Understanding How Life-History Traits and Environmental Gradients Structure Diversity

Understanding how life-history traits and environmental gradients structure diversity

Natalie Tamara Jones

A thesis submitted in conformity with the requirements for the degree of Doctor of Philosophy

Department of Ecology and Evolutionary Biology University of Toronto

Understanding how life-history traits and environmental gradients structure diversity

Natalie T. Jones

Doctor of Philosophy

Department of Ecology and Evolutionary Biology

University of Toronto

2016

Abstract

Determining how diversity is distributed through space and time is a fundamental goal of ecology. My research tested how species’ life-history traits structure diversity at landscape and broader scales and over time. I first asked how traits related to seed dispersal shape plant diversity in a naturally fragmented landscape by testing the relationship between diversity and patch characteristics (size and isolation) for species with different dispersal modes. Dispersal mode altered outcomes predicted from theory ‒ while fragment isolation had a negative effect on wind-dispersed species, it did not influence the diversity of animal-dispersed species. I then examined how zooplankton traits (body size and dormancy) correlate with species distributions at a large scale using lakes across an 1800 km north-south gradient in western Canada. Despite predictions that body size should decrease with latitude and low temperatures, I found only weak evidence for any effect of latitude on inter- and intraspecific body size. Zooplankton dormancy dynamics are virtually impossible to test through sampling, yet dormancy underpins seasonal fluctuations in abundance and long term persistence, and it is expected to vary with climate. I therefore used an experimental approach to test how temperature and photoperiod affect hatching rates of dormant eggs from lakes across the latitudinal gradient. My results suggest that mismatches between temperature and photoperiod, as predicted to result from climate change, could drive latitude-dependent shifts in zooplankton emergence. Finally, I examined the temporal stability of diversity across the same latitudinal gradient by examining species

ii colonization and extinction over 50 years. I found that low-latitude communities are increasingly diverse and comprised of small-bodied species despite more rapid temperature change at higher latitudes. Overall, my research has implications for how global changes, such as fragmentation and climate change, alter diversity by changing the viability of specific life-history strategies.

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Acknowledgments

The completion of this thesis was accomplished with the assistance of many people.

First and foremost, I thank my supervisor, Benjamin Gilbert. Ben has been a wonderful mentor, editor, constructive critic, sounding board all for which I am truly grateful. Ben was patient and generous with his time and challenged me to mature as a researcher. His sage advice and thoughtful perspective greatly improved this thesis. I continue to learn from Ben every day and consider myself incredibly fortunate to have had the opportunity to be his first doctoral student. I have no doubt that Ben will continue to find creative ways to tackle the big questions in ecology.

In the Gilbert lab I found a group of lifelong friends. I can’t imagine a more fun and supportive group of people to work with; together we laughed and commiserated, sharing the highs and lows of graduate school. Each member has a unique approach to science and life that has influenced my perspective. I am particularly indebted to Rachel Germain, who I have worked with for my entire tenure at UofT. Rachel continues to impress me every day with her ecological knowledge, problem solving skills and perspective on academia and life outside it. Tess Grainger is an excellent researcher and was an incredible addition to the lab. Tess taught me the importance of preparation, realistic expectations and being direct. Rachel and Tess are truly mentors to me. Kelly Carscadden became a wonderful friend and has taught me much about hard work and perseverance. Finally, Denon Start brought a youthful exuberance to the lab; his positive energy and cleverness is a pleasure to be around. All members have helped me to become a better scientist.

The EEB department at large both past and present has had an incredible impact on me. I have seen countless inspirational talks and had many discussions with the people working in EEB. I learnt a great deal from discussions with the Jackson and Krkosek labs. As committee members, Don Jackson and Megan Frederickson offered guidance that was very helpful over the years. I have made many wonderful friends. In particular, Alex De Serrano, Nicholas Mirotchnick, Frances Hauser and Jane Ogilvie have enriched my time at UofT.

This work could not have been completed without the tireless help of dedicated undergraduate students at the University of Toronto and beyond. Alexandra Barany, Ewelina Chojecka, Nathan

Lo, Patrick Beh, Jillian Moran and Veronica Jones were invaluable and approached the tedium of ecological lab and field work with a sense of humor and tenacity that was much appreciated.

Many staff members in EEB and CSB provided technical support for my research. Donna Wheeler, Jim Dix, Trung Luu, Bruce Hall and Andrew Petrie lent equipment, constructed experimental gear and fixed growth chambers for my projects. Kitty Lam and Helen Rodd were very helpful over the years. Helen in particular always put students first and does everything she can to help us succeed.

Andrew MacDougall and Lyn Baldwin were early mentors to me. They both helped me cultivate a love of plant ecology and natural history. There is no doubt that without their thoughtful supervision I would not have been inspired to pursue a PhD.

I could not have completed this work without the unwavering support of my family, especially my partner Scott Forster, who has been my best friend and cheerleader throughout the entire process. My siblings are a constant source of inspiration for me. Gwyneth has attended talks I have given and was my roommate for the first two years of my PhD. Her opinion was important to me during the early years of my dissertation. Veronica never ceases to amaze me with her cleverness and kind spirit. My brother Brendan has been in Toronto for the last year of my PhD and being in the same city as him for the first time in 20 years was an amazing bonus.

Beyond EEB I have been lucky to become friends with an amazing cast of characters; we have had many wonderful adventures over the years. Christina Doris, Elysse Schlein, Asher Miller and Linda Naccarato are amazing friends and I can’t wait to see what lies ahead for all of them.

This research was generously supported by Ontario Graduate Scholarships and fellowships from the University of Toronto and the Department of Ecology and Evolutionary Biology.

Table of Contents

Acknowledgments...... iv

List of Tables ...... x

List of Figures ...... xi

List of Appendices ...... xiii

CHAPTER 1 ...... 1

GENERAL INTRODUCTION ...... 1

Spatially structured landscapes ...... 2

Traits that affect dispersal rates ...... 2

The effect of temperature on traits that influence dispersal ...... 3

Dormancy, climate & dispersal through time ...... 4

Latitude & community stability ...... 5

Thesis overview ...... 6

Literature cited ...... 7

CHAPTER 2 ...... 12

DISPERSAL MODE MEDIATES THE EFFECT OF PATCH SIZE AND PATCH CONNECTIVITY ON METACOMMUNITY DIVERSITY… ...... 12

Abstract ...... 12

Introduction ...... 13

Materials & methods ...... 16

Study site & species sampling ...... 16

Data analyses ...... 19

Results ...... 22

Discussion ...... 29

Acknowledgments ...... 32

Literature cited ...... 33

CHAPTER 3 ...... 38

ARE SPECIES LARGER AT HIGH LATITUDES? TESTING LATITUDE-BODY SIZE RELATIONSHIPS IN ZOOPLANKTON ...... 38

Abstract ...... 38

Introduction ...... 39

Materials & methods ...... 41

Study species & species sampling ...... 41

Environmental covariates...... 42

Body size measurements ...... 42

Statistical analysis ...... 43

Results ...... 44

Discussion ...... 50

Acknowledgments ...... 53

Literature cited ...... 53

CHAPTER 4 ...... 57

CHANGING CLIMATE CUES DIFFERENTIALLY ALTER ZOOPLANKTON DORMANCY DYNAMICS ACROSS LATITUDE ...... 57

Abstract ...... 57

Introduction ...... 58

Materials & methods ...... 61

Sample collection & experimental design ...... 61

Data analyses ...... 65

Results ...... 67

Zooplankton eggs ...... 67

Phenology ...... 68 vii

Hatchling Diversity ...... 71

Discussion ...... 73

Acknowledgments ...... 77

Literature cited ...... 78

CHAPTER 5 ...... 83

GEOGRAPHIC SIGNATURES IN SPECIES TURNOVER: DECOUPLING COLONIZATION AND EXTINCTION ACROSS A LATITUDINAL GRADIENT ...... 83

Abstract ...... 83

Introduction ...... 84

Materials & methods ...... 87

Study system & species sampling ...... 87

Data analyses ...... 88

Results ...... 90

Discussion ...... 94

Acknowledgments ...... 97

Literature Cited ...... 98

CHAPTER 6 ...... 103

GENERAL CONCLUSION ...... 103

Chapter 2 ...... 103

Significance...... 103

Future directions ...... 103

Chapter 3 ...... 105

Significance...... 105

Future directions ...... 105

Chapter 4 ...... 106

Significance...... 106

viii

Future directions ...... 106

Chapter 5 ...... 107

Significance...... 107

Future directions ...... 107

Conclusion ...... 107

Literature cited ...... 108

List of Tables

Table 2.1 Effects of stand size and connectivity on log-transformed species richness. ‘All species’ includes all aspen-associated species from the three dispersal mode groups...... 27

Table 2.2 Effects of stand size and stand connectivity on species composition (axis 1 and 2 scores of PCoA using Jaccard dissimilarity coefficient) by dispersal mode...... 28

Table 3.1 Summary of latitudinal extremes and the body size of each species given by the model fit. Body size values were back transformed from the predicted values that were generated from the linear model on log-transformed body size. P-values less than 0.05 are highlighted in bold, and those less than 0.1 are highlighted with italics...... 46

Table 3.2 Results of log likelihood tests for the final model that includes latitude as well as additional environmental variables that were significantly associated with zooplankton body size in a separate linear mixed model. Table headings are: degrees of freedom (Df) and log-likelihood ratio (LRT)...... 47

Table 3.3 The number of species that significantly increased or decreased in body size with latitude, temperature or other environmental variables when tested in isolation...... 48

List of Figures

Figure 2.2 The effect of stand size and stand connectivity on species richness when all aspen- associated species are grouped together (top panels) and for each dispersal group considered separately. Species richness values were adjusted to account for the other factor in the model (size or connectivity) whenever that factor was significant...... 24

Figure 2.3 The effect of (a) stand size and (b) connectivity on the relative representation of species belonging to each dispersal mode group from a PCoA using the Bray-Curtis coefficient. We only display the stand characteristic-axis score combinations that were significantly correlated...... 25

Figure 2.4 Evidence for the role of competition but not herbivory in mediating relationships between the stand characteristics and species richness. (a) The observed degree of negative covariances in species richness between dispersal mode groups (solid line) compared to a null distribution of random outcomes...... 26

Figure 3.1 Plots of the slope (points) and 95% bootstrapped confidence intervals (lines). Lines that do not overlap with zero are significantly associated with (a) latitude or (b) temperature.... 45

Figure 4.1 Map displaying the location of the 25 lakes in western Canada that were sampled for sediment in July 2011...... 62

Figure 4.2 The relationship between latitude and the egg abundance of cladocerans (light grey), copepods (dark grey) and rotifers (black). Eggs were isolated from 100 grams of lake sediment using the sugar flotation method (see methods)...... 67

Figure 4.3 The effect of temperature (8°C; grey and 12°C; black) on the average number of days until the first individual (‘First’; circles) and half (‘50%’; triangles) of all individuals from each taxon hatch...... 68

Figure 5.1 Latitudinal patterns of diversity and temperature change. (a) Locations of the 43 lakes in this study; (b) the change in temperature over 70 years, based on differences (present – past)

xi of 30 years means: 1971 to 2000 – 1901 to 1930; (c) Species composition of zooplankton (first axis from a Nonmetric Multidimensional Scaling with a 2D solution [stress = 0.19] based on Sorensen dissimilarity), illustrating that closer sites are more compositionally similar; and (d) Zooplankton species richness with latitude...... 91

xii

List of Appendices

Appendix A: Supplementary information for Chapter 2 ...... 111

Model Fitting ...... 121

Appendix B: Supplementary information for Chapter 3...... 123

Appendix C: Supplementary information for Chapter 4...... 132

Literature cited ...... 148

Appendix D: Supplementary information for Chapter 5 ...... 149

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Chapter 1 General Introduction

“…the problem of pattern and scale is the central problem in ecology, unifying population biology and ecosystem science, and marrying basic and applied ecology… there is no single natural scale at which ecological phenomena should be studied; systems generally show characteristic variability on a range of spatial, temporal, and organizational scales.” (Levin 1992).

In the 1989 MacArthur Award lecture for the Ecological Society of America, Simon Levin argued that understanding ecological processes and patterns across spatial and temporal scales is among the largest challenges facing ecologists (Levin 1992). At landscape scales, for example, diversity patterns are hypothesized to be mainly influenced by environmental heterogeneity and metapopulation processes, whereas climatic gradients and the history of speciation may largely influence diversity at macro-ecological scales (Rosenzweig 1995). Across temporal scales, similar shifts in the importance of different factors also likely occur as environmental fluctuations over the short term give way to shifts in mean climatic conditions (Rosenzweig 1995; Wolkovich et al. 2014). Understanding spatial and temporal patterns of diversity, and their reliance on environmental heterogeneity, is becoming increasingly important in the Anthropocene, as environmental changes become increasingly common (Helmus, Mahler & Losos 2014; Wolkovich et al. 2014).

In this thesis, I examine how species traits and species responses to environmental conditions structure distributions at different spatial and temporal scales. At the landscape scale, I ask how traits related to dispersal (dispersal mode of plants) and responses to the environment structure diversity in natural habitat fragments. At a much larger spatial scale that spans 14° latitude (approx. 1800 km), I test the hypothesis that zooplankton life history traits vary with temperature and photoperiod, causing distinct ecological dynamics across this gradient. Finally, I use historical data collected at this larger scale to test how temporal dynamics differ across latitudes.

Considering species diversity at these different spatial and temporal scales requires integration of a number of concepts that are often considered separately in ecology, such as the links between

CHAPTER 1: GENERAL INTRODUCTION

dispersal-related traits, temperature, body size and dormancy. In what follows, I outline specific links in chapters two through five, and provide a brief overview of some of the concepts that I address in more detail in those chapters. I conclude the introduction with a concise overview of the subsequent chapters.

Spatially structured landscapes

The spatial tapestry linking biological communities underlies the diversity we see in nature. Many communities are not contiguous and instead rely on dispersal to connect local habitat patches (Wilson 1992). At the regional scale, the diversity of these so called ‘metacommunities’, is related to patch size and connectivity (Holyoak, Leibold & Holt 2005), which influences the colonization and extinction dynamics of local patches. Larger sites are able to support more species because higher colonization rates in combination with larger population sizes render species less vulnerable to extinction (MacArthur & Wilson 1967; Holt 1993; Leibold et al. 2004). At the same time, the proximity of patches to each other influences the rate that individuals colonize sites, thereby affecting diversity (Chisholm, Lindo & Gonzalez 2011; Gilbert 2012). Higher connectivity of patches in close proximity may thus promote persistence of many species, but can also limit the opportunity for species to find spatial refuge from predators or superior competitors (Leibold et al. 2004). In the last twenty years, much effort has been invested into clarifying how patch size and connectivity alter diversity, but more recently researchers have begun to consider how the asymmetric dispersal ability of co-occurring species can alter the magnitude of movement among patches, thereby influencing local and regional species composition (Chisholm et al. 2011; Haegeman & Loreau 2014).

Traits that affect dispersal rates

Interspecific differences in dispersal ability affect coexistence and diversity in local communities (Leibold et al. 2004; Holyoak et al. 2005). For any given assemblage of species, co-occurring individuals at the same trophic level often show remarkable differences in traits that influence dispersal (Howe & Smallwood 1982; De Bie et al. 2012). Adaptations that enhance movement between patches cause differences in the probability that a species will colonize a new site. Despite widespread recognition of the variation in dispersal ability, many experiments remove dispersal differences by controlling movement of all species in an identical way (Cadotte 2006;

2 CHAPTER 1: GENERAL INTRODUCTION

Howeth & Leibold 2010; Declerck et al. 2013), obscuring realistic tests of the effect of dispersal on metacommunity dynamics.

Traits associated with dispersal may be especially important for passively dispersed species, as they do not have behavioral adaptations that can influence colonization of new sites. For example, morphological adaptations in seeds have long been recognized to increase how far and how often plants colonize sites. Several classes of adaptations can be categorized into different syndromes that reflect adaptations to a variety of dispersal vectors such as wind, water or animals (Howe & Smallwood 1982). For passively dispersed animal species, adult body size directly influences colonization dynamics (Vanschoenwinkel et al. 2008). However, unlike with active dispersers, dispersal distance is negatively associated with body size, with smaller individuals travelling further and more often (Soons et al. 2008; De Bie et al. 2012). The range of dispersal propensities for species within a site suggests that the effect of patch size and connectivity will differ among species; species with no dispersal aid are likely to be more strongly associated with patch size and connectivity than species with adaptations to water, wind or animal dispersal. Similarly, habitat selection by animals that move seeds could alter the relationship between patch size and diversity if animal vectors prefer larger patches (Levey et al. 2005; Nathan et al. 2008; Evans et al. 2012). Focusing on patterns of diversity separately for species with different dispersal traits may reveal unique relationships between patch size or connectivity and diversity (Vanschoenwinkel, Buschke & Brendonck 2013).

The effect of temperature on traits that influence dispersal

The abiotic environment can affect traits that influence dispersal. The body size of organisms is often associated with latitude and temperature (Gillooly & Dodson 2000), with larger bodied species and individuals typically found at colder sites characteristic of more polar latitudes. This pattern has been generalized with three ecological rules: “Bergmann’s rule”, “James’ rule” and the “Temperature-size rule” (Mayr 1956; James 1970; Atkinson 1994). Recently, climate change has reignited interest in body size-latitude relationships. To date, there is no universally agreed upon mechanism for this pattern (Blackburn, Gaston & Loder 1999; Watt, Mitchell & Salewski 2010), however, scientists agree that temperature has a putative effect on body size. Geographical clines in body size for some taxa, along with the observation that temperature increases frequently cause a reduction in the average body size of many organisms (Atkinson

3 CHAPTER 1: GENERAL INTRODUCTION

1994; Daufresne, Lengfellner & Sommer 2009), suggest that the direct effect of temperature on body size could indirectly increase dispersal rates for passively dispersed species, and that these effects will have a spatial component due to different rates of temperature change with latitude.

Dormancy, climate & dispersal through time

In addition to dispersing to new sites, organisms inhabiting variable environments often evolve life-history strategies to persist in situ despite temporal fluctuations in habitat quality (Cohen 1968; Venable & Brown 1988). Many short-lived organisms produce dormant propagules such as eggs, seeds and cysts, that are characterized by reduced metabolic rate and halted development; these dormant propagules remain viable when active individuals would not survive (Tauber, Tauber & Masaki 1986). Dormant life-stages act as a bet hedging strategy by enabling persistence during unfavourable environmental conditions (Hairston, Hansen & Schaffner 2000; Hairston & Kearns 2002; Brendonck & Meester 2003). This strategy is often referred to as “temporal dispersal”. Prolonged dormant phases allow species to persist through unfavourable years but only at the expense of decreased population growth in favourable years (Venable & Brown 1988). The strategy of decreasing the mean and variance of population growth in order to persist over the long-term is likely to be more important in cold, stressful environments (Mousseau & Roff 1989; Molina-Montenegro & Naya 2012).

