats where landscapes are, in few localities worldwide, considered barren with thin soil prone to erosion, small pockets of vegetation and areas of exposed rock (Kozlov and Zvereva 2007). Barren communities may also be characterized by being essentially devoid of trees, having sparse vegetation and being dominated by bare rock, bare soil or dead organic material (Amiro and Courtin 1981). These landscapes often develop from a combination of factors that include decline of vegetation due to toxicity from a source of pollution (often non-ferrous smelters), disturbance such as clearcutting (often for mine timber and fuel) and fire that removes remaining woody debris (Kozlov and Zvereva 2007). In Sudbury, Canada, for example, the main smelting pollutants of such smelters include emissions of SO2 that caused ground level concentration to increase to 0.5ppm and an average of over 0.04 ppm until strict government standards and improved technology reduced it to under 0.02 ppm (Gunn et al. 1995; Potvin and Nagasunti 1995; Winterhalder 1996). Vegetation damage has been observed after four hours of exposure to 0.35ppm SO2 (Dreisinger and McGovern 1971). Aside from SO2, toxicity from soil acidity and heavy metal contamination from emission particulates have exacerbated vegetation loss and in some cases are considered to cause more longterm damage than S02 (Potvin and Nagasunti 1995; Winterhalder 1996). 67 The recovery of industrial barrens has been considered an example of primary succession (Picaud and Petit 2007), rather than secondary succession, which is observed after most stand-replacing disturbances in forest ecosystems. Bagatto and Shorthouse (1999) coined the term 'anthropogenic succession' to emphasize differences between natural and industrial disturbances where lingering soil contamination may have significant influence on the ability of the landscape to restore itself naturally. Such altered landscapes may result in new species compositions and altered ecosystem functioning to create a "novel ecosystem" as described by Hobbs et al. (2006). Many industrial barrens have thin, acidic and contaminated soil that does not allow for establishment of wind-borne immigrants or extant seeds in the seed bank (Winterhalder 1996; Kozlov and Zvereva 2007 and references therein). This creates a restrictive and stressful environment for both plants and insects already suffering from shade, water and nutrient stress typical of fire, wind and clearcutting. Sensitive early succession plant species and important insect fauna may be absent despite their role in succession. Terrestrial insects not only help disperse and pollinate plants (Kremen and Chaplin-Kramer 2007) but they form and redistribute soil between horizons, which helps maintain healthy soil ecosystems (Lyford 1963; Jouquet et al. 2006) and their presence or absence may significantly affect the rate of succession, as shown in secondary succession after a fire (Yanovskii 2005). Few studies have examined primary succession of insects from post-mining events (Picaud and Petit 2007) and even fewer examine the insect recovery in industrial barrens as defined here (Kozlov and Zvereva 2007). Since temporal succession can be comparable to spatial stress gradients (Vetaas 1997) and species may respond in a similar 68 manner to changes in the abiotic and biotic community such as shade, competition, nutrient availability in both temporal (succession) and spatial gradients (Pickett 1976), we have initiated succession studies of post-mining insects by examining the spatial gradients of stress extending from the source of pollution. Studies that have examined the effects of non-ferrous smelting activities on insects often focused on the major copper and nickel smelting complexes in Russia and Finland and some are still in operation, therefore succession cannot fully begin until the stressor is removed. The barrens of Revda, Russia were created by a copper smelter still in operation and gradient analyses show, compared to sites further from the smelter, sites closest to or within these barrens have a high abundance of carabids (Coleoptera: Carabid) (Ermakov 2004), sucking herbivorous invertebrates (Nesterkov and Vorobeichik 2009) and certain tolerant collembolans (Collembola) (Kuznetsova 2009); however the zone of intermediate disturbance had the highest species richness and total abundance of collembolans (Kuznetsova 2009). The sites furthest from the pollution had the highest chewing herbivorous and predaceous invertebrates (Nesterkov and Vorobeichik 2009). The copper-nickel smelter of Monchegorsk, Russia also has an impact gradient on insects with fewer biting flies (Diptera: Culicidae and Simuliidae) at sites closest to the smelter (Kozlov et al 2005). Various gradient hypotheses provide insight into general trends of diversity and abundance observed along such disturbance gradients; however, as general trends, they are often over simplified and may overlook important details of the community response. For example, if a general trend of a family shows an increase of abundance along the 69 gradient, a particular species within that group may have an opposite response (decrease) and would be ignored under the umbrella of the family. Examining several families or taxonomic resolutions may uncover opposite trends along the same gradient. Some argue that using lower or coarse taxonomic resolution and morphospecies for ecological studies reduces ecological information and increases variability; however, it can be and has been used for rapid bioassessments for a variety of insects (Feinstein et al. 2007; Cardoso et al. 2008; Paritsis and Aizen 2008; Wenninger and Inouye 2008) and it is even considered common practice to use family or order level for aquatic insect communities (Resh and McElravy 1993; Jones 2008). Another shortcoming of using morphospecies is the tendency to clump multiple species together or divide variable members of the same species; however, Derraik et al. (2002) have shown that the end result often evens out. Family-level diversity has also been successful in examining insect communities associated with Hawaiian plant hybrids (Drew and Roderick 2005), showing significant differences between insect sampling techniques (Hoback et al. 1999) and examining the beetle community near artificially created snags in a North American forest (Sandoval et al. 2007). If the use of lower taxonomic resolution can only detect a coarse or gross impact, as criticized by Taylor (1997), then we may still successfully show there is an impact of the smelter almost forty years after decommissioning and will have provided a base knowledge of insect communities along the stress gradient and at the extremely denuded sites undergoing primary succession. Three hypotheses used for disturbance gradients may apply to industrial barren succession and spatial gradient analyses; the intermediate disturbance hypothesis (IDH), 70 opportunistic species hypothesis, and habitat specialist hypothesis. The IDH suggests that species richness is highest at an intermediate level of disturbance (Connell 1978). The opportunistic species hypothesis suggests that opportunistic species will be dominant (both in abundance and species richness) in the most disturbed sites (Gray 1989). The habitat specialist hypothesis suggests that forest specialist species will decrease with an increase in disturbance (Magura and Molnar 2004). Depending on the type of disturbance, there will be an increase of particular habitat specialists, such as urban specialists along an urbanization gradient. These two hypotheses may also be considered part of IDH as they are the increasing slope and decreasing slope of the monotonic hump of IDH; however, each hypothesis can help explain the variety of trends that may be found along a pollution gradient extending from industrial barrens. Here, we broaden the use of these gradient hypotheses to examine diversity and richness as well as abundance for a variety of taxonomic resolutions and feeding guilds. Of the 36 industrial barrens examined by Kozlov and Zvereva (2007), six regions had over 10,000 ha of barren land. Within these six, Sudbury, Ontario, Canada had the fourth largest barren area with almost 20,000 ha of barren land and over 80,000 ha of semi- barren land. This region was once considered one of the most ecologically disturbed regions in Canada and suffered from the aforementioned causes of industrial barrens: toxic emissions (from open bed roasting and smelting), clearcutting for mine timber and fuel, and fire that removed remaining woody debris (Amiro and Courtin 1981; Winterhalder 1995). Although open-bed roastyards have been removed, emissions have been reduced by approximately 90% (Potvin and Negusanti 1995) and one of the three 71 smelters has been closed for almost forty years, since 1972 (Gunn et al. 1995), a distinct gradient remains on the landscape with an increase in vegetation diversity with increased distance from the pollution sources (Anand et al. 2002). Soils closest to the smelter also still have heavy metal concentrations (Anand et al. 2003) and have negatively affected root growth, biomass and reproduction of various plant species (Gundermann and Hutchinson 1995; Anand et al. 2003; Ryser and Sauder 2006). We examined the gradient extending from the decommissioned smelting complex of the Coniston region in the Greater City of Sudbury. Studies of terrestrial invertebrates in this region have examined the mite community at tailing sites (St. John et al. 2002) and the accumulation of metals in insect herbivores in the region (Bagatto and Shorthouse 1996); however, to our knowledge, no studies have examined the effects of the smelter on the terrestrial insect community along the pollution gradient. Furthermore, the decommissioned smelting complex provides an opportunity to monitor the primary succession or anthropogenic succession of industrial barrens. This spatial pollution gradient will provide information of current insect communities, which is essential for monitoring the succession of the community and ecosystem processes in these devastated landscapes. Although the site closest to the smelter has patches of exposed rock and bare soil, we expect to find unique insect community living within its boundaries as found in other unique habitat within other derelict landscapes (Spalding and Haes 1995; Kozlov and Zvereva 2007). The insect diversity and abundance will display a variety of trends depending on the taxa and ecological guild. For example, since Spalding and Haes (1995) emphasize the importance of open habitat for visual predator species, we expect a 72 decrease in abundance of such insects with increasing distance from the smelter. This abundance trend may be related to the habitat specialist hypothesis where open habitat taxa dominate in abundance, richness or diversity at the most stressed sites (Magura and Molnar 2004). METHODS Site description Five south-facing slopes were selected in the Sudbury region (46°09.830'N to 46°28.141'N and 80'51.423'W to 80°56.175'W) to represent a high to low stress gradient where the first site is closest to a source of past pollution, the Coniston decommissioned smelting complex, and the last site is furthest away at a distance of approximately 36 km (Figure 3.1). The sites were numbered 1-5 based on their distance from the smelter and named after nearby landmarks. These sites include Coniston (Site 1, 1.7km), Daisy Lake (Site 2, 4.2 km), Raft Lake (Site 3, 12 km), Horseshoe Lake (Site 4, 16 km) and Killarney (Site 5, 36 km). These sites have been previously examined for vegetation and soil microbial dynamics (Anand et al. 2003; Tucker and Anand 2003; Anand et al. 2005; Desrochers and Anand 2005; Rayfield et al. 2005) and belong to the Canadian Ecological Monitoring and Assessment Network (www. eman-rese.ca). The region lies within the Great Lakes-St. Lawrence forest ecotone of the Boreal Shield and is considered a transitional forest between the Boreal forest to the north and the temperate deciduous forest further south. These forests are often dominated by white pine 73 {Pinus strobus L.), white birch {Betula papyri/era Marshall) and red pine {Pinus resinosa Aiton) (Scott 1995). The soils are mainly podzol or gleysol along the gradient; however, there are distinct differences in the pH, canopy cover and heavy metal content. The canopy cover increases significantly across the gradient with percent cover of 0.5, 19.0, 42.9, 65.5, and 86.3 % for the sites in increasing distance from the pollution source. The heavy metal concentrations within the soil vary along the gradient while copper and nickel decrease with an increasing distance from the pollution source (Anand et al. 2003). The pH, in contrast has a convex non-monotonic trend (Anand et al. 2003) and years of acidification and erosion have resulted in thin acidic soils in the sites closest to the decommissioned smelting complex. Sampling Procedure Ramp pitfall traps were used to collect insects following the detailed methods described of Babin-Fenske and Anand (2010). Three stations containing four traps with propylene glycol (RV plumbing antifreeze), water and soap were placed 25 m apart along a 75- metre transect perpendicular to the slope of the hill. Although we recognize some bias of pitfall traps, as described by Lin et al. (2005), it is one of the most widely used methods for sampling terrestrial insects (Woodcock 2005). Samples from the pitfall traps were collected every week for five weeks in June and July of 2006. Further samples were taken in 2007 to increase sample size; five extra weeks for beetles, two weeks in July for ants and one week in July for higher taxa. 74 Sorting, Preserving and Identifying Statistical analyses were performed on adult specimens excluding adult male ants and queen ants due to their taxonomic difficulty and their capture does not necessarily indicate the presence of a colony (Longino et al. 2002). Specimens were identified to family or morphofamily using Borror et al. (1989) then ants and carabids were sent to specialists for further identification to genus and species respectively. Of the 134 taxa collected, 42 were chosen based on two major criteria: more than 15 individuals collected and found at more than two sites, except groups with greater than 100 individuals within those two sites. Two groups were removed due to trapping bias: Culicidae (Diptera) for its attraction to humans as they took the samples and Sarcophagidae (Diptera) for their attraction to dead organisms within the traps. The remaining 42 groups were assigned to broad trophic levels (carnivore, detritivore and herbivore) based on the literature or our knowledge of the biology of insects (Borror et al. 1989; Gratton and Denno 2005). We further subdivided carnivores into predators and parasitoids. Some groups could not be assigned a definitive trophic group due to the diversity of their taxa. Data Analysis Incidence data were used for analyses of ants (Longino et al. 2002) while abundance was used for other taxa. Incidence-based Coverage Estimate (ICE) has been used in past studies examining ant incidence data (Longino et al. 2002); however, individual-based 75 Coleman rarefaction allows for a comparison of estimates species richness curves between sites of unequal sampling efforts (Gotelli and Colwell 2001). Rarefaction was therefore used as an estimation of richness for sites and was calculated using Estimates version 7.5.2 for Mac (Colwell 2005). Shannon diversity was determined for the samples within each site for the ant genera and carabid species while the higher taxa abundance was pooled for each station resulting in three stations per site. Differences between sites were examined using regression analyses in Statistica 6 (Statsoft Inc. 2001). RESULTS The highest estimated richness (rarefaction) of ant genera was found in the middle sites while the sites closest or furthest from the smelter had the lowest richness (Figure 3.2a). This trend was also found for the Shannon diversity of the ant community (Figure 3.2b). The rarefaction for carabid species shows the sites closest and furthest from the smelter have the highest estimated richness (Figure 3.3a). This concave trend was not found in the Shannon diversity of the carabid species, which shows the highest diversity