Science, Faculty of
Zoology, Department of
DSpace
UBCV
Meldrum, Gennifer Eileen
Master of Science - MSc
University of British Columbia
Immigration from surrounding areas is known to benefit community recovery following disturbance. However, whether such rescue effects can increase regional diversity in landscapes subject to patchy disturbance has rarely been investigated experimentally. This study manipulated landscape connectivity and disturbance synchrony in moss patches, and examined the consequences for the embedded microarthropod communities. We assembled metacommunities with two patches connected by 0, 1, or 2 corridors. Patches were left undisturbed or were disturbed asynchronously or synchronously by Tullgren funnel extraction. We found evidence of rescue effects at the local-scale for microarthropods overall, especially for the oribatids and collembolans. However these rescue effects did not result in greater regional diversity for several reasons. First, rescue effects only occurred after one of the disturbances so they did not increase average local-scale diversity and any increase in local-scale diversity was offset by increasing compositional similarity across the landscape. Competitive and trophic interactions may have diminished the expected benefit of connectivity for diversity. Finally, disturbance and isolation did not always decrease local diversity as expected, suggesting a strong role for context-dependent dispersal behaviour and in situ recovery processes. Our results indicate that rescue effects mediated by habitat corridors can improve recovery of local community diversity following disturbance, but they may not be effective at maximizing regional diversity. Predator diversity may be more likely to benefit from rescue effects than prey diversity at the regional scale.
INTERACTIVE EFFECTS OF DISPERSAL RATE AND DISTURBANCE SYNCHRONY ON MICROARTHROPOD DIVERSITY AT MULTIPLE SPATIAL SCALES: RESCUE EFFECTS DO NOT INCREASE REGIONAL RICHNESS by GENNIFER EILEEN MELDRUM B.Sc., University of Calgary, 2008 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE STUDIES (Zoology) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) August 2012 © Gennifer Eileen Meldrum, 2012 ii Abstract Immigration from surrounding areas is known to benefit community recovery following disturbance. However, whether such rescue effects can increase regional diversity in landscapes subject to patchy disturbance has rarely been investigated experimentally. This study manipulated landscape connectivity and disturbance synchrony in moss patches, and examined the consequences for the embedded microarthropod communities. We assembled metacommunities with two patches connected by 0, 1, or 2 corridors. Patches were left undisturbed or were disturbed asynchronously or synchronously by Tullgren funnel extraction. We found evidence of rescue effects at the local-scale for microarthropods overall, especially for the oribatids and collembolans. However these rescue effects did not result in greater regional diversity for several reasons. First, rescue effects only occurred after one of the disturbances so they did not increase average local-scale diversity and any increase in local-scale diversity was offset by increasing compositional similarity across the landscape. Competitive and trophic interactions may have diminished the expected benefit of connectivity for diversity. Finally, disturbance and isolation did not always decrease local diversity as expected, suggesting a strong role for context-dependent dispersal behaviour and in situ recovery processes. Our results indicate that rescue effects mediated by habitat corridors can improve recovery of local community diversity following disturbance, but they may not be effective at maximizing regional diversity. Predator diversity may be more likely to benefit from rescue effects than prey diversity at the regional scale. iii Preface Chapter 1 is based on research performed as a collaboration between myself and my supervisor, Diane S. Srivastava. Diane suggested the research topic but we devised the design of the experiment together. I performed all of the field and lab work and carried out all of the statistical analyses, following the guidance of Diane and my committee. I prepared the majority of the manuscript, although Diane provided advice on its structure and major editing for the abstract and introduction. Chapter 1 will be submitted for publication. iv Table of Contents Table of Contents Abstract ......................................................................................................................................... ii Preface .......................................................................................................................................... iii Table of Contents ..........................................................................................................................iv List of Tables .................................................................................................................................. v List of Figures ...............................................................................................................................vi Acknowledgements ..................................................................................................................... vii Dedication ................................................................................................................................... viii Introduction ................................................................................................................................... 1 Interactive Effects of Disturbance and Fragmentation ................................................................ 2 Habitat Corridors ......................................................................................................................... 3 Metacommunity Ecology ............................................................................................................. 4 Model Systems in Metacommunity Ecology ............................................................................... 4 Research Questions ...................................................................................................................... 5 Interactive effects of dispersal rate and disturbance synchrony on microarthropod diversity at multiple spatial scales: Rescue effects do not increase regional richness ............. 7 Introduction .................................................................................................................................. 7 Hypotheses and Predictions .................................................................................................. 10 Methods ..................................................................................................................................... 12 Study Site .............................................................................................................................. 12 Experimental Design ............................................................................................................ 13 Analyses ................................................................................................................................ 14 Results........................................................................................................................................ 16 Rescue effects ....................................................................................................................... 17 Beta diversity ........................................................................................................................ 19 Dispersal Rate ....................................................................................................................... 19 Trophic Groups ..................................................................................................................... 20 Discussion .................................................................................................................................. 20 Tables and Figures ....................................................................................................................... 29 Conclusion .................................................................................................................................... 37 Future Directions ....................................................................................................................... 39 Management Implications ......................................................................................................... 40 Bibliography ................................................................................................................................. 43 Appendices ................................................................................................................................... 53 Appendix 1. Photos of experimental set-up ............................................................................... 53 Appendix 2. Model Selection Results ....................................................................................... 55 Microarthropods ................................................................................................................... 55 Mesostigmatids ..................................................................................................................... 57 Adult Oribatids ..................................................................................................................... 58 Juvenile Oribatids ................................................................................................................. 59 Prostigmatids ........................................................................................................................ 61 Predator: Prey Ratio .............................................................................................................. 62 Appendix 3. Alpha Diversity Figures ........................................................................................ 63 v List of Tables Table 1. Summary of linear models assessing the effect of connectivity and disturbance regime on local morphospecies richness (α), beta diversity (β), regional morphospecies richness (γ), and regional abundance (N) for all microarthropods combined and for different taxonomic, ontogenetic and trophic subgroups. Model results for metacommunity predator: prey ratio, calculated as the proportion of predatory individuals, are also presented. Significant results are indicated by an asterisk. .............................................. 29 vi List of Figures Figure 1. Generalized moss microarthropod food web. Original artwork by Pamela Matute...... 30 Figure 2. Predictions for isolated and connected metacommunities: The difference in local richness between asynchronously and synchronously disturbed metacommunities (A), as well as average local richness (B) and beta diversity under different disturbance regimes (C). Disturbance regime is indicated by symbol color and shape (black square= undisturbed, grey circle= asynchronous, and grey triangle= synchronous). ................... 