Many zooplankton species exhibit prolonged dormancy by forming an ‘egg bank’, or accumulating resting eggs in lake sediment (Hairston & Cáceres 1996). Relatively little is known about the dormancy dynamics of aquatic zooplankton (Hairston and Kearns 2012), despite a well-developed literature on dormancy in other organisms (Cohen 1968; Venable & Lawlor 1980; Venable & Brown 1988). However, temperature and day length appear to be the most important cue for the termination of dormancy in zooplankton (Gyllström & Hansson 2004; Vandekerkhove, Declerck & Brendonck 2005; Davidson et al. 2006; Schalau et al. 2008; Dupuis & Hann 2009; Angeler 2011).

Different environments favour distinct dormancy strategies, which results in variation in the prevalence of strategies across environmental gradients (Cohen 1968; Stearns 1992). Dormancy is predicted to be more important for population persistence in environments that have greater seasonal variation and shorter growing seasons. For example, the prevalence of prolonged

4 CHAPTER 1: GENERAL INTRODUCTION

dormancy has been found to increase at higher latitudes in some terrestrial invertebrates (Mousseau & Roff 1989) and marine copepods (Marcus & Lutz 1998). Nonetheless, little is known about the latitudinal distribution of zooplankton egg banks, and their dormancy dynamics, in aquatic systems (Vandekerkhove et al. 2005). This is because prior studies have either assessed emergence dynamics in a small number of lakes within a region (Cáceres 1997; Cáceres & Tessier 2003; Dupuis & Hann 2009), or collected egg banks from across a latitudinal gradient, but combined the samples into regional mixtures (Vandekerkhove et al. 2005), thus preventing an analysis of how hatching dynamics vary across a latitudinal gradient. By collecting sediment from across a latitudinal gradient, which naturally varies in temperature and growing season length, it may be possible to determine how sensitivity to hatching cues differ across a latitudinal gradient highlighting spatial variation in the contribution of the egg bank to community composition.

Latitude & community stability

The links between temperature, dispersal and dormancy are particularly important in the Anthropocene because they are expected to influence how latitudinal diversity patterns change through time and how they are being altered by global climate change. Scientists have predicted and observed differential warming across latitudes, with more warming occurring toward the poles (IPCC 2013). This pattern suggests that temperature-related traits that differ among species may cause shifts in the identity and abundances of species within communities, and that these shifts may be larger towards the poles. Species diversity also has a consistent pattern with latitude, with the vast majority of taxonomic groups having lower diversity at higher latitudes. This gradient in diversity may also cause larger changes at higher latitudes, as predicted by two hypotheses in community ecology. First, because species diversity is positively correlated with phenotypic variation, elevated diversity could reduce the opportunities for new species to establish even when they are no longer limited by climate (Elton 1958).

Second, diversity stabilizes food webs when they increase the number of weak interactions, as is typical in most food webs (McCann et al., 1998). To date, support for the positive effects of diversity on stability and resistance to new species has been mixed (May 1972; Levine & D’Antonio 1999; McCann 2000; Gilbert & Lechowicz 2005; Belote et al. 2008; Adrian et al. 2010; Clark & Johnston 2011). Further research that relates the degree of diversity to the

5 CHAPTER 1: GENERAL INTRODUCTION

magnitude of community change in natural systems is necessary to predict future shifts; currently there is limited evidence documenting a greater vulnerability in northern regions despite differences in diversity and temperature changes, but this may be due to a lack of long-term studies across broad spatial gradients (Heino, Virkkala & Toivonen 2009).

Thesis overview

In my thesis, I sample natural communities and conduct experiments to assess the role of species traits in structuring diversity at regional and broader spatial scales, and to determine whether temporal turnover in species varies across large spatial scales. In chapter 2, I employ a metacommunity framework to test how the dispersal mode of plants alters the effect of patch size and connectivity on diversity. For the subsequent chapters, I focus on zooplankton from lakes across a broad latitudinal gradient to address inter-related questions about temperature, species traits and latitudinal distributions. In chapter 3, I determine if latitudinal patterns in zooplankton body size, both within and among species, are consistent with macroecological hypotheses (James’ rule, Bergmann’s rule). Chapter 4 focuses on zooplankton egg banks across latitudes and experimentally isolates the effects of two climatic cues that break dormancy: temperature and day length. These cues are being modified by climate change, however we lack studies that test how the interactive effects of these cues will alter dormancy dynamics, and especially whether their effects depend on the latitude of the zooplankton communities. Finally, in chapter 5 I take advantage of the historical sampling of lakes in western Canada to compare contemporary and historic (40+ years) samples. I use this comparison to determine how zooplankton communities are changing, if these changes vary with latitude, the degree to which changes are driven by local extinctions versus colonization of new lakes, and how species traits such as body size mediate these changes. I conclude in chapter 6 with a summary of this work and highlight questions raised by my findings.

All of these chapters are written as stand-alone research papers. As a result there is some repetition in the Introductions and Methods sections. Benjamin Gilbert contributed substantially to all of the research chapters presented in this thesis. Chapter 2 was a collaboration with Rachel Germain, Tess Grainger, Aaron Hall and Lyn Baldwin. Chapter 3 was conducted in collaboration with Jillian Moran, a fourth year undergraduate student in EEB that I mentored. Chapter 3 is in preparation to be sent to Plos One and chapter 5 is currently in review at Global Ecology and

6 CHAPTER 1: GENERAL INTRODUCTION

Biogeography. Chapters 2 and 4 are published and have been included in this thesis with permission from the publishers, the citations are as follows:

Jones, N.T., Germain, R.M., Grainger, T.N., Hall, A., Baldwin, L. & Gilbert, B. (2015) Dispersal mode mediates the effect of patch size and patch connectivity on metacommunity diversity. Journal of Ecology, 103, 936–944.

Jones, N.T. & Gilbert, B. (2016) Changing climate cues differentially alter zooplankton dormancy dynamics across latitudes. The Journal of Animal Ecology, 85, 559–569.

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Chapter 2 Dispersal mode mediates the effect of patch size and patch connectivity on metacommunity diversity

Published as Jones, N. T., R. M. Germain, T. N. Grainger, A. Hall, L. Baldwin, & B. Gilbert. 2015. Dispersal mode mediates the effect of patch size and patch connectivity on metacommunity diversity. Journal of Ecology 103:934-943.

Abstract

Metacommunity theory predicts that increasing patch size and patch connectivity can alter local species diversity by affecting either colonization rates, extinction rates, or both. Although species’ dispersal abilities or ‘dispersal mode’ (e.g., gravity, wind, or animal dispersed seeds) can mediate the effects of patch size and connectivity on diversity, these important factors are frequently overlooked in empirical metacommunity work. We use a natural metacommunity of aspen stands within a grassland matrix to determine whether dispersal mode alters the influence of stand size and connectivity on understorey plant diversity. We sampled the same area in each patch, controlled for the presence of matrix species in aspen stands, and tested for the effects of size, connectivity, and dispersal mode on metacommunity richness. Because dispersal groups responded differently to patch size and connectivity, we created a null model and assessed ungulate activity to explore whether competitive dynamics or herbivory were driving diversity patterns. Animal-dispersed species and species with no dispersal aid had higher diversity per unit area in larger stands, likely because large stands can both support larger populations that are less prone to extinction and may also attract seed-dispersing animals such as birds and small mammals that are sensitive to edge effects. Consistent with other empirical work, we found a positive relationship between diversity and connectivity for wind-dispersed species. However, we detected a negative effect of stand connectivity on the diversity of species with no dispersal aid, possibly due to the presence of other highly competitive species groups dominating well- connected patches, as our null model results suggest. We found no evidence for higher ungulate activity in highly connected patches, suggesting that herbivory may not be driving the decline in diversity of plants with no dispersal aid. Overall, we see a positive effect of stand area on diversity for most groups despite sampling equal area in all stands, which is a prediction of

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metacommunity theory that is normally overlooked. Our results demonstrate the importance of considering variation in the dispersal modes of focal species in explaining the diversity patterns in natural metacommunities.

Introduction

Biological communities rarely occur in complete isolation, but instead often exist as part of a ‘metacommunity’ of local patches connected by dispersal (Wilson 1992). Island and pond systems are classic examples of metacommunities (Simberloff & Wilson 1970), as are other distinct assemblages of organisms that occur in patchily-distributed habitats. The metacommunity paradigm, based on concepts from metapopulation and island biogeography theories, was developed to understand the mechanisms that maintain species diversity in patchy landscapes (Leibold et al. 2004). Several classes of metacommunity dynamics have been identified, all of which recognize the importance of extinction and colonization dynamics of species within and among patches for explaining local and regional diversity patterns (Leibold et al. 2004). Recent theoretical and empirical work has focused on determining how factors that alter the extinction and colonization rates of species within metacommunities scale up to alter local and regional diversity (Altermatt, Schreiber & Holyoak 2011; Haegeman & Loreau 2014; LeCraw, Srivastava & Romero 2014).

Patch size and connectivity (inter-patch distance) both affect colonization and extinction dynamics and are predicted to be important drivers of diversity patterns in metacommunities (Holyoak et al. 2005). Larger patches can support a greater number of species per unit area, as higher colonization rates combined with larger population sizes that are less vulnerable to extinction result in an increase in the ratio of colonization to extinction rate (MacArthur & Wilson 1967; Holt 1993; Leibold et al. 2004). Similarly, by influencing the rate at which species move between patches, patch connectivity can strongly affect local diversity; this phenomenon has recently been demonstrated in both theoretical models (Pillai, Gonzalez & Loreau 2011; Gilbert 2012; Haegeman & Loreau 2014) and empirical studies (Howeth & Leibold 2010; Matthiessen, Mielke & Sommer 2010; Chisholm et al. 2011). In metacommunities with poorly- connected patches, local diversity tends to be low because dispersal-limited species cannot reach suitable patches (Cadotte 2006b) or priority effects exclude subsequent colonizers (Levins & 13

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Culver 1971). As patch connectivity increases, local diversity increases as incoming colonists rescue small populations from extinction (Brown & Kodric-Brown 1977). Finally, when dispersal rates are high, diversity can decline if competitively dominant species or generalist predators are able to reach all patches and drive other species locally extinct (Mouquet & Loreau 2003). Empirical studies have detected a variety of relationships between dispersal and diversity; reported relationships are often positive (Warren 1996; Gilbert, Gonzalez & Evans-Freke 1998; Cadotte 2006a; Chase, Burgett & Biro 2010) or hump-shaped (Kneitel & Miller 2003; Matthiessen & Hillebrand 2006; Howeth & Leibold 2010; Vanschoenwinkel et al. 2013), but negative relationships have also been detected (Matthiessen et al. 2010). However, it is difficult to interpret these patterns and draw broader conclusions about the ecological processes shaping natural systems, in part because of the difficulties associated with capturing a biologically relevant range of dispersal rates when dispersal is manipulated experimentally.

One of the most fundamental predictions of metacommunity theory is that interspecific differences in dispersal affect coexistence and diversity (Leibold et al. 2004; Holyoak, Leibold & Holt 2005). Although co-occurring species often differ greatly in dispersal ability (Howe & Smallwood 1982), these differences are often overlooked in experimental studies. For example, most studies manipulate dispersal by transferring a set proportion of a community among patches, thereby removing natural variation in species’ dispersal abilities (Kneitel & Miller 2003; Cadotte, Fortner & Fukami 2006; Howeth & Leibold 2010; Declerck et al. 2013; but see Cadotte 2006a; Limberger & Wickham 2011; Vanschoenwinkel, Buschke & Brendonck 2013; Guelzow, Dirks & Hillebrand 2014). Similarly, seed addition experiments used to test dispersal-diversity relationships often remove dispersal differences among species (Cadotte 2006a). Although these studies have made important advances in testing some aspects of metacommunity theory, the higher tractability associated with homogenizing dispersal rates across species comes at the expense of understanding how natural variation in dispersal abilities can affect the persistence of coexisting species within a metacommunity. Studies that allow differential dispersal rates are underrepresented in the literature (Logue et al. 2011), and are currently biased towards small passively-dispersed organisms inhabiting freshwater ponds (e.g., protists, algae and zooplankton; Louette & De Meester 2005; Vanschoenwinkel, Buschke & Brendonck 2013).

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The manner in which patch size and patch connectivity affect the colonization rates of coexisting species and subsequently shape diversity will depend on species’ traits that affect dispersal. In plants, dispersal differences can manifest through morphological adaptations in seeds, with the seed representing the primary dispersive stage of a plant’s life cycle. These adaptations can be categorized into different dispersal modes or syndromes, reflecting how (and how far) seeds move across the landscape. For example, common dispersal modes in plants include gravitropic dispersal via passive release from the parent plant, dispersal via insects such as ants (myrmecochory), wind dispersal via the presence of a feathery pappus, and vertebrate dispersal via fleshy fruited seeds or burs that are carried by birds or mammals (Howe & Smallwood 1982). Focusing on patterns of diversity separately for species with different dispersal modes can reveal unique relationships between patch size or connectivity and diversity (Vanschoenwinkel, Buschke & Brendonck 2013). For example, species that have no dispersal aid rarely disperse long distances and may be more strongly affected by patch connectivity than animal or wind- dispersed species that can easily reach all sites (Vanschoenwinkel, Buschke & Brendonck 2013). Similarly, habitat selection by animals that move seeds could alter the relationship between patch size and diversity if animal vectors prefer larger patches (Levey et al. 2005; Nathan et al. 2008; Evans et al. 2012). Despite the recognized importance of dispersal for metacommunity dynamics (Mouquet & Loreau 2003; Cadotte 2006b) and the ubiquity of variation in dispersal abilities among co-occurring species (Nathan & Muller-Landau 2000; Muller-Landau 2003; Gilbert, Turkington & Srivastava 2009), the implications of these dispersal differences on metacommunity diversity is only beginning to be tested in natural systems (Löbel, Snäll & Rydin 2009; Hájek et al. 2011; De Bie et al. 2012; Vanschoenwinkel, Buschke & Brendonck 2013).

In this paper, we investigate how patch size and connectivity affects understorey plant diversity in a naturally-patchy landscape of aspen stands. Aspen (Populus spp.) are common tree species in Northern climates, frequently occurring in grassland habitats where they form clonal forest stands with clear boundaries. These stands are naturally-patchy, and support a distinct plant community compared to the surrounding grassland matrix, indicating that aspen-associated understorey species function as a metacommunity. However, unlike pond or island patches, aspen stands have diffuse boundaries, meaning that important spatial dynamics may be swamped

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out by the presence of species that are not constrained to habitat patches in the metacommunity (e.g., generalists; Harrison 1999). How influential the presence of these species on our ability to resolve the dynamics of diffuse metacommunities remains an open question (Leibold et al. 2004).

In Lac Du Bois Provincial Park, British Columbia, Canada, we sampled understorey plant communities in aspen stands that varied in size and connectivity (Fig. 2.1). We sampled the same total area in all stands to remove the confounding effects of species-area relationships in our assessment of species diversity. Species were then categorized into three dispersal syndrome groups based on fruit morphology: no dispersal-aid, wind dispersed, and animal dispersed. We used these data to address four questions: (1) Does stand size and/or connectivity affect understorey plant diversity and species composition? (2) Does dispersal mode mediate these relationships? (3) Are the observed diversity patterns consistent with common ecological processes such as competition or herbivory? (4) How sensitive are our results to the inclusion of generalist and matrix-associated species, a common feature of metacommunities with diffuse boundaries?

Materials & methods

Study site & species sampling

This study was conducted in the high elevation grasslands of Lac Du Bois Provincial Park in the southern interior of British Columbia, Canada (latitude = 50.7007, longitude = -120.4603). The region is semiarid, with hot dry summers and little annual precipitation (279 mm), 27% of which falls as snow (Environment Canada 2014). Aspen (Populus tremuloides) cover ~100-ha of the park and occur primarily on moist, north-facing slopes (Dickinson 1998). They form clonal stands that support a unique flora of understorey plant species compared to the surrounding grassland matrix (Fig. S2.1 in Appendix A: Supplementary information for chapter 2). These stands are relatively undisturbed by humans, and range in age from approximately 24 to 148 years old.

In the summer of 2007, we randomly selected 24 of a total of 110 aspen stands in the park (Fig. 2.1), excluding any stands located within 50 meters of a road. The stands ranged from

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approximately 658 m2 to 37,622 m2 in size. We established a single 10 m × 25 m plot in the center of each stand and recorded the occurrences of all identifiable understorey vascular plant species. This large plot size was selected to capture species diversity at a scale that incorporates a reasonable level of microsite heterogeneity. By using the same plot size in all stands, we standardized sampling intensity and were thus able to assess species richness per unit area to avoid the confounding influence of species-area relationships on our diversity measurements. Although edge effects may be confounded with the size of the patch in our study (and in most naturally patchy ecosystems), we believe that these effects are negligible for two reasons. First, even the smallest stands were almost three times the size of the plot, and second, the abundance of matrix species was generally low (Fig. S2.2).

To confirm that aspen stands support a unique flora and to identify aspen- and matrix-associated species, we also sampled plant diversity in the adjacent grassland matrix. The grassland sampling followed the same sampling protocol as in the aspen stands, with at least one plot placed 25 to 50 m outside of each of the sampled aspen stands (n = 24 total; May & Baldwin 2011). See Data analyses for methods on statistically delineating grassland- and aspen-associated species. Concurrent with the plant survey, we recorded the amount of ungulate scat within our plots, ranked from 0 (none) to 3 (abundant), as a proxy for large herbivore activity (Bailey & Putman 1981; Heinze et al. 2011). Our surveys were conducted in a single year, and thus could not be used to track colonization and extinction as they happened. However, island biogeography theory predicts that the outcome of colonization/extinction dynamics can be inferred, rather than observed directly, from the equilibrium species richness of habitat patches. There was no relationship between species richness and the age of the stands (t1,23 = 0.31, P = 0.763) suggesting that the patterns observed were not driven by differences in time to accumulate species.

We classified all aspen-associated species into three dispersal mode categories based on seed morphology: (1) no dispersal aid [gravitropic, ballistic, or ant dispersal; n = 32]; (2) wind- dispersed [anemochorous; n = 17]; indicated by the presence of a pappus; and, (3) animal- dispersed [bird or large mammal dispersal; n = 18], indicated by the presence of burs or fleshy fruit. We grouped ant-dispersed species into the ‘no dispersal aid’ group because ants move

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seeds at a spatial scale comparable to passive gravitropically- or ballistically-dispersed seeds (Thomson et al. 2011). Only 2 of the 32 species in this dispersal mode category are known to be dispersed by ants.

Figure 2.1 Map of sampled (black; n = 24) and unsampled (grey; n = 86) aspen stands at the Lac Du Bois Provincial Park in the southern interior of British Columbia, Canada (latitude = 50.7007, longitude = -120.4603); both sampled and unsampled stands were included in our calculations of stand connectivity. The matrix habitat was primarily grassland.