at the site furthest from the smelter (Figure 3.3b). The other families that were examined for abundance showed a variety of responses to the gradient (Table 3.1) with positive, negative, non-linear or no relationship to the stress gradient. Eight taxa increased in abundance with distance from the decommissioned source of pollution while eleven taxa decreased in abundance, 16 had a quadratic relationship (convex), one was concave and six had no significant relationship along the 76 gradient. The abundance of the ant genera (Table 3.2) and carabid species (Table 3.3) also show varying patterns along the gradient. By separating the insect families into broad trophic guilds, we find a variety of trends and uncover distinct differences between abundance and Shannon diversity analyses. Predators had a significant increase in abundance along the gradient (R2=0.96, p<0.01) but a decrease in Shannon diversity of the families that was not significant (R2=0.65, p>0.05) (Figure 3.4a). Although parasitoids had a convex trend along the gradient for abundance (R 2 =0.93, p>0.05) and a slight decrease for Shannon diversity (R 2 =.10, p>0.05) (Figure 3.4b), neither were significant. Herbivores had a significant decrease in abundance (R2=78, p<0.05) of the gradient and a significant increase in Shannon diversity (R2=81, p<0.05) (Figure 3.4c). The detritivores did not have a significant trend, for either analyses of abundance (R2=0.63, p>0.05) or Shannon diversity (R2=0.79, p>0.05) (Figure 3.4d). DISCUSSION Diversity, richness, abundance and composition of insect communities were significantly altered along the stress gradient. The sites closest to the smelting complex remain barren (Anand et al. 2002) and primary succession of the insect community may still be in its earliest stages with open-habitat specific species dominating. The diversity and abundance of the insects examined here covered a variety of patterns and supported 77 numerous stress gradient hypotheses. The ant community supported the Intermediate Disturbance Hypothesis (Connell 1978); however, the most disturbed sites may simply be inhospitable habitat for ants genera due to the thin, acidic soil near the smelter. Although increased litter and obstacles may also make insects more difficult to trap with pitfall traps in forested areas (Agosti 2000; Woodcock 2005), our data show that other insects were easily trapped in spite of increased ground cover. The abundance of phorid flies also followed the same trend as the ants. Many species of phorids are parasitoids of ants (Disney 1994) and can have similar diversity patterns if the species are examined further. We also found taxa that followed the opportunistic species hypothesis, where the opportunistic species were dominant in the most disturbed sites (Gray 1989; Magura and Molnar 2004). Roaches (Blattaria), for example, are often considered opportunistic and indeed were found in abundance at the most disturbed sites. The only representatives of roaches (Blattaria) were of the genus Parcoblatta; however, which are often associated with rocky habitat within Ontario (Walker 1912). Roaches also indicate the presence of their hymenopterous parasitoids, such as Ampulicidae and Evaniidae (Lebeck 1991). Although individuals of these families were found at the intermediate sites, they were not found in large enough numbers to include in our analyses (one Ampulicidae, two Evaniidae). Although eight taxa increased in abundance with an increased distance from the decommissioned source of pollution, it is difficult to associate these particular taxa to specific habitat. One particular family, the feather-winged beetles (Ptiliidae) are minute beetles that live in rotting logs or leaf litter to feed on mold and fungus. It is therefore, not surprising to find they are absent at the most disturbed sites which have less leaf litter, woody debris, soil moisture and habitat for mold and fungus. These beetles reflect the habitat specialist hypothesis (Magura and Molnar 2004). Carabid beetles also appear to support this hypothesis by the elevated diversity at the least disturbed sites. Examining the species within this family, indeed, reveals that forest species, such as Calathus ingrates Dejean, Calosoma frigidum Kirby, Pterostichus pensylvanicus LeConte, and Pterostichus tristis Dejean and Synuchus impunctatus Say (Beaudry et al. 1997) were found in the least disturbed and more forested sites furthest from the smelter. Although the habitat specialist hypothesis may explain the presence of these particular species, we also speculate that the heavy metal gradient (Anand et al. 2003) affects the carabids. Stone et al. (2001) found that Pterostichus oblongopunctatus F. closest to a zinc smelter were more susceptible to additional stressors such as pesticides and food stress. The open-habitat species, Calosoma calidum Fabricius and Cymindis cribricollis Dejean (Beaudry et al. 1997) were found in the most disturbed sites. Having a few of these particular species captured at this site, may explain why the projected estimated richness (but not the current Shannon diversity) for this family was elevated at the most disturbed site. The degraded habitats closest to the smelting complex reveal unique community assemblages that include these dry-habitat carabids and diurnal wasps. It is, therefore, important to recognize the significance of naturally-recovering impact sites as important habitat for specialist species (Spalding and Haes 1995; Kozlov and Zvereva 2007). Despite support for some existing hypotheses, alternative trends of a variety of taxonomic levels may be equally important depending on the scope of the research. For example, specific families within the same trophic level or feeding guild had opposite patterns. The nocturnal predatory rove beetles (Staphylinidae) are often associated with decaying matter and would, therefore, increase in abundance from a dry open habitat to a covered, forest habitat. The diurnal predatory spider wasps (Pompilidae) are visual hunters that are associated with dry habitat and would therefore be more successful and abundant in a region completely degraded by past pollution. The phorid flies (Phoridae) have been discussed with their possible relationship as parasitoids of ants, therefore following the trends of their hosts as opposed to directly from the landscape changes. The broad trophic groupings demonstrated the strength that a few taxa may have on broad analyses. The herbivores, for example had an overall decrease in abundance but an increase in diversity along the stress gradient. This effect appears to be driven by the Lepidoptera (mainly microlepidoptera). Having certain taxa with high abundance at any one site results in a low Shannon diversity or evenness within the community due to its weight on the relative abundance of species (Stirling and Wilsey 2001; Bock et al. 2007). Furthermore, species richness tends to have a stronger positive correlation with abundance than diversity, although even this trend is dependant on the studied taxonomic group (Bock et al. 2007). This provides more support for distinguishing desired taxa and analyses as well as careful interpretation of the results. Whenever a study uses a taxonomic level above the species level, significant and valuable trends may remain hidden without further investigation. We showed that significant patterns can be found at the species (carabids), genera (ants) and family level and future studies should include further taxonomic breakdown of the families examined 80 here. Furthermore, this study is the first to demonstrate that after almost forty years of recovery since the decommissioning of a smelting complex, there remains a significant impact on the terrestrial insect community of this region. This study lays the groundwork for more intensive assessments of insect communities in the ecologically devastated region near Sudbury. It will hopefully lead to an increased recognition of the history of the region and the ecological importance of industrial barrens as sources of primary succession studies and potentially unique habitat for future conservation and research. Furthermore, this study illustrates the idiosyncratic responses of insect groups to stressors, information that could be useful for other studies of ecological impacts in the future. ACKNOWLEDGEMENTS We would like to thank the following for their assistance with the field and laboratory work: Wilder Leduc, Sarah Maki, Jenna Pillarella, Cory Laurin and Tom Fenske. For their help with insect identification, we thank Gary Umphrey and Matthius Buck (University of Guelph); and the National Identification Service, Canada, especially Patrice Bouchard and Henri Goulet. The site map was created by Leo Lariviere, Laurentian University. Funding for this research was provided by the Natural Sciences and Engineering Research Council, the Canada Research Chairs program, the Canadian Foundation for Innovation, the University of Guelph and Laurentian University grants to M. A. 81 REFERENCES Agosti D. 2000. Ants: Standard Methods for Measuring and Monitoring Biodiversity. Smithsonian Institution Press, Washington, DC. Amiro B. D., G. M. Courtin. 1981. Patterns of vegetation in the vicinity of an industrially disturbed ecosystem, Sudbury, Ontario. Canadian Journal of Botany 59:1623-1639. Anand M., B. C. Tucker, and R. Desrochers. 2002. Ecological monitoring of terrestrial ecosystem recovery from man-made perturbation: assessing community complexity. Pages 341-351 In C. A. Brebbia and J. F. Martin-Duque, editors. Air Pollution X. WIT Press, Southampton, United Kingdom. Anand M., S. Laurence, and B. Rayfield. 2005. Diversity relationships among taxonomic groups in recovering and restored forests. Conservation Biology 19:955-962. Anand M., K. Ma, A. Okonski, S. Levin, and D. McCreath. 2003. Characterising biocomplexity and soil microbial dynamics along a smelter-damaged landscape gradient. Science of The Total Environment 311:247-259. Babin-Fenske J. J., M. Anand. 2010. Terrestrial insect communities and the restoration of an industrially perturbed landscape: assessing success and surrogacy. Restoration Ecology (In Press). Bagatto G., J. D. Shorthouse. 1996. Accumulation of Cu and Ni in successive stages of Lymantria dispar L. (Lymantriidae, Lepidoptera) near ore smelters at Sudbury, Ontario, Canada. Environmental Pollution 92:7-12. 82 Bagatto G., J. D. Shorthouse. 1999. Biotic and abiotic characteristics of ecosystems on acid metalliferous mine tailings near Sudbury, Ontario. Canadian Journal of Botany 77:410-425. Beaudry S., L. C. Duchesne, and B. Cote. 1997. Short-term effects of three forestry practices on carabid assemblages in a jack pine forest. Canadian Journal of Forest Research 27:2065-2071. Bock C. E., Z. F. Jones, and J. H. Bock. 2007. Relationships between species richness, evenness and abundance in a southwestern savanna. Ecology 88:1322-1327. Borror D. J., C. A. Triplehorn, and N. F. Johnson. 1989. An Introduction to the Study of Insects. Saunders College Pub, Philadelphia. Cardoso P., N. Scharff, C. Gaspar, S. S. Henriques, R. Carvalho, P. H. Castro, J. B. Schmidt, I. Silva, T. Sziits, A. Castro, and L. C. Crespo. 2008. Rapid biodiversity assessment of spiders (Araneae) using semi-quantitative sampling: A case study in a Mediterranean forest. Insect Conservation and Diversity 1:71-84. Colwell R. K. 2005. EstimateS: Statistical Estimation of Species Richness and Shared Species from Samples. Version 7.5. User's Guide and Application. Published at: http://purLoclc.org.libmeb.iaurentian.ca/estimates. Connell J. H. 1978. Diversity in tropical rain forests and coral reefs. Science 199:1302- 1310. 83 Derraik J. G. B., G. P. Closs, K. J. M. Dickinson, P. Sirvid, B. I. P. Barratt, and B. H. Patrick. 2002. Arthropod morphospecies versus taxonomic species: A case study with Araneae, Coleoptera, and Lepidoptera. Conservation Biology 16:1015-1023. Desrochers R. E., M. Anand. 2005. Quantifying the components of biocomplexity along ecological perturbation gradients. Biodiversity and Conservation 14:3437-3455. Disney R. H. L. 1994. Scuttle Flies : The Phoridae. Chapman & Hall, London ; New York. Dreisinger B., P. McGovern. 1971. Sulphur Dioxide Levels and Vegetation Injury in the Sudbury Area During the 1970 Season. Department of Energy and Resources Management, Air Management Branch, Sudbury, Ontario. Drew A. E., G. K. Roderick. 2005. Insect biodiversity on plant hybrids within the Hawaiian silversword alliance (Asteraceae: Heliantheae-Madiinae). Environmental Entomology 34:1095-1108. Ermakov A. I. 2004. Structural changes in the carabid fauna of forest ecosystems under a toxic impact. Russian Journal of Ecology 35:403-408. Feinstein J., S. Mori, and A. Berkov. 2007. Saproflorivory: A diverse insect community in fallen flowers of Lecythidaceae in French Guiana. Biotropica 39:549-554. Gotelli N. J., R. K. Colwell. 2001. Quantifying biodiversity: Procedures and pitfalls in the measurement and comparison of species richness. Ecology Letters 4:379-391. 84 Gratton C., R. F. Denno. 2005. Restoration of arthropod assemblages in a Spartina salt marsh following removal of the invasive plant Phragmites australis . Restoration Ecology 13:358-372. Gray J. S. 1989. Effects of environmental stress on species rich assemblages. Biological Journal of the Linnean Society 37:19-32. Gundermann D. G., T. C. Hutchinson. 1995. Changes in soil chemistry 20 years after the closure of a nickel-copper smelter near Sudbury, Ontario, Canada. Journal of Geochemical Exploration 52:231-236. Gunn J. M., W. Keller, J. Negusanti, R. Potvin, P. Beckett, and K. Winterhalder. 1995. Ecosystem recovery after emission reductions: Sudbury, Canada. Water, Air, and Soil Pollution 85:1783-1788. Hoback W. W., T. M. Svatos, S. M. Spomer, and L. G. Higley. 1999. Trap color and placement affects estimates of insect family-level abundance and diversity in a Nebraska salt marsh. Entomologia Experimentalis et Applicata 91:393-402. Hobbs R. J., S. Arico, J. Aronson, J. S. Baron, P. Bridgewater, V. A. Cramer, P. R. Epstein, J. J. Ewel, C. A. Klink, A. E. Lugo, D. Norton, D. Ojima, D. M. Richardson, E. W. Sanderson, F. Valladares, M. Vii, R. Zamora, and M. Zobel. 2006. Novel ecosystems: Theoretical and management aspects of the new ecological world order. Global Ecology & Biogeography 15:1-7. 85 Jones F. C. 2008. Taxonomic sufficiency: The influence of taxonomic resolution on freshwater bioassessments using benthic macroinvertebrates. Environmental Reviews 16:45-69. Jouquet P., J. Dauber, J. Lagerlof, P. Lavelle, and M. Lepage. 2006. Soil invertebrates as ecosystem engineers: Intended and accidental effects on soil and feedback lodps. Applied Soil Ecology 32:153-164. Kozlov M. V., E. L. Zvereva. 2007. Industrial barrens: Extreme habitats created by non- ferrous metallurgy. Reviews in Environmental Science and Biotechnology 6:231- 259. Kozlov M. V., N. K. Brodskaya, A. Haarto, K. Kuusela, A. Schafer, and V. Zverev. 2005. Abundance and diversity of human-biting flies (Diptera : Ceratopogonidae, Culicidae, Tabanidae, Simuliidae) around a nickel-copper smelter at Monchegorsk, northwestern Russia. Journal of Vector Ecology 30:263-271. Kremen C., R. Chaplin-Kramer. 2007. Insects as providers of ecosystem services: crop pollination and pest control. Pages 349-382 In A. J. A. Stewart, T. R. New, and O. T. Lewis, editors. Insect conservation biology : proceedings of the Royal Entomological Society's 23nd symposium, CABI Publishing, Cambridge, MA. Kuznetsova N. A. 2009. Soil-dwelling Collembola in coniferous forests along the gradient of pollution with emissions from the Middle Ural Copper Smelter. Russian Journal of Ecology 40:415-423. 86 Lebeck L. M. 1991. A review of the hymenopterous natural enemies of cockroaches with emphasis on biological-control. Entomophaga 36:335-352. Lin Y., R. James, and P. M. Dolman. 2005. Are pitfalls biased? A comparison of carabid composition from pitfall trapping and hand searching in forest habitats. British Journal of Entomology and Natural History 18:17-25. Longino J. T., J. Coddington, and R. K. Colwell. 2002. The ant fauna of a tropical rain forest: Estimating species richness three different ways. Ecology 83:689-702. Lyford W. H. 1963. Importance of ants to brown podzolic soil genesis in New England. No. 7. Harvard Forest Paper, Petersham, MA. Magura T. T., B., T. Molnar. 