Forestry, Faculty of
DSpace
UBCV
Tikka, Kelsey
Master of Science - MSc
University of British Columbia
Within the predator guild of ecological communities are smaller-bodied mesopredators that have the ability to directly impact community structure and indirectly alter ecosystem processes. Interactions between predators can result in combined predator outcomes to their prey, termed Multiple Predator Effects (MPEs), that can be additive, antagonistic, or synergistic with the strength and direction contingent on predator identity and guild diversity. In streams on the west coast of North America, there are two co-occurring predatory stonefly larvae, Calineuria californica and Hesperoperla pacifica, both of which can cause direct depletion of the prey community which can cascade to indirectly alter leaf litter decomposition and periphyton standing stock. My objective was to quantify the role and outcome of intra- and interspecific interactions of C. californica and H. pacifica on stream food webs. I manipulated stonefly larvae identity and density, as well as richness of the predator guild, then compared larval growth and survival, prey community composition, and measures of basal resources to determine the MPE outcomes. I hypothesized that due to the high degree of niche overlap that competition would lead to antagonistic MPEs. I also hypothesized that increasing density and the presence of the more aggressive H. pacifica would lead to higher competition and stronger antagonistic MPEs. I found that stonefly larvae presence caused a 46% reduction in the prey community, and that increasing biomass of either species significantly caused this decline. For interspecific and intraspecific C. californica pairings there was density-dependent competition resulting in a switch from additive to antagonistic MPEs, while intraspecific H. pacifica pairings had antagonistic MPEs at all densities. I also found that the mechanism of predator impacts varied between the two species, with H. pacifica decreasing the prey community through consumption and C. californica through non-consumptive behavioural modification of prey. However, the effects to the prey community did not cascade to impact the basal resources. My results demonstrate that the type and strength of predator interactions may be contingent on the composition of the predator guild and may result in unexpected, non-linear outcomes to the community.
OUTCOMES OF STREAM INVERTEBRATE MESOPREDATOR INTERACTIONS TO BENTHIC FOOD WEBS AND ECOSYSTEM FUNCTIONS by Kelsey Tikka B.Sc. (Hons), University of British Columbia, 2020 B.Sc. (Hons), Wilfrid Laurier University, 2015 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Forestry) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) October 2022 © Kelsey Tikka, 2022 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Outcomes of stream invertebrate mesopredator interactions to benthic food webs and ecosystem functions submitted by Kelsey Tikka in partial fulfillment of the requirements for the degree of Master of Science in Forestry Examining Committee: John Richardson, Professor, Forestry, UBC Supervisor Katie Marshall, Assistant Professor, Zoology, UBC Supervisory Committee Member Christopher Harley, Professor, Zoology, UBC Supervisory Committee Member Juli Carrillo, Assistant Professor, Land and Food Systems, UBC Additional Examiner iii Abstract Within the predator guild of ecological communities are smaller-bodied mesopredators that have the ability to directly impact community structure and indirectly alter ecosystem processes. Interactions between predators can result in combined predator outcomes to their prey, termed Multiple Predator Effects (MPEs), that can be additive, antagonistic, or synergistic with the strength and direction contingent on predator identity and guild diversity. In streams on the west coast of North America, there are two co-occurring predatory stonefly larvae, Calineuria californica and Hesperoperla pacifica, both of which can cause direct depletion of the prey community which can cascade to indirectly alter leaf litter decomposition and periphyton standing stock. My objective was to quantify the role and outcome of intra- and interspecific interactions of C. californica and H. pacifica on stream food webs. I manipulated stonefly larvae identity and density, as well as richness of the predator guild, then compared larval growth and survival, prey community composition, and measures of basal resources to determine the MPE outcomes. I hypothesized that due to the high degree of niche overlap that competition would lead to antagonistic MPEs. I also hypothesized that increasing density and the presence of the more aggressive H. pacifica would lead to higher competition and stronger antagonistic MPEs. I found that stonefly larvae presence caused a 46% reduction in the prey community, and that increasing biomass of either species significantly caused this decline. For interspecific and intraspecific C. californica pairings there was density-dependent competition resulting in a switch from additive to antagonistic MPEs, while intraspecific H. pacifica pairings had antagonistic MPEs at all densities. I also found that the mechanism of predator impacts varied between the two species, with H. pacifica decreasing the prey community through consumption and C. californica through non-consumptive behavioural modification of prey. However, the effects to the prey community did not cascade to impact the basal resources. My results demonstrate that the type and strength of predator interactions may be contingent on the composition of the predator guild and may result in unexpected, non-linear outcomes to the community. iv Lay Summary Interactions between predators can have no impact to their consumption (feeding) rates or alternatively lead to decreased or increased consumption depending on the species and density of predators involved and the degree of overlap in prey resources. The changes in predator consumption can impact prey abundance as well as basal resources. My objectives were to determine the type of interaction between two predatory stonefly larvae and the impacts to prey, algae, and leaf litter in small streams. I found that the type and strength of predator interactions, and its effects to the prey community, differed between stonefly species and density. Generally, I found that both species interacted competitively leading to lower consumption than when larvae were alone. I also found that competitive interactions did not impact stonefly growth, survival, leaf litter or algae. My results further our understanding of the role of interactions between predatory individuals in impacting community structure. v Preface Kelsey Tikka was the primary author of this work and was responsible for completing the majority of the fieldwork conducted in UBC’s Malcolm Knapp Research Forest and laboratory work in John Richardson’s Stream and Riparian