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Data analyses

A presence-absence matrix was created for all taxa in the 24 sampled aspen stands and 24 grassland plots. We conducted a principal coordinates analysis (PCoA) using the Jaccard dissimilarity coefficient to identify compositional differences between aspen stands and the surrounding grassland matrix (Fig. S2.1). To identify and remove all species that were not strongly aspen-associated, we calculated the proportion of aspen to grassland plots that each species occurred in, and removed generalist and grassland specialist species that did not occur in aspen stands at least 66% of the time (n = 103 species; Table S2.1). We removed generalists and grassland specialists because only species that occur in favorable focal habitat patches imbedded in a matrix of unfavorable habitat constitute a metacommunity (Cook et al. 2002). We repeated our analyses using less stringent cut-offs (an analysis using all species and another requiring 50% of occurrences to be in aspen stands), and a more stringent cut-off (requiring 75% of occurrences to be in aspen stands). We found that including all species obscured patterns, but that our results were qualitatively similar (Table S2.2) at all other indicator cutoff levels; we therefore report the results generated using the 66% cutoff, which identified 67 aspen-associated species (Table 2.1) but also discuss the sensitivity of our results to the cut-off level that was used.

To calculate stand size and distances among stands, all sampled and unsampled aspen stands were digitized from online basemaps streamed through ArcGIS 10.1 (ESRI.com). The digitized stand locations and shapes were compared with field notes to confirm accuracy. We calculated the area of each stand and then created a matrix of pairwise Euclidian distances between all stands based on edge-to-edge distances, which were then used in the connectivity function described below.

Our model for incorporating stand size and connectivity came from a plant metapopulation model where the expected occupancy per species increases monotonically with the ratio of colonization (C) to extinction (E) rates. When summed across weakly interacting species, this relationship predicts that species richness per unit area (S) in stand i increases with this ratio:

S~Ci/Ei. Using a logarithmic transformation, this equation becomes:

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log(Si) ~ log(Ci) – log(Ei). The second of these terms, the probability of extinction (E) in stand i, is a decreasing function of stand area, and is often modeled as inversely related to area. The other term, colonization (C), is an increasing function of stand connectivity. We used a metapopulation approach (Hanski 1994; Gilbert & Levine 2013) for calculating the connectivity of a stand that incorporates the distance between stand i and all other j stands, and combined this with extinction to predict species richness per unit area:

푛

−푑푖푗/훼 푙표푔(푆푖) = 푖푛푡푒푟푐푒푝푡 + 푏1 푙표푔 ∑(푒 ) + 푏2 푙표푔(퐴푟푒푎푖) + 휀푖 푗≠푖 (1)

Where S is the species richness per unit area at site i, and ɛ is a normally distributed error term. The variable d is the distance between any two sites; the summation incorporates distances from all other sites. Our connectivity measure (the summation term in eqn. 1) uses the standard assumption of an exponential dispersal curve with a mean dispersal distance, α. As a result, connectivity between site i and j decreases at greater distances (dij) and increases with greater dispersal ability (α). This model has a similar functional form as Hanski’s incidence function (Equation 4 in Hanski 1994), but differs in that α represents the mean dispersal distance of seeds, as it is commonly presented in plant dispersal literature (Hanski 1994; Muller-Landau et al. 2008). Here, we consider α identical for all species within a dispersal mode group, and fit eqn. (1) separately for each group. To fit eqn. (1), we first used published estimates of mean dispersal distance for our dispersal mode groups (Thomson et al. 2011) and fitted the other parameters

(intercept, b1, and b2) using linear regressions. We also fitted all parameters (α, intercept, b1, and b2) using maximum likelihood; because the results predicted qualitatively similar effects of connectivity on species richness, we report the second approach in the supplementary material (Table S2.3). Specific details on the model fitting for both methods of estimating α are further explained in the supplementary material.

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When fitting eqn. (1), we noted that stand area and connectivity were often weakly correlated (r = 0.36, P = 0.086 when all species are included in the analysis). To account for this, we report our results for species richness from analyses with both stand size and connectivity included (Table 2.1) and also analyses with each factor tested separately (Table S2.4). This is important in interpreting our results because a significant effect of one stand characteristic could obscure meaningful relationships of the other stand characteristic, purely because the stand characteristics themselves are correlated.

Although our analyses of species richness allowed us to test if the dispersal mode groups responded to stand size and connectivity, we could not conclude with certainty that differences in responses between groups were statistically different because they were tested in separate linear models. To confirm that they were statistically different, we used a multivariate approach to test if the relative number of species belonging to any particular dispersal mode groups shifted with stand size and connectivity. To do this, we created a distance matrix of Bray-Curtis dissimilarity coefficients for all pairwise combinations of the 24 stands. Bray-Curtis dissimilarity is typically used to compare sites based on the abundances of multiple species; our analysis is analogous, in that we use ‘dispersal mode groups’ and ‘species richness’ rather than ‘species’ and ‘abundances’, respectively. We then ran a PCoA on the distance matrix, and used linear models to test the effects of log(stand size) and log(connectivity) on the first and second axes scores of the PCoA. Because sites with similar axis scores are compositionally similar in terms of dispersal modes, the presence of significant relationships would indicate that the dispersal mode groupings capture meaningful variation in how species are distributed across the landscape. For this analysis, the α used to calculate connectivity was the average α value of the three groups.

Because we observed a negative relationship between species richness and connectivity for one of the dispersal mode groups (Table 2.1; Fig. 2.2), we tested two additional hypotheses for the negative species richness-connectivity relationship that can occur at intermediate to high connectivity (i.e. the backend of a hump-shaped relationship). First, it is possible that increased connectivity allows the establishment of highly competitive species that exclude inferior competitors (Mouquet & Loreau 2003; Cadotte 2006a). We tested this hypothesis using a null model designed to identify negative relationships among dispersal mode groups, after accounting

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for environmental covariance. The model used was Schluter’s covariance test (Schluter 1984) tested against a randomized null expectation calculated with row and column sums held constant (the most conservative null model; Ulrich & Gotelli 2010). Second, the movement of large herbivores might be restricted by stand connectedness. We tested this possibility using a linear model looking at the effects of log(stand size) and log(connectivity) on the amount of ungulate scat found per stand during the understorey sampling period.

We also used a multivariate approach to look at turnover in species composition across stands within the dispersal mode groups to identify variation that is not accounted for by grouping by dispersal mode. Specifically, we created three distance matrices, one for each dispersal mode group, by calculating the Jaccard dissimilarity coefficient on the presence/absence data for all pairwise combinations of the 24 stands. The Jaccard dissimilarity coefficient is a resemblance measure that accounts for increased variation in species richness as species richness increases as expected with random sampling (e.g., MacArthur & Wilson 1967). We then performed PCoAs on the three distance matrices and used the first and second axis scores as response variables in linear models testing the effects of log(stand size) and log(connectivity). The presence of significant relationships would indicate that, within the dispersal mode groups, some species are more likely than others to encounter and persist in stands of varying size and connectivity.

Results

We found a significant effect of stand size (P < 0.001) and a marginally non- significant effect of connectivity (P = 0.078) on overall species richness, with higher richness observed in larger, less connected stands (Table 2.1; Fig. 2.2). However, when species were broken down by dispersal mode, the importance of these two stand characteristics varied markedly (Table 2.1). Specifically, we found a positive effect of stand size (P < 0.001) and a negative effect of connectivity (P = 0.041) on the species richness of the no-dispersal-aid group, whereas the number of animal-dispersed species increased with increasing stand size (P < 0.001) but was unaffected by stand connectivity (P = 0.768). The number of wind-dispersed species was not affected by stand size (P = 0.507) or connectivity (P = 0.107) when both factors were included in the model. However, when we considered each factor separately, species richness of wind- dispersed species increased with greater connectivity (P = 0.025; Table S2.4). In comparing 22

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among groups, there was a significant effect of stand size (axis 1; P < 0.001) and connectivity (axis 2; P = 0.0122) on the relative number of species represented by each group (Fig. 2.3). Together, these results support our hypothesis that both patch size and connectivity affect metacommunity diversity, and that these effects vary with species’ dispersal mode.

We found additional variation within the dispersal mode groups in how species responded to the stand size and stand connectivity (Table 2.2). Specifically, the composition of species with no dispersal aid changed with stand size (axis 2, P = 0.024), and animal-dispersed species changed with both stand size (axis 1; P = 0.002) and stand connectivity (axis 1; P = 0.012). We could not calculate compositional turnover for species in the wind-dispersed group, as a low frequency of joint presences precluded analysis with Jaccard similarity.

Because we found a negative relationship between species richness and stand connectivity for plants that lack a dispersal aid, we tested the possibility that competition or herbivory could be mediating this relationship (Fig. 2.4). Our null model revealed that, overall, the species richnesses of the dispersal groups negatively covaried across stands (P = 0.033). This means that, after accounting for and removing the common effects of stand size or connectivity among dispersal mode groups, the diversity of the different groups were negatively associated. We found no evidence to suggest that ungulates, common herbivores at the study site, were more active in highly-connected stands (t1,20 = -0.803, P = 0.432).

Our results on the effects of stand size and connectivity on species richness were qualitatively similar among analyses that used different cut-off values for identifying aspen-associated species (i.e., species occurring in aspen stands 50, 66, and 75% of the time; Table S2.2). In all three analyses, species with no dispersal aid were affected by stand size (all P < 0.001) and connectivity (all P ≤ 0.002), animal-dispersed species were affected by stand size only (all P < 0.001), and wind-dispersed species were not affected by either stand characteristic (all P ≥ 0.099). It was only when all species (i.e., generalists and grassland specialists) were included that we failed to detect any trends, except for the effect of stand size on the species richness of animal-dispersed species because animal-dispersed species did not occur in the grassland matrix.

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Figure 2.1 The effect of stand size and stand connectivity on species richness when all aspen- associated species are grouped together (top panels) and for each dispersal group considered separately. Species richness values were adjusted to account for the other factor in the model (size or connectivity) whenever that factor was significant. Fitted lines indicate when a factor was significant at P < 0.05 in a model with both factors (solid line) or only the significant factor (dashed line) included. All variables are log-transformed but shown on the original scale. 24

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Figure 2.2 The effect of (a) stand size and (b) connectivity on the relative representation of species belonging to each dispersal mode group from a PCoA using the Bray-Curtis coefficient. We only display the stand characteristic-axis score combinations that were significantly correlated. Each axis was delineated by changes in group representation: axis 1 primarily summarized variation in wind and animal dispersed species richness (rwind = -0.35, ranimal = 0.35) but not the richness of species with no dispersal aid (rno aid = -0.08). Axis 2 summarized variation in the richness of species with no dispersal aid (rno aid = 0.91), as well as wind (rwind = -0.63) and animal (ranimal = -0.51) dispersed species.

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Figure 2.3 Evidence for the role of competition but not herbivory in mediating relationships between the stand characteristics and species richness. (a) The observed degree of negative covariances in species richness between dispersal mode groups (solid line) compared to a null distribution of random outcomes. An observed value to the left of the distribution indicates that covariances are less than expected by chance, a result interpreted as indicating that competition among groups structures their distributions. (b) The effect of stand connectivity on ungulate herbivore activity, as estimated from scat survey data.

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Table 2.1 Effects of stand size and connectivity on log-transformed species richness. ‘All species’ includes all aspen-associated species from the three dispersal mode groups.

log Stand size log Stand connectivity # Dispersal mode α estimate species b t1,23 P b t1,23 P

All species 67 88.5 0.34 4.89 <0.001 -0.19 -1.85 0.078

No dispersal aid 32 5* 0.40 4.25 <0.001 -0.02 -2.18 0.0411

Wind-dispersed 17 8.5 0.07 0.68 0.507 0.03 1.68 0.1072

Animal-dispersed 18 254.5† 0.29 4.35 <0.001 -0.05 -0.30 0.768

Note: significant effects are bolded; all df = 24. b is the slope of the relationship.

1 Was only significant when stand size was included in the model (t1,23 = -0.002, P = 0.998; Table S2.4).

2 Was significant when stand size was not included in the model (t1,23 = 2.41, P = 0.025; Table S2.4).

*Using an α estimate of 2.43 m, the average for species with no dispersal aid from Thomson et al. (2011), provided qualitatively equivalent model fit for this group (log (Stand size) P < 0.001; log (Stand connectivity) P = 0.04; see supplementary material in Appendix A).

†Thomson et al. 2011 separated animal dispersal into ingestion (n = 116), attachment (n = 4) and seed-caching (n = 26). We calculated a weighted mean based on the number of species in each category.

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Table 2.2 Effects of stand size and stand connectivity on species composition (axis 1 and 2 scores of PCoA using Jaccard dissimilarity coefficient) by dispersal mode.

Axis Dispersal # α log Stand size log Stand connectivity # mode species estimate b t1,23 P b t1,23 P

1 All species 67 88.5 -0.11 -3.13 0.005 0.14 2.57 0.018

No dispersal 32 5* -0.02 -0.34 0.736 0.01 0.84 0.411 aid

Wind- 17 8.5 NA NA NA NA NA NA dispersed

Animal- 18 254.5 -0.15 -3.44 0.002 0.28 2.74 0.012 dispersed

2 All species 67 88.5 0.12 3.32 0.003 -0.07 -1.38 0.183

No dispersal 32 5* 0.12 2.44 0.024 -0.01 -0.98 0.341 aid

Wind- 17 8.5 NA NA NA NA NA NA dispersed

Animal- 18 254.5 -0.0650 -1.25 0.224 0.05 0.40 0.694 dispersed

Note: significant effects are bolded; all df = 24. b is the slope of the relationship. We could not calculate Jaccard dissimilarity for plots in the wind-dispersed species group, because had many species had single occurrences.

*α estimates ranging from 2-5 m provided qualitatively equivalent model fit for this group.

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Discussion

Our study highlights the importance of considering variation in species’ dispersal modes in metacommunity studies. When dispersal mode was ignored and all aspen-associated species were grouped together, species richness per unit area was positivity associated with stand size only (Table 2.1; Fig. 2.2), which has been observed in some (Holt, Robinson & Gaines 1995; Harvey & MacDougall 2014) but not all (Holt, Robinson and Gaines 1995) metacommunities. Our approach of separating species by fruit type, a life history characteristic that affects how seeds are dispersed across landscapes, clarified how relationships between stand size, connectivity, and diversity differ among species’ with different dispersal modes (Table 2.1; Fig. 2.2).

Larger stands contained more animal-dispersed species and species with no dispersal aid, a pattern consistent with classic theory in which bigger patches support larger populations that are less prone to extinction. However, animal-dispersed species’ responses to stand size might also be explained by habitat selection by seed-dispersing animals. If animals preferentially select larger patches, animal-dispersed species might be underrepresented in small patches simply because their dispersal agents do not transport them there. Although we did not quantify animal abundances within the aspen patches, previous work has documented that many bird and large mammal species prefer larger stands (Johns 1993; Oaten & Larsen 2008), and are thus more likely to deposit seeds in these stands. Interestingly, the diversity of wind-dispersed species was unaffected by stand size. Although we can’t isolate the specific mechanism driving this pattern, many of the wind-dispersed species found in our study, such as the Antennaria, Cirsium, and Lactuca, are considered ruderal species, therefore their persistence should be more generally limited by disturbance events (which in this system likely occur at low levels among all patches) than factors such as stand size.

Although the range of relationships between connectivity and diversity presented by previous empirical work precludes a single prediction, we expected to see a positive or hump-shaped relationship, as these have most commonly been found in other studies (Kneitel & Miller 2003; Matthiessen & Hillebrand 2006; Howeth & Leibold 2010; Chase et al. 2010; Vanschoenwinkel, Buschke & Brendonck 2013). Consistent with these studies, we found evidence that connectivity 29

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had a positive effect on the richness of wind-dispersed species (Fig. 2.2, Table S2.4), indicating that colonization rates in this group are limited by connectivity; the most distant, least connected site had only a single wind-dispersed species. Although wind-dispersed species may access all stands via infrequent long-distance dispersal events (e.g., in wind storms; Soons, Nathan & Katul 2004), colonization events would be rare compared to extinctions, thus creating this gradient in diversity.

We also detected a negative relationship between connectivity and richness for species with no dispersal aid, which may be suggestive of the declining half of a hump-shaped curve. The most widely accepted explanation for a decline in richness in highly connected patches is that competitively dominant or generalist predator species that are poor dispersers can dominate highly-connected patches and drive other species locally extinct (Forbes & Chase 2002; Kneitel & Miller 2003; Cadotte 2006b; Chase et al. 2010; Matthiessen et al. 2010; Vanschoenwinkel, Buschke & Brendonck 2013). If this were the case, we would expect to see either negative relationships between dispersal mode groups (competitor hypothesis), increased herbivore activity in highly connected patches (predator hypothesis), or both. Although our observational dataset does not allow us to discriminate definitively among the mechanisms underlying observed patterns, estimates of competition and herbivory were used to determine whether observed patterns were consistent with either of these mechanisms. We found some evidence in support of the competitor hypothesis only: the null model revealed negative covariance among dispersal mode groups (P = 0.038; Fig. 2.4a). This suggests that species with no dispersal aid might be competitively suppressed by the other dispersal mode groups in highly-connected stands. We note, however, that theory predicts that the no dispersal aid group should be competitively dominant, and our results suggest the opposite. Our results are nonetheless consistent with experimental work in aspen stands in the boreal forest (Gilbert, Turkington & Srivastava 2009), and raises questions about persistence of weak dispersers when they are also weak competitors.

Our investigation of turnover in species composition among dispersal mode groups suggests that these groupings capture meaningful variation in how species in this aspen metacommunity move across the landscape (Fig. 2.3). Interestingly, our analyses also indicate that there is additional

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variation within groups in how species are responding to stand size and connectivity (Table 2.2). For example, both Rocky Mountain juniper (Juniperus scopulorum) and prickly wild rose (Rosa acicularis) are animal dispersed, but differ in their association with large or small stands. This variation would not likely be fully accounted for by incorporating information on species- specific dispersal abilities, because species also varied in their responses to stand size. This result could reflect interspecific variation in sensitivity to local extinction, or different animal vectors (i.e., bird, rodent, deer) for animal-dispersed species. Overall, our findings indicate that while including dispersal mode is important for understanding metacommunity dynamics, investigation of interspecific differences in dispersal within modes may further clarify how spatial dynamics structure diversity in this ecosystem.

Early metacommunity theory posited that species richness will increase per unit area in highly connected patches when communities are comprised of weakly interacting species (Holt 1993). This prediction is often overlooked, with many metacommunity studies estimating diversity across a patch size gradient and confounding patch size with the area sampled by increasing sampling effort proportionally with patch size. Other researchers have recognized this problem and subsequently accounted for unequal sampling post hoc through rarefaction or by randomly selecting a subset of patches (e.g., Meynard et al. 2013). Although our approach is unlikely to capture the total diversity across all aspen stands, it is more consistent with metacommunity predictions than approaches that attempt to standardize sampling effort post hoc. Standardizing area in metacommunity sampling has long been advocated (Holt 1993) because this method directly tests species’ responses to patch size by eliminating the confounding effects on species richness of increased sampling effort and habitat heterogeneity in larger patches.