2004. Changes in carabid beetle assemblages along an urbanisation gradient in the city of Debrecen, Hungary. Landscape Ecology 19:747- 759. Nesterkov A. V., E. L. Vorobeichik. 2009. Changes in the structure of chortobiont invertebrate community exposed to emissions from a copper smelter. Russian Journal of Ecology 40:286-296. Paritsis J., M. A. Aizen. 2008. Effects of exotic conifer plantations on the biodiversity of understory plants, epigeal beetles and birds in Nothofagus dombeyi forests. Forest Ecology and Management 255:1575-1583. Picaud F., D. P. Petit. 2007. Primary succession of Orthoptera on mine tailings: Role of vegetation. Annales de la Societe Entomologique de France 43:69-79. 87 Pickett S. T. A. 1976. Succession: An evolutionary interpretation. American Naturalist 110:107-119. Potvin R., J. Negusanti. 1995. Declining industrial emissions, improving air quality and reduced damage to vegetation. Pages 51-65 In J. Gunn, editor. Environmental Restoration and Recovery of an Industrial region, Springer-Verlag, New York. Rayfield B., M. Anand, and S. Laurence. 2005. Assessing simple versus complex restoration strategies for industrially disturbed forests. Restoration Ecology 13:639- 650. Resh, V.H., E.P. McElravy. 1993. Contemporary quantitative approaches to biomonitoring using benthic macroinvertebrates. Pages 159-194 In D.M Rosenberg and V.H. Resh, editors. Freshwater Biomonitoring and Benthic Macroinvertebrates, Chapman and Hall, New York. Ryser P., W. R. Sauder. 2006. Effects of heavy-metal-contaminated soil on growth, phenology and biomass turnover of Hieracium piloselloides. Environmental Pollution 140:52-61. Sandoval S. J., S. P. Cook, F. W. Merickel, and H. L. Osborne. 2007. Diversity of the beetle (Coleoptera) community captured at artificially-created snags of Douglas-fir and Grand fir. Pan-Pacific Entomologist 83:41-49. Scott G. A. J. 1995. Canada's Vegetation : A World Perspective. McGill-Queen's University Press, Montreal. 88 Spalding A., E. C. M. Haes. 1995. Contaminated land - A resource for wildlife: A review and survey of insects on metalliferous mine sites in Cornwall. Land Contamination and Reclamation 3:24-29. St. John M. G., G. Bagatto, V. Behan-Pelletier, E. E. Lindquist, J. D. Shorthouse, and I. M. Smith. 2002. Mite (Acari) colonization of vegetated mine tailings near Sudbury, Ontario, Canada. Plant and Soil 245:295-305. Statsoft Inc. 2001. STATISTICA: Data analysis software system, Version 6. Stirling G., B. Wilsey. 2001. Empirical relationships between species richness, evenness, and proportional diversity. American Naturalist 158:286-299. Stone D., P. Jepson, P. Kramarz, and R. Laskowski. 2001. Time to death response in carabid beetles exposed to multiple stressors along a gradient of heavy metal pollution. Environmental Pollution 113:239-244. Taylor B. R. 1997. Rapid assessment procedures: Radical re-invention or just sloppy science? Human and Ecological Risk Assessment: An International Journal 3:1005- 1016. Tucker B. C., M. Anand. 2003. The use of matrix models to detect natural and pollution- induced forest gradients. Community Ecology 4:89-100. Vetaas O. R. 1997. Relationships between floristic gradients in a primary succession. Journal of Vegetation Science 8:665-676. 89 Walker E. M. 1912. The Blattidae of Ontario. Canadian Entomologist 44:171-172. Wenninger E. J., R. S. Inouye. 2008. Insect community response to plant diversity and productivity in a sagebrush-steppe ecosystem. Journal of Arid Environments 72:24- 33. Winterhalder K. 1996. Environmental degradation and rehabilitation of the landscape around Sudbury, a major mining and smelting area. Environmental Reviews 4:185- 224. Winterhalder K. 1995. Early history of human activities in the Sudbury area and ecological damage to the landscape. Pages 17-31 In J. Gunn, editor. Environmental Restoration and Recovery of an Industrial region, Springer-Verlag, New York. Woodcock B. A. 2005. Pitfall trapping in ecological studies. Pages 37-57 In S. Leather, editor. Insect Sampling in Forest Ecosystems, Blackwell Publishing, Maiden, MA. Yanovskii V. M. 2005. Role of the forest entomofauna in successional processes. Russian Journal of Ecology 36:205-208. 90 Figure 3.1. Map showing the location of the five study sites and the decommissioned smelting complex near Sudbury, Ontario, Canada. Numbered circles indicate sites. 91 A 12 Sample number B Distance from smelter (km) Figure 3.2. Rarefaction (A) and Shannon diversity (B) of ant genera along the stress gradient. The site numbers are located at the edge of each trend with increased numbers for an increase of distance from the smelting complex. 92 A 12 5 10 1 4 2 3 S 2 10 20 30 40 50 Sample number B £ °-8 " Distance from smelter (km) Figure 3.3. Rarefaction (A) and Shannon diversity (B) of carabid beetle species along the stress gradient. Site numbers are located at the edge of each trend with increased numbers for an increase of distance from the smelting complex. 93 A 1200 £> 3 „ 1000 y = -0.02x + 1.54 y = 7.90x + 58.39 «s - 800 > 2 2 R2 = 0.96** R = 0.65 600 400 s 1 200 aB 0 aJSs 0 10 20 30 40 10 20 30 40 Distance from Smelter (km) Distance from Smelter (km) 4- 3 1200 B y = -O.OOSx + 0.75 1000 > 2 2 800 a R = 0.10 600 2 e 400 y = -1.79x + 74.70x + 186.14 09 200 2 5j o 0 R = 0.93 10 20 30 40 0 10 20 30 40 Distance from Smelter (km) Distance from Smelter (km) 1200 1000 u« y = -13.87x + 642.13 e 800 •a R2 = 0.78* e 600 y = 0.02x + 1.56 3 400 R2 = 0.81* < 200 0 10 20 30 40 10 20 30 40 Distance from Smelter (km) Distance from Smelter (km) D X200 u 1000 y = 5.87x + 274.77 y = -0.003x + O.llx + 0.55 | 800 2 2 R = 0.63 R = 0.79 H 600 2 400 < 200 0 0 10 20 30 40 0 10 20 30 Distance from Smelter (km) Distance from Smelter (km) Figure 3.4. Trends along a stress gradient for the abundance and Shannon diversity of predators (A), parasitoids (B), herbivores (C) and detritivores (D). Significance is denoted by * to represent p<0.05 and ** to represent p<0.01. 94 Table 3.1. Abundance of taxa along the stress gradient. Guilds include predators (Pr), parasitoids (Pa), herbivores (H), detritivores (D) and unknown (U). Taxa Guild site Abundance Trend 1 2 3 4 5 Coleoptera Carabidae Pr 10 25 12 17 182 inc ** Coleoptera Ptiliidae H 0 0 4 13 16 inc ** Coleoptera Staphylinidae Pr 17 15 71 168 137 inc ** Diptera Anisopodidae H 2 3 1 4 8 inc ** Diptera Drosophilidae D 4 1 167 229 351 inc ** Homoptera Aphididae H 24 8 20 35 46 inc ** Hymenoptera Scelionidae Pa 3 5 10 3 14 inc ** Psocoptera H 5 3 14 6 17 inc ** Blattaria Blattellidae D 6 154 36 0 0 dec ** Coleoptera Elateridae H 37 46 23 11 6 dec ** Coleoptera Pselaphidae Pr 6 14 11 2 0 dec ** Diptera Anthomyiidae H 103 148 43 23 11 dec ** Diptera Mycetophilidae D 214 70 44 20 61 dec ** Hymenoptera Pompilidae Pr 30 26 3 0 1 dec ** Lepidoptera H 403 201 104 121 13 dec ** Orthoptera Gryllidae H 13 237 0 0 0 dec ** Thysanoptera Phlaeothripidae U 10 31 16 2 0 dec ** Coleoptera Chrysomelidae H 5 7 1 2 0 dec * Hymenoptera Chalcidoidea Pa 76 72 79 29 38 dec * Coleoptera Curculionidae H 15 2 83 4 44 convex ** Coleoptera Histeridae Pr 0 0 2 23 6 convex ** Coleoptera Hydrophilidae Pr 0 0 19 9 2 convex ** Coleoptera Lathridiidae D 10 14 70 32 18 convex ** Coleoptera Leiodidae D 1 0 19 17 7 convex ** Coleoptera Nitidulidae H 0 5 14 14 15 convex ** Diptera Heleomyzidae D 1 1 4 7 5 convex ** Diptera Muscidae U 9 8 29 26 32 convex ** Diptera Phoridae Pa 279 287 589 915 444 convex ** Diptera Sphaeroceridae D 3 3 83 93 2 convex ** Hemiptera Lygaeidae H 1 2 11 67 4 convex ** Homoptera Cicadellidae H 3 6 23 3 6 convex ** Hymenoptera Diapriidae Pa 12 18 83 39 41 convex ** Orthoptera Gryllacrididae H 2 0 2 15 9 convex ** Coleoptera Melandryidae U 0 3 12 1 3 convex * Coleoptera Scydmaenidae Pr 3 3 11 2 1 convex * Homoptera Eriosomatidae H 9 5 0 1 0 concave ** Coleoptera Scarabidae D 11 3 14 5 4 n/s Diptera Chloropidae H 7 6 3 4 6 n/s Hymenoptera Braconidae Pa 5 2 5 2 1 n/s Hymenoptera Ichneumonidae Pa 7 1 5 3 5 n/s Hymenoptera Vespidae Pr 3 2 5 2 4 n/s Thysanoptera Thripidae H 24 16 10 5 8 n/s 95 Table 3.2. Abundance of ant genera along the stress gradient. Note that analyses used incidence data instead of abundance. Site Taxa 1 2 3 4 5 Acanthomyops 0 1 0 1 0 Aphaenogaster 0 8 0 0 0 Brachymyrmex 0 9 5 0 0 Camponotus 4 3 7 4 13 Crematogaster 21 164 517 1 0 Dolichoderus 0 2 0 5 0 Formica 42 97 75 59 25 Lasius 352 273 1 4 25 Myrmica 2 1 66 53 32 Tapinoma 2 50 88 23 0 Temnothorax 0 0 1 0 0 96 Table 3.3. Abundance of carabid species along the stress gradient. Site Taxa 1 3 4 5 6 Agonum cupripenne 0 2 0 0 0 Agonum thoreyi 0 0 0 0 2 Amara angustata 0 1 1 0 0 Apristus subsulcatus 3 0 0 0 0 Calathus ingratus 0 0 0 0 7 Calosoma calidum 2 0 0 0 0 Calosoma frigidum 0 0 0 1 0 Cicindela longilabris 0 3 3 0 0 Cicindela sexguttata 2 8 0 0 0 Cymindis cribricollis 2 0 0 0 0 Cymindis neglecta 1 1 0 0 2 Dyschirius sphaericollis 0 1 0 0 0 Harpalus lewisi 0 0 0 1 0 Lebia pumila 0 1 0 0 0 Miscodera arctics 2 0 0 0 0 Notiophiius zeneus 0 0 0 2 0 Pterostichus corracinus 0 0 0 0 2 Pterostichus mutus 3 5 7 0 1 Pterostichus pensylvanicus 0 0 0 2 15 Pterostichus tristis 0 0 1 0 50 Sphaeroderus canadensis 0 0 0 0 26 Sphaeroderus stenotomus lecontei 0 0 0 7 1 Syntomus americanus 0 0 1 1 2 Synuchus impunctatus 1 1 9 7 142 97 (IV) Forest Tent Caterpillar {Malacosoma disstria Hiibner) Population Density along a Stress Gradient in a Northern Ontario Forest 98 ABSTRACT Although air pollution and soil contaminants can have direct toxic effects on insects, the indirect effects due to plant stress may affect insect defoliators through changes in host (tree) quality (e.g., palatability) and quantity. Such changes may, perhaps contrary to intuition, be beneficial to defoliators by increasing their fecundity, which can subsequently increase the frequency of outbreaks. We estimated the presence of an insect defoliator, the forest tent caterpillar (FTC) {Malacosoma disstria Hiibner) on host trees along a stress gradient of Sudbury, Ontario, Canada. Population density of FTC was determined by counting egg masses. We find that population density of FTC was highest at environmentally stressed sites closest to a decommissioned smelting complex. Our results suggest that this is related to the presence of alternate hosts (overall diversity) but not host tree density. Our results confirm previous suggestions that there is increased density of FTC and potentially increased magnitude and/or duration of FTC outbreaks in areas closest to a source of pollution. 99 INTRODUCTION The forest tent caterpillar, Malacosoma disstria Hiibner (Lepidoptera: Lasiocampidae) (FTC), is a native hardwood defoliator in North America with a distinct population cycle of approximately ten years (Sippell 1962; Cooke and Lorenzetti 2006). Although this species will feed on most deciduous hardwood trees in North America including sugar maple Acer rubrum L., red oak (Quercus rubra L.) and white birch (Betulapapyrifera Marshall), it has distinct oviposition preference for trembling aspen (Populus tremuloides Michx.) in the northern Unites States and Canadian provinces like Ontario (Howse 1995). Defoliation of the host trees decreases the basal area growth of the tree and three consecutive years of heavy defoliation may cause mortality (Churchill et al. 1964; Cooke et al. 2009) causing economic damage for lumber, paper and maple sugar industries (Howse 1995). Understanding events and processes that affect FTC may aid in forest management practices that attempt to control outbreaks and damage done by this economic pest. Disturbance and stress play important roles in the population dynamics of forest insects such as the FTC. For example, the lingering stress after forest fires can leave trees weakened, damaged and vulnerable to attack from pine beetles and bark beetles (McHugh et al. 2003; Schwilk et al. 2006). Similarly, a forest stressed from factors such as pollution or frequent fires, may also be more susceptible to insect attack (Skuhravy and Srot 1991; McCullough et al. 1998). The effects of pollution on insects has been shown to be more complicated than simply causing a weakened state of the host tree 100 according to a review by Alstad et al. (1982). Increased exposure to pollutants such as NO2, CO2, O3 and SO2 can have negative affects on various insects by delaying cocooning, reducing activity and affecting various components of fecundity. In some cases, however, elevated levels of pollutants can increase herbivore populations by reducing predator populations, causing suppression of plant defenses or promoting the release of palatable plant compounds (Alstad et al. 1982; Roth et al. 1997; Volney and Fleming 2000; Kopper and Lindroth 2003). In the case of FTC, anthropogenic disturbance such as fragmentation can cause lingering stress from increased host tree exposure, sun intensity and distance from patches. These factors, in turn, affect rate of development, incidence of virus and dispersal of small parasitoids (Roland 1993; Rothman and Roland 1998). Areas with increased forest fragmentation, therefore, have less FTC mortality (Rothman and Roland 1998) and longer outbreaks (Roland 1993). Roland (1993) suggested there is an anomaly in the region of Sudbury, Ontario, Canada where outbreaks are longer when fragmentation was not high and the suggestion that lingering effects of a decommissioned copper-nickel smelting operations has not yet been explored. In this paper we focus on the region of Sudbury where logging, mining and smelting practices once removed large amounts of woody vegetation, released SO2 into the air and released heavy metals and contaminants into the lakes and soil of surrounding areas (Gunn et al. 1995; Winterhalder 1995). This stressed ecosystem is distinguished by its decreased tree diversity, thin acidic soils and heavy metal contamination (Winterhalder 1995; Anand et al. 2003; Anand et al. 2005; Rayfield et al. 2005). The majority of the 101 surviving trees in the region are potential hosts of FTC and these factors may make them more susceptible to insect herbivores. Furthermore, certain pollutants have been shown to increase population size and fecundity of insect herbivores as they respond to the changes in host leaf quality and changes in nutrient availability (Butler and Trumble 2008 and references therein). We examined if the lingering effects of pollution promote increased egg mass density (an estimate of population size) of FTC in this region. METHODS FTC density was measured in the area surrounding Sudbury, Ontario, Canada (46°30'N, 81°00'W) along a north-south perturbation gradient. Vegetation and soil microbial dynamics have been previously studied at these sites (Anand et al. 2003; Tucker and Anand 2003; Anand et al. 2005; Desrochers and Anand 2005; Rayfield et al. 2005) and some belong to the Canadian Ecological Monitoring and Assessment Network (www.eman-rese. ca). This gradient includes five naturally recovering sites that are named after nearby landmarks and numbered based on their distance from a smelting complex that was decommissioned in 1972 (Gunn et al. 1995). These sites include Coniston (Site 1, 1.7km), Daisy Lake (Site 2, 4.2 km), Raft Lake (Site 3, 12 km), Horseshoe Lake (Site 4, 16 km) and Killarney (Site 5, 36 km) (Figure 4.1). Soils closest to this smelting complex had higher heavy metal concentrations and thin acidic soils from years of acidification and erosion (Anand et al. 2003) and studies show the soils have negative effects on root growth, biomass and reproduction of various plant species (Gundermann and Hutchinson 1995, Ryser and Sauder 2006). 