31 Figure 3. Experimental moss metacommunity treatments established on a concrete matrix. Three levels of connectivity were created by connecting patches with increasing numbers of moss corridors. The pseudocorridor tabs ensured that all metacommunities had similar area and geometry. The connectivity treatments were crossed with four disturbance regime treatments. The timing of disturbance is indicated by the color of the circle (white= undisturbed, dark grey= disturbed in May, light grey= disturbed in August, black= disturbed in both May and August). Each of the 12 treatments was replicated 5 times. ................................................................................................................................. 32 Figure 4. Difference in local microarthropod and mesostigmatid richness and abundance between metacommunities that were asynchronously (A) and synchronously (S) disturbed under different levels of connectivity. Bootstrapped mean differences and 95% confidence intervals were calculated using patches that were disturbed in the same month (filled circles= May and empty circles= August). Significant differences (95% confidence intervals do not overlap zero) are indicated by asterisks. ................................................. 33 Figure 5. Regional richness and abundance of different subgroups of microarthropod (A-G) and the predator: prey ratio, calculated as the proportion of predatory individuals (H), in two-patch metacommunities with different disturbance regimes and levels of connectivity; N=5, error bars are SEM. Disturbance regime is indicated by symbol shape and color (black square= undisturbed (U), grey circle= asynchronous (A), grey triangle= synchronous May (SM), and white triangle= synchronous August (SA)). Significant contrasts are shown as inequalities on the figure panel (treatment contrasts) or below the connectivity level of the figure panel (interaction contrasts), with all contrasts following significant main effects and interactions (Table 1)........................................................... 34 Figure 6. Microarthropod (A), mesostigmatid (B), and juvenile oribatid (C) beta diversity in two-patch metacommunities with different disturbance regimes and levels of connectivity; N=5, error bars are SEM. Disturbance regime is indicated by symbol shape and color (black square= undisturbed (U), grey circle= asynchronous (A), grey triangle= synchronous May (SM), and white triangle= synchronous August (SA)). Significant contrasts are shown as inequalities on the figure panel (treatment contrasts) or below the connectivity level of the figure panel (interaction contrasts),with all contrasts following significant main effects and interactions (Table 1)........................................................... 36 vii Acknowledgements I am grateful to all who provided comments on this manuscript and input on the design of the experiment including, John Richardson, Greg Crutsinger, and Mark Vellend. Many thanks to Youhua Chen, Jiichiro Yoshimoto, Rebecca Taves, Pamela Matute, and Olga Lansdorpe for assistance in the lab and field. I am also indebted to Andrew MacDonald for his guidance in statistical programming. This research was funded by a grant from the National Science and Engineering Research Council of Canada and the UBC Graduate Studies Department. viii Dedication To mom, dad, Steve, Kat, Clint, and Juniper. Thank you for your ‘mitey’ support throughout my studies. 1 Introduction Land conversion for industry, agriculture and urbanization is driving a global decline in biodiversity (Sala et al. 2000). Habitat destruction resulting from these impacts also tends to erode landscape connectivity, which reaches a critical threshold when less than 20-30% of the original habitat remains (Andrén 1994, Radford et al. 2005). The smaller and more isolated populations surviving in these fragmented habitats suffer increased extinction risk, which is exacerbated by higher rates of inbreeding (Lange et al. 2010), loss of basal resources (Komonen et al. 2000), and edge effects (Santos and Tellería 1992, Camargo and Kapos 1995). Consequently, habitat fragmentation often results in greater species loss than is expected by habitat destruction alone (Fahrig 2003). Biodiversity is considered fundamental to ecosystem function and stability. A diversity of species and functional groups can enhance ecosystem function through ‘complementarity effects’ and ‘sampling effects’ (reviewed by Balvanera et al. 2006, Cardinale et al. 2006). For example, above ground primary productivity in European grasslands increases with species richness and functional diversity, but especially when a particular nitrogen-fixing species is included in the plots (Hector et al. 1999). The presence of a diversity of species with different responses to environmental conditions can also stabilize ecosystem function through environmental perturbation, as it enables compensatory dynamics or ‘insurance effects’ (Yachi and Loreau 1999, Elmqvist et al. 2003). Given the great importance of biodiversity for ecosystem function and stability, determining strategies to maintain biodiversity in fragmented landscapes is a matter of critical importance. 2 Interactive Effects of Disturbance and Fragmentation Habitat fragmentation often occurs in tandem with a multitude of other human imposed stressors (Christensen et al. 2006, O’Gorman et al. 2012). In particular, the interaction between disturbance and habitat fragmentation is of major concern for the conservation of biodiversity (Sala et al. 2000). Fragmented habitats tend to experience intensified disturbance through edge effects (Cochrane and Laurance 2002) and to be more affected by large-scale disturbance than intact habitats (Foppen et al. 1999). The frequency and intensity of disturbance is also increasing generally due to the effects of global climate change (Turner 2010). Increased disturbance may be highly detrimental for fragmented communities because the loss of biodiversity and connectivity may undermine their resilience (Starzomski and Srivastava 2007), defined as their capacity to recover structure and function following perturbation (Gunderson 2000). Communities recover from disturbance by the reproduction of local survivors and recolonization from surrounding areas (Bengtsson et al. 2003). Loss of connectivity in fragmented landscapes may impede recolonization, thereby hindering the recovery of diversity following disturbance (Starzomski and Srivastava 2007). Meanwhile, the decline in regional diversity may reduce the availability of source areas (Nyström and Folke 2001, Gathorne-Hardy et al. 2002, Loreau et al. 2003). Despite the importance of this problem, surprisingly few studies have investigated the interaction between disturbance and habitat connectivity (Warren 1996, Loreau et al. 2003, Östman et al. 2006, Starzomski and Srivastava 2007, Howeth and Leibold 2010, Altermatt et al. 2011, Chisholm et al. 2011, Åström and Pärt In Press). 3 Habitat Corridors Habitat corridors have frequently been proposed as a means of reducing species loss in fragmented landscapes (e.g. Harrison 1992; Lindenmayer & Nix 1993). These linear strips of habitat physically join larger areas of habitat to encourage movement of organisms between patches (Gilbert-Norton et al. 2010). By increasing connectivity, corridors can increase effective population sizes (Brown and Kodric-Brown 1977) and enable recolonization of extinct populations (Hanski 1999). Such ‘rescue effects’ have been shown to enhance the recovery of local diversity following disturbance (Starzomski and Srivastava 2007). They may also maintain regional diversity in disturbed landscapes by enabling disturbance-sensitive species to persist in the landscape by tracking undisturbed refugia (Loreau et al. 2003, Gonzalez et al. 2009). However, this concept remains largely untested. There are several reasons why corridors may not mitigate regional species diversity decline in disturbed landscapes. Rescue effects rely on the asynchrony of population dynamics across the region (Hanski 1999). Thus the presence of corridors may have little benefit for community recovery if disturbance occurs synchronously across the landscape. Disturbance frequency and intensity must also match the regenerative potential of populations to grow and produce enough dispersing individuals in order for rescue effects to be effective (Moloney and Levin 1996). Elimination of spatial refuge from competition and predation at high connectivity may additionally limit the benefit of corridors for regional diversity (Cadotte and Fukami 2005, Chase et al. 2005). 4 Metacommunity Ecology A metacommunity approach is commonly used to study species persistence in fragmented habitats because dispersal between patches is often restricted by an inhospitable matrix (Gonzalez 2005, Holyoak et al. 2005). Metacommunity ecology builds on the foundational work of island biogeography (MacArthur and Wilson 1967) and metapopulation biology (Hanski 1999) to investigate how community structure and function are affected by processes occurring at multiple spatial scales (Leibold et al. 2004, Holyoak et al. 2005). For instance, communities in fragmented habitats may be structured by processes occurring at the local scale, such as environmental conditions and species interactions, as well as processes occurring at the regional scale, such as dispersal (Logue et al. 2011). Beta diversity, or the divergence in species composition between patches in a region, is a third component of diversity that emerges in a spatial context (Legendre et al. 2005). Through its consideration of influences occurring at multiple spatial scales, metacommunity theory has the potential to provide great insight into the conservation of species diversity in fragmented landscapes. Model Systems in Metacommunity Ecology The large scale of questions concerning habitat fragmentation and metacommunity ecology makes experimental investigation highly challenging. The vast amounts of land required to ensure adequate treatment replication may be unfeasible to obtain under tight research budgets. The natural heterogeneity of landscapes also makes it difficult to control for habitat area and quality. As a means of overcoming these constraints, ecologists commonly use communities of small organisms in miniature landscapes as model systems to investigate metacommunity problems (Srivastava et al. 2004). The condensed size and temporal dynamics (i.e. short 5 generation times) of these systems are tractable to investigation of how habitat structure at multiple scales affects community structure and function (Srivastava et al. 2004). One of these models is the epilithic moss ecosystem, which contains an incredible diversity and abundance of microarthropods (Lindo and Gonzalez 2010). The density of microarthropods varies with the amount of humus and litter but can range up to 225,000 individuals/m 2 (Lindo and Gonzalez 2010). The food web is based on fungus and detritus, which is consumed by oribatid mites, prostigmatid mites and collembola that are preyed upon by predatory mesostigmatid and prostigmatid mites (Figure 1; Johnston 2000, Oliver et al. 2005, Holtkamp et al. 2008, Schneider and Maraun 2009). The organisms play an important role as secondary decomposers, processing organic matter into smaller pieces that are more readily available for decomposition by bacteria and fungus (Behan and Hill 1978). Relatively little is known about mite dispersal, however, soil dwelling species typically disperse by walking (Ojala and Huhta 2001, Lehmitz et al. 2011, 2012). A bare rock surface has been shown to present a significant dispersal barrier to the microarthropods, but connecting patches with moss corridors encourages inter-patch dispersal (Gilbert et al. 1998, Gonzalez et al. 1998, Staddon et al. 2010). Research Questions In this study we used the moss microarthropod ecosystem to investigate how the level of habitat connectivity and disturbance synchrony interact to affect regional diversity. By comparing the effects of synchronous and asynchronous disturbance we are able to assess the relative role of local and spatial processes in the recovery of species richness following disturbance. We test the hypothesis that rescue effects will increase regional diversity, as they enable disturbance-sensitive species to persist regionally by tracking undisturbed refugia. 