Unlike more classic examples of metacommunities, such as ponds or islands, the boundaries of aspen stands are diffuse to some species that also occur in the surrounding grassland matrix. For example, matrix-associated species may be present in the aspen stands if they are generalists that persist in both habitat types, or if they are grassland specialists experiencing source-sink dynamics whereby populations in aspen stands are supplemented with incoming colonists from the matrix. In either case, these species’ pose a conceptual and methodological challenge for how the metacommunity is defined, given that the matrix may be inhospitable to some species but not

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others (Delong & Gibson 2012). In our study, we used a paired plot design consisting of one grassland-matrix plot surveyed adjacent to each aspen stand. This method allowed us to identify and exclude species that were highly associated with the grassland matrix, and that were therefore not likely to be constrained by the boundaries of the aspen metacommunity. Of the 170 species observed in our paired plot surveys, 66 and 44 species were found primarily (≥ 66% of the time) or exclusively in aspen stands, respectively, with 36 species occurring only in grassland plots. This means that, of the 110 total species found in the aspen stand plots, 66 experience the grassland matrix as inhospitable, and thus adhere to classic metacommunity definitions (Leibold et al. 2004). Our data revealed effects of patch size and connectivity on diversity that were robust to the choice of cut-off that was used (i.e., species occurring in aspen stands at least 50, 66, and 75% of the time; Table S2.2). It was only when all species (i.e., generalists and grassland specialists) were included that we failed to detect these trends. The paired plot design used here could be implemented in future work in similarly diffuse habitat-patch networks (e.g., coral reefs, serpentine hummocks etc.), a recognized class of metacommunties that dominates many landscapes (Leibold et al. 2004).

Our assessment of the effects of stand size and connectivity on diversity is one of the first to use a naturally-patchy metacommunity to test how differences in species dispersal modes influence local diversity. In doing so, we show that dispersal mode mediates the effects of stand size and connectivity on metacommunity diversity in ways that would be obscured if all species were grouped together. Our results also raise the intriguing possibility that life history traits that affect dispersal may also alter distributions of these groups through differences in competitive ability, habitat specific movement of animal vectors, and different local extinction rates. Our approach to studying the effects of dispersal and patch characteristics on metacommunity diversity has provided new insights into the complex relationship between patch characteristics and metacommunity diversity.

Acknowledgments

We would like to thank Laura May for field assistance. N. T. J. received financial assistance from the Thompson Rivers University Undergraduate Student Research Experience Award

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(UREAP). We also thank two anonymous reviewers whose thoughtful comments on a previous version of this manuscript improved it considerably.

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Chapter 3 Are species larger at high latitudes? Testing latitude-body size relationships in zooplankton

This paper in preparation to be published as: Jones, N.T., Moran J. & Gilbert, B. Are species larger at high latitudes? Testing latitude-body size relationships in zooplankton.

Abstract

According to classic ecological rules, mean body size within and among species increases with lower temperatures, creating a gradient of increasing body size with increasing latitude. Short- term experimental evidence appears to support this prediction for zooplankton, as they commonly decrease in size in warmer waters. However, latitudinal body size patterns remain unclear for many ectothermic animals, but need to be clarified in order to understand long-term effects of temperature on body size. We examined how body size within and among freshwater aquatic zooplankton species changes with latitude by measuring the body size of crustacean zooplankton communities (Cladocera and Copepoda) from 19 freshwater lakes that are spread across an 1800 km gradient from southern British Columbia to the Yukon Territory. We found weak evidence that body size is associated with latitude, and no evidence that suggests there is a consistent trend in body size across species. When examining body size within species, we found a significant effect of latitude for only three species, with two species showing significant increases in size with latitude, and one species showing a marginal decrease. The overall null result for within-species trends was not due to low power – species that occurred more frequently had smaller confidence intervals but estimates that were much closer to zero. When examining body size among species, we also found no trend for the mean community body size with respect to latitude, regardless if body size was weighted by local abundance or simply averaged across species. Additional environmental variables impacted the body size of a subset of species, but similar to latitude, the overall effects were variable, and including these variables in our analysis did not change the overall relationship between body size and latitude. Our results are consistent with previous research investigating the body size patterns of insects, and indicate that latitude- body size relationships cannot be consistently applied to ectothermic organisms. When considered in relation to results of short-term experimental studies, our findings suggest that the

38 CHAPTER 3: BODY-SIZE LATITUDE RELATIONSHIPS

effects of climate change on the body size of zooplankton communities will be difficult to predict and may show different short- and long-term trends.

Introduction

Differences in body size, both within and among species, have long fascinated biologists (Schmidt-Nielsen 1984; Peters 1986). The body size of organisms is often associated with latitude and temperature (Gillooly and Dodson 2012) and contemporary temperature increases with climate change have renewed interest in temperature-body size relationships (Millien et al. 2006; Teplitsky et al. 2008). The effect of temperature on body size is particularly relevant for ectotherms as temperature directly modifies development time and fitness for those organisms (Atkinson 1994; Gillooly et al. 2001). Body size also has important implications for many ecological processes, including energy requirements for population maintenance, competitive asymmetries, and predator-prey dynamics (Yodzis & Innes 1992). Despite the increase in studies examining latitude-body size relationships (e.g., Rypel 2014), high variation in the association between body size and latitude for ectotherms indicates that additional studies are necessary to clarify how the relationship manifests in diverse taxa (Shelomi 2012).

Three ecological rules attempt to explain geographic patterns of inter- and intra-specific body size. Associations between geography and body size were first formalized by Bergmann (1847) who observed the ecogeographical pattern of larger species being found in cooler regions, whereas warm climates contain relatively small species, this pattern is now referred to as “Bergmann’s rule” (translated in Mayr 1956 and James 1970). Over time, Bergmann’s rule has been extended to explain interspecific (Blackburn, Gaston & Loder 1999) and intraspecific (James’s rule; James 1970) differences in body size across a climatic gradient; with body size generally increasing among species and populations at high latitudes where colder temperatures prevail. Some scholars argue that Bergmann originally created the rule to explain size differences in endotherms (although there is debate on this; Rensch 1938, Geist 1987, Watt et al. 2010), but more recently additional efforts have been made to explain body size variation in ectotherms across broad biogeographic gradients (e.g. Berke et al. 2013).

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Experimental research has often supported the underlying link between higher temperatures and smaller body size. For example, syntheses of experiments found empirical evidence that was consistent with Bergmann’s hypothesis by demonstrating that individuals reared at higher temperatures were usually smaller than individuals reared at low temperatures (Atkinson 1994; Forster, Hirst & Atkinson 2012). This finding is more generally referred to as the “Temperature- Size rule”, and appears to be particularly important in aquatic ecosystems (Forster et al. 2012).

The effect of temperature on body size may be direct or indirect. Temperature directly speeds up metabolic rates (Gillooly et al. 2001; Brown et al. 2004), with higher temperatures causing juveniles to reach adulthood faster, but this accelerated maturation comes with the cost of a reduction in body size. This smaller body size has been hypothesized to be adaptive because it may be thermally advantageous in a warmer climate, as smaller size provides a greater amount of surface area relative to total body volume, which facilitates heat loss at high temperatures (Mayr 1956; Meiri 2011). Temperature may also have an indirect effect through oxygen availability in aquatic ecosystems, where a greater surface area to volume ratio can aid uptake in warmer waters that contain less available oxygen (Forster et al. 2012). Temperature can also indirectly affect body size through its influence on food availability and predation risk (Gliwicz 1990; DeLong & Hanson 2011; Gilbert et al. 2014; DeLong et al. 2015). The large array of temperature-dependent factors that can influence body size has led to considerable debate about the mechanisms driving the biogeographical patterns of body size (Blackburn et al. 1999; Watt et al. 2010). Regardless of the underlying mechanism(s) driving body size-temperature relationships, theory and experimental research suggest that temperature should have an important effect on body size.

The strength of support for Bergmann’s rule appears to depend on the life-history characteristics of the organism. Many studies of homeotherms have documented a positive relationship between body size and latitude. For example, the majority of studies on mammals (up to 65%) have concluded that body size increases with latitude (Blackburn & Hawkins 2004) and meta-analyses examining Bergmann’s rule in birds also tend to support the theory (Ashton 2002; Meiri & Dayan 2003). On the other hand, studies of ectotherms provide less evidence for positive latitude body-size clines (Blackburn et al. 1999). For example, poikilothermic groups such as turtles, have been shown to increase in body size as latitude increases, while other groups such as fishes,

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lizards and snakes exhibit reverse Bergmann clines (Ashton & Feldman 2003). Insects vary strongly in their tendency to support Bergmann’s predictions, displaying a diversity of body-size latitude relationships (Shelomi 2012). Research on latitudinal patterns in body size of freshwater cladocerans has shown a different pattern altogether, with one study showing body size declining north and south of 60° latitude (Gillooly & Dodson 2000), and another showing weak or non- existent trends (Havens et al. 2014). However, in many instances this research has been criticized for methodological concerns, such as examining mean interspecific trends (e.g., Gillooly & Dodson 2000; Havens et al. 2014), while failing to account for intraspecific differences in body size (Shelomi 2012).

In this paper, we investigate latitudinal patterns in zooplankton body size across a latitudinal gradient in western Canada. Latitudinal gradients offer a convenient proxy for temperature, as temperature, in the lakes we sampled and more generally, is negatively correlated with increasing latitude (Fig. S3.1). We collected freshwater crustacean zooplankton (Cladocera and Copepoda) from 19 lakes that span an 1800 km latitudinal gradient to ask the following questions: 1) what is the relationship between zooplankton body size and latitude? 2) Are these patterns consistent among species? 3) do these relationships scale to the community level? And, 4) are other lake characteristics, besides latitude and temperature, associated with zooplankton body size? Understanding how the body size of organisms is affected by different temperatures over latitudinal gradients may provide important insight into how organisms will respond to elevate temperatures associated with climate change.

Materials & methods

Study species & species sampling

The 19 lakes included in this study were part of a larger sampling effort in 2011 that collected zooplankton communities from 43 freshwater lakes (Table S3.1 and Table S3.2 in Appendix B: Supplementary information for chapter 3) across a ~1800 km latitudinal gradient in western Canada, ranging from southern British Columbia to the middle of the Yukon Territory. We used the contemporary zooplankton community data from chapter 5 to select the appropriate lakes to include in this study. We had two main selection criteria. First, to isolate intra-specific body size patterns, we chose lakes that contained species which occurred in at least three lakes. Second, 41

CHAPTER 3: BODY-SIZE LATITUDE RELATIONSHIPS

because the primary goal of this study was to determine the relationship between body size and latitude, we selected lakes containing species that were distributed across a latitudinal range of at least five degrees latitude.

To control for any confounding effects of the growing season on body size, we began sampling lakes in the southern portion of the latitudinal gradient, sampling a subset of lakes as we moved north along the transect, and others as we returned south. Plankton communities were collected by hauling a Wisconsin net [mouth diameter 24 cm, net mesh 76 µm] through the water column, beginning from near the lake bottom, at the approximate center of each lake. Two vertical plankton tows per lake were taken and zooplankton communities were immediately preserved in 70% ethanol.

Environmental covariates

Temperature is not the only factor that affects body size. To determine if local abiotic conditions impact the body-size latitude relationships we observed, we quantified a subset of biotic and abiotic characteristics that can also directly and indirectly affect the body size of zooplankton (lake depth, chlorophyll a concentration (a measure of productivity), dissolved oxygen concentration, fish predation; Table S3.1, Table S3.3). We used a YSI 6-series multiparameter water quality sonde (Integrated Systems & Services, Yellow Spring, OH, USA) to determine the water temperature, chlorophyll a concentration and dissolved oxygen concentration at the time that we sampled the zooplankton communities. We used published estimates of lake depth and the diversity of fish communities from the literature (Anderson 1974; Lindsey et al. 1981). Due to the limited availability of data on fish density in these lakes, we simply used the number of fish species in a lake as a proxy for zooplankton predation, as many species of fish eat zooplankton at some developmental stage.

Body size measurements

We combined the two plankton tows and then randomly took subsamples, measuring the first 30 adults encountered for each species in a lake. Species names follow the taxonomy of Thorp and Covich (2010) and Sandercock and Scudder (1994). For a subset of rare species we were unable to find thirty individuals to measure. In these cases, we scanned samples and measured as many

CHAPTER 3: BODY-SIZE LATITUDE RELATIONSHIPS

individuals as possible. Next, we measured zooplankton body length under a dissecting microscope using Olympus Stream software. The body size of Cladocera was measured from the center of the eye, to the base of the tail spine (Gliwicz 1990; Yurista & Brien 2001). For Copepoda, we measured the length of the prosome (Breteler & Gonzalez 1988; Ban 1994).

Statistical analysis

Prior to analysis of within-species trends, we removed all individuals that could not be identified to the species level; Ceriodaphnia, Chydorus and Diaptomus species could not be identified to species level and were removed. We also eliminated eight species that were so uncommon that they occurred in less than three lakes, as we could not test the slope of the relationship between latitude and body size for these species. We note that although these removed species could not be used for within-species trends, they were incorporated into community-level mean body size estimates that used each lake as the unit of measurement (below).

Following these removals, our within-species data set consisted of 10 species from a total pool of 21 species that have been documented in these lakes. Body size measurements were logarithmically transformed to minimize heteroscedasticity and meet normality assumptions. Before conducting any species-latitude analyses, we confirmed that latitude is a good proxy for water temperature using linear regression. We used statistical software R for all analyses (R Core Team 2014).

We used linear mixed models to conduct a cross-species analysis that tested if zooplankton body size is associated with latitude (lmer function in lme4 package; Bates et al. 2014). The full model included latitude, species and their interaction as fixed effects. The individual lake and species were included in the model as random effects to account for correlated errors. The multispecies model indicated that the effect of latitude on body size depended on the species considered, therefore we ran a separate mixed model for each species to isolate the species-specific effect of latitude on body size. To generate an average slope estimate across species, we reran the analysis with all species and latitude as a fixed effect with a random slope and intercept, as well as a random effect for lake.

CHAPTER 3: BODY-SIZE LATITUDE RELATIONSHIPS

Because we observed no significant effect of latitude on body size for the majority of the species we considered (Table 3.1; Fig. 3.1), we tested how additional environmental factors (chlorophyll a, dissolved oxygen and lake depth) influence the average adult body size of zooplankton. We used a similar statistical approach as described above. First, we tested if the interaction between the environmental variable and species improved model fit (using log ratio tests). If the interaction did improve model fit, we added that variable to a final model that included latitude. This resulted in a final model that included latitude, depth, chlorophyll a, dissolved oxygen, fish predation (and their interaction with species).

To test if the body size of the entire crustacean zooplankton community shifted across a latitudinal gradient, we calculated two measures: mean community body size and mean weighted community body size. Mean weighted community body size was calculated by multiplying the average body size of each species by its relative abundance within a lake (data from Jones and Gilbert 2016 in review). For (unweighted) mean community body size, each species contributed equally to the average, regardless of its local abundance in the lake. We used linear regression to test if the mean weighted and unweighted community body size changed with latitude. Unlike the previous analysis, all species present in each lake ‒ regardless of the number of times they occurred in a lake ‒ were included in the calculation of community body size.

Results

2 Lake water temperature declined as latitude increased (F1,16 = 12.42, P <0.0001, r = 0.41; Fig. S3.1), indicating that the latitudinal gradient we sampled represents a temperature cline. The effect of latitude on body size depended on which zooplankton species was being considered (significant latitude*species interaction; df = 6, χ2= -162.80, P < 0.0001), and the overall slope for all species was not different from zero (P = 0.70). When we ran separate linear mixed models for each species, we found weak evidence that adult body size is associated with latitude. In the majority of cases (8/10 species), latitude had no effect on the average body size of zooplankton (Table 3.1, Fig. 3.1a, Fig. S3.2). Importantly, the two species that do display a statistically significant body size-latitude relationship occurred in few lakes. Specifically, the copepod species, Acanthocyclops vernalis, increased in length by an average of 14%, while the cladoceran species, Holopedium gibberum, increased by more than 50% (Table 3.1). However, sample sizes 44

CHAPTER 3: BODY-SIZE LATITUDE RELATIONSHIPS

for these species were small, with A. vernalis occurring in four lakes and H. gibberum occurring in only three lakes. We saw weak evidence for reverse Bergmann clines (larger body size at lower latitude sites), with only Leptodora kindii showing a marginally non-significant trend (P = 0.068). We re-ran the analysis with lake temperature as the independent variable and found similar relationships (Table S3.3; Fig. 3.1b), except that the effect of temperature was weaker; only one species showed a clear trend of increasing body size at lower temperatures.

Figure 3.1 Plots of the slope (points) and 95% bootstrapped confidence intervals (lines). Lines that do not overlap with zero are significantly associated with (a) latitude or (b) temperature. Numbers indicate the number of lakes that the species was present.

CHAPTER 3: BODY-SIZE LATITUDE RELATIONSHIPS

Minimum Maximum

Latitude Predicted body Latitude Predicted body Number of P-value % change in size (µm) (°) size (µm) lakes body size Species (°)

Acanthocyclops vernalis 49.38 202 54.25 234 4 0.025 14

Bosmina longirostris 49.38 185 62.30 232 16 0.318 20

Cyclops scutifer 54.02 304 62.30 296 8 0.362 -3

Daphnia longiremis 49.90 338 62.30 389 10 0.439 13

Daphnia longispina 50.88 447 62.30 386 6 0.880 -16

Daphnia pulex 49.38 521 58.45 415 8 0.412 -25

Diacyclops thomasi 49.38 271 58.45 314 12 0.907 14

Diaphanosoma luechtenb. 50.02 272 54.37 482 7 0.671 44

Holopedium gibberum 49.38 210 54.37 448 3 0.001 53

Leptodora kindii 50.08 1837 54.25 1123 3 0.069 -64

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The four environmental variables we considered (chlorophyll a, dissolved oxygen, lake depth, fish diversity) all significantly improved model fit (Table 3.2). Similar to the effect of latitude on body size, each of these variables showed significant interactions with species, and in general the species-specific effect of each variable was idiosyncratic, with species showing positive and negative relationships (Table 3.3). However, including these factors as covariates in the latitude versus body size analysis did not change the overall effect of latitude. There was still no consistent effect of latitude among species (main latitude effect P = 0.38), and the slopes for individual species were consistent with the first analysis (correlation of estimates, r = 0.86), although some species showed slightly stronger positive trends with latitude (e.g., H. gibberum) and some showed stronger negative trends (e.g., Daphnia longiremis; Table S3.4).

Df LRT p-value

Latitude*species 6 162.8 <0.001

Depth*species 6 75.9 <0.001

Fish richness*species 6 77.5 <0.001

Chlorophyll a*species 6 41.1 <0.001

Dissolved oxygen*species 6 111.0 <0.001

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Table 3.3 The number of species that significantly increased or decreased in body size with latitude, temperature or other environmental variables when tested in isolation.