Research lab, along with the data analysis, and thesis preparation. Kelsey worked in collaboration with John Richardson, who provided guidance throughout the development of project ideas, experimental design, and thesis preparation. Fieldwork and laboratory assistance was provided by several assistants, particularly Karlee Orvis, Grace Melchers, and Paulina Chalmers. This thesis will be edited for manuscript form to be submitted for publication under co-authorship of Kelsey Tikka and John Richardson. vi Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ............................................................................................................................... iv Preface .............................................................................................................................................v Table of Contents ......................................................................................................................... vi List of Tables .............................................................................................................................. viii List of Figures ............................................................................................................................. viii List of Abbreviations ...................................................................................................................xv Acknowledgements .................................................................................................................... xvi 1. Introduction ............................................................................................................................1 1.1 Predator-prey dynamics and community-level processes ............................................... 2 1.2 Predator-Predator Interactions ........................................................................................ 6 1.3 Stream communities...................................................................................................... 10 1.4 Objectives and hypothesis............................................................................................. 13 2. Methods .................................................................................................................................18 2.1 Experimental design...................................................................................................... 18 2.2 Response parameters ..................................................................................................... 20 2.3 Statistical analysis ......................................................................................................... 23 3. Results ...................................................................................................................................29 3.1 Larval growth and survival ........................................................................................... 29 3.2 Benthic invertebrate community ................................................................................... 30 3.3 Leaf pack invertebrate community ............................................................................... 33 3.4 Ecosystem function ....................................................................................................... 34 4. Discussion..............................................................................................................................53 4.1 Impacts to benthic invertebrate abundance and MPEs ................................................. 53 4.2 Leaf pack invertebrates – consumptive vs behavioural impacts ................................... 58 4.3 Community structure .................................................................................................... 59 4.4 Impacts to stonefly larvae growth and survival ............................................................ 61 4.5 Trophic cascades ........................................................................................................... 63 5. Limitations and future directions .......................................................................................65 vii 6. Conclusions ...........................................................................................................................70 References .....................................................................................................................................72 Appendices ....................................................................................................................................84 Appendix A: Intraspecific interactions of Calineuria californica across a density gradient and implications for benthic food webs and ecosystem function in laboratory microcosms .......... 84 Appendix B: Supplemental figures ......................................................................................... 110 viii List of Tables Table 3.1 The number of larvae at the beginning of the experiment, and those recovered from each treatment, as well as the total percentage recovery and precent of successful replicates per treatment. Treatment abbreviations correspond to 1 C. californica (1Cc), 1 H. pacifica (1Hp), 2 C. californica (2Cc), 2 H. pacifica (2Hp), 1 C. californica + 1 H. pacifica (1Cc1Hp), 4 C. californica (4Cc, 4 H. pacifica (4Hp), and 2 C. californica + 2 H. pacifica (n = 4). ................... 35 Table A.1 The number of C. californica (Cc) larvae at the beginning of the experiment, and those recovered from treatments with 1, 2, 3, or 4 individuals, as well as the total percentage recovery and precent of successful replicates per treatment. ........................................................ 93 Table A.2 Summary (mean and standard deviation (SD)) of prey abundance for each subset of data in treatments with 0 (control), 1, 2, 3, or 4 C. californica (Cc). Survival/Prey model was the one used for all data analysis (n=14). ........................................................................................... 95 Table A.3 The number of observations, AICc values and weights for the 4 subsets of data used to run models for prey abundance to determine appropriate model to use for all response variables...................................................................................................................................................... 107 Table A.4 Functional feeding group (FFG) association of all identified taxa. Percentages in parentheses correspond to the relative contribution of each taxon to the associated FFG. ........ 109 Table B.1 The number of observations, AICc values and weights, and adjusted R2 for the 3 subsets of data used to run models for prey abundance to determine most appropriate model to use for all response variables. The Full dataset model did not meet model assumptions ........... 