6 However, we expect that enhanced regional competition and top down control in connected metacommunities may reduce the benefit of rescue effects for regional diversity and that these effects that may be more pronounced at higher dispersal rates. 7 Interactive effects of dispersal rate and disturbance synchrony on microarthropod diversity at multiple spatial scales: Rescue effects do not increase regional richness Introduction Habitat destruction is driving a global decline in biodiversity and fragmenting remaining habitat into smaller more isolated patches (Saunders et al. 1991, Sala et al. 2000). Such changes in landscape extent and connectivity may interact synergistically with increasing rates of other disturbances (Sala et al. 2000, Turner 2010). In particular, habitat fragmentation may erode ecosystem resilience (Starzomski and Srivastava 2007, Thrush et al. 2008) that is, the capacity of ecosystems to rebound from perturbations in terms of biotic structure and function (Gunderson 2000). Species surviving in fragmented landscapes may exist as metacommunities, in which dispersal between habitat patches is limited by an inhospitable matrix (Leibold et al. 2004, Holyoak et al. 2005). However, habitat corridors between patches can encourage the movement of organisms between habitat patches (Gilbert-Norton et al. 2010), thereby boosting population sizes and encouraging reestablishment of locally extinct populations (Brown and Kodric-Brown 1977, Hanski 1999, Haddad and Tewksbury 2006). Such ‘rescue effects’ have been demonstrated by numerous studies to facilitate the recovery of local diversity following disturbance (e.g. Levin and Paine 1974, Turner et al. 1998, Fowler 2002) but only a handful of studies have investigated whether rescue effects could also maintain regional diversity in disturbed landscapes (Warren 1996, Loreau et al. 2003, Östman et al. 2006, Starzomski and 8 Srivastava 2007, Howeth and Leibold 2010, Altermatt et al. 2011, Chisholm et al. 2011, Åström and Pärt In Press). Rescue effects will be most effective when disturbance occurs asynchronously across the landscape, so that source areas exist that can repopulate disturbed areas (Hanski 1999). The spatial insurance hypothesis proposes that the combination of asynchronous disturbance and interpatch dispersal could enable persistence of disturbance sensitive species in undisturbed refugia (Loreau et al. 2003, Gonzalez et al. 2009). The location of the refugia may change though time as disturbance proceeds asynchronously across the landscape and rescued communities become source areas when their populations recover. Indeed, under these conditions, inter-patch dispersal may not only prevent loss of species from disturbed landscapes, it may also enhance regional diversity by enabling coexistence of competitors with different environmental preferences, competitive and dispersal abilities (Chesson 1985, Loreau et al. 2003, Shea et al. 2004). By contrast, spatially extensive disturbance could hinder rescue effects by synchronizing population dynamics and reducing the regional availability of propagules (Turner et al. 1998, Gathorne-Hardy et al. 2002, Leibold et al. 2004). The degree of temporal synchrony in patch disturbance is central to all of the above theoretical predictions, yet surprisingly few empirical studies have explicitly considered the role of disturbance synchrony for rescue effects (Limberger and Wickham 2012). The ability of a local population to be “rescued” from extinction will not only depend on the species’ dispersal abilities and disturbance sensitivity, but also on its interactions with other species in the patch. For example, dispersal between asynchronously disturbed patches can rescue species from local extinction but also exposes species typical of the early stages of recovery to those typical of more mature communities, which may include competitive 9 dominants that can homogenize the composition of the patches (Cadotte 2006; Matthiessen & Hillebrand 2006; Mouquet & Loreau 2003; Östman et al. 2006). Indeed, metacommunity theory suggests that dispersal will typically have a negative effect on regional diversity due to enhanced regional competition (Loreau et al. 2003, Mouquet and Loreau 2003, Chase et al. 2005), which has been supported by observations in a variety of ecosystems (serpentine grasslands: Harrison 1999, wetland invertebrate communities: Chase 2003, protist communities in pitcher plants: Miller and Kneitel 2005). It is unclear, however, if the same relationship holds in disturbed metacommunities because disturbance may interrupt competitive hierarchies that lead to homogenization with increased connectivity (Östman et al. 2006). The effects of connectivity and disturbance regime on individual species will depend largely on their traits and trophic positions (Hudgens and Haddad 2003, Henle et al. 2004, de Bie et al. 2012). Different species experience different levels of functional connectivity with the same level of landscape connectivity (Pearson et al. 1996, Taylor et al. 2006). Some species may even cross the matrix to access isolated habitats, and so features of the matrix have a greater influence on their dispersal rate than connectivity (Robichaud et al. 2002, Selonen and Hanski 2003, Taylor et al. 2006). In particular, predatory species are often more vulnerable to extinction in fragmented habitats than prey species because of their smaller population sizes and larger area requirements (Didham et al. 1998, Holyoak 2000, Staddon et al. 2010). Greater mobility of predatory species may mean that habitat corridors enable their dispersal between habitats more readily than for prey species and make rescue effects more likely for higher trophic levels (Gilbert et al. 1998). An increase in predator presence with connectivity then could result in differences in top-down control and indirect effects on regional diversity (Holyoak 2000, Duffy 2003, Staddon et al. 2010). 10 In this experiment we used a multitrophic moss microarthropod ecosystem to investigate how landscape connectivity and synchrony of drought disturbance interactively affect regional biodiversity of two-patch metacommunities. Small patches of moss contain a high diversity and abundance of microarthropods (primarily mites and collembolans) that exhibit a variety of feeding relationships (Lindo and Gonzalez 2010). The complexity of this ecosystem and compact size make it ideal for investigation of landscape-scale questions with the benefit of experimental control and treatment replication (Srivastava et al. 2004). This system has previously provided evidence that connecting moss patches with corridors reduces extinction rates due to fragmentation (Gilbert et al. 1998, Gonzalez et al. 1998, Staddon et al. 2010) and particularly when the communities experience drought stress (Hoyle and Gilbert 2004). This system has also shown that connecting patches with corridors increases community resilience to disturbance at the local scale (Starzomski and Srivastava 2007). We expand on this work to investigate how the level of connectivity affects resilience to disturbance. By comparing the effects of synchronous and asynchronous disturbance we also are able to assess the relative role of local and spatial processes in the recovery of species richness following disturbance. Hypotheses and Predictions Our main hypothesis is that rescue effects will increase regional diversity, as they enable disturbance-sensitive species to persist in undisturbed refugia. However, we also expect that enhanced regional competition and top down control in connected metacommunities may reduce the benefit of rescue effects for regional diversity, and that these effects may be more 11 pronounced at higher dispersal rates. Mechanistically, for this hypothesis to be true, we make the following predictions: Rescue effects allow disturbed patches to repopulate via dispersal from connected, undisturbed (or less recently disturbed) patches. (a) If rescue effects are important, we expect the species richness and total abundance of a patch to be greater when its connected neighbour is disturbed at a different, as opposed to similar time, (b) but no effect of disturbance synchrony if the neighbour is not connected (Fig 2A, B). (c) If rescue effects allow the maintenance of disturbance-sensitive species in the metacommunity, we expect regional species richness and total abundance to be affected by the interaction between disturbance synchrony and connectivity in a similar manner as for the local scale. Beta diversity will be high in isolated metacommunities and will decline with increasing connectivity, reflecting the homogenizing effect of dispersal (Fig 2C). These opposing effects of connectivity on beta (as compared to local) diversity could reduce the benefit of rescue effects for regional diversity. Beta diversity will also be affected by disturbance regime, although the direction of this effect is less clear. Disturbance increases environmental filtering, which may decrease beta diversity (Leibold et al. 2004, Balata et al. 2007, Chase 2007). However, disturbance reduces population sizes, which may enhance beta diversity by increasing community drift (Evanno et al. 2009). In either case, disturbance imposed at different times may increase beta diversity by selecting for different species and increasing heterogeneity in the recovery state of communities (Caswell and Cohen 1991, Warren 1996, Limberger and Wickham 2012). 