102 We measured egg mass counts, which is a traditional technique for estimating FTC populations (Shepherd and Brown 1971), in the spring of 2007 before budbreak. Trees were selected using stratified random sampling with the requirements that trees were a minimum of 5 metres apart, they were over 1.5 metres in height and they had a stem diameter at breast height (DBH) of 15-25 mm. This range was used because larger trees are not readily available at the sites closest to the smelter. Small trees were chosen to provide comparable results among sites despite the presence of larger trees at some sites. Past studies have shown that larger trees will have more egg masses, but it is not known whether or not insects will actively avoid small trees when large trees are available (Batzer et al. 1995). The potential hosts species were identified as trembling aspen (preferred host), paper birch (Betula papyrifera Marshall) and red oak (Quercus rubra L.). When possible, ten trees each of these potential host species were examined at each site providing a maximum of 30 trees per site. The top four branches (excluding the terminal) were examined and all fresh (laid in 2006) FTC egg masses were counted on each branch (Shepherd and Brown 1971). The mean number of egg masses per branch for each tree was recorded and used for analyses. The mean overall tree density (number of trees per 500 m2), tree species diversity and tree species richness were estimated from data collected in 2006 and 2007 by examining all trees taller than 1.5 m (including trees > 25 mm DBH) along a 100 m long by 5 m wide transect. Diversity and density were measured from five random quadrats within the length of the transect for correlations. The entire sampling area was used for site averages,. When examining potential hosts, all hardwoods were considered except red maple (Acer rubrum L.) because they are not defoliated by FTC due to the chemical composition of red maple leaves (Abou-Zaid et al. 2001). Data were examined for fit to the normal distribution, and nonparametric Spearman correlations were performed when appropriate, otherwise linear regression was used with JMP 5.1 for Mac. RESULTS Total sample sizes across all sites were 45 birch, 28 trembling aspen and 15 red oak with four branches examined on each, which is comparable to past studies that examined 5-20 trees or 30 branches (Shepherd and Brown 1971; Nyrop et al. 1979). No species had the required 10 trees at all sites (Table 4.1). There was a significant decrease in the mean number of egg masses per branch for each tree along the gradient (Spearman p= -0.9, p<0.05, Figure 4.2A), although the total mean for sites had an observed trend that was not significant (Figure 4.2B). Egg masses were found on different hosts at each site (Table 4.1) and trembling aspen and red oak had more egg masses per branch than paper birch when they were present at the site. The estimated overall tree density of the five random quadrats (number of trees per 125 m2) (all DBH) did not have a significant relationship with the distance from the smelter (Spearman p= 0.50, P>0.05) (Figure 4.2C). The overall tree diversity (Shannon diversity index) changed along the gradient showing higher diversity with an increase in distance from the smelter (Spearman p = 0.81, p<0.01) (Figure 4.2D). 104 When examining the total site averages and data, tree diversity had a significant negative relationship with the mean number of egg masses per branch decreased (R = 0.8, p < 0.05) (Figure 4.3A) while tree density did not have a significant relationship with egg masses (R2 = 0.01, p > 0.05) (Figure 4.3B). DISCUSSION We have shown that there is a decrease in the number of egg masses of FTC with an increase in distance from a major source of past pollution and that this egg mass reduction is correlated with an increase in tree diversity, but not tree density. Tree diversity is substantially lower closer to the smelter and impacts the population of FTC as three of the four prominent tree species are potential hosts for FTC. Our results are preliminary due to lack of sample size and replication in time and space; therefore we propose to continue studying these sites for trends in FTC egg masses. Our results also demonstrated a positive correlation between tree diversity and distance from the smelter as well as a negative relationship with the number of egg masses per branch. Forests with higher diversity have less herbivory by forest insects, possibly due to physical and chemical barriers created by non-host species (Jactel and Brockerhoff 2007). After the initial degradation of the landscape and reduction in local sources of pollutino, the first trees to recover were those that were hardy, early successional, had vegetative means of propagation or may have survived in the seed bank (Winterhalder 1996). This resulted in three major hosts of FTC (paper birch, trembling aspen and red 105 oak) among the most abundant trees in this area. The combination of low tree diversity with a high percentage of host trees may be significant in the dynamics of this insect. Although we are correlating the observed trend in egg mass counts with tree diversity, we also recognize the influence of the long-term effects of smelting pollution including heavy metal and acid contamination of soils, which may alter forest defoliator population dynamics, infestation cycles, leaf chemistry, palatability and nutritional value (Alstad et al. 1982; Pimentel 1994; McLaughlin 1998; Kiikkila 2003). Furthermore, injury and stress from chronic exposure to elevated pollution or degraded soils may increase susceptibility to insects and may cause more frequent attacks. These factors are all significant concerns in terms of FTC population dynamics as they may not only create regions with larger FTC populations, but may be the cause of longer outbreaks, as observed in the Sudbury region (Roland 1993). By altering the defoliating insect's fecundity or reducing the predator/parasitoid population, such factors may also alter the duration and frequency of the insect outbreaks (Alstad et al. 1982; Butler and Trumble 2008). Roland (1993) found that FTC outbreaks in the Sudbury district were 1.1 years longer on average that other districts with similar fragmentation (km of forest edge per total km2 of the district), questioning if there is a relationship between these longer outbreaks and the elevated pollution emissions of the past. He suggested that the altered tree species and stand structure may play an important part in his study and we show that indeed tree diversity is an important factor, however, further studies must be performed. Finally, we hypothesize that as stress increasingly affects forests through increased 106 urbanization or climate change (Pimentel 1994), there will be an increase in length or frequency of insect defoliator cycles throughout Canada and more work demonstrating these effects at larger scales or in other forest systems is encouraged. ACKNOWLEDGEMENTS We thank T. Fenske, P. Larochelle, W. Leduc, J. Pillarella, S. Rintala, and N. Webster for their assistance with field data collection. We are grateful for funding from the Natural Sciences and Engineering Council of Canada, Canada Research Chairs Program, Canadian Foundation for Innovation, the University of Guelph and Laurentian University. The site map was created by Leo Lariviere, Laurentian University. We would also like to thank G. Courtin, B. Lyons, T. Scarr, the Ontario Ministry of Natural Resources and Canadian Forest Service for their help with this project. 107 REFERENCES Abou-Zaid M. M., B. V. Helson, C. Nozzolillo, and J. T. Arnason. 2001. Ethyl m- Digallate from Red Maple, Acer rubrum L., as the major resistance factor to forest tent caterpillar, Malacosoma disstria Hbn. Journal of Chemical Ecology 27:2517- 2527. Alstad D. N., G. F. J. Edmunds, and L. H. Weinstein. 1982. Effects of air pollutants on insect populations. Annual Review of Entomology 27:369-384. Anand M., S. Laurence, and B. Rayfield. 2005. Diversity relationships among taxonomic groups in recovering and restored forests. Conservation Biology 19:955-962. Anand M., K. Ma, A. Okonski, S. Levin, and D. McCreath. 2003. Characterising biocomplexity and soil microbial dynamics along a smelter-damaged landscape gradient. Science of The Total Environment 311:247-259. Batzer H. O., M. P. Martin, W. J. Mattson, and W. E. Miller. 1995. The forest tent caterpillar in aspen stands: distribution and density estimation of four life stages in four vegetation strata. Forest Science 41:99-121. Butler C. D., J. T. Trumble. 2008. Effects of pollutants on bottom-up and top-down processes in insect-plant interactions. Environmental Pollution 156:1-10. Churchill G. B., H. H. John, D. P. Duncan, and A. C. Hodson. 1964. Long-term effects of defoliation of aspen by the forest tent caterpillar. Ecology 45:630-633. 108 Colwell R. K. 2005. EstimateS: Statistical Estimation of Species Richness and Shared Species from Samples. Version 7.5. User's Guide and Application. Published at: http://purl.oclc.org.librweb.laurentian.ca/estimates. Cooke B. J., F. Lorenzetti, and J. Roland. 2009. On the duration and distribution of forest tent caterpillar outbreaks in east-central Canada. Journal of the Entomological Society of Ontario 140:3-18. Cooke B. J., F. Lorenzetti. 2006. The dynamics of forest tent caterpillar outbreaks in Quebec, Canada. Forest Ecology and Management 226:110-121. Desrochers R. E., M. Anand. 2005. Quantifying the components of biocomplexity along ecological perturbation gradients. Biodiversity and conservation 14:3437-3455. Gundermann D. G., T. C. Hutchinson. 1995. Changes in soil chemistry 20 years after the closure of a nickel-copper smelter near Sudbury, Ontario, Canada. Journal of Geochemical Exploration 52:231-236. Gunn J. M., W. Keller, J. Negusanti, R. Potvin, P. Beckett, and K. Winterhalder. 1995. Ecosystem recovery after emission reductions: Sudbury, Canada. Water, Air, and Soil Pollution 85:1783-1788. Howse G. M. 1995. Forest Insect Pests in the Ontario Region. Pages 41-57 In J. A. Armstrong and W. G. H. Ives, editors. Forest Insect Pests in Canada, Natural Resources Canada, Canadian Forest Service, Ottawa, Ontario. 109 Jactel H., E. G. Brockerhoff. 2007. Tree diversity reduces herbivory by forest insects. Ecology Letters 10:835-848. Kiikkila O. 2003. Heavy-metal pollution and remediation of forest soil around the Harjavalta Cu-Ni smelter, in SW Finland. Silva Fennica 37:399-415. Kopper B. J., R. L. Lindroth. 2003. Effects of elevated carbon dioxide and ozone on the phytochemistry of aspen and performance of an herbivore. Oecologia 134:95-103. McCullough D. G., R. A. Werner, and D. Neumann. 1998. Fire and insects in northern and boreal forests of North America. Annual Review of Entomology 43:107-127. McHugh C. W., T. E. Kolb, and J. L. Wilson. 2003. Bark beetle attacks on ponderosa pine following fire in northern Arizona. Environmental Entomology 32:510-522. McLaughlin D. 1998. A decade of forest tree monitoring in Canada: Evidence of air pollution effects. Environmental Reviews 6:151-171. Nyrop J. P., R. L. Murray, and D. G. Mosher. 1979. Predicting forest tent caterpillar defoliation on sugar maple. Michigan Dept. Natural Resources Forest Pest Management Report MR-2-79 :4 pp. Pimentel D. 1994. Insect population responses to environmental stress and pollutants Environmental Reviews 2:1-15. 110 Rayfleld B., M. Anand, and S. Laurence. 2005. Assessing simple versus complex restoration strategies for industrially disturbed forests. Restoration Ecology 13:639- 650. Roland J. 1993. Large-scale forest fragmentation increases the duration of tent caterpillar outbreaks. Oecologia 93:25-30. Roth S., E. P. McDonald, and R. L. Lindroth. 1997. Atmospheric C02 and soil'water availability: consequences for tree-insect interactions. Canadian Journal of Forest Research 27:1281-1290. Rothman L., J. Roland. 1998. Relationships between forest fragmentation and colony performance in the forest tent caterpillar, Malacosoma disstria. Ecography 21:383- 391. Ryser P., W. R. Sauder. 2006. Effects of heavy-metal-contaminated soil on growth, phenology and biomass turnover of Hieracium piloselloides. Environmental Pollution 140:52-61. Schwilk D. W., E. Knapp, S. Ferrenberg, J. E. Keeley, and A. C. Caprio. 2006. Tree mortality from fire and bark beetles following early and late season prescribed fires in a Sierra Nevada mixed-conifer forest. Forest Ecology and Management 232:36- 45. Ill Shepherd R. F., C. E. Brown. 1971. Sequential egg-band sampling and probability methods of predicting defoliation by Malacosoma disstria (Lasiocampidae: Lepidoptera). The Canadian Entomologist 103:1371-1379. Sippell L. 1962. Outbreaks of the forest tent caterpillar, Malacosoma disstria Hbn. a periodic defoliator of broad-leaved trees in Ontario. The Canadian Entomologist 94:408-416. Skuhravy V., M. Srot. 1991. Potencialni vztah mezi imisemi a vyskytem nekterych hmyzich shudcu [Potential relationship between the emissions and the occurrence of some insect pests]. Lesnictvi (Prague) 37:571-576. Tucker B. C., M. Anand. 2003. The use of matrix models to detect natural and pollution- induced forest gradients. Community Ecology 4:89-100. Volney W. J. A., R. A. Fleming. 2000. Climate change and impacts of boreal forest insects. Agriculture Ecosystems and Environment 82:283-294. Winterhalder K. 1996. Environmental degradation and rehabilitation of the landscape around Sudbury, a major mining and smelting area. Environmental Reviews 4:185- 224. Winterhalder K. 1995. Early history of human activities in the Sudbury area and ecological damage to the landscape. Pages 17-31 In J. Gunn, editor. Environmental Restoration and Recovery of an Industrial region, Springer-Verlag, New York. 112 Figure 4.1. Map showing the location of the five study sites and the decommissioned smelting complex near Sudbury, Ontario, Canada. Numbered circles indicate sites. 113 A B 0.40 w y = -0.0099x + 0.3184 c y = -O.OlOlx + 0.3092 p= -0.32, p < 0.01 R2 = 0.75, p = 0.056 if) ® 0.20 eSBs 1i WD „ WD 0 • m• w 0 20 40 0 20 40 Distance from smelter (km) Distance from smelter (km) D y = 0.0366x - 0.0979 y = 0.0056x + 0.2336 p= 0.81, p < 0.01 p= 0.50, p > 0.05 0) V 0 20 40 0 20 Distance from smelter (km) Distance from smelter (km) Figure 4.2. Distance from the smelting complex correlated with mean number of egg masses counted per branch for each tree (A) mean number of egg masses counted per branch for each site (B), tree density within 125 m2 (C) and tree Shannon diversity of all tree species (D). 114 B 43 0.40 ja 0.50 -0.0361x + 0.194 u y = -0.2039x + 0.3476 u 2 2 0.30 2 I 0.40 R = 0.0055 . a R = 0.8, p < 0.05 ^ 0.30 s °-20 ss i 0.20 6 0.10 on ^0.10 Ot wd w 0.00 -i W 0.00 0 2 0.5 Tree diversity Tree density Figure 4.3. Mean egg mass per branch for each site compared to total site tree diversity (A) and density of trees in 500m2 (B). 115 Table 4.1. Mean number of egg masses per branch for each species of tree examined and tree density for each site. Not applicable (na) denotes where tree samples were not found. Tree density expressed as number of trees per 500 m2 for all trees taller than 1.5m. Sitel Site2 Site3 Site4 Site5 Distance from smelter (km) 1.7 4.2 12 16 36 Egg masses: paper birch 0.03 0.10 0.00 0.00 0.00 Egg masses: trembling aspen 0.53 na na 0.10 0.00 Egg masses: red oak na 1.06 0.40 0.00 na Egg masses: all trees pooled 0.28 0.38 0.20 0.05 0.00 Density of all trees 0.002 0.744 0.262 0.28 0.718 Density of potential host trees 0.002 0.736 0.196 0.228 0.472 116 (V) Agent-Based Simulation Model Shows that Stress May Promote Forest Tent Caterpillar Defoliation 117 ABSTRACT The forest tent caterpillar (Malacosoma disstria Hiibner) (FTC) has an outbreak cycle of approximately 10 years; however, smaller spatial scale analyses show some regions have longer or more frequent periods of high defoliation. This may be a result of local forest fragmentation, pollution or other sources of stress that may affect FTC directly or indirectly through stress on their hosts or parasitoids. Population dynamics of FTC were examined to investigate how stress may alter the severity and frequency of defoliation. We developed a spatially-explicit agent-based model to simulate the host-parasitoid dynamics of FTC. Theoretical and empirically-derived parameters were established using past literature and over 50 years of population data of FTC from Ontario, Canada. We find that increasing FTC fecundity, FTC dispersal or parasitoid mortality resulted in more severe outbreaks while a decrease in parasitoid fecundity or searching efficiency resulted in an overall elevation of defoliation. Parasitoid efficiency was the most effective parameter for altering the FTC defoliation. Since plant stress has been shown to alter several of these parameters in nature due to changes in food quality, habitat suitability, and chemical cue interference, our results suggest that forests affected by stressors such as climate change and pollution will have more severe and widespread defoliation from these insects than surrounding unaffected forests. As stressors such as drought and pollution emissions are predicted to increase in frequency or intensity over the next few decades, understanding how they may affect the outbreak cycle of a forest defoliator can aid in planning strategies to reduce the detrimental effects of this insect. 