Variable Increase Decrease

Latitude (°) 2 0

Temperature (°C) 0 1

Depth (m) 2 2

Chlorophyll a (µg/L) 0 0

Dissolved oxygen (mg/L) 1 2

Fish (n) 1 2

CHAPTER 3: BODY-SIZE LATITUDE RELATIONSHIPS

We also tested for evidence of a community level shift in the average body size of zooplankton. There was no relationship between latitude and the mean body size of the entire crustacean community. This relationship was consistent whether we considered the raw average (t = -0.39, P= 0.71; Fig 3.2a) or weighted body size by the relative abundance of species’ (t = -0.73, P = 0.48; Fig 3.2b).

Figure 3.2 The association between latitude and the mean a) unweighted and b) weighted zooplankton community body size. Community body size was weighted by the local abundance of each species. Neither relationship is significant (F1,17 = 0.15, P = 0.70 and F1,17 = 0.53, P = 0.47 respectively).

CHAPTER 3: BODY-SIZE LATITUDE RELATIONSHIPS

Discussion

The macroecological pattern of shifts in body size with latitude is one of the most widely accepted ecological patterns in nature, and increasingly important to understand given global shifts in climate. The results of our study highlight that the body size patterns of aquatic zooplankton taken from an 1800 km north-south gradient do not conform to the predictions of Bergmann (1847), James (1970) and Atkinson (1994). Below, we discuss how our results relate to previous work on geographic patterns in body size as well as empirical studies on temperature and body size.

Our results revealed that shifts in body size with latitude and temperature are largely absent from zooplankton communities that we collected, despite having a samples from lakes that ranged by 1800 km and approximately 10° C (summer surface temperature) along a north-south gradient. This result adds to the growing number of case studies where body-size latitude associations do not display Bergmann clines. For example, in a recent meta-analysis on insects, Shelomi (2012) revealed idiosyncratic body-size latitude relationships, with equal support for Bergmann and non-Bergmann clines. Similarly, temperature can have inconsistent effects on the body size of marine zooplankton, suggesting that zooplankton body size may be more strongly affected by other factors (Sebastian et al. 2012). These studies are consistent with our work and suggest that the body size of zooplankton and other ectotherms may respond heterogeneously to temperature and latitudinal changes. The idiosyncratic response of body size to latitudinal increases that we observed suggest that latitude- body size relationships that have been observed among birds and mammals cannot be unanimously applied to ectothermic organisms such as zooplankton.

Although our results are consistent with some recent studies in other taxa, they differ from work that has explicitly considered the relationship between body size and latitude in freshwater zooplankton (e.g., Beaver et al. 2014). For example, Gillooly & Dodson (2000) amassed an impressive cladoceran body-size dataset, from over 1100 western lakes that spanned Southern and Northern hemispheres, and observed a striking increase in body size from tropical to temperature regions. Differences in experimental methodology are a strong candidate for explaining the discrepancy between their study and the results presented here. In this study we sampled fewer lakes but more extensively, capturing accurate estimates of intraspecific size differences. In contrast, Gillooly and Dodson (2000) used published species lists to indirectly 50

CHAPTER 3: BODY-SIZE LATITUDE RELATIONSHIPS

estimate body size for many lakes and did not incorporate intraspecific variation or species abundance within a site. Indeed, a subsequent study that used more accurate body size estimates showed weak or no support for Bergmann’s Rule, depending on the taxa considered (Havens et al. 2014). The different results obtained by these studies and our own indicate that more detailed measurements at the lake level can alter support for correlations between latitude and body size.

A common concern with analyses that fail to support a hypothesis is that the analysis is not powerful enough, or that important covariates were not considered. The results from our initial analysis, and follow-up analyses, suggest that these concerns are not likely to account for the null results that we observed. For example, species that showed the largest (positive and negative) changes in body size with latitude were those that had the smallest sample sizes (Fig. 3.1). Indeed, the best-sampled species had very narrow confidence intervals, but slopes that were extremely close to zero. Similarly, after accounting for potential covariates of body size, the overall effect of latitude on body size was still not significant (P = 0.38), and we saw that changes in the slope or standard error of the slope resulted in more positive and negative relationships. In other words, accounting for covariates did not change support for a common latitude-body size relationship within species.

Each of the environmental variables that we considered as covariates appears to be about as important as latitude for zooplankton body size (Table 3.3), at least in our system. While it is impossible to know with certainty what mechanism(s) drive body size in the lakes we considered, factors beyond temperature have been hypothesized to be important (Atkinson 1995, Gardner et al. 2011). For instance, it has been suggested that food availability and predation risk may drive changes in zooplankton body size (Gliwicz 1990, Hart and Bychek 2011). However, consistent with recent work testing the impact of biotic and biotic forces on the body length of zooplankton in reservoirs across the western United States, the concentration of chlorophyll a, a proxy for resource abundance, on zooplankton body size was weak (Beaver et al. 2014). Fish predation is associated with smaller zooplankton because fish preferentially predate on larger individuals (Dodson & Brooks 1965), which selects for rapid development (Allan 1976). We found some evidence that supports this hypothesis, the number of fish species decreased the average body size of two species, however, one species showed the opposite trend (Table 3.2). The direct and indirect effects of environmental variables are complex and likely interact; future

CHAPTER 3: BODY-SIZE LATITUDE RELATIONSHIPS

work that disentangles the influence of these factors could help explain deviations from ecogeographic rules.

Our results also highlight discordance between short-term experiments and observational biogeographic studies. Ecologists have been attempting to generate clear predictions for how organisms will react to climate-change driven temperature increases (Gilman et al. 2010). Recent research suggests that ectotherms will undergo a reduction in body size as a response to global warming (Daufresne et al. 2009), a phenomenon that has been referred to as the “third universal response to global warming”. Controlled studies that manipulate temperature and subsequently measure body size usually find a reduction in body size at higher temperatures. For instance, a meta-analysis of the response of aquatic ectotherms to warmer temperatures found that 90 % of aquatic ectotherm species decreased in size at higher temperatures; specifically, this study found that 12 out of 13 species of Crustacea reached smaller body sizes at higher temperatures (Atkinson 1995). However, these studies normally do not differentiate between the role of phenotypic plasticity and microevolution in generating these patters (Kingsolver & Huey 2008; Teplitsky et al. 2008). Within a given population, larger phenotypes are frequently more fit, and thus selection within a specific temperature regime may lead to larger individuals with time, counteracting plastic responses (Kingsolver & Huey 2008). These different responses could explain why communities that have been collected from nature and evolved in situ under different thermal regimes do not support the predictions of the Temperature-Size rule etc., while results from controlled experiments often do support these rules.

Thermal stratification and habitat partitioning in lakes may contribute to the weak evidence for geographic clines in body size that we documented. Many of the zooplankton species in this study are found throughout the water column. In addition, some species such as H. gibberum have been observed to migrate within the water column during the day (Balcer, Korda & Dodson 1984), while other species such as the copepod species D. thomasi and C. scutifer, tend to be found deeper in the water column below the thermocline, where temperatures are low throughout the growing season (Elgmork 1967). Because the zooplankton community integrates individuals from throughout the water column, associations between temperature and body size may be particularly weak in this these taxa. More generally, thermally stratified lakes are one example of a habitat that allows species to maintain thermal conditions that are distinct from the surrounding

CHAPTER 3: BODY-SIZE LATITUDE RELATIONSHIPS

environment, and thus may provide opportunities for species to avoid typical temperature constraints.

In conclusion, the lack of response of zooplankton body size to latitudinal changes that we observed support a growing number of studies that show Bergmann’s rule cannot explain zooplankton patterns of body size across latitudinal gradients. The different conclusions of controlled experiments and observational studies of body size patterns in nature suggest that it may be difficult to predict how body size of crustacean zooplankton will respond to global warming.

Acknowledgments

We would like to thank Veronica Jones for field assistance and NSERC (B.G., Discovery Grant) as well as Ontario Graduate Scholarships (N.T.J.) for funding.

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Chapter 4 Changing climate cues differentially alter zooplankton dormancy dynamics across latitude

This paper is published as: Jones, N.T. & Gilbert, B. (2016) Changing climate cues differentially alter zooplankton dormancy dynamics across latitudes. The Journal of Animal Ecology, 85, 559– 569.

Abstract

In seasonal climates, dormancy is a common strategy that structures biodiversity and is necessary for the persistence of many species. Climate change will likely alter dormancy dynamics in zooplankton, the basis of aquatic food webs, by altering two important hatching cues: mean temperatures during the ice-free season, and mean day length when lakes become ice free. Theory suggests that these changes could alter diversity, hatchling abundances and phenology within lakes, and that these responses may diverge across latitudes due to differences in optimal hatching cues and strategies. To examine the role of temperature and day length on hatching dynamics, we collected sediment from 25 lakes across a 1800 km latitudinal gradient and exposed sediment samples to a factorial combination of two photoperiods (12 and 16 hours) and two temperatures (8ºC and 12 ºC) representative of historical southern (short photoperiod, warm) and northern (long photoperiod, cool) lake conditions. We tested whether sensitivity to these hatching cues varies by latitudinal origin and differs among taxa. Higher temperatures advanced phenology for all taxa, and these advances were greatest for cladocerans followed by copepods and rotifers. Although phenology differed among taxa, the effect of temperature did not vary with latitude. The latitudinal origin of the egg bank influenced egg abundance and hatchling abundance and diversity, with these latter effects varying with taxon, temperature and photoperiod. Copepod hatchling abundances peaked at mid latitudes in the high temperature and long photoperiod treatments, whereas hatchling abundances of other zooplankton were greatest at low latitudes and high temperature. The overall diversity of crustacean zooplankton (copepods and cladocerans) also reflected distinct responses of each taxon to our treatments, with the greatest diversity occurring at mid latitudes (~56° N) in the shorter photoperiod treatment. Our results demonstrate that hatching cues differ for broad taxonomic groups that vary in

57 CHAPTER 4: DORMANCY & CLIMATE CUES

developmental and life-history strategies. These differences are predicted to drive latitude- specific shifts in zooplankton emergence with climate change, and could alter the base of aquatic food webs.

Introduction

Dormancy is a common strategy that is essential to the persistence of many species in seasonal climates and has the potential to be strongly impacted by climate change (Hance et al. 2007; Williams, Henry & Sinclair 2015). Both the onset and termination of dormancy depend on environmental cues, with many species from diverse taxa responding to climatic conditions such as temperature and precipitation (Vandekerkhove et al. 2005; Hance et al. 2007; Levine, Mceachern & Cowan 2008). Despite the importance of dormancy for community assembly and ecological dynamics generally (Hairston & Kearns 1995; Ellner et al. 1999; McNamara & Houston 2008), there has been relatively little research on the impacts of climate on dormancy dynamics for many taxa, and the work that has been done has often been too localized to allow for the general predictions needed when planning for climate change (Hairston 1996; Dupuis & Hann 2009; Angeler 2011).

Zooplankton are numerically and functionally dominant animals that form the basis of aquatic food webs, with taxa performing different roles within lake ecosystems (Barnett, Finlay & Beisner 2007). Although dormancy is a critical part of the annual life cycle of most zooplankton species (Varpe 2012), biogeographic trends in zooplankton dormancy dynamics, and their climatic underpinnings, are not understood. Nonetheless, most zooplankton species are sensitive to environmental cues that alter their hatching dynamics, and as a result may be particularly sensitive to climate change. Shifts in the timing, abundance or diversity of species that hatch as climate cues shift could scale up to impact the functioning and trophic structure of aquatic ecosystems (Winder & Schindler 2004; Woodward, Perkins & Brown 2010; Dossena et al. 2012).

In freshwater lakes, climate change is altering cues that terminate zooplankton dormancy by changing the timing of ice-free conditions in spring and average spring temperatures (IPCC 2013). In temperate and polar aquatic ecosystems, water temperature and photoperiod are

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considered the primary cues for terminating zooplankton dormancy (Stross 1966; Sorgeloos 1973; May 1987; De Stasio 2004). Many zooplankton have long-term dormancy strategies, where some proportion of eggs hatch in a given year and the remainder lay dormant, potentially hatching in subsequent years (Cáceres & Tessier 2003). Despite some overwintering under lake ice (e.g., Vanderploeg et al. 1992), most species produce eggs in the fall that hatch somewhat synchronously in the spring as day length and temperature increase (Hairston, Hansen & Schaffner 2000; but see De Stasio, 1990), producing a seasonal succession in the taxa that appear (Hutchinson 1967).

A major challenge to predicting the impact of climate change on dormancy dynamics within ecological communities is that hatching rates, or termination of dormancy, are likely to differ across latitudes, even for similar taxa (Posledovich et al. 2015). In regions where active individuals fail to reproduce in some years, species are predicted to have lower average hatching rates (Cohen 1966; Levins 1969; Ellner 1985). As a result, the prevalence of dormancy has been shown to increase towards the poles in some taxa, such as plants and insects, because high seasonal variation and short growing seasons have selected for dormancy (Mousseau & Roff 1989; Molina-Montenegro & Naya 2012). This “temporal dispersal” strategy, referred to as bet- hedging in the evolutionary literature (e.g. Venable 2007), and storage in literature on species coexistence (e.g., Chesson 1994), maintains long term persistence by decreasing the mean and variability of population growth among years (Slatkin 1974; Ellner 1985).

In addition to a gradient in hatching rates across latitudes, strong selection for high latitude species to emerge and reproduce in a short growing season may result in a gradient of sensitivity to the cues that break dormancy (Conover, Duffy & Hice 2009); the importance of fast emergence from dormancy may be reduced in lower latitude regions with longer growing seasons (Masaki 1961). As a result, conditions that are typical of an ideal spring (warm temperatures during a short photoperiod), may elicit higher and faster hatching rates in northern compared with southern lakes. More generally, the interplay among latitude, long-term dormancy and phenology is expected to lead to latitudinal differences in hatching rates and cues that correspond to differences in species’ traits (species sorting, e.g., Whittaker 1975) as well as differences among populations of widespread species (local adaptation; e.g., Kawecki & Ebert 2004). 59

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A second challenge to predicting the effects of climate on dormancy lies in determining whether co-occurring taxa have qualitatively similar responses to changing climatic cues. When most species in a community are limited by similar environmental constraints, responses to climatic cues should be similar, as has been seen for some annual plants (Elmendorf & Harrison 2009). However, the major zooplankton taxa have very different rates of development (Gillooly 2000), minimum sizes at which reproduction occurs (Geller 1987; Maier 1994), and reproductive modes and, as a result, rates of reproduction (Allan 1976). These differences may lead to a systematic divergence in responses to the climatic cues that terminate dormancy, with smaller taxa being more responsive to temperature (Winder & Schindler 2004; Adrian, Wilhelm & Gerten 2006). In addition, species that have dormant stages may coexist by specializing on environmental conditions that occur in only some years (via the storage effect; Chesson 1994). Indeed, the sensitivity of zooplankton to hatching cues can differ at several taxonomic levels, from broad zooplankton taxa (copepods, cladocerans and rotifers), to co-occurring species within lakes (e.g., Dupuis & Hann 2009). However, much of the literature on hatching dynamics has focused on subsets of the diversity within a lake by examining a single species or taxon at a time.

Despite the potential for different responses to cues that end dormancy across latitudes and among taxa, aquatic studies have yet to incorporate this complexity into studies of plankton dormancy dynamics to understand the effects of current and changing climatic conditions. Prior research has mainly focused on assessing dormancy dynamics in a small number of lakes within a region (e.g., Arnott & Yan 2002) or has combined lake samples into regional mixtures (e.g.,Vandekerkhove et al. 2005), precluding an analysis of latitudinal variation in hatching dynamics.

In this study, we determine how temperature and day length impact dormancy dynamics of freshwater zooplankton that differ in latitudinal origin. We collected sediment containing ‘egg banks’ from 25 lakes across an 1800 km latitudinal gradient and exposed a subsample of the sediment from each lake to a factorial treatment of high and low temperature crossed with long and short photoperiod. By assessing the effects of temperature and photoperiod on hatching abundance, diversity and phenology within each lake, we were able to test how these climatic cues drive biotic responses of taxa that co-occur across a latitudinal gradient. Based on the ecological and evolutionary factors considered above, we predicted that: 1) at higher latitudes, 60

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the density of eggs in the egg bank will increase, while under typical spring conditions the abundance of hatchlings will decrease at higher latitudes because selection for dormancy is higher in northern regions; 2) high temperatures will advance hatching phenology, and this advance will be greatest for small-bodied taxa; 3) conditions suggestive of a good, early season (warm temperature and short photoperiod) will generate the greatest abundance of hatchlings in northern lakes, because the ability to capitalize on favorable conditions is essential for persistence in those regions; and, 4) conditions typical of a late season (long days coupled with high temperature) will decrease hatchling abundance and diversity, and this effect will be strongest in northern lakes because they typically experience short growing seasons.

Materials & methods

Sample collection & experimental design

We collected sediment samples from 25 lakes along an 1800 km latitudinal gradient that ranged from southern British Columbia to the mid-latitude Yukon Territory in Canada in July 2011 (Fig. 4.1). The pelagic zooplankton community of these lakes had been previously characterized in the 1960s and 1970s (Lindsey et al. 1981; Patalas, Patalas & Salki 1994) and were again characterized in 2011 (Jones unpublished). Chemical and physical properties of lakes were also characterized in earlier studies, and were used to select lakes that showed no latitudinal patterns in these properties (Table S3.1 and Table S3.2 in Appendix B: Supplementary information for chapter 3; Fig. S4.1 in Appendix C: Supplementary information for chapter 4).

We used a 15” x 15” x 15”cm Eckman dredge to collect the top 5 centimeters of the sediment from nearshore areas, from a maximum depth of 20 m if shallower samples could not be collected (2 samples per lake which were combined). Most hatching occurs in nearshore environments (De Stasio, 1989; but see Hairston et al., 2000), which are characterized by higher temperatures and light levels as well as more substantial mixing events (Hairston & Kearns 2002). Eggs that settle in the deeper parts of the lake require mixing events to re-suspend and transport them to the sediment surface in shallower nearshore waters (Kerfoot et al. 2004). Previous work investigating egg viability through time has provided mixed results; some studies show that egg quality declines with age (e.g.,Weider et al., 1997), while others have found that 61

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viability is maintained through time for decades to hundreds of years (e.g., Cousyn & Meester 1998). Our collection was designed to maximize egg collection by targeting depths where eggs settle but would still be likely to re-suspend through mixing events. Because our sampling was consistent across lakes, and eggs from deeper waters can hatch when incubated under nearshore conditions (Cáceres & Tessier 2003), we expect our results to reflect general trends.

Figure 4.1 Map displaying the location of the 25 lakes in western Canada that were sampled for sediment in July 2011.