12 Dispersal Rate will be higher with 2 corridors than 1 corridor, which may result in greater diversity via enhancement of rescue effects or may depress local and regional diversity with respect to 1-corridor metacommunities by allowing a competitive dominant to become regionally prevalent. Trophic groups may respond differently to disturbance and connectivity creating indirect effects of these factors. In particular, predators may respond more strongly to the level of landscape connectivity because they tend to be wider ranging and have smaller population sizes than their prey. Predators may thus decline in isolated metacommunities, with cascading effects on community structure. Methods Study Site We collected moss from a large homogeneous patch (primarily composed of Racometrium and Polytrichum) growing on a granite outcrop in southern British Columbia, Canada (GPS: N 49°20.965', W 123°13.964'). We fragmented the moss into patches 10 cm in diameter and assembled them haphazardly into two-patch metacommunities. Patches were placed 8 cm apart on concrete blocks that were approximately 40×20×4 cm in dimension. The concrete surface had a similar texture to the rock the moss was growing upon in the field, which has been demonstrated in previous experiments to present a significant dispersal barrier to moss microarthropods (Gilbert et al. 1998, Gonzalez et al. 1998, Staddon et al. 2010). The concrete blocks were arranged in a grid pattern on a polyurethane tarp, with gaps approximately 10 cm 13 between blocks. Treatments were randomly assigned to a location within the grid. Their position was also randomly rearranged midway through the experiment to break up any influence that location within the grid may have on the microarthropod community. The experiment was set up in a field on the south UBC campus. The location for the experiment was slightly more exposed than the rocky outcrop from where the moss was collected, so we covered the moss with 50% shade cloth. We watered the moss once every 7 days (if it had not rained) to ensure that the mite communities were not completely desiccated. Bird netting was hung around the experiment to prevent tampering by wildlife. The experiment ran for 6 months from May through November, 2010, which is sufficient time for one or several generations to pass for many microarthropods (Gilbert et al. 1998). Photos of the experimental set-up are available in Appendix 1. Experimental Design We set up our two-patch metacommunities as a factorial manipulation of three connectivity treatments and four disturbance regime treatments. The two moss patches were unconnected in our isolated treatment or linked by one or two moss corridors (Fig. 3). We used pseudocorridor tabs to control for habitat area and microclimate effects of fragmentation, such that all patches were similar in their geometry and surface area. We had two synchronous disturbance treatments to assist in distinguishing the effect of recovery time from the effect of disturbance synchrony. In these treatments both patches in the metacommunity were disturbed either in May (SM) or in August (SA). Asynchronously disturbed (A) metacommunities had one patch disturbed in May and the other August. An undisturbed treatment (U) acted as a control and point of comparison for community resilience. In total we had 12 treatments that were each replicated five times, for a total of 60 metacommunities and 120 patches. 14 Disturbance was imposed by partial Tullgren funnel extraction (slow drying under a dim light bulb) for 36 hours. This process imposes a heat and light gradient that initiates a behavioral response in the microarthropods to travel downward, where they fall through a funnel and into a collecting jar. The disturbance removes a large number of individuals from the moss patch but leaves some survivors behind (Starzomski and Srivastava 2007). The drying also simulates drought, which these communities experience naturally in Southern British Columbia and which results in significant negative effects on community richness and abundance (Lindo et al. 2012). For the May and August disturbances, all patches were packaged in plastic bags and transported to the lab. Patches that were not disturbed were kept in the refrigerator at 4°C for the duration of the extraction. Every corridor and pseudocorridor was disturbed in both rounds of disturbance to ensure that they were not a source of colonists. We also used Tullgren funnel extraction to sample the mites but this extraction was longer (72 hours) and more complete as compared to the disturbance. Due to material limitations, we performed two extraction rounds. Samples were collected in a 70% ethanol-20% glycerol solution. Microarthropods were sorted to morphospecies under a 115 X dissection microscope. The specimen library is viewable at www.zoology.ubc.ca/~srivast/mites.html. Analyses Regional scale We used linear models to examine the effect of connectivity and disturbance regime on regional species richness and abundance. Covariates included in the analyses were the combined mass of both patches following extraction (M), the position of the metacommunity relative the edge of the grid for the first and second half of the experiment (and their interaction) (P1, P2, 15 and P1:P2), the names of the people that sorted the samples (S), and the extraction round (ER). Models were constructed that included the two treatments, their interaction (connectivity × disturbance regime), and all possible combinations of the covariates. Akaike information criterion (AIC) was used to select the best candidate model (Appendix 2). Planned contrasts were performed for main effects of connectivity to compare (i) connected to isolated treatments and (ii) 1-corridor to 2-corridor treatments. For main effects of disturbance regime we compared (i) disturbed to undisturbed metacommunities (A,SM,SA vs. U), (ii) synchronously to asynchronously disturbed metacommunities (SM,SA vs. A) and (iii) the two synchronously disturbed treatments (SM vs. SA). Where a significant interaction between connectivity and disturbance regime was found, interaction contrasts were performed by collapsing the connectivity and disturbance treatments into a single 'treatment' variable and then performing the disturbance contrasts within levels of connectivity. Local Scale The procedure described above was also used to analyse beta diversity and average local richness. Beta diversity was calculated as regional richness divided by average alpha richness (Whittaker 1960). This multiplicative measure of beta diversity is less sensitive to variation in local richness than other recently developed measures of beta diversity (Wilsey 2010, Fukami and Nakajima 2011). We also performed a targeted local-scale analysis to help disentangle the effects of recovery time and disturbance synchrony on local richness and abundance. We calculated the difference in response between patches from asynchronously and synchronously disturbed metacommunities that were disturbed in the same month using a bootstrapping procedure to 16 control for non-independence resulting from patches being connected to one another. This involved randomly selecting samples of five patches that were disturbed in the same month within a disturbance regime treatment, with replacement, ensuring that patches located on the same block could not be selected. We repeated the procedure 1000 times to obtain the mean difference in local richness between asynchronously and synchronously disturbed metacommunities and the 95% confidence interval. Statistical analyses were performed for all microarthropods together and then for different taxonomic and functional subgroups, which differ in their dispersal and life history characteristics: mesostigmatid, prostigmatid, adult and juvenile oribatid mites, and collembolans. All analyses were performed in R Version 2.13.2 (R Development Core Team 2009). Results We counted a total 29,673 microarthropods from 105 morphospecies in this study. In general, disturbance regime and connectivity interacted in complex ways to influence diversity and abundance at both local and regional scales. The overall pattern observed for diversity and abundance across the 12 connectivity and disturbance regime treatments was very similar at local and regional scales. As such, only the figures for regional richness are presented here and figures for local richness are provided in Appendix 3. We found support for most of our predictions, although evidence was often found for particular subgroups of microarthropod and not as an overall pattern for all microarthropods. We now describe the evidence for each prediction in detail. 17 Rescue effects (a) Local Scale (Connected) We hypothesized that the combination of connectivity and asynchronous disturbance would mitigate the detrimental influence of disturbance by enabling rescue effects. We found evidence of rescue effects at the local scale for all microarthropods combined and particularly for the oribatid mites and the collembola. Specifically, compared to synchronous disturbance, asynchronous disturbance yielded higher oribatid, collembolan, and overall microarthropod local richness when patches were connected to their neighbouring patch, although these results were generally only significant for patches connected by one corridor and disturbed in May (bootstrapped 95% CI for difference asynchronous-synchronous: oribatids 0.20 to 3.40; collembola 0.40 to 4.20; microarthropods Fig. 4A). By contrast, mesostigmatid local richness and abundance were not significantly higher in asynchronously, as opposed to synchronously, disturbed patches with corridors, although there was a strong tendency in patches connected by one corridor and disturbed in August (species richness p = 0.162; abundance p = 0.064; Fig. 4C,D). (b) Local Scale (Isolated) We expected that isolated patches would not be affected by when their neighbouring patch was disturbed, since the concrete platform was assumed to be impermeable to dispersal. Contrary to this prediction, asynchronous disturbance often had a detrimental effect on isolated communities when compared to synchronous disturbance. Specifically, in isolated patches disturbed in May, overall microarthropod local richness and abundance were significantly lower when their unconnected neighbour was disturbed asynchronously, i.e. in August rather than also 18 in May (bootstrapped 95% CIs ≤ 0) (Fig. 4 A,B). The same effect was seen for mesostigmatid local richness and abundance in patches disturbed in May (Fig. 4 C,D) and for adult oribatid local richness in patches disturbed in May and August (bootstrapped 95% CIs May: 0 to -2.8, August: 0 to -2.6). (c) Regional scale We hypothesized that local-level rescue effects may scale up to increase regional diversity. Specifically we expected that connected asynchronously disturbed metacommunities would maintain higher regional richness and abundance than synchronously disturbed and isolated metacommunities. We did not find a significant effect of the connectivity and disturbance regime treatments for microarthropod richness or abundance (Table, 1; Figure 5A,B). We found evidence of an interactive effect of connectivity and disturbance regime for mesostigmatid abundance and collembola species richness at the regional scale (Table 1). However, only the mesostigmatid mites responded in the direction hypothesized for rescue effects (asynchronous disturbance yielded higher regional abundance than synchronous disturbance in 1-corridor metacommunities, Fig. 5D), while the collembola showed a response that was nearly opposite prediction (a decline in regional richness with increasing connectivity for disturbed metacommunities, Fig. 5E). We caution that while some aspects of the mesostigmatid response agreed with prediction for rescue effects, there were several aspects of their response that didn't match prediction. Notably, this hypothesis was based on mitigation of the negative influence of disturbance by its asynchronous imposition and connectivity in the landscape. Counter to expectation, disturbance did not have a substantially negative influence on the regional richness and abundance of any 19 group of microarthropod and mesostigmatid regional abundance was actually higher with disturbance in 2-corridor metacommunities. Beta diversity The experimental treatments had a complex influence on beta diversity. There was an interactive effect of disturbance regime and connectivity for microarthropod, mesostigmatid and juvenile oribatid beta diversity and the effects were not consistent across groups (Table 1). We predicted that beta diversity would decline with connectivity due to the homogenizing effect of dispersal. In line with expectation, microarthropod and mesostigmatid beta diversity declined with connectivity under certain disturbance regimes and particularly with asynchronous disturbance (Fig 6A,B). However, the opposite pattern was found for mesostigmatid beta diversity in undisturbed metacommunities. Juvenile oribatid beta diversity also increased as connectivity increased from one to two corridors (Fig 6C). We predicted that disturbance regime would also influence beta diversity but that the direction of this effect would differ depending on the strength of environmental filtering and community drift. We did not find consistent evidence that disturbance decreased or increased beta diversity for any group. However, our prediction that asynchronous disturbance would increase beta diversity by increasing heterogeneity was supported for microarthropods and mesostigmatids in isolated communities. Dispersal Rate We expected that the dispersal rate of microarthropods would increase with the number of corridors and that regional richness and abundance may increase linearly or show a unimodal 20 relationship with connectivity depending on the importance of rescue effects and regional competition. We did not find strong support for either a linear or nonlinear effect of dispersal rate on regional richness. Mesostigmatid regional richness was higher in connected metacommunities than in isolated metacommunities, but 1 and 2-corridor systems did not significantly differ (Fig. 5C). Juvenile oribatid regional richness was significantly higher in 2-corridor than 1-corridor metacommunities, although it was intermediate in isolated metacommunities (Fig.5G). Trophic Groups We hypothesized that predators may be more sensitive to isolation than their prey and that this may lead to changes in trophic structure and indirect effects of connectivity and disturbance regime treatments on diversity and abundance. Mesostigmatid mites were the most numerically abundant predators in these metacommunities and collembola were the most numerically abundant prey. Accordingly, the predator: prey ratio varied with connectivity and disturbance in strong agreement with their responses (Fig. 5D,E,H). In 1-corridor systems, asynchronously disturbed metacommunities had significantly greater proportion of predatory individuals than synchronously disturbed metacommunities and with 2-corridors, disturbed metacommunities had a significantly higher proportion of predatory individuals than undisturbed metacommunities. Discussion In this study we documented rescue effects for most groups of microarthropods at the local scale but these rescue effects did not result in greater regional diversity. We did not find 21 strong evidence for a linear or nonlinear effect of the level of connectivity on regional or local diversity. However, rescue effects were only observed at the local scale at an intermediate level of connectivity. Our results corroborate previous studies on this system that rescue effects mediated by habitat corridors reduce microarthropod extinction rates following habitat fragmentation (Gilbert et al. 1998, Gonzalez et al. 1998, Staddon et al. 2010) and increase community resilience to drought disturbance at the local level (Starzomski and Srivastava 2007). The importance of immigration for local population and community recovery from disturbance is well documented in other systems (e.g. Levin and Paine 1974, Turner et al. 1998, Gathorne- Hardy et al. 2002) and implies that the regional species pool will have an influence on community recovery from disturbance. However, it is largely unknown whether such rescue effects can also help maintain regional diversity. In this study we demonstrate that local-scale rescue effects do not result in increased regional species richness. This attenuation of rescue effects at the regional scale likely occurred for five reasons, which we explore in the paragraphs that follow. Firstly, rescue effects did not substantially increase average alpha diversity, as rescue effects typically occurred in only one of two disturbance events (primarily in May). Patches disturbed in August may have been behind in recovery as compared to patches disturbed in May because they had less time to repopulate prior to sampling (in November). Additionally, rescued patches may have had smaller population sizes than undisturbed patches, making them a less effective source of colonists (Pulliam 1988, Hill et al. 1996). A seasonal propensity for dispersal may have further contributed to differences in recovery between May and August disturbed patches. This is conceivable as lower temperatures in the autumn reduce the rate of dispersal of microarthropods (Auger et al. 1999, Ojala and Huhta 2001, Lehmitz et al. 2012). Therefore, it is 22 possible that if the communities were left to recover for a longer period of time that the benefit of rescue effects for diversity may have become apparent at the regional scale. Any increase in average alpha diversity due to rescue effects in connected metacommunities was offset by opposite trends in beta diversity. Specifically, connectivity increased microarthropod alpha diversity in asynchronously disturbed metacommunities but connectivity simultaneously reduced beta diversity in these same metacommunities, leading to no net effect of connectivity on gamma diversity. Why might connectivity reduce beta diversity in asynchronously disturbed metacommunities? Disturbance asynchrony creates a mosaic of patches in different stages of recovery (Caswell and Cohen 1991, Warren 1996, Limberger and Wickham 2012) and may also select for different species, as moss microarthropod communities are strongly seasonal (Stamou and Sgardelis 1989, Starzomski et al. 2008). Connectivity, on the other hand, homogenizes community composition by enabling dispersal of organisms throughout the landscape and enhancing regional competition (Mouquet and Loreau 2003, Chase et al. 2005). Disturbance imposed at different times thus tended to result in divergent community composition only in the absence of connectivity between patches. Rescue effects did not occur in isolated communities, as we predicted. Instead, we found a surprising ‘inverse rescue effect’ for isolated communities, whereby asynchronous disturbance was more detrimental to alpha diversity than synchronous disturbance. This result was consistent across most groups of microarthropod but its cause was unclear. Tullgren funnel extraction, imposed as a disturbance in this experiment, induces microarthropods to travel downward in response to a heat and light gradient. Microarthropods remaining in the desiccated moss patches following disturbance may have been cued to evacuate the patches, crossing the concrete matrix in isolated metacommunities. For example, drought has been shown to increase dispersal of the 23 mesostigmatid mite Neoseiulus californicus across a plastic surface (Auger et al. 1999). A similar evacuation response has been observed in a variety of taxa in response to disturbance (e.g. Carabid beetles and floods: Bates et al. 2006, salamanders and clearcuts: Semlitsch et al. 2008). When disturbance occurred asynchronously, the evacuation response may have resulted in decimation of regional diversity, as microarthropods surviving the first disturbance may have migrated to the adjacent patch, only to be extracted later in the experiment. By contrast, in synchronously disturbed metacommunities, this evacuation response may have resulted in emigration to a patch that was not disturbed further. This counterintuitive response may have obscured the pattern expected for rescue effects mediated by the moss corridors, as synchronously disturbed metacommunities had much higher than expected diversity in isolation. A fourth reason why rescue effects did not increase regional diversity is that connectivity may have increased top-down effects on the collembolans, such that significant rescue effects at the local scale did not result in higher regional diversity in these treatments. Rather, collembolans in disturbed habitats reached maximum diversity in isolated metacommunities, a pattern inverse to that of most other microarthropods, including the mesostigmatids. Collembolan dominance in isolated patches may have reflected lower predation pressure from mesostigmatids in such patches. Mesostigmatids prey on many of the undefended fungivorous microarthropods in the food web, including collembolans (Holtkamp et al. 2008, Schneider and Maraun 2009). Loss of habitat connectivity between moss patches has previously been shown to reduce mesostigmatid abundances, resulting in a release of fungivorous microarthropods (Staddon et al. 2010). It is unclear why this trophic cascade was not also observed in undisturbed metacommunities. However, it is possible that desiccation from the Tullgren funnel, as part of the disturbance, may have stimulated increases in collembolan abundance that were masked in 24 connected metacommunities by top-down control by mesostigmatids. Previous work in this system has also found that collembolans thrive in desiccated and isolated patches (Starzomski and Srivastava 2007, Åström and Bengtsson 2011). Aside from predator release, there may be increases in fungal growth or stimulation of egg hatching with desiccation that resulted in increases in their populations (Waagner et al. 2011). Orchesella collembolans, which were common in our samples, are known to reproduce after a period of starvation and renewed food availability (Siepel 1994). Inherent in the concept of rescue effects is the assumption that disturbance reduces community richness. For most groups, we did not find that disturbance significantly lowered diversity, even when it occurred globally (i.e. synchronously or in isolated habitats). This suggests a strong role for local sources in community recovery and a fifth reason why rescue effects did not substantially enhance regional diversity. The Tullgren funnel extraction was not a complete disturbance, so a proportion of microarthropods survived (André et al. 2002, Starzomski and Srivastava 2007). Reproduction by survivors with fast life cycles (e.g. collembolans and some small prostigmatids) could enable these communities to rebound quickly following disturbance. These moss microarthropod communities are also well-adapted to drought, which occurs regularly in Southern British Columbia. Mites and collembola survive these periods of environmental stress through resistant life stages such as eggs (Davidson 1932, Siepel 1994) and by entering dormant states (Siepel 1994). If there were many of these resistant forms present in the moss they would be available to repopulate the community following Tullgren funnel disturbance. As we didn’t see significant declines in species richness in disturbed patches, rescue effects may not have been necessary to maintain regional biodiversity. This result is consistent with findings from other microarthropod-based studies in which benign 25 conditions led to a minimal effect of corridors on diversity (Rantalainen et al. 2004, Hoyle and Gilbert 2004). Collectively the five processes described above may explain why rescue effects at the local scale did not result in greater regional diversity. This result does not support the spatial insurance hypothesis, which proposes that connectivity between habitats can maximize regional species richness in a variable environment by enabling species to track their specific niche as it fluctuates across the landscape (Loreau et al. 2003, Gonzalez et al. 2009). It also contrasts with the results of experiments performed in protist-based microcosms, which found inter-patch dispersal to counteract species loss from disturbance at regional scales (Warren 1996, Östman et al. 2006). The difference in results is likely attributable to the nonlinear effects of disturbance and dispersal on regional diversity (Miller and Kneitel 2005, Cadotte 2007). How these factors interact to affect