118 INTRODUCTION The forest tent caterpillar (Malacosoma disstria Hiibner) (FTC) is a native defoliator of most hardwoods in North America that causes economic damage to not only lumber and paper industries but also the maple sugar industry. While defoliation often decreases the basal area growth of trees, just three consecutive years of heavy defoliation has been shown to cause mortality in aspen (Populus sp.) (Churchill et al. 1964; Cooke et al. 2009). In areas affected by a severe outbreak large patches of forest can have 25-50% tree mortality, often caused by secondary factors such as susceptibility to fungi, wood borers and mechanical damage (Churchill et al. 1964; Howse 1995). Such an outbreak can be devastating for local communities and industries and has cost millions of dollars to the Ontario sugar maple industry in the 1970's (Howse 1995). Understanding relationships and processes that affect this insect may aid in forest management practices that attempt to control the outbreaks and damage done by this economic pest and those which display similar behaviour. The population of FTC fluctuates in Ontario with a distinct cycle approximately 10 years in length (Sippell 1962; Cooke and Lorenzetti 2006). The cycling of many forest lepidopterans have been associated with changes in winter/spring temperatures (Blais et al. 1955; Witter et al 1972; Ives 1973; Wetzel et al 1973; Daniel and Myers 1995; Roland et al. 1998; Cooke and Roland 2003) and host quality (Ginzburg and Taneyhill 1994; Turchin et al 2003 Baltensweiler and Fischlin 1988; Haukioja et al 1988), and host-parasitoid interactions (Varley 1949). Although not a new concept, the host- parasitoid interactions theory is the most recently accepted theory (Berryman 1996; 119 Turchin et al. 2003; Cobbold et al. 2005; Cooke and Lorenzetti 2006 and references therein). The FTC has numerous predators, including over 60 species of birds, and over 100 dipteran and hymenopteran parasites and parasitoids of the egg, larval and pupal stages (Witter and Kulman 1972; Sippell 1957). Despite this large number of predators and parasites, one pupal parasitoid, Arachnidomyia (=Sarcophaga) aldrichi (Parker), is considered the primary cause of mortality (Hodson 1941), has been used as the model species for the host-parasitoid dynamics (Cobbold et al. 2005) and although it had lower rates of parasitism in Alberta compared to Ontario, it is still the most common parasitoid of FTC in that province (Parry 1995). FTC cycles are closely associated with their parasitoid population cycles and simulation models have suggested that the searching efficiency of parasitoids may change the timing and intensity of outbreaks (Cobbold et al. 2005). Disturbance and stress can also play an important role in the general population dynamics of forest insects. For example, FTC outbreaks last longer and are more frequent in areas with more fragmentation and in one anomalous region, Sudbury, Ontario that suffers from lingering stress of past smelting pollution (Roland 1993). Cobbold et al. (2005) used patch size to examine changes in the host-parasitoid cycle and found that fragmentation (which may be either a source of stress or caused by stress from disturbances such as logging) may alter the emergence time and efficiency of parasitoids and in turn, increase the severity of outbreaks. The integrodifference model of Cobbold et al. (2005) demonstrated how an increase in searching efficiency or promotion of early emergence of parasitoids might induce less frequent but longer host outbreaks. 120 Previous population models of FTC have employed differential and integrodifference equations to elucidate how the fragmentation of a forest affects the FTC-parasitoid relationship and how to predict average length of the population cycles of the pest (Rejmanek et al. 1987; Cobbold et al. 2005). To our knowledge, there have been no agent-based, spatially-explicit models based on FTC developed to examine how stress- mediated changes in life-history traits such as the fecundity and dispersal of both the host and parasitoid may affect population dynamics, in particular the frequency and severity of outbreaks. Here, we develop such a model, the purpose of which is to simulate the spatial and temporal population dynamics of FTC. The combination of an agent-based and spatially explicit model provides an opportunity to examine the movement and interactions between FTC and its parasitoid within the unique shape of Ontario and boundaries of FTC distribution range. Our model was chosen to be a spatially explicit agent-based model for a number of reasons. Movement patterns of forest defoliators such as FTC have revealed traveling waves of outbreaks (Cooke et al. 2009) and patch size and shape within simulation models can have significant impacts on the dynamics of the agents within the model (Cobbold et al. 2005). A spatially explicit model can therefore simulate spatial patterns (such as traveling waves) at a larger spatial scale than a local cell. Furthermore, agent- based models provide more information about individual (in our case, it will be subpopulation) variation than equation-based models, which helps examine spatial variability, local interactions and movement (DeAngelis and Mooij 2005). For example, 121 equation-based models cannot incorporate complex behavioural sequences like feeding, dispersing and mating along with individual interactions without difficulty (DeAngelis and Mooij 2005). Our model lies between simple toy models where the model organism does not necessarily have empirical basis (Beer 2003) and a completely empirical model using observed values for all parameters. Although abstract or toy models have been criticized for their lack of biological significance (Webb 2009), they have often been developed, accepted and deemed relevant by the scientific community through their subsequent use to explore new theories and provide hypothetical yet testable scenarios (Grimm and Railsback 2005; Husbands 2009). For example, Beer (2003) used an agent that had no empirical association to any specific organism to model cognitive behaviour. Furthermore, the Lotka-Volterra model of predator-prey dynamics is considered an extremely simple model with little empirical background, yet remains a significant reference for many population dynamics studies (Peck 2004). Our model was developed with as many empirically-derived values for parameters as possible with a few values based on closely-related organisms. It was intended to create a realistic pattern of host- parasitoid dynamics and to then examine how stress-sensitive parameters may affect the outbreak cycle of the host species, a forest defoliator. With these simulations, we hoped to provide testable hypotheses for future scenarios. Perhaps an obvious effect of stress on any organism would be changes in fecundity or susceptibility to disease and other causes of mortality; however, this is not always the 122 case when examining a stressed forest and its insect defoliators. For example, heavy metals can decrease parasitoid population growth rate to a larger degree than its herbivore host suggesting that such pollution can be beneficial to the herbivore in terms of reducing predator/parasitoid pressure (Kramarz and Stark 2003). We manipulated parameters associated with fecundity, mortality, dispersal and searching efficiency of the caterpillar and its parasitoid to show how it may change the dynamics of the FTC cycle. By studying how changes in such parameters alter the FTC cycle and which are most effective at reducing defoliation, researchers may better predict the outbreaks, understand which parameters affect the population and show how future scenarios of stress and climate change can not only change the cycle but perhaps the distribution of this insect. With this knowledge we may find methods to reduce insect defoliator populations and help strengthen resistance to them. METHODS Model details Our model was implemented in Netlogo (Wilensky 1999) (see mode code and screen captures in Appendix A), a software platform for agent-based modelling. The interactions between the three trophic levels (tree, FTC, parasitoid) generate population dynamics for each level, which we follow over time, but we are interested primarily in the dynamics of the FTC population and resulting defoliation. Several parameters, explained below, are necessary to describe the behaviour of the variables. Within these parameters, six were 123 altered in the presence of a stressor. These were Caterpillar Dispersal (adult) (CD), Caterpillar Fecundity (CF), Parasitoid Dispersal (PD), Parasitoid Fecundity (PF), Parasitoid Efficiency (PE), Parasitoid Mortality (PM) (adult) (Table 5.1). Other parameters that were not affected by stress include parasitoid preadult mortality, parasitoid radius of attack and caterpillar preadult dispersal. Our rationale for parameterization (or parameter tuning) included use of biological intuition as well as a mixture of calibration and validation strategies (Grimm and Railsback 2005). We chose parameters for which we could find realistic ranges for all values based on previously reported literature to the best of our ability. We also chose values for certain parameters, which, while remaining reasonable, also best fit the observed FTC dynamics over a period of over 50 years. Each cell in our model represents a square plot of land approximately 17 km wide, resulting in a forest patch of approximately 289 km2 within Ontario, Canada. These forest patches were classified as either potential food habitat for FTC or not (areas with no history of defoliation between 1948-2005) based on spatial data of the provincial defoliation from FTC obtained from the Forest Health Monitoring of the Canadian Forest Service (CFS), Great Lakes Forestry Centre, Natural Resources Canada (NRC) in cooperation with the Ontario Ministry of Natural Resources (OMNR). Areas without defoliation tend to correspond to regions of agriculture and urbanization or are simply beyond the northern range of this species. A theoretical variable called 'energy' was assigned to each cell (forest patch with potential food habitat) to represent quality of food available for FTC. There are five possible energy levels (states) and each cell revitalizes 124 an energy value each year (time step) to the maximum of five based on the assumption of forest growth/recovery over time. When defoliation occurs consecutively in the same patch (which may occur within one year from multiple caterpillars) and results in the forest energy level dropping to the minimum value, the forest patches do not begin revitalizing until three years have passed, named tree-lag in the model. This is based on studies that show quality of tree foliage is reduced after severe defoliation, may not provide enough nutrients to support a large population of defoliators and may take over two years to recover (Baltensweiler and Fischlin 1988; Turchin et al. 2003). The energy variable is also used to represent nutrients received by FTC from the forest patch and was depleted through dispersal as described below. Using this theoretical energy variable provides a blackbox surrogate to explicitly model forest growth dynamics, FTC food quality and physiology. Agents within the model represent a subpopulation of insects (either FTC or parasitoid) since millions of insects may occur within the 289 km2 cell size. The term "agent" will herein refer to an individual within the model; therefore it will symbolize a subpopulation. There may be over 20,000 FTC on a single tree during a period of high defoliation (Stairs 1972). Initial population size of FTC is 180 and 50 for the parasitoids; however, the simulation model was run for 500 iterations and the final 100 time steps (years) were used for analyses to allow the model to flush the initial conditions. The theoretical parasitoid was based on the primary source of mortality for the FTC; the pupal parasitoid sarcophagid fly A. aldrichi Parker (Hodson 1941). 125 The term 'dispersal' was used in the model to represent population spread. Agents of both FTC (adult) and parasitoids move to a random cell within their dispersal limits (two cells wide; 34 km) each year. Little information is available on the dispersal of these insects; however, similar calliphorid flies can fly 8 km/hour, their population spread can be over 2000 km/year (Norris 1965) and strong winds from cold fronts have been shown to carry FTC moths hundreds of kilometres in one year (Brown 1965). A tachinid parasitoid (Diptera: Tachinidae) of mole crickets, Ormia depleta Weidemann, is also in a closely related family of flies and has been shown to have a population spread of 64 km per year over 2 years (Frank et al. 1996). On the other hand, Cobbold et al. (2005) used a maximum of 1 km dispersal for their host-parasitoid model of FTC and Arachnidomyia aldrichi but this seems to be based on individual dispersal instead of a larger population spread. Our value lies in between these two extremes and was chosen because it, combined with other realistic parameter values, was able to reproduce the observed dynamics of FTC. The traveling waves observed in FTC outbreaks clearly show the potential for movement of defoliation and FTC populations within a one-year timeframe (Cooke et al. 2009). The FTC loses one energy value each year from dispersal and death occurs if energy falls below one. If an agent leaves the limits of the zone of defoliation, they turn back to their original location of the beginning of the year. This equalizes immigration and emigration. FTC foraging occurs as they move to a new cell (forest patch) and defoliate it by taking energy from it and receiving one energy value in return. The energy they receive from foraging depends on the forest patch's energy value. After three years of consecutive 126 defoliation, the forest patches have a three-year lag to recover (see above). Parasitoid efficiency was defined as the percentage of parasitoid eggs (see fecundity) to be successfully laid on a host caterpillar (pupa) and thus takes into account searching efficiency. The successful eggs then "kill" the caterpillar and become a new parasitoid. Since few studies have examined the efficiency of sarcophagid flies, parasitoid efficiency was created and calibrated to our model at a value of 6%, which lies within the broad range from 0-29% from recent studies with parasitoid wasps (Skovgard 2006; Birkemoe et al. 2009). Parasitoids have a radius of attack by the ability to parasitize caterpillars within a radius of five cells (85km). This range was set at a larger value than the dispersal because it is a direct movement of the parasitoids to search for hosts, whereas the dispersal of the parasitoids is a smaller scale, random shift in population. The reproduction of the agents (i.e. the growth rate of the subpopulation) is based on generation times of FTC and its parasitoid. The FTC fecundity is set at 3 agents/year and the parasitoid at 50 agents /year. This difference is based on the behaviour of the organisms and the life-stage represented in the model. For FTC, fecundity represents the larvae that survived from egg to the pupal stage. One female FTC can lay between 94- 250 eggs (Hodson 1941; Stehr and Cook 1968) but survival rate to pupae can be lower than 10% (Witter et al. 1972; Fitzgerald 1995), at which point the pupal parasitoid is the primary source of mortality (Hodson 1941; Witter et al. 1972). FTC fecundity was set at three agents for the model, which provided a feasible number. The FTC immediately disperse zero to two grid cells in a random direction (preadult dispersal), are assigned a random energy level between one and four and have an age of zero. The fecundity of the 127 parasitoids represents the number of eggs held in ovaries of the female. Since sarcophagid flies may have a lifetime fecundity of48-106 larvae/female (Denlinger et al. 1988), our parasitoid fecundity of 50 falls within this range. The number of successful eggs laid is much less due to the constraints of searching efficiency and mortality explained below. To simulate natural death due to factors such as disease and physiological stress for parasitoids, we introduced a parameter of induced mortality (such as pupal parasitism and energy starvation). Age-induced death also occurs for all agents once age is greater than one year since these insects complete their life cycle in one year. Parasitoid mortality in this model has two components. The first component occurs after laying eggs since only a certain percentage of the eggs will succeed to the pupal stage. This parameter is considered the preadult mortality and is set at 50% mortality. The second component is a parameter that can be altered according to the source of stress. This is mortality of the parasitoid after pupation and its initial value is 40. Few studies examine the life table of sarcophagid flies; however, Dahlem and Naczi (2006) recorded pupal mortality of sarcophagids that live in pitcher plants as high as 65%. A tachinid parasitoid of the Mexican rice borer moth had a pupal mortality ranging from 48.4 to 76% (Lauziere et al., 2001). In both cases, however, temperature and humidity are believed to play an important role. Abou Zied et al. (2003) found that there was a 30% prepupal mortality observed in sheep blow flies (Diptera: Calliphoridae) and 46% mortality during the adult stage. Our preadult and adult mortality rates are therefore similar to or within these limits of mortality. 