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The collected sediment was packaged in black whirlpak bags to eliminate light then stored in the dark at 4º C in a refrigerator (to simulate the conditions of a lake bottom to maintain dormancy) until the experiments were initiated in 2012. We determined the density of copepod, cladoceran and rotifer eggs using the sugar floatation method on a 100g subsample of sediment (Marcus 1990). We identified different types of eggs by morphology and counted the eggs of cladocerans (eggs within undamaged, unopened ephippia), rotifers and copepods. Cyclopoid copepods diapause as juveniles (Ferrari & Dahms 2007), therefore our egg counts of copepods refer to the density of calanoid eggs only.

To mimic spring conditions when the bulk of hatching occurs (Hutchinson 1967; Hairston et al. 2000), we compiled thaw dates for our focal lakes using national (Polar Data Catalogue) and international (The National Snow and Ice Data Center) databases. We determined average ice thaw dates by converting annual thaw dates into Julian dates and taking the average from 1971- 2000. The average day length and air temperature for that month was recorded to determine appropriate treatments. We were unable to collect this information for all lakes, but had data for lakes across our entire gradient and used typical conditions from northern and southern lakes for our treatments (Table S4.1).

Our experimental treatments were designed to simulate a nearshore aquatic environment, as the majority of spring hatching occurs in the littoral zone for freshwater crustaceans (Cáceres & Schwalbach 2001; Cáceres & Tessier 2003). Our experiment crossed temperature (two levels; 8 ºC and 12ºC) and light (16 hours and 12 hours), which represent the approximate mean spring temperatures and photoperiods at the northern limit and southern limit respectively. We conducted the experiment in a growth chamber, by setting up 10 racks that each had a single photoperiod treatment. Within these treatments, we randomized the placement of 20 water baths (each bath was 76” x 56” x 27”cm), with water baths randomly assigned to racks and equally divided between two temperatures. We then placed egg banks from five lakes inside each bath, with the egg banks housed in their own 7-litre aquaria (Fig. S4.2; Table S4.2). Thus, the treatment combination was nested in bath and rack, which we account for using a mixed model (below). We used submersible heaters to increase water temperature and water pumps to circulate water within each bath. We enclosed each rack with shade cloth to eliminate

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surrounding light. After 12 hours, lights in the short-day treatment would turn off, while the 16 hour photoperiod treatment would receive light for an additional four hours. For each lake, we divided the sediment into four samples of 75 grams, and randomly assigned each sample to a temperature by light treatment (temperature x light x 25 lakes = 100 experimental units; Fig. S4.2; Table S4.2). By incorporating the lake as a random effect we were able to account for the lack of independence among treatments (see data analyses section). However, because each lake was exposed to each treatment combination only once, we do not have an estimate of error for each lake within a treatment. The sediment layer was spread evenly to < 1 cm thick across the aquarium, such that all eggs were close enough to the sediment surface to experience treatment conditions.

To create a suitable environment for zooplankton, aquaria were filled with four litres of fresh artificial Daphnia medium (ADaM) and four phytoplankton species (Ankistrodesmus sp., Chlorella vulgaris, Scenedesmus obliqous, Pseudokirchneriella subcapitata; approximately 30 x 106 cells of each species). We replenished the ADaM and phytoplankton every 6-10 days, and topped up the mesocosms with dechlorinated water as needed every three days.

The experiment ran for sixty days, with zooplankton collected from each aquarium every three days. To collect zooplankton, we created polycarbonate (lexan) inserts that were the length of the aquaria and 1 cm deep. The inserts were placed in the bottom of the aquaria prior to the initiation of the experiment. We also created 20µm mesh filters that were designed to exactly fit the dimensions of the aquaria. To collect the plankton that hatched, we conducted a single “sweep” by anchoring the filter on the lexan guide rails at one end of the aquarium, then gently pushing the filter through the water, along the length of the aquarium. This method moderately disturbed the sediment layer, but this layer remained < 1 cm deep.

On sampling days we counted all copepods, cladocerans and rotifers. At the same time, we identified juvenile crustaceans to the family level (cladocerans) or order level (copepods) using a dissecting microscope. We did not identify rotifers, therefore the analysis and discussion of zooplankton diversity refers to the crustacean community only. Crustacean zooplankton juveniles were individually reared in 50 ml centrifuge tubes. We maintained individuals by

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transferring them every 3-7 days into fresh ADaM and feeding them approximately 30 x 106 cells of a mixture of the four phytoplankton species previously described every three or four days. Following the rearing process we identified the individuals that survived to maturity (65%). The individuals that did not survive to maturity could only be included in the abundance analysis as they were not identified to species or genus.

Data analyses

We used R statistical software for all analyses (R Core Team, 2014). We tested for a relationship between latitude and the density of dormant eggs (log transformed to account for heteroscedasticity of residuals) using a linear mixed model (lmer function in lme4 package; Bates et al., 2014). Taxon, latitude and their interaction were included as fixed factors and lake as a random factor.

In all analyses (egg density, phenology abundance, and diversity), we began with the most complex model for fixed effects and dropped higher order terms if they did not significantly improve model fit (using log likelihood ratios based on maximum likelihood) until we arrived at a best-fit model. All random effects were kept in models, as these reflected known constraints on sampling (i.e., a random effect for lake as each lake was used in all four treatment combinations) and on experimental design (a random effect for bath nested within rack to account for the nesting structure). We initially explored the effect of number of eggs on emergence dynamics. However, egg number was not a significant predictor of abundance or diversity in any group (all P values > 0.20), and we therefore discuss the difference in these responses qualitatively instead of including egg number as a covariate in abundance and diversity analyses.

To test for changes in phenology, we calculated the first hatching day and the time for 50% of individuals to hatch for each taxon (cladocerans, copepods, rotifers) in each lake over the 60 day experiment. We fit linear mixed models with a Gaussian distribution and the same fixed factors and random factors as described previously. A single lake, Watson, was an outlier and drove a 3 way interaction (Table S4.3 and S4.4) so we removed it from all subsequent phenology analyses.

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We determined how our treatments affected the number of hatchlings of copepods, cladocerans and rotifers using generalized linear mixed models with a Poisson distribution and a log link function. To account for a non-linear trend in the hatching rates across the latitudinal gradient, we created a second order polynomial latitude variable (after centering latitude), which accounted for the curvature in the data relationship. Initial models included latitude, latitude2, temperature (8 or 12 °C), day length (16 h or 12 h), and taxon (copepod, cladocerans, rotifer), and their interactions as fixed effects. The individual lake was included as a random effect and the experimental water bath nested within the shelf rack was added as an additional random effect. Zooplankton hatching was calculated as the total number of individuals that emerged over the 60 day duration of the experiment. If we detected a significant 4th order interaction (temperature x photoperiod x latitude x taxon interaction), we fit the models separately for each taxon as the scale differed among taxa by orders of magnitude.

To test how seasonal cues impact crustacean hatchling diversity across latitudes, we used a similar statistical approach. The predictor variables for the initial full model contained latitude, latitude2, temperature, day length, and taxon (copepod or cladoceran), and their interactions as fixed effects, and the same random effects as in the abundance analysis. For our response variable, we developed a ‘proportional diversity’ measure that counted the number of species that emerged relative to the total number of species found in the lake [based on previous standardized sampling from the lakes (Lindsey et al. 1981; Patalas et al. 1994) and samples that we collected following the same methods in 2011 (Jones unpublished)]. The proportional diversity approach allowed us to account for differences in species richness among the lakes, which also shows a latitudinal trend (Fig. S4.3). Our resulting data were binomial (hatching species/total species), and analyzed using a generalized linear mixed model with a logit link function. As with the hatchling abundance analysis, we fit models separately for each taxon after detecting a significant 4th-order interaction.

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Results

Zooplankton eggs

We found a significant effect of taxon (F = 11.5, P < 0.0001) and latitude (F = 7.6, P = 0.010) on the density of zooplankton resting eggs. Contrary to our prediction, the density of eggs declined latitudinally for all taxa (no latitude x taxon interaction; F = 0.71, P = 0.50), but each taxon differed in their average egg density at a given latitude (Fig. 4.2).

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Phenology

Phenology was affected by temperature and latitude. Higher temperatures advanced the first and median hatching day (Fig. 4.3; Table S4.3 and S4.4) for all taxa. The magnitude of the temperature effect depended on taxon, but not in the way that we expected; the hatching of the smallest taxon, rotifers, advanced the least (Fig. 4.3). The days to hatch was advanced the most for cladocerans, by approximately 10 days, followed by copepods ~ 5 days and rotifers by ~ 2 days. The patterns were qualitatively similar for the first and median days to hatch, except that rotifers took the longest to reach 50% hatching, likely due to their higher abundances. For the first hatching day, temperature caused the order of emergence among taxa to reverse at 12°C relative to 8°C. The time for 50% of individuals to hatch was slightly affected by latitude for copepods (t = 2.92, P = 0.004) and rotifers (t = 2.34, P = 0.02) (Table S4.3). Day length did not impact phenology (all P values > 0.20).

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Hatchling Abundances

The abundance of hatchlings of each taxon was affected differently by latitude, temperature and photoperiod (temperature x photoperiod x latitude x taxon interaction; F = 34.30, P < 0.001). The abundance of cladocerans that hatched varied with temperature and day length, but the effects of these cues depended on the latitude of the lake (significant temperature x photoperiod x latitude interaction, χ2 = 33.6, P < 0.0001; Fig. 4.4a,b; Table S4.5). Warmer conditions and long days caused a greater number of individuals to hatch in low latitude lakes, but not in high latitude lakes (Fig. 4.4b). In contrast, in the low temperature treatment, latitude and photoperiod had no effect on the abundance of cladocerans that hatched (Fig. 4.4a).

For copepods, the number of individuals hatching peaked at mid-latitudes (~ 56 °N), with the height of this peak differing by treatment (Fig. 4.4c,d); higher temperatures and longer days led to more copepods hatching (significant third order interactions; linear = χ2 = 8.6, P = 0.0034, non-linear = χ2 = 7.9, P= 0.005; Table S4.5).

The abundance of rotifers that hatched was greatest at low latitudes (Fig. 4.4e,f). However, unlike the crustaceans, the greatest abundance of rotifer hatchlings occurred at the higher temperature and shorter photoperiod treatment (Fig. 4.4f). In particular, the higher temperature caused a large increase in rotifer hatching in the 12 hour photoperiod treatment (solid lines in Figs. 4.4e,f), and caused a more modest increase in the 16 hour photoperiod treatment (dashed lines in Fig. 4.4e,f; significant third order interaction, χ2 = 131.7, P < 0.0001; Table S4.5). Together these results provide mixed support for our hypotheses that hatching will be higher at low latitudes and that early spring conditions will increase hatching in northern lakes. Under simulated spring conditions, hatching declined at higher latitudes for copepods and cladocerans, however these conditions caused higher hatching for rotifers.

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Figure 4.4 The effect of temperature and photoperiod on the emergence of (a-b) cladocera individuals, (c-d) copepods individuals, and (e-f) rotifera individuals that hatched from 25 lakes across a 1800 km latitudinal gradient in western Canada. Emergence is summed by lake across the 60 day sampling period. Data points are the abundance of hatchlings + 1. Lines are the fitted curves for a general linear mixed model for Poisson distributed data using a log link function. Note that the y-axes are presented on a logarithmic scale.

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Hatchling Diversity

In total, 406 individual crustaceans hatched from the egg banks (9 cladoceran species and 9 copepod species, Table S4.6) which represent 41% of the species documented in these lakes. Thirty-five percent of the hatchlings did not survive to adulthood, but survival did not differ between copepods and cladocerans (χ2 = 2.0, P = 0.16). Due to potentially confounding patterns in crustacean diversity with latitude (Fig. S4.3), we tested for trends in relative diversity by examining the proportion of species present in each lake that emerged – our relative diversity measure therefore calculates the fraction of species in each lake that were both present in the egg bank and responded to our experimental treatments. The relative diversity of species that emerged differed between cladocerans and copepods, and these diversity responses were distinct from abundance responses for both taxa (temperature x photoperiod x latitude x taxon interaction; χ2 = 5.14, P = 0.0233). When all crustaceans species were considered together, diversity showed a unimodal trend with latitude (χ2 = 5.5, P = 0.002), with the location of the peak in diversity depending on photoperiod (significant photoperiod x latitude interaction, χ2 = 9.4, P = 0.002; Table S4.7; Fig 4.5a,b).

Cladoceran diversity responded strongly to photoperiod and latitude, but not temperature (photoperiod x latitude interaction, χ2 = 5.5, P = 0.02; temperature, χ2 =2.3, P = 0.13; Fig. 4.5c,d). In the longer (16 hr) photoperiod, the relative diversity of cladoceran species that hatched was the highest at low latitudes, whereas in the shorter photoperiod treatment relative diversity was greatest at high latitudes (Fig. 4.5 c,d).

Copepod diversity varied with temperature and day length, but the effects of these cues depended on the latitude of the lake (significant third-order interactions; linear χ2 = 8.8, P = 0.003, quadratic χ2 = 4.00, P = 0.046; Fig. 4.5e,f; Table S4.7). We predicted that conditions typical of a late season (long days coupled with high temperature) would decrease the diversity of the hatching community; however, diversity was highest at mid latitudes, with 30% or more of species emerging when day length was short and temperatures were low. Copepod diversity was lower in the warmer temperature treatment, with the maximum peak of approximately 20% of species hatching (Fig. 4.5f). Interestingly, the treatment that combined long day length and low temperatures had higher copepod diversity in lower latitudes (Fig. 4.5e). 71

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Figure 4.5 The effect of temperature and photoperiod on the proportion of the (a-b) total crustacean diversity, (c-d) cladoceran diversity and (e-f) copepod diversity that hatched from 25 lakes across a 1800 km latitudinal gradient in western Canada. Diversity is summed by lake across the 60 day sampling period. Data points are the proportion of species that hatched. Lines are the fitted curves for a general linear mixed model using a logit link function. 72

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Discussion

Our study demonstrates that several responses of zooplankton resting eggs to hatching cues change with latitude, and that the pattern of this change differs among taxa. Our assessment of the effects of day length and temperature on the phenology, abundance and diversity of zooplankton communities is the first to systematically collect egg banks from across a latitudinal gradient. In doing so, we have shown that cues associated with changing climate can have consistent (phenology) or distinct (abundance, diversity) effects at different latitudes, indicating that we cannot accurately predict responses to climate change without considering how these factors interact across biologically diverse landscapes.

Contrary to our hypothesis, phenological shifts in response to temperature caused the relative order of the first hatching to reverse for the three taxa (Fig. 4.3). At 8°C, phenological patterns were consistent with previous research, with rotifers hatching first and cladocerans hatching last, but rotifers showed a surprising lack of phenological response to temperature, thereby reversing the relative order of first appearance. Our phenology results are partially consistent with field research, which has shown that crustacean zooplankton dominating the water column in early spring (i.e., cladocerans) are more sensitive to temperature than later successional taxa (i.e., copepods) (Adrian et al. 2006). It is, however, inconsistent with a meta-analysis that spanned many species and showed that high temperatures advance phenology, but that species with the smallest egg sizes always tend to emerge first (Gillooly & Dodson 2000b). For rotifers, our taxa with the smallest eggs, we clearly did not see this pattern. Similarly, Winder and Schindler (2004) used long-term monitoring of a single lake to show that rotifer populations advanced their phenology over a 40 year period of warmer springs whereas cladocerans did not. Although we do not have an explanation for the reversal of hatching times observed, our results suggest that elevated spring temperatures have the potential to alter the order that zooplankton hatch in lakes. Given the importance of phenological differences for competitive and successional dynamics, further verification of this trend and its causes are important for aquatic ecology.

Beyond phenological changes, the effect of climate on community composition can be quantified through two general responses: changes in abundance of specific taxa and changes in diversity. Numeric and diversity effects are frequently considered inter-dependent as they are often 73

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correlated in nature (via the species-accumulation curve; e.g., Ugland et al., 2003), suggesting that higher hatching rates should translate into a greater proportion of the community emerging. However, abundance responses appear to have been influenced by high hatching rates from a subset of species, as our results show that copepods and cladocerans have qualitatively distinct abundance and diversity responses (compare Fig. 4.4 and Fig. 4.5). For example, the higher temperature increased the abundance of cladocerans in the long photoperiod treatment, but did not impact cladoceran diversity. A similar result was found by Preston & Rusak (2010), who showed that temperature effects manifested as a numerical response, have little impact on diversity. However, those authors linked ice-off date with community composition and found that spring warming reduced zooplankton density, while in our study the higher temperature treatment generally increased hatching. Overall, this difference between numeric and diversity responses suggests that the effects of climate change can manifest by favouring a small subset of species and by simultaneously altering the diversity of communities.

The effects of climate cues on zooplankton hatchling diversity offers new insights into how climate can differentially structure community dynamics across latitudinal gradients. We expected that hatching rates would be greatest in southern latitudes, where growing seasons are longer and climatic conditions are milder. Surprisingly, the dynamics we observed were more complex, and could not have been predicted from a geographically and taxonomically restricted study. In particular, cladoceran diversity was only influenced by photoperiod, with a longer photoperiod increasing diversity at low latitudes, but decreasing diversity at high latitudes (Fig. 4.5). The reversal of the day length effect at high latitudes is consistent with our hypothesis that northern zooplankton may experience strong selection to emerge and reproduce in a short growing season, causing northern populations to be locally adapted to those conditions (Kawecki & Ebert 2004; McNamara & Houston 2008). However, when we investigated the hatching dynamics of three common species (copepods: Diaptomus sicilis and Hetercope sepentrionalis; cladoceran: Ceriodaphnia lacustris), we did not detect evidence for local adaptation. Instead, differences among populations of widespread species were idiosyncratic (Fig. S4.4), suggesting that the apparent consistency with our hypothesis was due to species sorting effects. We note, however, that our experiment is not well-suited to testing local adaptation because we have no measure of individual fitness and no control of maternal effects; more targeted tests of local

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adaptation in plankton from across latitudes would be valuable. Our results, which effectively average the effects of climate cues over species that change along the latitudinal gradient (Patalas et al. 1994), indicate that northern cladoceran communities respond positively to shorter days, as is predicted when growing season is limited (Conover et al. 2009) or shorter day length corresponds with increases in food availability (Cáceres & Schwalbach 2001).

Differential responses of taxa to climate cues also challenge simple models for community change across latitudinal gradients. Space-for-time substitutions, which are often employed where temporal replication is difficult, can be a powerful tool to predict community or population level responses to climate change (Pickett 1989). If experimental temperature responses are correlated with the temperature response across latitude in nature, then a space-for- time substitution would capture how the community will respond to climate change (Dunne et al. 2004). Our experiment revealed that numeric and diversity responses of zooplankton to temperature and photoperiod can differ across latitude, suggesting that we may be unable to construct predictions for how temperature will alter community composition based on spatial patterns of temperature responses.