regional diversity is not well understood and certainly depends on the realized disturbance and dispersal rates (Caswell and Cohen 1991). For instance, dispersal was most important for the recovery of local and regional diversity at high disturbance intensities in microalgal and protist metacommunities (Warren 1996, Matthiessen et al. 2010). Incomplete disturbance in another protist microcosm meant that reproduction by surviving individuals was sufficient to maintain community composition and connection to undisturbed patches did not improve regional diversity, although it improved population recovery following disturbance (Altermatt et al. 2011). Given the strong local regeneration observed in our experiment, it is possible that disturbance intensity was not high enough for a difference in dispersal rate mediated by our corridor treatments to become apparent. Just as the disturbance intensity may have been too low for the importance of rescue effects to become apparent at the regional scale, the lag in recovery of August patches suggests 26 that the disturbance frequency may have been too high to match the recolonization rate of microarthropods crossing the moss corridors. Many previous studies have shown that disturbance frequency and intensity must match the regenerative potential of communities in order to maintain maximal regional diversity (e.g. Moloney and Levin 1996, Collins et al. 2001, Limberger and Wickham 2012). Indeed, the parameterization for the period of environmental fluctuations in the spatial insurance model requires that it is large enough to ensure competitive exclusion in the absence of dispersal (Loreau et al. 2003). Deviations from this ideal disturbance frequency could thus be at the root of the discrepancy in results between this experiment and the model predictions. The presence of trophic interactions may also underlie the difference between our results, the predictions of the spatial insurance hypothesis (Loreau et al. 2003), and findings from protist-based microcosms (Warren 1996, Östman et al. 2006). Although we did not find that rescue effects increased overall microarthropod regional diversity, we did find evidence of this effect for the predatory mesostigmatid mites. This result is not surprising, as the greater mobility of predators could increase their propensity for rescue effects (Gilbert et al. 1998). However, the positive effect of corridors for predators may have made it less likely for prey diversity to be recovered by rescue effects. This notion is supported in experimental protist metacommunities, where loss of spatial refuge from a generalist predator with increasing connectivity resulted in regional diversity decline (Cadotte and Fukami 2005). Like the majority of metacommunity theory to date, the spatial insurance hypothesis is based in a system with a single trophic level, where competition drives the dynamics. Other experiments have found the features of multitrophic systems to disrupt patterns observed in single trophic systems. For example, the presence of filter-feeding mosquito larvae in pitcher 27 plants flattened the hump-shaped relationship seen between dispersal rate and protozoa and rotifer diversity (Kneitel and Miller 2003). On a similar note, active dispersal and habitat selection by crustacean grazers in seagrass metacommunities nullified the stabilizing effect of biodiversity on regional primary and secondary production (France and Duffy 2006). Here we show that trophic interactions may affect the ability for rescue effects to enhance the regional diversity of prey species. It is noted that although predators had a negative effect on prey diversity in this experiment, predators can often have a positive effect on prey diversity by mediating coexistence of competitors (Shurin and Allen 2001, Chase et al. 2002). Although we did not find that habitat corridors were necessary to maintain regional diversity, other conservation values of corridors were demonstrated in this work. Corridors mediated rescue effects that enhanced the recovery of local diversity following disturbance, particularly for prey species. This important aspect of ecosystem resilience will fundamentally depend on the presence of biodiversity in the region and could ultimately contribute to its maintenance. Indeed, rescue effects may be more important for maintaining regional biodiversity under higher intensity disturbance than was used in this experiment (Warren 1996). Although, the higher predator: prey ratio in connected habitats may have disrupted rescue effects for prey, it may also indicate greater resilience of these communities to fragmentation and disturbance. Intact and well-connected habitats across many ecosystem types are characterized by a higher predator: prey ratio than fragmented habitats (insects on fungus: Komonen et al. 2000, bark- beetles in forest fragments: Ryall and Fahrig 2005, aquatic insect larvae: Shulman and Chase 2007, moss microarthropods: Staddon et al. 2010). We caution that increased connectivity can enhance species interactions that may limit the value of corridors for regional diversity but we 28 also note that ongoing habitat fragmentation is resulting in such a rapid erosion of connectivity that it may be unlikely for "too much" connectivity to be obtained by corridor manipulations. 29 Tables and Figures Table 1. Summary of linear models assessing the effect of connectivity and disturbance regime on local morphospecies richness (α), beta diversity (β), regional morphospecies richness (γ), and regional abundance (N) for all microarthropods combined and for different taxonomic, ontogenetic and trophic subgroups. Model results for metacommunity predator: prey ratio, calculated as the proportion of predatory individuals, are also presented. Significant results are indicated by an asterisk. Response Linear Model P-Value Significant Covariates Connectivity Disturbance Connectivity: Disturbance All Microarthropods α 0.713 0.280 0.652 ER, P2 β 0.377 0.143 0.035* γ 0.460 0.689 0.452 ER N 0.741 0.931 0.554 ER, P1, P2 Mesostigmatid α 0.016* 0.728 0.067 S, P2 β 0.499 0.881 0.030* P2 γ 0.015* 0.812 0.445 P2 N 0.176 0.755 0.043* P2 Collembola α 0.853 0.897 0.001* P1 β 0.760 0.966 0.338 S γ 0.547 0.811 0.007* N 0.996 0.916 0.079 ER, P1 Adult Oribatid α 0.236 0.036* 0.768 ER, P2 β 0.494 0.322 0.349 γ 0.596 0.010*A 0.326 N 0.181 0.502 0.714 ER, P2 Juvenile Oribatid α 0.193 0.051 0.009 S β 0.009* 0.038* 0.050* M,ER γ 0.038* 0.150 0.165 N 0.751 0.584 0.297 Prostigmatid α 0.516 0.861 0.758 β 0.273 0.800 0.938 γ 0.911 0.727 0.689 N 0.857 0.480 0.198 Predator: Prey Ratio N 0.078 0.565 0.002* P2 A Adult Oribatid γ: Synch August > Synch May, P=0.005 30 Figure 1. Generalized moss microarthropod food web. Original artwork by Pamela Matute. 31 Figure 2. Predictions for isolated and connected metacommunities: The difference in local richness between asynchronously and synchronously disturbed metacommunities (A), as well as average local richness (B) and beta diversity under different disturbance regimes (C). Disturbance regime is indicated by symbol color and shape (black square= undisturbed, grey circle= asynchronous, and grey triangle= synchronous). -6 -4 -2 0 2 4 6 Isolated Connected D if fe re n c e in l o c a l ri c h n e s s A>S A=S A<S A Isolated Connected Isolated Connected Isolated Connected Connectivity B C 32 Figure 3. Experimental moss metacommunity treatments established on a concrete matrix. Three levels of connectivity were created by connecting patches with increasing numbers of moss corridors. The pseudocorridor tabs ensured that all metacommunities had similar area and geometry. The connectivity treatments were crossed with four disturbance regime treatments. The timing of disturbance is indicated by the color of the circle (white= undisturbed, dark grey= disturbed in May, light grey= disturbed in August, black= disturbed in both May and August). Each of the 12 treatments was replicated 5 times. . Pseudocorridor Corridor Moss Patch 10 cm Isolated 1-Corridor 2-Corridor Disturbance Regime Undisturbed May Undisturbed Asynchronous Synchronous May Synchronous August Concrete matrix Connectivity 33 A B C D Figure 4. Difference in local microarthropod and mesostigmatid richness and abundance between metacommunities that were asynchronously (A) and synchronously (S) disturbed under different levels of connectivity. Bootstrapped mean differences and 95% confidence intervals were calculated using patches that were disturbed in the same month (filled circles= May and empty circles= August). Significant differences (95% confidence intervals do not overlap zero) are indicated by asterisks. -15 -10 -5 0 5 10 15 Isolated 1-Corridor 2-Corridor D if fe re n c e i n l o c a l ri c h n e s s -250 -200 -150 -100 -50 0 50 100 150 200 250 Isolated 1-Corridor 2-Corridor D if fe re n c e i n l o c a l a b u n d a n c e -5 -4 -3 -2 -1 0 1 2 3 4 5 Isolated 1-Corridor 2-Corridor D if fe re n c e i n l o c a l ri c h n e s s -60 -40 -20 0 20 40 60 Isolated 1-Corridor 2-Corridor D if fe re n c e i n l o c a l a b u n d a n c e * * * * A >S A=S A<S Microarthropods A >S A=S A<S Mesostigmatids Mesostigmatids Connectivity Connectivity Microarthropods * 34 Figure 5. Regional richness and abundance of different subgroups of microarthropod (A-G) and the predator: prey ratio, calculated as the proportion of predatory individuals (H), in two-patch metacommunities with different disturbance regimes and levels of connectivity; N=5, error bars are SEM. Disturbance regime is indicated by symbol shape and color (black square= undisturbed (U), grey circle= asynchronous (A), grey triangle= synchronous May (SM), and white triangle= synchronous August (SA)). Significant contrasts are shown as inequalities on the figure panel (treatment contrasts) or below the connectivity level of the figure panel (interaction contrasts), with all contrasts following significant main effects and interactions (Table 1). 