128 Data analysis Simulated defoliation was correlated with caterpillar population to support its use as a surrogate for population size. The simulated total (provincial) defoliation was compared to the observed FTC defoliation (provided by OMNR and NRC for years, 1948-2005) using cross-correlation to examine if the simulation gives a realistic pattern of the defoliation within Ontario. Six chosen parameters were then varied to examine how local stress (manifested in effects on life-history traits of these organisms) may alter the local and global defoliation of FTC (Table 5.1) during a 100-year time span. The location of this source of stress was placed in northwestern Ontario, because this is an area on the map that contains large contiguous patches of forest. The mean total yearly defoliation within an 85 km radius (5 five cells) around the source of stress was calculated. Although sensitivity analyses are not commonly used for agent-based models, varying these chosen parameters one at a time and examining the model output through regression provided a type of sensitivity analysis of this model (Bart 1995; Grimm and Railsback 2005). To examine how local stress may affect other or larger regions, we examined two other spatial areas: a neighbouring swath of land further than 204 km from the source of stress and the global scale (entire province of Ontario). The mean defoliation for each change in each parameter was compared between the northwest, northeast and provincial regions. Relationships were then examined using correlation analyses. 129 Changes in the defoliation cycles were examined by first determining how many peaks occurred within 100 years. This timeframe was chosen to provide an appropriate number of outbreaks for our analyses and a timeframe comparable to the 57 years of observed data. One hundred years of defoliation were examined for the base model and for two values for each parameter, one that increased mean defoliation and another that decreased mean defoliation. The number of years between each dominant peak was then counted to determine the length of time between periods of high defoliation and the mean was used for analyses. These peaks did not necessarily correspond to outbreaks, as they may not have been severe, therefore a threshold was established to determine which peaks should be considered severe enough to be an outbreak. We determined this threshold by examining the baseline model dynamics and choosing a level of defoliation that was higher than the mean defoliation for the 100 years. For each peak of defoliation, the number of consecutive years that were above this threshold was recorded to determine the length of the outbreak. Length of outbreaks and frequency of defoliation peaks were then compared to base model values using T-tests. Parameters were initially modified one at a time to determine if the model was sensitive to changes in their values. To examine some possible interactions, we then chose the same two values for each parameter that were used in the cycle analyses. The value that increased defoliation was then combined with the value that decreased defoliation for each other parameter. The length and frequency of high defoliation were then compared to the base model values using T-tests. All statistical analyses were performed with Statistica 6 (Statsoft Inc. 2001). 130 RESULTS Defoliation caused by FTC and population size of FTC were strongly correlated (r=0.86, p<0.001). We may therefore use defoliation as a surrogate for FTC population henceforth. Using baseline parameters (Table 5.1), the simulation model created a cyclic pattern in the defoliation that was comparable to the observed historical pattern in Ontario (Figure 5.1; cross-correlation = 0.53; p<0.05). The defoliation patterns created with our model without either the forest patch quality lag or the presence of parasitoids resulted in an unrealistic cyclic pattern. Therefore, the combination of parasitoids and forest patch lag were required to produce more realistic cycles for our base model. Our analyses demonstrated that an increase in FTC dispersal resulted in only a slight increase in the defoliation that was not significant (R2 = 0.44); however, increasing caterpillar fecundity (R2 = 0.66, p<0.01), parasitoid dispersal (R2 = 0.73, p<0.05) and parasitoid mortality (R2 = 0.80, p<0.01) all resulted in an increase in the mean defoliation of the immediate region (85 km radius) around the source of stress (Figures 5.2a-d). The caterpillar fecundity showed a log-linear relationship demonstrating that minimal changes at the smaller values results in more drastic changes in defoliation. Decreasing parasitoid fecundity (R2 = 0.85, p<0.01) and efficiency (R2 = 0.58, p<0.01) resulted in an increase in mean defoliation (Figures 5.2e,f). Both of these relationships were log-linear and revealed significant changes in defoliation with minor alteration of the parameter at the smaller values. This suggests that the model is more sensitive to such alterations. The 131 range of parameters values over which trends were established are biologically reasonable. An outbreak was considered as any defoliation that covered more than 45 cells within the immediate region (85 km radius) around the source of stress. This threshold is slightly higher than the average of 42.12 cells. This provided a minimal level of defoliation above which we considered high defoliation or outbreak status. The parameter combinations revealed that caterpillar fecundity and parasitoid efficiency had the strongest effect on the other parameters by effectively decreasing the length of the outbreak for three of the five possible combinations. When the other parameters were adjusted to increase defoliation, the presence of a low caterpillar fecundity reduced the length of outbreaks for caterpillar dispersal (t=4.43, p<0.01), parasitoid efficiency (t=-7.57, p<0.01), and parasitoid fecundity (t=-3.30, p<0.01). The presence of high parasitoid efficiency decreased the length of the outbreaks when combined with a high caterpillar dispersal (t=3.86, p<0.01), caterpillar fecundity (t=-5.75, p<0.01), and parasitoid mortality (t=-6.12, p<0.01). High parasitoid fecundity was effective when combined with high caterpillar fecundity (t=- 2.46, p<0.01) and parasitoid mortality (t=-2.95, p<0.05). Low caterpillar dispersal was only effective when combined with a high caterpillar fecundity (t=-4.28, p<0.01) and low parasitoid mortality was only effective when combined with high caterpillar fecundity (t=-2.46, p<0.05). Only one parameter combination effectively altered the frequency of outbreaks; an increased parasitoid mortality with a decreased parasitoid dispersal (t=2.34, p<0.05). 132 All parameters effectively altered either the number or frequency of peaks in the defoliation cycle (Figure 5.3). The frequency of defoliation peaks was increased by an increase of parasitoid dispersal or a decrease in parasitoid dispersal or mortality. The number of consecutive years above the outbreak threshold (length of outbreak) was increased by a decrease in parasitoid efficiency. This number was decreased by an increase in parasitoid fecundity or a decrease in caterpillar dispersal, caterpillar fecundity, parasitoid dispersal or parasitoid mortality. Examining the effects of the local changes in defoliation on the regional or provincial scale, we found that changes in the mean defoliation at the local scale did not affect the defoliation dynamics in a neigbouring region. Only three parameters created a significant relationship between local defoliation and the global (provincial) defoliation; caterpillar dispersal (R2 = 0.71, p<0.05), parasitoid fecundity (R2 = 0.80, p<0.01) and parasitoid efficiency (R2 = 0.85, p<0.01). Screen shots of the model further demonstrate the population dynamics and traveling waves of defoliation we observed through this model and the provincial observed data (Figure 5.4). DISCUSSION By developing a simulation model to represent the observed FTC dynamics in a temperate North American forest, we showed how stress may change patterns of defoliation. Our model demonstrates that if stress were to alter certain demographic parameters, it can significantly affect the defoliation caused by FTC within a local area 133 directly affected by the source of stress, which can be detected at the provincial level. It is also important to highlight the fact that the combination of parasitoid interactions and forest patch quality lag was essential in providing a simulation model that mirrored the observed trends. This supports the hypothesis that tree host quality plays an important role in the population dynamics of forest defoliators (Ginzburg and Taneyhill 1994; Berryman 1996; Turchin et al. 2003 Baltensweiler and Fischlin 1988; Haukioja et al. 1988). There were differences in the amplitudes of the observed defoliation cycle and the simulated cycle that could be partly due to the methods of the defoliation evaluation. The observed Ontario outbreaks were represented by large polygons from GIS maps, which may overestimate the defoliation of an area as it includes non-host stands, roads and urban areas. The simulation model may have fewer areas of defoliation, as its cells are approximately 289 km2 and do not span large polygons across the landscape. Alternately, aerial assessment may underestimate the defoliation of FTC during years of diminished populations, as the defoliation may not be detected despite a presence of FTC in the forest stand. The simulation model detects even low levels of defoliation for small areas. Stressed forests may have longer outbreaks, more frequent outbreaks or a region-wide increase in defoliation for a number of reasons that may relate to demographic parameters such as the ones we examined here: dispersal, fecundity, mortality and searching efficiency. First, changes within a habitat may alter the dispersal rate or dispersal ability of certain species. Fragmentation alters both the cyclic dynamics (Roland 2005) and host- 134 parasitoid dynamics (Cobbold et al. 2005) of FTC and may promote greater emigration through the increase in forest edge. Habitat quality has also been suggested to affect dispersal for spruce budworm (Choristoneura fumiferana Clemens) since poor quality sites appear to have higher emigration (Royama 1984). Although few studies have examined the effects of climate change on dispersal, Bale et al. (2002) suggest that temperature may alter insect dispersal capabilities due to physiological changes in wings and extended flight seasons. Stressed trees have altered chemical compounds such as nitrogen and phenolic glycosides (Kopper and Lindroth 2003) that may improve leaf quality for insect herbivores and subsequently increase fecundity. For example, air pollutants like CO2 and O3 have increased larval performance for FTC by altering the nitrogen levels in the host leaves (Kopper and Lindroth 2003). Alternatively, in a scientific review, Zvereva and Kozlov (2010) suggested that different trophic levels may be more susceptible to toxins in an area of pollution, therefore, such an environment may result in a decrease in predator and parasitoid fitness or increase in mortality. They suggested that the effects of pollution may not always be the same for every trophic level as herbivore density increased, predator density decreased and parasitoid density remained unchanged. Although searching efficiency of parasitoids may also be altered by stress such as fragmentation (Roland and Taylor 1997), results may depend on the parasitoid species and their searching behaviour (Cobbold et al. 2005). Air pollution affects searching efficiency through interference of chemical cues, as demonstrated by Gate et al. (1995) when elevated O3 resulted in a diminished searching efficiency of a hymenopteran parasitoid. Many parasitoids use chemical cues such as those from pheromones or chemicals in the frass of the host (Feener and Brown 1997). Here we 135 showed, for the first time, that changes in these parameters, including dispersal and fecundity of either FTC or its parasitoids, could have significant effects on the severity and length of outbreaks. The most effective parameter for altering the defoliation cycle was parasitoid efficiency followed by caterpillar fecundity, caterpillar dispersal and parasitoid fecundity. The least sensitive parameters were parasitoid dispersal and mortality. Parasitoid efficiency altered the local defoliation to a degree that was observable at the provincial scale, could significantly increase the length of an outbreak and was effective at reducing outbreak length and frequency in combination with three of the five other parameters. The presence of a log-linear relationship between the parameter value and defoliation demonstrates that small changes in efficiency at the lower values of the parameter can have the most severe affect on defoliation. Although an increase of parasitoid efficiency was able to decrease the average defoliation caused by FTC, this could not be significantly demonstrated for the cycle analyses. This was due to the constant low level of defoliation and FTC population, which occasionally caused a crash in the local parasitoid population. There was a subsequent peak in FTC as the population grows unrestricted until new parasitoid populations immigrated into the region. We stress that these hypotheses generated by the model may be examined with future empirical examination of FTC-parasitoid dynamics. The parasitoid parameters that were least effective at altering the FTC cycle (dispersal, fecundity and mortality) focus on parasitoids and their population or movement. Further 136 studies may support our suggestion that no matter how many parasitoids are available or how far they may travel, they are not as effective in suppressing a large population of caterpillars if they are not efficient. We suggest that future management and monitoring programs consider these various parasitoid parameters. For example, an increase in release rate (the number of biological control agents released) does not necessarily result in stronger control on the pest insect (Crowder 2007). Our model suggests that it may be more effective to enhance the efficiency of the locally occurring population of parasitoids. Although changes in fragmentation (Roland and Taylor 1997) and air pollution (Gate et al. 1995) may alter searching efficiency of parasitoids, recent studies have also suggested the use of herbivore-induced plant volatiles (HIPVs) to attract parasitoids (Khan et al. 2008; Gurr and Kvedaras 2010). We suggest that using these chemicals not only attracts parasitoids to host trees but may enhance their searching efficiency. Changes in local defoliation did not result in changes in neighbouring forest patches in our