An important question that arises from our study is how our findings can be generalized to different habitats and organisms. Marine plankton, for example, differ from freshwater plankton in that long term dormancy is less prevalent overall (Hairston & Cáceres 1996), potentially because of the more continuous nature of the marine realm. However, the hatching of marine zooplankton is also influenced by temperature and photoperiod (Uye, Kasahara & Onb 1979; Preziosi & Runge 2014), but more work is needed to understand how these dynamics vary latitudinally. In addition, extrapolating our results to latitudes beyond our sampling sites is challenging due to the complexity of the responses we observed. Future work should extend sampling to determine whether egg banks continue to increase at low latitudes, and assess patterns in hatching dynamics. In most cases we see declines in hatching at the northern extreme of the latitudinal gradient that we sampled, but species persist at (and beyond) these latitudes (Patalas, Patalas & Salki 1994), raising questions about the nature of this latitudinal variation that should be addressed with more detailed studies within and across species.

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Life-history differences among zooplankton are likely candidates for the different responses to light and temperature that we observed, and may be generally useful for predicting responses to changing climate cues. Cladocerans are born as miniature adults and are facultatively sexual, reaching reproductive maturity in 5-10 days at 20°C (Geller 1987). In contrast, copepods are obligately sexual and have a development time of 20 - 42 days at 20°C depending on species (Maier 1994). Fast generation times and parthenogenesis cause cladocerans to have higher growth rates than copepods (Allan 1976), and may structure differences in the successional niches of these taxa (Adrian et al. 2006). Growing season lengths declines latitudinally (Environment Canada 2014), and lower temperatures that are characteristic of northern lakes slow development of all zooplankton (Gillooly 2000). This time constraint could be especially acute for copepods because of their comparatively long development times. Moreover, when cladocerans undergo sexual reproduction they have large egg size to adult body size ratios compared to copepods, leading to relatively long development times for the egg stage (Gillooly 2000). This systematic difference between taxa may impose different selection pressures on the initiation of egg development in response to environmental cues. For example, the relatively slow development rates of sexual cladoceran eggs into juveniles may cause cladocerans to be more strongly impacted by longer-term environmental conditions, as may be signaled by day length.

Although we were unable to quantify rotifer diversity in our lakes, we saw that rotifer abundance responded to temperature and that the size of this response depended on day length (Fig. 4.4). Our results for rotifers supports previous work that used a 40 year time series to show that the abundance of rotifers can increase in response to spring warming (Winder & Schindler 2004). Rotifers play a critical role in lakes by acting as a food source for crustacean zooplankton (copepods and cladocerans) and by facilitating nutrient cycling by consuming bacteria, detritus and algae (Hutchinson 1967; Bogdan & Gilbert 1982; Arndt 1993). The strong, positive effect of short days and high temperature on the abundance of rotifers that hatch raises the possibility that changing climate cues could greatly increase rotifer abundances, and thus alter nutrient cycling and the supply of food to higher trophic levels.

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Interestingly, the abundance and diversity responses of zooplankton were not related to the density of eggs in lake sediment, which declined latitudinally for all taxa (Fig. 4.2). This pattern of declining egg density may be due to the negative correlation between season length and latitude, reducing the number of generations per growing season in the north (Corbet, Suhling & Soendgerath 2006). However, in addition to lower voltinism in higher latitudes, the density of eggs in lake sediment is also a consequence of the accumulation of eggs that are produced but do not hatch the following year. Because of short growing seasons and lower temperatures, we predicted this unhatched fraction to represent a greater proportion of eggs produced at higher latitudes. Egg density is ultimately the product of both processes; the reservoir of eggs declines with latitude because of lower voltinism, but the fraction of these eggs that hatch determine the number that remain in the sediment. Our study suggests that the latter of these two processes is unlikely to account for differences in egg densities, as hatchling densities were not universally higher in northern lakes for any of the taxa studied (Fig. 4.4).

Our investigation of the effects of temperature and day length on the termination of dormancy is one of the first to choose communities that differ in latitudinal origin. In doing so, we have demonstrated that the sensitivity of zooplankton to temperature and day length can differ across latitude and between co-occurring taxa, a result that would be obscured if we selected communities from the same region. By considering how climatic cues may shift dynamics across latitudes, we were able to provide new insights that suggest changes in dormancy dynamics with spring warming may be an under-appreciated but important consequence of climate change, and could lead to zooplankton community shifts that will depend on latitudinal origin.

Acknowledgments

We thank A. Barany, E. Chojecka, V. Jones and N. Lo for sampling assistance and members of the Gilbert lab for helpful comments on a previous version of this manuscript. We also thank the Editor and two anonymous referees whose comments improved this manuscript. This work was supported by NSERC (B.G., Discovery Grant) as well as Ontario Graduate Scholarships (N.T.J.).

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Chapter 5 Geographic signatures in species turnover: decoupling colonization and extinction across a latitudinal gradient

In review as Jones, N.T., & Gilbert B. Geographic signatures in species turnover: decoupling colonization and extinction across a latitudinal gradient. Global Ecology & Biogeography

Abstract

High latitude areas are characterized by low species richness and rapid warming with climate change. As a result, temporal turnover of communities is expected to be greatest at high latitudes. We assess colonization and extinction rates of zooplankton through time across a latitudinal gradient to test this prediction, and further test whether species-specific rates are predicted by body size local abundance, or regional occupancy of lakes. Lakes across an 1800 km latitudinal gradient in western Canada (49°N - 64°N).We resampled zooplankton communities from 43 lakes that had been sampled 25-75 years previously. We evaluated temporal turnover of copepod and cladoceran species using Sorensen dissimilarity, colonization and extinction. We tested whether lake-level turnover, colonization or extinction changed with latitude. We also tested whether species-level differences in colonization and extinction were explained by body size, local abundance (abundance when present in a lake), and regional occupancy. Lake-level temporal turnover was highest at low latitudes due to by higher colonization rates at lower latitudes, and consistent extinction rates across the latitudinal gradient. At the species level, colonization increased with regional occupancy, and tended to increase for abundant species with small body sizes. Local extinction rates decreased with local abundance and regional occupancy, but were not influenced by body size. Contrary to expectations, low-latitude zooplankton communities are changing faster than high-latitude communities and becoming more species rich. Moreover, colonization and extinction trends suggest that lakes have become increasingly dominated by species with smaller body sizes and that are already common locally and regionally. Together, these findings indicate that rates of species turnover in freshwater lakes across the latitudinal gradient are not predicted by rates of temperature change, but that species

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turnover is nonetheless resulting in trait-shifts that are consistent with predictions for temperature change.

Introduction

Species turnover through time has long fascinated ecologists, with classic theories positing that that local and biogeographical properties of communities determine rates of turnover (Elton 1958; MacArthur & Wilson 1967; May 1973). Recently, there has been renewed interest in the factors that promote temporal turnover. Classic work on species-time relationships suggest that turnover dynamics are partially the consequence of island biogeography or metapopulation processes (Rosenzweig 1998; Nuvoloni, Feres & Gilbert 2016) whereas more recent research has focused on how global climate change is modifying the latitudinal range of many species, thereby altering the composition of communities (Chen et al. 2011; Burrows et al. 2014). Species dynamics in the anthropocene are increasingly influenced by a mixture of metapopulation and anthropogenic processes (Helmus, Mahler & Losos 2014). As a result, determining patterns of species turnover through time and across broad spatial scales is increasingly important for conservation and basic ecology (Wolkovich et al. 2014).

Temporal turnover is the outcome of a variety of dynamic processes that result in two changes to local diversity: gain of species through new colonization events and loss of species through local extinction events (Anderson 2007). Island biogeography and metacommunity theory highlight how the relative importance of colonization and extinction may differ across regional gradients (MacArthur & Wilson 1967; Leibold et al. 2004; Viana et al. 2015). Although these theories make general predictions about characteristics of patches and species that may lead to qualitatively different patterns of diversity and turnover, empirical patterns are often far more complex than suggested from these models (Matthews & Pomati, 2012; Jones et al. 2015). The observed complexity is due to an incredible variation in the importance of dispersal limitation, local interactions and species-environment relationships among ecosystems that make predictions of turnover for any particular community difficult (Shurin et al. 2007; Bennett et al. 2010; Matthews & Pomati 2012; Jones et al. 2015). This challenge is particularly difficult for studies across latitudinal gradients, because there is a simultaneous change in three determinants

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of turnover: environmental conditions, species traits, and the composition of communities (James, 1970; Parmesan, 2006; Jones & Gilbert 2016).

Latitudinal gradients in environmental conditions and anthropogenic change set the stage for spatial directionality to community change over time. In North America, mean temperatures decline northward along a latitudinal transect and long-term data indicates that during the last 100 years, temperatures have increased more in northern regions (IPCC, 2013; Environment Canada, 2014). As a result, mean temperature and temperature increases are negatively correlated across a latitudinal gradient, rendering high latitude sites more vulnerable to the effects of climate change (e.g., Smol et al., 2005). However, geographic gradients in other aspects of global change suggest that the opposite pattern could occur. Specifically, larger human populations and urbanization characterize lower latitude regions. This increased anthropogenic pressure has led to land-use changes at lower latitudes, such as higher road density and increased recreational use of natural areas (Gayton, 2007; Ministry of Forests, Mines and Lands, 2010), which have increased connectivity among discrete habitats such as lakes (Kelly et al. 2012). Given the more pronounced temperature changes at high latitudes and the increased anthropogenic pressure at southern latitudes, the resulting effect of these global changes on colonization-extinction dynamics across latitudinal gradients remains unknown.

In aquatic communities, two life-history characteristics are hypothesized to drive colonization and extinction dynamics of zooplankton: body size, and the local abundances of species. Local abundances reflect a suite of traits that determine the impacts of intra- and inter-specific interactions and resource specialization, and are often broadly defined as species carrying capacities (Levin 2009). From a metapopulation or meta-community perspective, high local abundance buffers against local extinction, and also provides more propagules that can disperse to other lakes (Hanski 1994), and thus is commonly related to occupancy, or the proportion of lakes where a species is found (Hanski, Kouki & Halkka 1993). Likewise, body size affects both local and regional distributions. Locally, body size may structure competitive asymmetries among species (Gliwicz 1990) and also increase trophic position (Woodward et al. 2005). Body size can also indirectly impact local success if larger body sizes are associated with smaller population sizes and/or slower growth rate (Savage et al. 2004). Apart from these local effects, body size also directly influences colonization dynamics in passively dispersed organisms such 85

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as aquatic zooplankton, which are dispersed via wind, water or animals (Vanschoenwinkel et al. 2008). For these species, dispersal distance is negatively associated with body size (Soons et al. 2008; De Bie et al. 2012), with smaller individuals travelling further and more often. Together, the associations between body size and dispersal for passive dispersers suggest that traits conferring competitive dominance locally may come at the expense of dispersal among lakes, making the overall impact of body size difficult to predict in a regional context. Moreover, body size is a trait that often changes with latitude. Bergmann’s rule and James’ rule, for example, describe how body size within and among species increases in cooler regions, and thus increases with latitude (James 1970). Because body size-latitude relationships in ectotherms can be highly variable (Shelomi 2012b), it is important to quantify the joint and independent effects of latitude and body size on species turnover to understand proximate and ultimate causes of diversity patterns with latitude.

Differences in species diversity across latitudes are also predicted to impact patterns of turnover. Higher latitude regions contain fewer species on average (Shurin et al., 2007; Jones & Gilbert, 2016) and low diversity is expected to be associated with high rates of temporal turnover. This prediction arises from two hypotheses in community ecology. First, because species diversity is positively correlated with phenotypic variation, elevated diversity could reduce opportunities for new species to establish even when they are no longer limited by climate (Elton 1958). Second, diversity is predicted to stabilize community composition by increasing the number of weak interactions in food-webs, which reduce large fluctuations in predators and their prey (McCann et al. 1998). When considered in terms of latitudinal patterns of diversity, these competitive and food-web models predict higher turnover (lower stability) in high latitude communities.

In this paper, we investigate temporal turnover in freshwater zooplankton communities from across an 1800 km latitudinal gradient in western Canada that has shown typical shifts in temperature over the past 70 years (Fig. 5.1a,b). Zooplankton are ubiquitous ectothermic animals in freshwater lakes that form the basis of lake food-webs, and display a latitudinal gradient in species diversity and composition typical of many organisms (Fig. 5.1c,d). We resampled zooplankton communities that were originally sampled fifty years ago on average, and asked the following four questions: (1) Is there evidence for a latitudinal trend in species turnover? (2) How do colonization and local extinction events within lakes structure this temporal turnover? 86

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(3) Are body size, local abundance and occupancy predictive of species’ colonization and local extinction rates? And, if so, (4) do body size and local abundance change predictably with latitude?

Materials & methods

Study system & species sampling

This study was conducted in freshwater lakes across a ~1800 km latitudinal gradient in Canada, ranging from southern British Columbia to the middle of the Yukon Territory (Fig. 5.1a). Long- term temperature averages indicate there is a positive relationship between latitude and the magnitude of temperature warming across our study sites during the last 100 years (Fig. 5.1b). Lakes that are closer together have more species in common (Fig. 5.1c) and species richness declines at higher latitudes (Fig. 5.1d).

Using data from Patalas et al. (1994), we systematically selected 43 lakes that were originally sampled between 1939-1986 (details on how we accounted for differences in time between historic and contemporary samples are given in the data analyses section below). We chose lakes that spanned the latitudinal gradient and had similar levels of known environmental variables (phosphorus, nitrogen, turbidity, etc.). We followed the original collection methods of Anderson (1974), Lindsey et al. (1981) and Patalas et al. (1994), and sampled in the same season (July 4 - July 28, 2011). To minimize any confounding effects of species succession through the growing season, we began sampling in the southern portion of the latitudinal gradient, sampling some lakes as we moved north along the transect, and others as we returned south. Plankton communities were collected by hauling a Wisconsin net [mouth diameter 24 cm, net mesh 76 µm] through the water column, beginning from near the lake bottom, at the approximate center of each lake. Two vertical tows per lake were taken. Zooplankton were immediately preserved in 70% ethanol.

We combined the two replicate tows and randomly identified zooplankton, following the taxonomy of Thorp and Covich (2010) and Sandercock and Scudder (1994) and additional keys as needed, until we had identified at least 500 adult individuals. Some morphologically similar species could not be differentiated. In those cases, we decreased the taxonomic resolution to the

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generic or family level (e.g. Bosmina). This resulted in a consolidated species list, with 25 species/genera/families, making our estimate of turnover relatively conservative. For simplicity we refer to each grouping as a “species” throughout the manuscript.

We measured adult body size for 30 randomly selected individuals of each species for a subset of 19 lakes across the latitudinal gradient (Table S3.2). Body size of cladocera was measured from the centre of the eye to the base of the tail spine (Gliwicz 1990, Yurista and O’Brien 2001), while we measured the length of the prosome for copepods (Klein Breteler and Gonzalez 1988, Ban 1994). The historical relative abundance of zooplankton species was available for 31 lakes. We estimated local abundance by averaging the abundance of each species (or genus or family) across all the lakes they were present in the historical sampling dataset (Anderson 1974; Lindsey et al. 1981; Patalas 1990). In total, we had both body size and local abundance estimates for 14 species (Table S5.2). Finally, we determined historic occupancy for each species (hereafter simply ‘occupancy’) as the proportion of lakes historically occupied relative to all the lakes that fall within the latitudinal range of that species (see explanation of colonization, below).

We selected lakes to minimize differences in local abiotic factors, which can also impact diversity patterns (Dodson 1992; Hessen et al. 2006), so that differences in turnover could be attributed primarily to latitude. We verified this by characterizing a subset of physical and chemical characteristics of our focal lakes (Table S3.1 and Table S3.2 in Appendix B: Supplementary information for chapter 3). We quantified chlorophyll a (a measure of productivity) measurements mid-lake using a YSI 6-series multiparameter water quality sonde (Integrated Systems & Services, Yellow Spring, OH, USA). We used published estimates of lake size and depth from the literature (Anderson 1974; Lindsey et al. 1981).

Data analyses

To test how zooplankton communities have changed since the historical survey, we transformed the zooplankton species abundance matrix into a presence-absence data matrix for both time periods, then calculated two measure of community change: the total change in species richness and the Sorenson dissimilarity. Because we observed heterogeneity in variance, we used Generalized Least Squares (GLS) in the lme4 package in R (Bates et al., 2014; R Core Team, 2014) to determine how the total change in species richness and Sorenson dissimilarity changed 88

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across a latitudinal gradient. We accounted for differences in time between historic and contemporary samples by including historic sampling date as a covariate in community-level models; it did not improve model fit (Fig. S5.1 in Appendix D: Supplementary information for chapter 5; Table S5.3) and there is no correlation between sampling date and latitude (Fig. S5.2), so we do not report it further below.

We next determined how colonization and local extinction contributed to turnover (Table S5.1). We define colonization in a lake as the proportion of species in the contemporary survey that were not present in the historic survey, and extinction as the proportion of species present in the historic survey that were absent in the contemporary survey. This approach allowed us to account for differences in the species richness among the lakes, which showed a latitudinal trend (Fig. 5.1d). We analyzed latitudinal variation in colonization and extinction with a generalized linear model (GLM) using a quasibinomial error distribution and a logit link function.

We determined how body size, local abundance and occupancy influence colonization and extinction. In this case, the denominator for colonization and extinction were calculated for each species. For colonization, we extracted the latitudinal range of each species from Patalas (1994) and created a potential colonization data-frame by summing the number of times a species was not historically present in a lake that occurs within the maximum and minimum latitudinal distribution of that species – colonization was defined as the proportion of these potential lakes that were colonized in the contemporary sample. Occupancy was defined as the proportion of lakes within a species’ latitudinal distribution where it was historically found. Extinction was calculated as the proportion of lakes where a species was present in the historical sample and absent in the contemporary sample. Because colonization and extinction were binomial responses, they were analysed using GLMs with a quasibinomial error distribution to account for overdispersion. We conducted separate analyses to test whether body size and local abundance changed predictably with latitude and to test for a correlation between occupancy and local abundance.

We used linear mixed models to confirm that patterns in temporal turnover were not driven by three environmental factors that can also impact diversity patterns: lake size, lake depth and a measure of productivity (chlorophyll a) (Hessen et al. 2006).

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Results

We found a significant effect of latitude on temporal turnover; both the change in species richness (Fig. 5.2a; t = -3.19, P = 0.003) and species turnover declined with latitude (Fig. 5.2b; t = -2.96, P = 0.005; Table S5.4). The patterns of species gains and losses differed across the latitudinal gradient, with turnover primarily driven by colonization in the southern portion of the latitudinal gradient (Fig. 5.2c, z = -4.28, P < 0.0001) and local extinction rates showing no trend with latitude (Fig. 5.2d, z = -0.83, P = 0.41).