35 Isolated 1-Corridor 2-Corridor Isolated 1-Corridor 2-Corridor Isolated 1-Corridor 2-Corridor *0<1,2 * 2>1 *A>SM>SA *U<A,SM,SA *U<A,SM,SA *U>A,SM,SA *U<A,SM,SA *A<SM,SA *A>SM>SA Connectivity Connectivity P re d a to r: P re y R a ti o R e g io n a l a b u n d a n c e R e g io n a l s p e c ie s r ic h n e s s R e g io n a l a b u n d a n c e R e g io n a l a b u n d a n c e Isolated 1-Corridor 2-Corridor Isolated 1-Corridor 2-Corridor Isolated 1-Corridor 2-Corridor Isolated 1-Corridor 2-Corridor Isolated 1-Corridor 2-Corridor R e g io n a l s p e c ie s r ic h n e s s R e g io n a l s p e c ie s r ic h n e s s R e g io n a l s p e c ie s r ic h n e s s A C E G B D F H 36 Figure 6. Microarthropod (A), mesostigmatid (B), and juvenile oribatid (C) beta diversity in two-patch metacommunities with different disturbance regimes and levels of connectivity; N=5, error bars are SEM. Disturbance regime is indicated by symbol shape and color (black square= undisturbed (U), grey circle= asynchronous (A), grey triangle= synchronous May (SM), and white triangle= synchronous August (SA)). Significant contrasts are shown as inequalities on the figure panel (treatment contrasts) or below the connectivity level of the figure panel (interaction contrasts),with all contrasts following significant main effects and interactions (Table 1). Isolated 1-Corridor 2-Corridor Isolated 1-Corridor 2-Corridor Isolated 1-Corridor 2-Corridor *A>SM,SA *SM<SA *U>A,SM,SA *U<A,SM,SA *U>A,SA,SB A B C Connectivity 37 Conclusion Habitat corridors enabled rescue effects across most groups of microarthropod that facilitated the recovery of local diversity following disturbance. These results corroborate other studies that demonstrate that rescue effects mitigate microarthropod extinction after fragmentation (Gilbert et al. 1998, Gonzalez et al. 1998, Staddon et al. 2010) and enhance the resilience of microarthropod communities to drought disturbance at the local scale (Starzomski and Srivastava 2007). It was expected that rescue effects may also result in higher regional diversity in disturbed metacommunities, as they could enable disturbance sensitive species to survive in the landscape by tracking undisturbed refugia (Loreau et al. 2003, Gonzalez et al. 2009). However, this hypothesis was not supported for five main reasons: 1) average alpha diversity was not significantly improved by rescue effects as they occurred in only one of the two disturbance events, 2) beta diversity declined with connectivity, which counteracted any increase in average alpha diversity, 3) an 'inverse rescue effect' in isolated systems led to synchronously disturbed metacommunities having higher regional diversity than asynchronously disturbed metacommunities, 4) top down control by mesostigmatids in connected systems had a negative impact on collembola diversity, 5) and disturbance did not have a substantially negative impact such, that rescue effects were not critical to maintain regional diversity. Our finding that rescue effects did not increase regional diversity does not agree with the results of experiments performed in protist-based microcosms (Warren 1996, Östman et al. 2006). Nonlinear influences of dispersal and disturbance on regional diversity likely contributed to the difference in results (Matthiessen and Hillebrand 2006, Cadotte 2007). Dispersal and disturbance are both capable of enhancing or decreasing diversity and the interaction between 38 these factors could thus be highly complex (Caswell and Cohen 1991). The difference in results between this experiment and those performed in protist-based microcosms highlights the complexity of this interaction and the importance of investigating questions in a variety of experimental systems to ensure broad applicability of results. This experiment does not support the prediction of the spatial insurance hypothesis that interpatch dispersal in asynchronously disturbed metacommunities will maximize regional diversity (Loreau et al. 2003). This is expected to occur as disturbance-tolerant and disturbance-sensitive species track their preferred environmental conditions across the landscape (Loreau et al. 2003, Gonzalez et al. 2009). Fundamental differences in the features of the moss microarthropod system and the assumptions of the spatial insurance model contributed to the difference in results. In particular, the presence of different trophic groups led to indirect effects that changed the expected outcome of corridor manipulations for prey diversity. The inclusion of trophic interactions has been found by other researchers to disrupt the patterns observed in systems with a single trophic level (Kneitel and Miller 2003, France and Duffy 2006). However, most metacommunity theory to date does not include trophic interactions so there is a lack of theory for multitrophic systems. Gaining greater understanding of how trophic interactions in a spatial context affect the structure and function of communities represents a major avenue of research that community ecologists are only beginning to explore (e.g. Pillai et al. 2009, Gonzalez et al. 2011). The findings of this study make an important contribution to this endeavor. Although we did not find support for the maximizing effect of interpatch dispersal for regional diversity that is predicted by the spatial insurance hypothesis, our experiment does not refute this hypothesis. Indeed our evidence of rescue effects at the local scale demonstrates an 39 important element of spatial insurance in that colonization from surrounding areas enhanced local community recovery following disturbance. Rescue effects will ultimately rely upon the maintenance of regional diversity, so the importance of determining strategies to maintain regional biodiversity in fragmented landscapes is critical to ensuring ecosystem resilience. Future Directions An important aspect of spatial insurance that is not addressed in this experiment, or indeed by any experiment performed to date, is the capacity for dispersal to stabilize ecosystem function under fluctuating environmental conditions. This stabilization is expected to occur as dispersal enables species to access and thrive in the areas where they are best suited to the prevailing environmental conditions (Loreau et al. 2003). To assess the stabilizing effect of interpatch dispersal, it would be necessary to collect time series data (A. Gonzalez, personal communication). This may not be possible in the moss microarthropod system due to the destructive nature of the sampling. A test of the spatial insurance hypothesis using a different experimental system such as a protist-based microcosm could thus be warranted. In addition to the ability to sample such as system over time, the simpler nature of the food web would facilitate interpretation of the mechanisms behind the results. As we were working with morphospecies in the moss microarthropod system, very little information was known about their specific biology, including their competitive and trophic interactions. Even if proper identification had been performed, this information is often not available for microarthropod species but would be very helpful in interpreting the outcomes of the experiment. The 'inverse rescue effect' we observed in isolated habitats challenges our initial assumption of no dispersal across the concrete matrix. This assumption was based on previous 40 studies with this system that were typically conducted without disturbance by Tullgren funnel extraction (but see Starzomski and Srivastava 2007). However, recent findings by Åstrom and Pårt (In Press) suggest that matrix quality has a substantial influence on microarthropod communities, lending additional support to the importance of microarthropod dispersal across the matrix. Mites may have abandoned disturbed patches in search of higher quality habitat and may have only evacuated patches in asynchronously disturbed systems because they could sense the presence of higher quality habitat nearby. As this response is only implied by the results of this experiment, further investigation into the evacuation response of microarthropods to Tullgren funnel extraction is warranted. This response may have resulted in dispersal of mites between our experimental metacommunities, which could have reduced the effectiveness of the treatments and made it more difficult to detect corridor effects. Albeit, the clear evidence we found for rescue effects and the strong response seen for mesostigmatid mites to the corridor treatments suggests that dispersal by these means was not so strong as to undermine the importance of the corridors. Management Implications Several experiments have demonstrated the value of corridors for curbing species extinctions resulting from habitat fragmentation (e.g. Gonzalez et al. 1998, Damschen et al. 2006). However, few have examined the role of corridors in maintaining diversity in disturbed metacommunities (Warren 1996, Loreau et al. 2003, Östman et al. 2006, Starzomski and Srivastava 2007, Howeth and Leibold 2010, Altermatt et al. 2011, Chisholm et al. 2011, Åström and Pärt In Press). Our results suggest that habitat corridors may not be the most effective means of maintaining regional biodiversity in disturbed metacommunities. While greater connectivity 41 mediated by the corridors enabled rescue effects, it also eliminated spatial refuge from competition and predation, which counteracted the benefit of rescue effects for regional diversity. This homogenizing effect of connectivity is well supported by metacommunity theory (Mouquet and Loreau 2003, Chase et al. 2005). Although we do not find strong support for corridors enhancing regional diversity, we caution, that corridors may play an important role in maintaining regional biodiversity under higher disturbance intensity than was used in this experiment (Warren 1996). Clear evidence of rescue effects at the local scale also provides strong support for the conservation value of habitat corridors. Faster recovery of diversity following disturbance is indicative of greater ecosystem resilience and could ultimately contribute to the maintenance of regional biodiversity. Our results additionally suggest that corridor manipulations may be an effective strategy for increasing predator diversity. Connectivity increased predatory mesostigmatid mite diversity and the predator: prey ratio, which corroborates the findings of other experiments (Gilbert et al. 1998, Komonen et al. 2000, Shulman and Chase 2007, Staddon et al. 2010). As corridors can result in very different trophic structures, conservation managers should consider the desired outcome of corridor manipulations carefully. For instance, if the objective is to increase prey diversity, corridors may not be the best approach. It is noted, that the dispersal characteristics and body size of predators and prey will have bearing on the generality of this result (de Bie et al. 2012). For example, a system dominated by lie-in-wait predators and wide ranging prey species may respond very differently than the moss microarthropod system examined here. While habitat corridors are a potentially important means of increasing connectivity of communities in fragmented habitats, the 'inverse rescue effect' seen in this experiment highlights that the qualities of matrix habitat can also have a large influence on the level of dispersal 42 between habitats. The role of matrix quality for connectivity in fragmented habitats has been demonstrated in several other studies (Robichaud et al. 2002, Selonen and Hanski 2003, Taylor et al. 2006, Castellón and Sieving 2006, Åström and Pärt In Press). 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Biodiversity and ecosystem productivity in a fluctuating environment: The insurance hypothesis. Proceedings of the National Academy of Sciences of the United States of America 96:1463-1468. 53 Appendices Appendix 1. Photos of experimental set-up Figure A1.1.Photograph of the moss prior to collection for the experiment. Figure A1.2. Photographs of the moss connectivity treatments. 54 Figure A1.3. Photograph of experimental moss metacommunities arranged on concrete slabs in a grid pattern on the south UBC campus. Figure A1.4. Photograph of experimental moss metacommunities showing bird netting and 50% shade-cloth, which protected the moss from dessication and wildlife. 55 Appendix 2. Model Selection Results Model selection results for local richness, beta diversity, and regional richness and abundance are presented in below. Models tested included connectivity level (Connectivity), disturbance regime (Disturbance), their interaction (Connectivity × Disturbance), and all possible combinations of the following covariates: the combined mass of both patches (Mass), the extraction round (ExtractRound), the names of the people that sorted the samples (Sorter), and the position of the metacommunity relative the edge of the grid for the first (Pos1) and second half of the experiment (Pos2), as well as their interaction (Pos1:Pos2). AIC was used to select the final model. The model with the lowest AIC value was selected unless there was an equivalent model (with an AIC value within 2 units of the “best” model) that included fewer covariates but the same significant variables. The tables below present all candidate models and the model that was selected is highlighted. Microarthropods Table A2. 