model. This suggests that the local population dynamics did not create unusually large traveling waves of either the forest tent caterpillar or its parasitoid. Although traveling waves of defoliation are an observed phenomena of this insect (Cooke et al. 2009), we find that as large populations (from increased fecundity, decreased mortality, etc.) of FTC or parasitoid moved away from the source of stress and as their dynamics changed, their population reverted to a regular base-model size. Three of the parameters cause severe changes in the populations within the region of stress that were large enough to affect the provincial defoliation. This shows how small regional-scale disturbances and 137 stress can be significant in determining large-scale patterns of population dynamics and specifically, FTC forest defoliation. This heterogeneity has been examined for areas with increased fragmentation (Roland 1993) and areas with increased population or roads (Cook et al. 2009). Further studies may also examine the effects of past pollution and climate change. Roland (1993) found that although the region of Sudbury, Ontario did not have an elevated level of fragmentation, the outbreaks were longer. He suggested that the lingering effects of past pollution from mining activities, such as altered tree species and stand structure, might have played an important role. Cooke et al. (2009) found most regional outbreaks within Ontario last only 1-2 years; however, if this threshold is surpassed, significant damage and mortality occurs. Our results demonstrate that small changes in specific parameters of either the caterpillar or its parasitoid can cause an increase in outbreak length. Since the level of stress in the forest stand can influence these parameters, we suggest they should play important roles in the management of this insect. For example, we demonstrated that all four parasitoid parameters (especially parasitoid efficiency) were capable of altering the mean defoliation caused by FTC in the model. These simulated scenarios may promote further studies into the use of biocontrol agents for this forest defoliator. By studying the cycle of FTC, researchers may better predict the outbreaks and show how future scenarios of stress and climate change can change the cycle. With this knowledge we may find methods to reduce insect defoliator populations and help strengthen resistance to them. 138 While our model was aimed specifically at FTC, as one of the most widely distributed hardwood defoliator in North America (Coyle et al. 2005), the basic premise of the model could be applied to other insect defoliators that exhibit similar cyclical dynamics affected by parasitoids and host quality. Specific parameters would then be altered to correspond to defoliators such as the Larch budmoth (Zeiraphera diniana Guenee) and Gypsy moth (Lymantria dispar L.). Furthermore, we suggest further studies to elucidate the particular effects of various stressors such as climate change and pollution on some of the parameters studied here, to improve the predictive value of our model. Since these stressors will likely alter phenology, population growth rate and expand the distribution of these insect populations in the near future, this understanding will help us to respond to these changes (Ayres and Lombardero 2000; Logan et al. 2003; Dukes et al. 2009; Logan etal. 2010). ACKNOWLEDGEMENTS We would like to thank the Canadian Forest Service and Ontario Ministry of Natural resources, especially Barry Cooke, Ron Fournier, Barry Lyons and Taylor Scarr for their advice, comments and access to information. For his invaluable input for the development of the model, we also thank Aaron Langille. Funding for this research project was provided by Laurentian University, the University of Guelph, the Natural 139 Sciences and Engineering Research Council of Canada, the Canadian Foundation for Innovation and the Canada Research Chairs program to M.A. REFERENCES Abou Zied E. M., R. M. Gabre, and H. Chi. 2003. Life table of the Australian sheep blow fly Luciliacuprina (Wiedemann) (Diptera: Calliphoridae). Egyptian Journal of Zoology 41:29-45. Ayres M. P., M. J. Lombardero. 2000. Assessing the consequences of global change for forest disturbance from herbivores and pathogens. The Science of the Total Environment 262:263-286. Bale J. S., G. J. Masters, I. D. Hodkinson, C. Awmack, T. M. Bezemer, V. K. Brown, J. Butterfield, A. Buse, J. C. Coulson, J. Farrar, J. E. G. Good, R. Harrington, S. Hartley, T. H. Jones, R. L. Lindroth, M. C. Press, I. Symrnioudis, A. D. Watt, and J. B. Whittaker. 2002. Herbivory in global climate change research: direct effects of rising temperature on insect herbivores. Global Change Biology 8:1-16. Baltensweiler W., A. Fischlin. 1988. The larch bud moth in the Alps. Pages 331-351 In A: A. Berryman, editor. Dynamics of Forest Insect Populations: Patterns, Causes, Implications, Plenum Press, New York. Bart J. 1995. Acceptance criteria for using individual-based models to make management decisions. Ecological Applications 5:411-420. 140 Beer R. D. 2003. The dynamics of active categorical perception in an evolved model agent. Adaptive Behavior 11:209-243. Berryman A. A. 1996. What causes population cycles of forest Lepidoptera? Trends in Ecology and Evolution 11:28-32. Birkemoe T., A. Soleng, and A. Aak. 2009. Biological control of Musca domestica and Stomoxys calcitrans by mass releases of the parasitoid Spalangia cameroni on two Norwegian pig farms. BioControl 54:425-436. Blais J. R., R. M. Prentice, W. L. Sippell, and D. R. Wallace. 1955. Effects of weather on the forest tent caterpillar Malacosoma disstria Hbn., in central Canada in the spring of 1953. Canadian Entomologist 87:1-8. Brown C. E. 1965. Mass transport of forest tent caterpillar Malacosoma disstria Hubner moths by a cold front. Canadian Entomologist 97:1073-1075. Churchill G. B., H. H. John, D. P. Duncan, and A. C. Hodson. 1964. Long-term effects of defoliation of aspen by the forest tent caterpillar. Ecology 45:630-633. Cobbold C. A., M. A. Lewis, F. Lutscher, and J. Roland. 2005. How parasitism affects critical patch-size in a host-parasitoid model: Application to the forest tent caterpillar. Theoretical Population Biology 67:109-125. Cooke B. J., J. Roland. 2003. The effect of winter temperature on forest tent caterpillar (Lepidoptera: Lasiocampidae) egg survival and population dynamics in northern climates. Environmental Entomology 32:299-311. 141 Cooke B. J., F. Lorenzetti, and J. Roland. 2009. On the duration and distribution of forest tent caterpillar outbreaks in east-central Canada. Journal of the Entomological Society of Ontario 140:3-18. Cooke B. J., F. Lorenzetti. 2006. The dynamics of forest tent caterpillar outbreaks in Quebec, Canada. Forest Ecology and Management 226:110-121. Coyle D. R., T. E. Nebeker, E. R. Hart, and W. J. Mattson. 2005. Biology and management of insect pests in North American intensively managed hardwood forest systems. Annual Review of Entomology 50:1-29. Crowder D. W. 2007. Impact of release rates on the effectiveness of augmentative biological control agents. Journal of Insect Science 7:1-11. Dahlem G. A., R. F. C. Naczi. 2006. Flesh Flies (Diptera: Sarcophagidae) associated with North American pitcher plants (Sarraceniaceae), with descriptions of three new species. Annals of the Entomological Society of America 99:218-240. Daniel C. J., J. H. Myers. 1995. Climate and outbreaks of the forest tent caterpillar. Ecography 18:353-362. DeAngelis D. L., W. M. Mooij. 2005. Individual-based modeling of ecological and evolutionary processes. Annual Review of Ecology, Evolution, and Systematics 36:147-168. Denlinger D. L., C. P. Chen, and S. Tanaka. 1988. The impact of diapause on the evolution of other life-history traits in flesh flies. Oecologia 77:350-356. 142 Dukes J. S., J. Pontius, D. Orwig, J. R. Garnas, V. L. Rodgers, N. Brazee, B. Cooke, K. A. Theoharides, E. E. Stange, R. Harrington, J. Ehrenfeld, J. Gurevitch, M. Lerdau, K. Stinson, R. Wick, and M. Ayres. 2009. Responses of insect pests, pathogens, and invasive plant species to climate change in the forests of northeastern North America: What can we predict? Canadian Journal of Forest Research 39:231-248. Feener D. H., B. V. Brown. 1997. Diptera as parasitoids. Annual Review of Entomology 42:73-97. Fitzgerald T. D. 1995. The Tent Caterpillars. Cornell University Press, New York. Frank J. H., T. J. Walker, and J. P. Parkman. 1996. The introduction, establishment, and spread of Ormia depleta in Florida. Biological Control 6:368-377. Ginzburg L. R., D. E. Taneyhill. 1994. Population cycles of forest lepidoptera: A maternal effect hypothesis. The Journal of Animal Ecology 63:79-92. Grimm V., S. F. Railsback. 2005. Individual-based Modeling and Ecology. Princeton University Press, Princeton, New Jersey. Gurr G. M., O. L. Kvedaras. 2010. Synergizing biological control: Scope for sterile insect technique, induced plant defences and cultural techniques to enhance natural enemy impact. Biological Control 52:198-207. Haukioja E., S. Neuvonen, S. Hanhimaki, and P. Niemela. 1988. The autumnal moth in Fennoscandia. Pages 163-178 In A. A. Berryman, editor. Dynamics of Forest Insect Populations: Patterns, Causes, Implications, Plenum Press, New York. 143 Hodson A. C. 1941. An ecological study of the forest tent caterpillar, Malacosoma disstria Hbn. in northern Minnesota. University of Minnesota Agricultural Experiment Station Technical Bulletin 148:1-55. Howse G. M. 1995. Forest Insect Pests in the Ontario Region. Pages 41-57 In J. A. Armstrong and W. G. H. Ives, editors. Forest Insect Pests in Canada, Natural Resources Canada, Canadian Forest Service, Ottawa, Ontario. Husbands P. 2009. Never mind the iguana, what about the tortoise? Models in adaptive behavior. Adaptive Behavior 17:320-324. Ives W. G. H. 1973. Heat units and outbreaks of the forest tent caterpillar, Malacosoma disstria. Canadian Entomologist 105:529-543. Khan Z. R., D. G. James, C. A. O. Midega, and J. A. Pickett. 2008. Chemical ecology and conservation biological control. Biological Control 45:210-224. Kopper B. J., R. L. Lindroth. 2003. Effects of elevated carbon dioxide and ozone on the phytochemistry of aspen and performance of an herbivore. Oecologia 134:95-103. Kramarz P., J. D. Stark. 2003. Population level effects of cadmium and the insecticide imidacloprid to the parasitoid, Aphidius ervi after exposure through its host, the pea aphid, Acyrthosiphon pisum (Harris). Biological Control 27:310-314. Lauziere I., J. C. Legaspi, B. C. Legaspi Jr, J. W. Smith Jr, and W. A. Jones. 2001. Life- history studies of Lydella jalisco (Diptera: Tachinidae), a parasitoid of Eoreuma loftini (Lepidoptera: Pyralidae). BioControl 46:71-90. 144 Logan J. A., W. W. Macfarlane, and L. Willcox. 2010. Whitebark pine vulnerability to climate change induced mountain pine beetle disturbance in the Greater Yellowstone Ecosystem. Ecological Applications e-View. doi: 10.1890/09-0655. Logan J. A., J. Regniere, and J. A. Powell. 2003. Assessing the impacts of global warming on forest pest dynamics. Frontiers in Ecology and the Environment 1:130- 137. Norris K. R. 1965. The bionomics of blowflies. Annual Review of Entomology 10:47-68. Parry D. 1995. Larval and pupal parasitism of the forest tent caterpillar in Alberta. Canadian Entomologist 127:877-893. Peck, S.L. 2004. Simulation as experiment: A philosophical reassessment for biological modeling. Trends in Ecology and Evolution 19:530-534. Rejmanek M., J. D. Smith, and R. A. Goyer. 1987. Population dynamics of the forest tent caterpillar {Malacosoma disstria) in a water tupelo {Nyssa aquatica) forest: A simulation model. Ecological Modelling 39:287-305. Roland J. 1993. Large-scale forest fragmentation increases the duration of tent caterpillar outbreaks. Oecologia 93:25-30. Roland J. 2005. Are the "seeds" of spatial variation in cyclic dynamics apparent in spatially-replicated short time-series? An example from the forest tent caterpillar. Annales Zoologici Fennici 42:397-407. 145 Roland J., P. D. Taylor. 1997. Insect parasitoids species respond to forest structure at different spatial scales. Nature 386:713. Roland J., B. G. Mackey, and B. Cooke. 1998. Effects of climate and forest structure on duration of forest tent caterpillar outbreaks across central Ontario, Canada. Canadian Entomologist 130:703-714. Royama T. 1984. Population-dynamics of the spruce budworm Choristoneura fumiferana. Ecological Monographs 54:429-462. Sippell W. L. 1957. A study of the forest tent caterpillar and its parasite complex in Ontario. Agriculture Canada, Great Lakes Forest Research Centre, Ontario Region, Unpubl. Rep. Sippell W. L. 1962. Outbreaks of the forest tent caterpillar, Malacosoma disstria Hbn. a periodic defoliator of broad-leaved trees in Ontario. The Canadian Entomologist 94:408-416. Skovgard H. 2006. Search efficiency of Spalangia cameroni and Muscidifurax raptor on Musca domestica pupae in dairy cattle farms in Denmark. BioControl 51:49-64. Stairs G. R. 1972. Pathogenic microorganisms in the regulation of forest insect populations. Annual Review of Entomology 17:355-372. Statsoft Inc. 2001. STATISTICA: Data analysis software system, Version 6. 146 Stehr F. W., E. F. Cook. 1968. A revision of the genus Malacosoma Hiibner in North America (Lepidoptera, Lasiocampidae), systematics, biology, immatures, and parasites. Smithsonian Inst., U.S. Nat. Mus. Bull. 276,. Turchin P., S. N. Wood, S. P. Ellner, B. E. Kendall, W. W. Murdoch, A. Fischlin, J. Casas, E. McCauley, and C. J. Briggs. 2003. Dynamical effects of plant quality and parasitism on population cycles of larch budmoth. Ecology 84:1207. Varley G. C. 1949. Population changes in German forest pests. Journal of Animal Ecology 18:117-122. Webb B. 2009. Animals versus animats: Or why not model the real iguana? Adaptive Behavior 17:269-286. Wetzel B. W., H. M. Kulman, and J. A. Witter. 1973. Effects of cold temperatures on hatching of the forest tent caterpillar, Malacosoma disstria (Lepidoptera: Lasiocampidae). Canadian Entomologist 105:1145-1149. Wilensky U. 1999. NetLogo. http://ccl.northwestern.edu/netlogo/. Center for Connected Learning and Computer-Based Modeling, Northwestern University, Evanston, IL. Witter J. A., H. M. Kulman. 1972. A review of the parasites and predators of tent caterpillars (Malacosoma spp.) in North America. University of Minnesota Agricultural Experiment Station Technical Bulletin 289:1-48. Witter J. A., H. M. Kulman, and A. C. Hodson. 1972. Life tables for the forest tent caterpillar. Annals of the Entomological Society of America 65:25-31. 147 Zvereva E. L., M. V. Kozlov. 2010. Responses of terrestrial arthropods to air pollution: A meta-analysis. Environmental Science and Pollution Research 17:297-311. 148 1948 1967 1986 2005 Time (Year) Figure 5.1. Percent forest tent caterpillar defoliation in Ontario, Canada from observed data from Canadian Forest Service and Ministry of Natural Resources (black) and the simulation output (gray). Parameter values are given in Table 5.1. 149 (a) CD (b) PD 120 R2 = 0.44 120 R2 = 0.73* s •«B 80 S 80 a | 40 is 40 Q a 2 4 6 8 2 4 6 Parameter value Parameter value (c) CF 120 2 R2 = 0.66** R = 0.80** s 80 .3 1 0) 40 Q 0 40 80 120 Parameter value Parameter value (f)PE 120 2 R2 = 0.85** R = 0.58** IC S 80 40 » 100 200 40 80 120 Parameter value Parameter value Figure 5.2. Changes in mean forest tent caterpillar defoliation through altering the parameter values with significance of p<0.05* and p<0.01**. Grey diamonds represent the base model value. CD = caterpillar dispersal, PD = parasitoid dispersal, CF = caterpillar fecundity, PM = parasitoid mortality, PF = Parasitoid fecundity, PE = parasitoid efficiency. 150 150 CD 2 PF 50 Base Model i/VK/L CF 3 PE 6 0 50 100 Time (years) PD 2 PM 40 CD 1 CD 8 •2 150 a so °u 0 50 100 Time (years) Time (years) PD 1 At 2150 PD 8 2150 •j~100 | SO Jo \J\MaM A/VvWVv O 0 O 0 50 50 Time (years) Time (years) CF 1 2-150 CF 8 9 150 1100 2 50 Jo a o 50 100 Time (years) PM 6 At PM 100 2"3 150 ~ 100 o *-s a so is a o 50 PF 5 Time (years) PF 110 •s150' ~ 100 0 1 5(1 5 50 WyAV 50 100 50 PE 1J Time (years) PE 20 Time (years) 2 150 ywA/yw -•100 .3 50 £1 50 a o •AAA\ 0 50 100 50 Time (years) Time (years) Figure 5.3. Changes in forest tent caterpillar defoliation cycle from altering parameter values. CD = caterpillar dispersal, PD = parasitoid dispersal, CF = caterpillar fecundity, PM = parasitoid mortality, PF = Parasitoid fecundity, PE = parasitoid efficiency.