Body size, local abundance and regional occupancy influenced the frequency of colonization and local extinction among species, but in different ways (Table S5.5; Fig. 5.3). Colonization rates were highest for species that had high occupancy historically (Fig. 5.3c; t = 2.5, P = 0.03), and tended to be higher for small-bodied zooplankton (Fig. 5.3a; t = -1.02, P = 0.051), and species with high local abundance (Fig. 5.3b; t = 0.29, P = 0.061). Body size had no relationship with local extinction rates (Fig. 5.3d; t = 0.58, P = 0.38). However, locally abundant species and those with high historical occupancy were extirpated less often (Fig. 5.3e, t = -0.59, P = 0.003; and Fig. 5.3f, t = -3.18, P = 0.008).

To test whether body size and local abundance were independently predictive of colonization and extinction rates, we tested for the correlation between these traits and latitude. We detected no correlation between body size and local abundance (Pearson correlation test, r = 0.17, P = 0.52; Fig. S5.3), suggesting that, for this group of aquatic zooplankton, smaller bodied species do not have larger population sizes on average. Similarly, the average body size of crustacean zooplankton communities did not change across a latitudinal gradient (Fig.S5.4a; t = -0.53, P = 0.60), and there was no relationship between average local abundance and latitude (Fig. S5.4b; t = 0.53, P = 0.60). There was, however, a strong relationship between occupancy and local abundance of species (r = 0.70, P = 0.008; Fig. S5.5). Overall, these relationships show that species traits influence colonization and extinction rates independent of latitude, and suggest that

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Figure 5.1 Latitudinal patterns of diversity and temperature change. (a) Locations of the 43 lakes in this study; (b) the change in air temperature over 70 years, based on differences (present – past) of 30 years means: 1971 to 2000 – 1901 to 1930; (c) Species composition of zooplankton (first axis from a Nonmetric Multidimensional Scaling with a 2D solution [stress = 0.19] based on Sorensen dissimilarity), illustrating that closer sites are more compositionally similar; and (d) Zooplankton species richness with latitude. Data used in (c) and (d) pooled species in historic and current samples for each lake. Lines display the model fit for significant relationships at α = 0.05. Data for (b) was extracted from the Canadian Center for Climate Normals (URL:http://climate.weather.gc.ca/climate_normals/index_e.html)

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Figure 5.2 The relationship between latitude and (a) the change in species richness, (b) species turnover, measured using the Sorenson dissimilarity metric, (c) the proportion of new species per lake, and (d) the proportion of species that went locally extinct. All graphs compare historic zooplankton samples with contemporary samples (see methods). In (c) colonization = the number of species that colonized the lake / the contemporary species richness. In (d), extinction = the number of species that were locally extirpated / the historical species richness. Lines display the model fit if the relationship was significant at α < 0.05. We report correlation coefficients here, but the statistical tests for panels a and b were done using generalised least squares to account for error heteroscedasticity, while a generalised linear model with a quasibinomial error distribution was used for panels c and d (see data analyses section).

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Figure 5.3 Species traits influence colonization and extinction rates. The relationship between colonization and (a) zooplankton body size, (b) local abundance, and (c) occupancy. Bottom panels: the relationship between extinction and (d) zooplankton body size, (e) local abundance, and (f) occupancy. Local abundance is a species’ mean abundance when present, and occupancy is the proportion of lakes that a species historically occupied within its latitudinal range. Lines display the model fit if the relationship was significant (solid lines; P < 0.05) or marginal (hashed lines; 0.05 < P< 0.10).

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local abundance or regional occupancy reflect a common suite of species traits that influence colonization and extinction rates.

To ensure that our standardization of lake environments (other than temperature) was successful, we tested the relationship between turnover and lake size, maximum lake depth and productivity. None of these were significant (all P > 0.14, Table S5.6).

Discussion

Our study highlights how considering colonization and extinction leads to a richer understanding of the causes of latitudinal gradients in species turnover. We found that higher latitudes had lower turnover, a trend that has been observed in several latitudinal studies (e.g., Shurin et al., 2007; Korhonen et al., 2010; but see Soininen et al., 2004). However, by decomposing turnover into local losses and gains, we were able to attribute the spatial signature in compositional change to elevated colonization events in the southern portion of the latitudinal gradient. Moreover, our results suggest that species-specific patterns of turnover can be partially explained by commonly measured traits: body size, local abundance and regional occupancy. Together, these biogeographical and species-specific perspectives on colonization and extinction provide insights into the directions and rates of change in ecological communities across latitudes.

The latitudinal patterns of colonization and extinction that we document in this study may be important for understanding how climate influences community changes more generally. Although arctic and subarctic lakes are often considered to be “sentinels of climate change” (Adrian 2009), our results did not support the hypothesis that communities in high latitude lakes are more likely to show compositional shifts (Fig. 5.2). This result was surprising, given that these lakes have experienced larger changes in temperature (Fig. 5.1b), and also support less diverse assemblages of species (Fig. 5.1d). The apparent compositional stability of subarctic zooplankton communities through time may arise from several factors that together slow change in high latitude communities. First, relatively extreme seasonal fluctuations in environmental conditions may prevent new species from colonizing those sites directly by causing a higher variation in population growth rates (e.g., Lande, 1988) and by creating a shorter seasonal window in which colonization is possible. Second, shorter growing seasons may slow absolute

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population growth over the season, again increasing chances of stochastic extinction in newly establishing species or generating longer lags between colonization of sites and detection of species in high latitude lakes. Third, many zooplankton have long-lived dormant stages, which may buffer species from extinction across the latitudinal gradient (Jones & Gilbert 2016). Finally, these lakes thermally stratify in the summer months, but zooplankton species’ are distributed throughout the water column in the pelagic zone. Zooplankton may avoid extreme fluctuations by capitalizing on refugia below the thermocline, where cool waters persist throughout the summer months.

Instead of greater species turnover in northern lakes, our study shows a clear pattern of higher colonization in southern lakes. Interestingly, this increase arose without the addition of new species to the study, and thus suggests that lakes were either in disequilibrium in early surveys, or that the non-equilibrium dynamics observed have resulted from increased rates of colonization between surveys (~70 years). Although we cannot isolate the causal mechanism driving this pattern, the association between latitude and colonization events may reflect an increase in connectivity in lower latitude lakes. The southern portion of the latitudinal gradient in our study occurs in regions with relatively high anthropogenic influences, such as higher road density (Ministry of Forests, Mines and Lands, 2010) and larger human populations (Gayton 2007). As a result, dispersal limitation may be relaxed in those areas due to inadvertent movement via boats and bait fish with water (Kelly et al. 2012), facilitating the introduction of zooplankton into lakes. An increase in diversity is predicted by metapopulation and island biogeography theory in such cases, so long as local abiotic and biotic conditions do not prevent recruitment (Shurin 2000). The geographic distribution of many passively dispersed aquatic invertebrates is limited by dispersal (Bohonak & Jenkins 2003), therefore increased connectivity among lakes may be an important component of the anthropocene, altering the diversity of local communities.

Through linking body size, local abundance and regional occupancy to colonization and extinction dynamics, our results illustrate how trait-based approaches are useful for predicting turnover and metacommunity dynamics (De Bie et al. 2012; Jones et al. 2015). Body size is important for passively dispersed organisms, and our results support previous work which has shown that for passive organisms, larger individuals tend to colonize fewer sites. This is in contrast to active dispersers, where larger individuals normally sequester more resources and 95

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disperse farther (Shurin, Cottenie & Hillebrand 2009). The observation that temperature increases during the last 100 years has caused a reduction in the average body size of many organisms (Daufresne et al. 2009) raises the intriguing possibly that the direct effect of temperature on body size could indirectly increase dispersal rates for passively dispersed species.

Our results also support a growing number of studies that show a positive association between local abundance and occupancy (e.g., Soininen & Heino, 2005; but see Thompson et al., 1998). A number of mechanisms have been put forth to explain why this pattern persists across distantly related species (reviewed in Gaston et al., 2000). Although no single mechanism has emerged as the sole explanation for this pattern, the association between regional occupancy and colonization-extinction dynamics has important implications for predicting species range expansion and extinction. Specifically, if the proportion of inhabitable lakes a species occurs in is known, detailed abundance data may be unnecessary to estimate how vulnerable that species is to local extinction or the likelihood that it will colonize new lakes (Gaston et al. 2000).

An important question for communities facing global changes is whether patterns of diversity are at an equilibrium or, alternately, if they are shifting over time (Nuvoloni et al. 2016). When communities and species’ are at equilibrium in a landscape, both are expected to show equal rates of colonization and extinction on average. Our results highlight two important non- equilibrium trends that are shifting lake communities. First, non-equilibrium dynamics in southern communities are causing an increase in diversity, whereas more northern communities appear to be in equilibrium (Fig. 5.2a). Interestingly, many studies of turnover do not explicitly consider non-equilibrium colonization-extinction dynamics as drivers of turnover (but see Matthews & Pomati, 2012; Nuvoloni et al., 2016). Second, we observed different non- equilibrium dynamics among species, with these dynamics predicted by species traits (Fig. 5.3). These trends suggest that relatively small, and locally abundant species that are widespread are becoming even more common, while species with low local abundances are disappearing from lakes at a greater rate than they are establishing elsewhere. In other words, these species-level non-equilibrium dynamics indicate that conditions over the past several decades are causing directional shifts in the traits of species by favouring small, common species to a greater degree than they were historically favoured.

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The results from our study also suggest that space-for-time substitutions are inappropriate for predicting changes with climate in temperate and northern aquatic communities. Space-for-time substitution is often used to replace temporal replication and can be a powerful tool for predicting community and population level responses to climate change (Dunne et al. 2004; Blois et al. 2013). However, smaller changes in northern lakes relative to southern lakes, despite greater temperature change in the north, indicates that temperature alone is a poor predictor of changes to community composition, at least over the timescale of this study (approx. 50 years). Regardless of whether these differences are mainly due to larger anthropogenic influences in temperate lakes, higher seasonal variation in northern lakes, or other mechanisms, failing to incorporate this greater complexity into climate change studies will lead to erroneous predictions for biological communities (Jones & Gilbert 2016).

In conclusion, by decoupling community responses across a latitudinal gradient, we were able to demonstrate colonization and extinction dynamics that depend on geographic location and species traits. Lakes are particularly vulnerable to the effects of global change because they are naturally fragmented and often heavily exploited (Woodward 2009). By resampling communities, we were able to refute a common hypothesis, that high latitude communities exposed to greater temperature increases will change at a faster rate, and provide evidence that intraspecific traits such as body size and local abundance predict colonization and extinction rates. These results provide a first step towards informing ecologists about species turnover across latitudes, and offer new insights into the proximate drivers of this turnover.

Acknowledgments

We would like to thank Veronica Jones for field assistance and Kazimierz Patalas for generously sharing his historical sampling data with us. We also thank NSERC for funding (B.G., Discovery Grant) as well as Ontario Graduate Scholarships (N.T.J.).

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Chapter 6 General Conclusion

This thesis was motivated by two main questions: how does species diversity change over space and time? And, are these changes structured by differences in traits among species and across environmental gradients? I used historical data, observational surveys and manipulative experiments to address these questions. I found that traits modulate diversity patterns both at regional scales where metacommunity processes predominate (chapter 2) and across latitudinal gradients where climate and historical factors are also important for structuring diversity (chapters 3-5). In what follows, I summarize the main findings and significance of the previous chapters, while considering some remaining uncertainties. Addressing these uncertainties will help inform how species traits will structure species diversity under future climatic conditions.

Chapter 2

Significance

The ability of species to disperse through patchy landscapes drive the diversity patterns we see in nature (Wilson 1992; Holyoak, Leibold & Holt 2005), however metacommunity studies often ignore or remove dispersal differences among species (Cadotte, Fortner & Fukami 2006; Howeth & Leibold 2010; Declerck et al. 2013). Chapter 2 considered the dispersal mode of plants and demonstrated the importance of considering dispersal modes of focal species for explaining the diversity patterns of heterogeneous metacommunities. I found that patch isolation and patch area have surprisingly variable effects on plant diversity that depend on dispersal mode. Wind- dispersed plants, for example, show no increase in diversity with patch size but a strong response to patch connectivity, whereas animal dispersed species show the opposite patterns.

Future directions

Although grouping plants by their dispersal mode clarified the influence of patch size and connectivity on diversity, I found that not all species within a dispersal group responded similarly. For example, both Rocky Mountain juniper (Juniperus scopulorum) and prickly wild rose (Rosa acicularis) are animal dispersed, but differ in their association with large or small

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stands. I suspect that this within group variation for plants dispersed by animal vectors reflect species-specific habitat constraints. If species are selecting habitat using different criteria or are being excluded by competitors (Chase, Burgett & Biro 2010; Vanschoenwinkel, Buschke & Brendonck 2013), the influence of size and connectivity will be obscured (Resetarits 2005; Matthiessen, Mielke & Sommer 2010). Future work that explicitly considers interspecific differences in dispersal and species interactions within the broader “mode” classification will help isolate how spatial dynamics structure diversity in this ecosystem.

The empirical sampling I used was powerful in that it used a naturally patchy metacommunity of understory plants. This allowed me to avoid confounding effects that occur with anthropogenic fragmentation, which can cause extinction debts that alter diversity estimates (Vellend et al. 2006; Krauss et al. 2010), or create artificial communities, that do not function as a metacommunity under natural conditions (Cadotte 2006). However, this observational approach necessitated that I make some assumptions regarding the status of the understory plant community. Specifically, I assumed that communities were at equilibrium (sensu MacArthur & Wilson 1967), which, as I observed in chapter 5, is not necessarily a safe assumption. Moreover, my approach precluded me from discriminating definitively among the mechanisms underlying the patterns I observed. Recently, ecologists have articulated an experimental metacommunity “best practices” to serve a guide for researchers to craft experiments that can differentiate between alternative hypotheses (Grainger & Gilbert 2016). Chief among their recommendations is the selection of species that reflect real differences in dispersal and experimental designs that allow species to colonize patches naturally. By demonstrating that traits associated with dispersal alter the association between patch size and connectivity, this work represents an important first step that should be followed by a more general shift to experimentally testing how interspecific differences in dispersal maintain diversity in natural systems.

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Chapter 3

Significance

An increase in organism body size at higher latitudes is a widely accepted ecogeographic rule (e.g., Ashton 2002). However, in chapter 3 of this thesis I document body size-latitude associations that do not conform to expected patterns. Unlike previous research that tests only interspecific body size trends and shows a decrease in body size at lower latitudes (e.g., Gillooly & Dodson 2000; Beaver et al. 2014), I tested inter- and intra-specific trends and detected weak and variable relationships between zooplankton body size and latitude. Moreover, other environmental factors were just as likely as latitude to affect the body size of zooplankton. These results appear to be in opposition to many recent experimental studies, which have documented a reduction in the body size of ectotherms at higher temperatures (Daufresne, Lengfellner & Sommer 2009).

Future directions

Overall, the intraspecific results of this study suggest that experiments demonstrating a reduction in body size at high temperatures may represent plastic changes (Teplitsky et al. 2008), as these patterns are not consistent with samples collected in nature that have adapted to their temperature regime over long time periods. Determining the effects of temperature on the fitness, development time and body size of ectotherms represent a considerable challenge (Ohlberger 2013). This is largely because dynamic plastic responses to temperature can obscure long-term responses to temperature and lead to trade-offs in development time and fitness (Savage et al. 2004; Gotthard, Berger & Walters 2007). In future work, efforts should focus on disentangling plastic from genetic changes to isolate directional and stabilizing selection on body size with increasing temperature. Future research will also need to address how plastic and genetic changes in body size alter population and community dynamics (Kingsolver & Pfenning 2007; Kingsolver & Huey 2008). Although these are formidable challenges, they are necessary to address in order to understand and predict short- and long-term responses of communities to global climate change.

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Chapter 4

Significance

The importance of dormancy for community dynamics in both aquatic and terrestrial ecosystems is often overlooked, especially in climate change research. In chapter 4, I tested the effects of day length and temperature on the hatching dynamics of zooplankton that originate from lakes spanning an 1800 km latitudinal gradient. These cues consistently terminate dormancy in zooplankton (Stross 1966; May 1987; De Stasio 2004), and are being modified by climate change; however, we lack studies that test how the interactive effects of these cues will alter dormancy dynamics, and especially whether their effects depend on the latitude of the zooplankton communities. Moreover, the majority of egg bank studies to date have considered the responses of a single taxon at a time (e.g., Vandekerkhove, Declerck & Brendonck 2005), preventing an analysis of the generality of species’ responses. Indeed, my results are the first to reveal that copepods and cladocerans from a common set of lakes show systematically different responses to day length and temperature.

Future directions

This project documents interesting latitudinal patterns in zooplankton hatching, however I was unable to determine if the differences in hatching that I observed represent an evolutionary stable bet hedging strategy. Bet hedging should cause a reduction in hatching rates as temporal variation increases (Cohen 1968; Ellner 1985). The role of dormancy for optimizing reproduction in heterogeneous environments has been well explored in plant communities. For example, Venable (2007) used a long-term dataset of desert annual plants to demonstrate that the relationship between environmental conditions, reproductive variability, and germination fractions are consistent with theory on bet hedging. However, despite the influence of environmental conditions on the fitness of freshwater zooplankton, we lack evidence that differences in environmental responses and reproductive variability correspond to dormancy in zooplankton. Future work should focus on predictions for bet hedging both within communities and across a latitudinal gradient, to test whether higher rates of dormancy are indeed adaptive at higher latitudes. This knowledge is critical to understanding the effects of climate change and climate variability on species persistence.

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Chapter 5

Significance

The effect of climate change on species persistence depends on the biotic and abiotic attributes of those communities. In chapter 5, I resampled zooplankton communities and provide evidence that changes to community composition depend on geographic location and are associated with differences in colonization-extinction dynamics and species traits. By resampling communities across a broad north-south latitudinal gradient, I test and subsequently reject a common hypothesis that higher latitude communities change faster than lower latitude sites (e.g., Smol et al. 2005). Determining if rates of community change depend on geographic location, and the traits associated with this change, is an important first step to predicting the vulnerability of communities to anthropogenic change.

Future directions

The association between species traits and colonization success that I document suggest that current environmental conditions are favoring smaller, locally abundant species. Although, the generality of this compositional shift should be investigated in additional taxa, this observation has the potential to have large consequences. For aquatic zooplankton, body size affects ecological processes including population maintenance, competitive asymmetries and predator- prey dynamics (Gliwicz 1990; Yodzis & Innes 1992; Woodward et al. 2005). Together, this suggests that changes to community composition could scale up to alter ecosystem dynamics, and based on my results, these effects will be greater in temperate lakes.

Conclusion

The findings presented in this thesis attempt to connect the characteristics of species and their environment to make inferences about the forces that structure diversity. I demonstrate the importance of traits for diversity patterns locally and across broad latitudinal gradients. My results caution against the use of space-for-time substitutions, as latitudinal differences in hatching dynamics (chapter 4) and community shifts (chapter 5) would not have been predicted based on environmental conditions alone. The geographic signature of community shifts, as well

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as persistence strategies such as dormancy that are influenced by climate, should be incorporated into future work that tests how global changes will alter community dynamics.