1. Model selection results for microarthropod local richness. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+Mass+ExtractRound+Pos2 328.027 0.000 0.713 0.280 0.652 ExtractRound;Pos2 3 Connectivity:Disturbance+Mass+ExtractRound+Pos1+Pos2 329.695 1.668 0.657 0.252 0.548 ExtractRound;Pos2 4 56 Table A2.2. Model selection results for microarthropod beta diversity. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+Sorter+Pos1 -79.697 0.000 0.377 0.143 0.035* 2 Connectivity:Disturbance+Pos1 -79.350 0.347 0.392 0.108 0.112 1 Connectivity:Disturbance -78.459 1.238 0.459 0.265 0.176 0 Connectivity:Disturbance+Mass+Pos1 -78.235 1.462 0.565 0.163 0.157 2 Connectivity:Disturbance+Sorter+ExtractRound+Pos1 -77.884 1.813 0.382 0.147 0.038* 3 Connectivity:Disturbance+Mass+Sorter+Pos1 -77.768 1.929 0.565 0.212 0.054* 3 Table A2.3. Model selection results for microarthropod regional richness. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+ExtractRound+Pos2 364.976 0.000 0.700 0.422 0.709 ExtractRound 2 Connectivity:Disturbance+ExtractRound 365.621 0.644 0.460 0.689 0.452 ExtractRound 1 Connectivity:Disturbance+Mass+ExtractRound+Pos2 366.512 1.536 0.706 0.403 0.695 ExtractRound 3 Connectivity:Disturbance+ExtractRound+Pos1+Pos2 366.913 1.936 0.688 0.390 0.605 ExtractRound 3 Table A2.4. Model selection results for microarthropod regional abundance. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+Mass+ExtractRound+Pos1+Pos2 +Pos1:Pos2 761.623 0.000 0.730 0.926 0.471 ExtractRound; Pos1;Pos2 5 Connectivity:Disturbance+Mass+ExtractRound+Pos1+Pos2 762.444 0.821 0.741 0.931 0.554 ExtractRound; Pos1;Pos2 4 Connectivity:Disturbance+Mass+Sorter+ExtractRound +Pos1+Pos2+Pos1:Pos2 763.448 1.825 0.817 0.897 0.277 ExtractRound; Pos1;Pos2 6 57 Mesostigmatids Table A2.5. Model selection results for mesostigmatid local richness. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+Mass+Sorter+ExtractRound+Pos2 192.654 0.000 0.045 0.370 0.139 Sorter;Pos2 4 Connectivity:Disturbance+Sorter+ExtractRound+Pos2 193.130 0.477 0.016* 0.728 0.067* Sorter;Pos2 3 Table A2.6. Model selection results for mesostigmatid beta diversity. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+Sorter+ExtractRound+Pos1+Pos2 35.493 0.000 0.402 0.742 0.016* Pos2 4 Connectivity:Disturbance+Sorter+ExtractRound+Pos1 35.648 0.155 0.166 0.957 0.002* 3 Connectivity:Disturbance+Sorter+ExtractRound+Pos2 36.935 1.442 0.499 0.881 0.030* Pos2 3 Connectivity:Disturbance+Mass+Sorter+ExtractRound+Pos1 37.412 1.919 0.215 0.966 0.003* 4 Connectivity:Disturbance+Mass+Sorter+ExtractRound+Pos1+Pos2 37.484 1.991 0.502 0.723 0.022* Pos2 5 Table A2.7. Model selection results for mesostigmatid regional richness. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+Mass+Sorter+ExtractRound+Pos2 208.684 0.000 0.058* 0.393 0.489 Pos2 4 Connectivity:Disturbance+ExtractRound+Pos2 208.999 0.316 0.015* 0.812 0.445 Pos2 2 Connectivity:Disturbance+Pos2 209.635 0.951 0.023* 0.897 0.520 Pos2 1 Connectivity:Disturbance+Mass+ExtractRound+Pos2 210.056 1.372 0.028* 0.753 0.564 Pos2 3 Connectivity:Disturbance+Sorter+ExtractRound+Pos2 210.042 1.358 0.022* 0.730 0.265 Pos2 3 58 Table A2.8. Model selection results for mesostigmatid regional abundance. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+Sorter+ExtractRound+Pos1+Pos2 528.375 0.000 0.146 0.637 0.024 Pos2 4 Connectivity:Disturbance+ExtractRound+Pos2 528.800 0.425 0.155 0.838 0.189 Pos2 2 Connectivity:Disturbance+Mass+Sorter+ExtractRound+Pos1+Pos2 528.970 0.595 0.308 0.687 0.051 Mass;Pos2 5 Connectivity:Disturbance+Mass+ExtractRound+Pos2 529.352 0.977 0.292 0.877 0.255 Mass;Pos2 3 Connectivity:Disturbance+Pos2 529.846 1.471 0.183 0.849 0.306 Pos2 1 Connectivity:Disturbance+Mass+Sorter+ExtractRound+Pos2 529.880 1.505 0.326 0.787 0.060 Mass;Pos2 4 Connectivity:Disturbance+Sorter+ExtractRound+Pos1+Pos2+Pos1:Pos2 529.982 1.607 0.149 0.639 0.011 Pos2 5 Connectivity:Disturbance+Sorter+Pos1+Pos2 530.226 1.851 0.174 0.665 0.052 Pos2 3 Connectivity:Disturbance+Sorter+ExtractRound+Pos2 530.335 1.960 0.176 0.755 0.043 Pos2 3 Adult Oribatids Table A2.9. Model selection results for adult oribatid local richness. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+ExtractRound+Pos1+Pos2+Pos1:Pos2 166.750 0.000 0.162 0.044 0.335 ExtractRound;Pos2 4 Connectivity:Disturbance+ExtractRound+Pos2 168.740 1.990 0.236 0.036 0.768 ExtractRound;Pos2 2 Connectivity:Disturbance+Mass+ExtractRound+Pos1+Pos2+Pos1:Pos2 168.704 1.955 0.195 0.051 0.349 ExtractRound;Pos2 5 Table A2.10. Model selection results for adult oribatid beta diversity. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance 65.169 0.000 0.494 0.322 0.349 0 Connectivity:Disturbance+Mass 66.862 1.693 0.451 0.361 0.339 1 Connectivity:Disturbance+ExtractRound 66.993 1.824 0.522 0.304 0.489 1 59 Table A2.11. Model selection results for adult oribatid regional richness. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+ExtractRound 211.766 0.000 0.656 0.008 0.191 1 Connectivity:Disturbance+ExtractRound+Pos2 212.274 0.508 0.499 0.004 0.442 2 Connectivity:Disturbance 213.233 1.467 0.596 0.010 0.326 0 Connectivity:Disturbance+Pos2 213.307 1.541 0.435 0.004 0.625 1 Connectivity:Disturbance+Mass+ExtractRound 213.679 1.913 0.642 0.011 0.198 2 Table A2.12. Model selection results for adult oribatid regional abundance. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+ExtractRound+Pos2 606.348 0.000 0.181 0.502 0.714 ExtractRound;Pos2 2 Connectivity:Disturbance+Mass+ExtractRound+Pos2 608.206 1.858 0.209 0.443 0.769 ExtractRound;Pos2 3 Juvenile Oribatids Table A2.13. Model selection results for juvenile oribatid local richness. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+Sorter+Pos1 118.146 0.000 0.193 0.051 0.009 Sorter 2 Connectivity:Disturbance+Mass+Sorter+Pos1 118.393 0.247 0.188 0.054 0.007 Sorter 3 Connectivity:Disturbance+Mass+Sorter+ExtractRound+Pos1 118.410 0.264 0.166 0.046 0.011 Sorter 4 Connectivity:Disturbance+Sorter+Pos1+Pos2 118.979 0.833 0.204 0.040 0.007 Sorter 3 Connectivity:Disturbance+Sorter+ExtractRound+Pos1 119.361 1.215 0.176 0.047 0.014 Sorter 3 Connectivity:Disturbance+Mass+Sorter+Pos1+Pos2 120.023 1.877 0.194 0.049 0.006 Sorter 4 60 Table A2.14. Model selection results for juvenile oribatid beta diversity. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+Mass+Sorter+ExtractRound +Pos1+Pos2+Pos1:Pos2 170.058 0.000 0.009 0.038 0.050 Mass;Pos1 6 Table A2.15. Model selection results for juvenile oribatid regional richness. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+Sorter+Pos1 187.619 0.000 0.038 0.150 0.165 2 Connectivity:Disturbance+Mass+Sorter+Pos1 188.361 0.742 0.037 0.125 0.198 3 Connectivity:Disturbance+Mass+Sorter+ExtractRound+Pos1 188.570 0.951 0.036 0.109 0.162 4 Connectivity:Disturbance+Sorter+ExtractRound+Pos1 188.825 1.206 0.039 0.151 0.150 3 Connectivity:Disturbance+Sorter+Pos1+Pos2 189.410 1.791 0.045 0.162 0.122 3 Table A2.16. Model selection results for juvenile oribatid regional abundance. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+Sorter 452.844 0.000 0.599 0.526 0.220 1 Connectivity:Disturbance+Sorter+Pos1 452.919 0.075 0.511 0.584 0.194 2 Connectivity:Disturbance+Sorter+ExtractRound+Pos1 453.597 0.753 0.561 0.614 0.159 3 Connectivity:Disturbance 454.213 1.369 0.751 0.584 0.297 0 Connectivity:Disturbance+Mass+Pos1 454.358 1.515 0.628 0.631 0.181 2 Connectivity:Disturbance+Sorter+ExtractRound 454.413 1.569 0.684 0.620 0.239 2 Connectivity:Disturbance+Mass 454.514 1.670 0.677 0.559 0.228 1 Connectivity:Disturbance+Pos1 454.553 1.709 0.716 0.646 0.254 1 Connectivity:Disturbance+Mass+Sorter 454.716 1.872 0.643 0.532 0.228 2 Connectivity:Disturbance+Mass+Sorter+Pos1 454.711 1.867 0.529 0.590 0.198 3 61 Prostigmatids Table A2.17. Model selection results for prostigmatid local richness. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+Mass+ExtractRound 247.955 0.000 0.776 0.874 0.826 2 Connectivity:Disturbance+ExtractRound 249.490 1.535 0.516 0.861 0.758 1 Connectivity:Disturbance+Mass+ExtractRound+Pos2 249.688 1.734 0.897 0.738 0.906 3 Table A2.18. Model selection results for prostigmatid beta diversity. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance -26.518 0.000 0.273 0.800 0.938 0 Connectivity:Disturbance+Mass -26.382 0.136 0.485 0.896 0.938 1 Connectivity:Disturbance+Sorter -25.985 0.533 0.342 0.540 0.796 1 Connectivity:Disturbance+ExtractRound -24.553 1.965 0.266 0.788 0.959 1 Connectivity:Disturbance+Mass+Sorter -24.563 1.955 0.541 0.666 0.803 2 Connectivity:Disturbance+Mass+ExtractRound -24.540 1.978 0.481 0.891 0.971 2 Connectivity:Disturbance+Mass+Pos2 -24.980 1.538 0.390 0.936 0.937 2 Connectivity:Disturbance+Sorter+ExtractRound -25.483 1.035 0.365 0.538 0.664 2 Connectivity:Disturbance+Sorter+Pos1 -24.612 1.906 0.385 0.524 0.730 2 Connectivity:Disturbance+Sorter+Pos2 -25.255 1.263 0.241 0.666 0.698 2 62 Table A2.19. Model selection results for prostigmatid regional richness. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+ExtractRound 275.783 0.000 0.848 0.728 0.533 1 Connectivity:Disturbance+Pos2 277.307 1.523 0.888 0.572 0.789 1 Connectivity:Disturbance+Mass+ExtractRound 276.175 0.391 0.819 0.671 0.584 2 Connectivity:Disturbance+Sorter+ExtractRound 275.960 0.177 0.933 0.820 0.252 2 Connectivity:Disturbance+ExtractRound+Pos2 276.511 0.728 0.912 0.579 0.680 2 Connectivity:Disturbance+Mass+Sorter+ExtractRound 276.352 0.569 0.899 0.649 0.334 3 Connectivity:Disturbance+Mass+ExtractRound+Pos2 276.253 0.470 0.803 0.453 0.742 3 Connectivity:Disturbance 277.209 1.426 0.911 0.727 0.689 0 Table A2.20. Model selection results for prostigmatid regional abundance. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance 599.973 0.000 0.857 0.480 0.198 0 Connectivity:Disturbance+Mass 600.825 0.852 0.930 0.485 0.168 1 Connectivity:Disturbance+ExtractRound 600.912 0.938 0.753 0.414 0.293 1 Connectivity:Disturbance+Mass+ExtractRound 601.350 1.377 0.865 0.417 0.252 2 Predator: Prey Ratio Table A2.21. Model selection results for predator: prey ratio, calculated as the proportion of predatory individuals in the metacommunity. Model Terms AIC DiffAIC Connect Disturb Int SigCov # Cov Connectivity:Disturbance+Sorter+ExtractRound+Pos2 -246.861 0.000 0.078 0.565 0.002 Pos2 3 Connectivity:Disturbance+Mass+Sorter+ExtractRound+Pos2 -244.870 1.991 0.148 0.626 0.003 Pos2 4 Connectivity:Disturbance+Sorter+ExtractRound+Pos1+Pos2+Pos1:Pos2 -246.156 0.705 0.071 0.608 0.001 Pos2 5 63 Appendix 3. Alpha Diversity Figures Connectivity Figure A3.1 Average alpha richness of different subgroups of microarthropods in two-patch metacommunities with different disturbance regimes and levels of connectivity; N=5, error bars are SEM. Disturbance regime is indicated by symbol shape and color (black square = Undisturbed (U), grey circle = Asynchronous (A), grey triangle = synchronous May (SM), white triangle = synchronous August (SA)). Significant contrasts are shown as inequalities on the figure panel (treatment contrasts) or below the connectivity level of the figure panel (interaction contrasts),with all contrasts following significant main effects and interactions (Table 1). *2,1>0 * U<A,SM,SA * U>A,SM,SA * SM<SA
Thesis/Dissertation
eng
Zoology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Interactive effects of dispersal rate and disturbance synchrony on microarthropod diversity at multiple spatial scales : rescue effects do not increase regional richness
Text