* increased or* decreased length of outbreak (p<0.05); A increased frequency of defoliation peaks (p<0.05). 151 Timestep 410 Timestep 411 Timestep 412 1988 1989 1990 Figure 5.4 Screen shot of simulated defoliation (black squares) within FTC boundaries (grey) of Ontario and the observed FTC defoliation (grey polygons) showing Sudbury, Ontario (black dot). 152 Table 5.1. Parameter values for the base model of the forest tent caterpillar population dynamics. Base Parameter value Interpretation References Caterpillar Dispersal (CD) 0-2 0-34 km/year 8-2000 km/year (1,2,3,4) Caterpillar Fecundity (CF) 3 3 agents/year <10 (5-8) Parasitoid Dispersal (PD) 0-2 ' 0-34 km /yr 8-2000 km/year (1,2,3,4) Parasitoid Fecundity (PF) 50 50 eggs/year 48-106 (9) Parasitoid Efficiency (PE) 6 6% success 0-29% (10,11) Parasitoid (adult) Mortality 40% mortality 46% (12) (PM) 40 Parasitoid radius of attack 5 radius of 85 km 8-2000 km/year (1,2,3,4) Parasitoid pre-adult mortality 50 50% mortality 54-90% (12, 13) Caterpillar prepupal dispersal 0-2 0-34 km/year 8-2000 km/year (1,2,3,4) 1. Norris 1965. 2. Brown 1965. 3. Frank et al. 1996. 4.Cooke et al. 2009. 5. Hodson 1941. 6. Stehr and Cook 1968. 7. Witter et al. 1972. 8. Fitzgerald 1995, 9. Denlinger et al., 1988. 10. Skovgard 2006. 11. Birkemoe et al. 2009. 12. Abou Zaid et al. 2003. 13. Lauziere et al. 2001. 153 (VI) Final Conclusion and Future Endeavors 154 FINAL CONCLUSION I have shown that stress-mediated changes within a forest ecosystem have and will have significant impact on population size, population dynamics and community composition of a wide range of insect taxa including forest defoliators and soil enhancing ants. Furthermore, despite years of restoration efforts, certain insects are not recovering in the stressed environment found in Sudbury, Ontario. Canada. I demonstrated that the natural recovery and success of assisted recovery in a forest stressed from decommissioned copper-nickel smelting operations, such as forests near Sudbury, greatly depends on the specific group of insects studied; however, may not correlate to the recovery of the plant community (II). A stress-gradient also shows a completely altered taxonomic composition of insect communities revealing open-habitat species at the sites with increased stress (III). More specifically, plant stress increases the density, abundance, mean defoliation and frequency of outbreaks of forest insects by affecting the population size and demographic parameters of the defoliator and its primary parasitoid (IV, V). I found that searching efficiency of the parasitoid had the strongest influence on the dynamics of FTC compared to the other demographic parameters (V). With a projected increase in stress in the environment, from increased pollution (Fowler et al. 1999; Cape, 2008) and the numerous effects of climate change (Dale 2001; IPCC 2007), understanding how an ecosystem responds may help manage and decrease the deleterious effects. In a review, Cape (2008) found that many predictive models suggest that O3 (and emissions that are precursors to O3) will increase to levels that will 155 significantly affect the plant community. Dale et al. (2001) showed that if future scenarios of climate change were correct, there would be an impact on fire, drought, species introductions, pathogen and insect outbreaks, as well as numerous natural disasters. The stress resulting from these events and disturbances will result in either an excess or lack of essential habitat components such as nutrients, water and shade for flora and fauna with the possibility of disastrous reductions in biodiversity. I have discussed mainly the terrestrial environment; however, the importance of the aquatic environments should not be overlooked. If stress from events such as climate change, pollution and species introductions (further) decreased the biodiversity of the freshwater ecosystem, we would lose species that are essential for our fisheries and water filtration (Dudgeon et al. 2006). The marine ecosystem also provides food and tourism to the world and projections suggest that there will be an exponential collapse of fisheries as biodiversity decreases (Worm et al. 2006). I demonstrated that terrestrial insects have numerous responses to a stressed environment in terms of diversity, abundance, density and population dynamics and these responses may have significant impact on their relationships with the plant community. We must increase our knowledge of the effects of stress on the insect community due to their intimate relationship with plants, their habitat and the biological processes within it. Insects should, therefore, be incorporated in the management of recovery and restoration. They have the ability to increase plant dispersal, change the species composition and alter ecosystem functioning (MacMahon et al. 2000). As ecosystem engineers (Jouquet et al. 156 2006; Moore 2006), they play a crucial role in the survival and recovery of other flora and fauna in stressed environments. The stress gradient found around the region of Sudbury, Ontario, Canada demonstrates how past disturbance and severe pollution can result in a footprint on the landscape that persists for many years. It provides an opportunity to study recovery and primary succession for the flora and fauna, both naturally and through human-assistance. I showed how insect communities have a very unique composition in the most stressed sites, suggesting that there must remain untouched areas for natural recovery. I found the FTC has a higher density in the most stressed sites and this suggests that indeed, the lengthened outbreaks of the region may be partly due to the stress on the recovering landscape as suggested by Roland (1993). Furthermore, I showed that the traditional restoration techniques are not effective for the insect taxa examined. With the city of Sudbury launching the Biodiversity Action Plan in 2009 and new restoration techniques being reviewed, such as forest floor transplants (Braun 2008; Stephen Monet, pers. comm.), I emphasize the importance of the insect community in the future development of programs and monitoring of this stressed system. FUTURE ENDEAVORS With the vast amount of data obtained and accessed for this thesis, there are a number of additional questions to be examined. The historical data of forest tent caterpillar defoliation have been examined for regional differences (Cooke et al. 2009); however, 157 they may be further examined and correlated with drought or fire data of the province of Ontario. As McCullough et al. (1998) demonstrated, there are many studies showing how forest fires may promote insect outbreaks and, alternatively, insect outbreaks may promote fires. The occurrence of drought may also play an important role in this cycle. I will also continue to examine the insect fauna of the stress gradient to determine species patterns for other families such as rove beetles (Coleoptera: Staphylinidae) and weevils (Coleoptera: Curculionidae). For example, my data confirms the first Ontario record of at least one introduced and economically important species of weevil, Polydrusus cervinus L. (Patrice Bouchard, pers. comm.) and I hope to examine the trends of the weevil species. Future examination of FTC egg masses of the Sudbury, Ontario region may provide further insight into the population dynamics of this defoliator. This may be especially important for monitoring purposes as the introduced and potentially competitive gypsy moth Lymantria dispar L. (Lepidoptera: Lymantriidae) has increased in population in Ontario and is correlated with an increase in climatic suitability of the habitat (Regniere et al. 2009). 158 REFERENCES Braun J. R. 2008. Changing richness of plant species aids reclamation on smelter- damaged lands in Sudbury, Ontario, Canada. Master of Science Thesis. Laurentian University, Sudbury, Ontario. Cape J. N. 2008. Surface ozone concentrations and ecosystem health: past trends and a guide to future projections. Science of The Total Environment 400:257-269. Cooke B. J., F. Lorenzetti, and J. Roland. 2009. On the duration and distribution of forest tent caterpillar outbreaks in east-central Canada. Journal of the Entomological Society of Ontario 140:3-18. Dale V. H., L. A. Joyce, S. McNulty, R. P. Neilson, M. P. Ayres, M. D. Flannigan, P. J. Hanson, L. C. Irland, A. E. Lugo, C. J. Peterson, D. Simberloff, F. J. Swanson, B. J. Stocks, and M. Wotton. 2001. Climate change and forest disturbances. Bioscience 51:723-734. Dudgeon D., A. H. Arthington, M. O. Gessner, Z. Kawabata, D. J. Knowler, C. Leveque, R. J. Naiman, A. Prieur-Richard, D. Soto, M. L. J. Stiassny, and C. A. Sullivan. 2006. Freshwater biodiversity: Importance, threats, status and conservation challenges. Biological Reviews 81:163-182. 159 Fowler D., J. N. Cape, M. Coyle, C. Flechard, J. Kuylenstierna, K. Hicks, D. Derwent, C. Johnson, and D. Stevenson. 1999. The global exposure of forests to air pollutants. Water, Air, and Soil Pollution 116:5-32. IPCC. 2007. Climate Change 2007: Synthesis Report. Contribution of Working Groups I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, Pachauri, R.K and Reisinger, A. (eds.)]. IPCC, Geneva, Switzerland. Jouquet P., J. Dauber, J. Lagerlof, P. Lavelle, and M. Lepage. 2006. Soil invertebrates as ecosystem engineers: Intended and accidental effects on soil and feedback loops. Applied Soil Ecology 32:153-164. MacMahon J. A., J. F. Mull, and T. O. Crist. 2000. Harvester ants (Pogonomyrmex spp.): Their community and ecosystem influences. Annual Review of Ecology & Systematics 31:265-291. McCullough D. G., R. A. Werner, and D. Neumann. 1998. Fire and insects in northern and boreal forests of North America. Annual Review of Entomology 43:107-127. Moore J. W. 2006. Animal ecosystem engineers in streams. Bioscience 56:237-246. Regniere J., V. Nealis, and K. Porter. 2009. Climate suitability and management of the gypsy moth invasion into Canada. Biological Invasions 11:135-148. Roland J. 1993. Large-scale forest fragmentation increases the duration of tent caterpillar outbreaks. Oecologia 93:25-30. 160 Worm B., E. B. Barbier, N. Beaumont, J. E. Duffy, C. Folke, B. S. Halpern, J. B. C. Jackson, H. K. Lotze, F. Micheli, S. R. Palumbi, E. Sala, K. A. Selkoe, J. J. Stachowicz, and R. Watson. 2006. Impacts of biodiversity loss on ocean ecosystem services. Science 314: 787-790. 161 APPENDIX A Model code from Netlogo. patches-own [ patchEnergy patchdiff lagTime eatenNow ] breed [ caterpillars caterpillar ] breed [ parasitoids parasitoid ] breed [ disturbances disturbance ] caterpillars-own [ energy age ] parasitoids-own [energy age ] disturbances-own [energy age ] globals [ tickers numDead numEaten ] to setup clear-all import-world "Model 9 world.csv" ;this is a map of Ontario with 50 parasitoids and 180 caterpillars dispersed within ;the outbreak range of FTC (Fig. A.l) 162 rearrange colours since the map has numerous shades ask caterpillars [ set shape "bug" set color yellow ] ask turtles [ set energy random 5 ] ask parasitoids [ set shape "plant small" set color 12 ] ask turtles [ set age random 3 ] ask patches [ set lagTime 0 set eatenNow 0 ] end to go set numDead 0 set numEaten 0 ask patches [ set eatenNow 0 ] revitalize ask caterpillars [ move-cat eat-tree birth-death-cat oldage ] ask parasitoids [ move-para eat-caterpillar birth-death-para oldage] update-plot if tickers >= 550 [ stop ] set tickers (tickers +1) ask turtles [ set age age + 1 ] 163 end to move-cat let currentspot patch-here let proximity count patches in-radius 5 with [pcolor = blue] rt random 50 It random 50 if proximity >= 1 [fd random CatDisperseStress ] if proximity = 0 [fd random CatDisperseNoStress] set energy energy - 1 if pcolor > 55 or pcolor <51 [move-to currentspot] end to move-para let currentspot patch-here let proximity count patches in-radius 5 with [pcolor = blue] rt random 50 It random 50 164 if proximity >= 1 [fd random ParaDisperseStress ] if proximity = 0 [fd random ParaDisperseNoStress] set energy energy - 1 if pcolor > 55 or pcolor <51 [move-to currentspot] end to revitalize ask patches [ if pcolor = 51 and lagTime < TreeLag [ set lagTime lagTime + 1 ] if (pcolor <55 and pcolor >51 ) or (pcolor = 51 and lagTime >= TreeLag ) [ set patchEnergy patchEnergy + 1 set pcolor patchEnergy set patchdiff patchenergy - 51 set lagTime 0 ] ] end to eat-tree if pcolor < 56 and pcolor >51 [set patchEnergy patchEnergy - 1 set pcolor patchEnergy set patchdiff patchenergy - 51 set energy energy + patchdiff if eatenNow = 0 [ set numEaten numEaten + 1 set eatenNow eatenNow + 1] ] if pcolor <51 [set energy energy - 1 ] end 165 to eat-caterpillar let maxSaturation 0 let prey caterpillars in-radius 5 let countprey count prey let proximity count patches in-radius 5 with [pcolor = blue] ifelse countprey < 50 [ set maxSaturation countprey ] [ set maxSaturation 50 ] If proximity >= 1 [ ifelse countprey < ParaClutchStress [ set maxSaturation countprey ] [ set maxSaturation ParaClutchStress ] ask n-of maxSaturation prey [ if random 100 < ParaEfficientStress [ set breed parasitoids set numDead numDead + 1 set color 12 set energy random 4 set age 0 if random 100 <50 [die] ]]] If proximity = 0 [ ifelse countprey < ParaClutchNoStress [ set maxSaturation countprey ] [ set maxSaturation ParaClutchNoStress ] ask n-of maxSaturation prey [ if random 100 < ParaEfficientNoStress [ 166 set breed parasitoids set numDead numDead + 1 set color 12 set energy random 4 set age 0 if random 100 <50 [die] ]]] end to birth-death-cat let proximity count patches in-radius 5 with [pcolor = blue] if proximity >= 1 [ if energy > 4 [ set energy energy / 2 set age 0 hatch CatHatchStress [ rt random-float 360 fd random 2 ] set color 45 set energy random 4 set age 0 ] ] if proximity = 0 [ if energy > 4 [ set energy energy / 2 set age 0 hatch CatHatchNoStress [ rt random-float 360 fd random 2 ] set color 45 set energy random 4 set age 0 ] ] if energy < 1 [ die ] 167 end to birth-death-para let proximity count patches in-radius 5 with [pcolor = blue] if proximity >= 1 [ if random 100 < ParaDeathStress [ die] ] if proximity = 0 [ if random 100 < ParaDeathNoStress [ die] ] end to oldage if age > 1 [ die ] end to update-plot set-current-plot "defoliation" set-current-plot-pen "defoliated" plot (count patches with [ pcolor > 50 and pcolor < 55 ] / count patches with [pcolor > 15 and pcolor < 130]) * 100 168 set-current-plot "defoliation2" set-current-plot-pen "defoliated2" plot (numEaten / count patches with [pcolor >15 and pcolor < 130 ]) * 100 set-current-plot "caterpillar" set-current-plot-pen "caterpillars" plot count caterpillars set-current-plot "killed" set-current-plot-pen "killeds" plot numDead set-current-plot "parasitoid" set-current-plot-pen "paraPop" plot count parasitoids set-current-plot "Northwest Defoliation" set-current-plot-pen "northwest" 169 plot count patches with [ pcolor > 50 and pcolor < 55 and pxcor < -15 ] set-current-plot "Northeast Defoliation" set-current-plot-pen "northeast" plot count patches with [ pcolor > 50 and pcolor < 55 and pxcor > -14 and pxcor < 12 ] set-current-plot "Southeast Defoliation" set-current-plot-pen "southeast" plot count patches with [ pcolor > 50 and pcolor < 55 and pxcor > 12 ] set-current-plot "roaddefoliation" set-current-plot-pen "roaddefoliation" plot count patches with [ pcolor >50 and pcolor <55 and count patches in-radius 5 with [pcolor = blue] > 1 ] ;plots are shown on the model interface (Figure A.2) end 170 Figure A.l. Initial setup of the simulation model showing the map of Ontario outline with the range of past FTC outbreaks (grey), caterpillars (dark grey squares) and parasitoids (black squares). 171 ii i BH^^ ticks: 0 Saup • §o j. VatcRoids „< — 5 J CatOispcrseStress 2 i Pirapi t pe r 5 eS tres s 1 j : n.z CatDisperseNoSu... 2 ! ParaDisperseNoStresas Par aDeathS tress 40 1 Parasitoid Northwes t Defoliation Northeast Defoliation Southeas t Defoliation 10 10 10 10 0 0 0 0 0 10 0 10 0 10 0 10 RoadDefoSiaticsi killed Defoliation? 10 10 10 10 10 Figure A.2. Netlogo interface showing how parameters may be altered by the user while the output may be monitored immediately on the lower graphs. 172