110 ix List of Figures Figure 1.1 Visual representation of the proportion of prey consumed by individual predators A and B in independent isolated systems and the additive (blue), antagonistic (red), and synergistic (green) Multiple Predator Effects (MPEs) that may arise due to intra- and interspecific pairings. Note, units of prey consumed are arbitrary and are used for ease of interpretation of MPEs. ..... 16 Figure 1.2 Predicted outcomes to prey abundance (solid lines) and periphyton and detritus amounts (dashed lines) of the (1) Additive MPE hypothesis (blue), (2) Antagonistic MPE hypothesis (red), and (3) Synergistic MPE hypothesis (green) with increasing perlid larvae density…... .................................................................................................................................... 17 Figure 2.1 (A) Photo of 36 aquarium microcosms used. (B) Birdseye view of a single aquarium, where the red arrow points to the plastic deflector with the airstone underneath. 1 corresponds to leaf packs used to measure leaf litter decomposition rates, 2 corresponds to the tile used to weigh down temperature dataloggers, and 3 corresponds to the unglazed ceramic tile used to quantify impacts to periphyton standing stock. ........................................................................................... 28 Figure 3.1 Specific growth rate (SGR) of C. californica and H. pacifica weight (%/day) in aquaria containing 1 - 4 stoneflies in predator guild assemblages of single and multiple species. Boxplots display the median, 25th and 75th percentiles whiskers (1.5 times the IQR) for this and all subsequent boxplots. Data points correspond to individual stonefly predators and not averages within a replicate, individuals depicted are from aquaria with no mortality. Dotted line corresponds to no change in mass, while above the line corresponds to increasing weight (gain) and below to decreasing weight (loss). ......................................................................................... 37 Figure 3.2 Number of benthic invertebrates remaining in treatments with no stonefly predators (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica (Cc), H. pacifica (Hp), or a combination of the two (Cc+Hp). Black dots correspond to observations from independent aquarium. .................................................................................................................. 38 Figure 3.3 Number of benthic invertebrates in control aquaria with no stonefly predators added (n = 3, red) and aquaria with stonefly predator additions (n = 26, blue). ..................................... 39 Figure 3.4 Number of benthic invertebrates remaining in treatments with no stonefly predators (controls) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two regressed against (A) C. californica biomass (mg) or (B) H. pacifica x biomass (mg). Trend lines are based on linear models of only C. californica or H. pacifica as sole predictor variables. ................................................................................................................ 40 Figure 3.5 Observed proportion of prey depleted (effect size) by (A) two or (B) four predatory stonefly individuals in predator guild assemblages consisting of just C. californica (Cc, blue), just H. pacifica (Hp, green), or a mixed assemblage with both species (CcHp, yellow). Dotted lines indicate expected prey depletion calculated using multiplicative models based on single individual treatments. Asterisks indicate a significant difference between observed and expected prey depletion (* p < 0.05). nt denotes no statistical test performed due to inadequate number of replicates to perform one-sample t-test. ........................................................................................ 41 Figure 3.6 Pielou’s eveness of benthic taxa treatments with neither no stonefly predators present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species in (a) treatment categorical comparisons, or regressed against (B) C. californica biomass (mg) and (C) H. pacifica biomass (mg). Shape legend for Number of larvae corresponds to panels (B) and (C) only.............................................................................. 42 Figure 3.7 Non-metric multidimensional scaling (NMDS) ordination of benthic community assemblages showing dissimilarities of taxa in treatments with no stonefly predators present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species. Taxa included are from >1 % of the total macroinvertebrate abundance. Stress= 0.216, non-metric fit R2 = 0.953, linear fit R2 = 0.78, dimensions (k) = 2. Panel A is a zoomed-out representation to depict taxa while B is a close-up version (note different axis scales) to more accurately show differences between observations. ...................... 43 Figure 3.8 Number of invertebrates in the benthos that belong to the scraper functional feeding group (FFG) in treatments with neither species present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species in (a) treatment categorical comparisons, or regressed against (B) C. californica biomass (mg) and (C) H. pacifica biomass (mg). Shape legend for Number of larvae corresponds to panels (B) and (C) only. ................................................................................................................ 44 Figure 3.9 Number of invertebrates in the benthos that belong to the collector-filterer (CF) functional feeding group (FFG) in treatments with no stonefly predators present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of xi the two species in (A) treatment categorical comparisons, or regressed against (B) C. californica biomass (mg) and (C) H. pacifica biomass (mg). Shape legend for Number of larvae corresponds to panels (B) and (C) only. ............................................................................................................ 45 Figure 3.10 Number of invertebrates found within leaf packs in aquaria with no stonefly predators present (control) or with predator guild assemblages of 1, 2, or 4 C. californica (Cc), H. pacifica (Hp), or a combination of the two species. ................................................................ 46 Figure 3.11 Number of invertebrates within leaf packs in treatments with no stonefly predators (controls) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two regressed against (A) C. californica biomass (mg) or (B) H. pacifica biomass (mg). Trend lines are based on linear models of only C. californica or H. pacifica as sole predictor variables ................................................................................................................. 47 Figure 3.12 Pielou’s eveness of leaf pack invertebrate taxa in treatments with no stonefly predators present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species in (A) treatment categorical comparisons, or regressed against (B) C. californica biomass (mg) and (C) H. pacifica biomass (mg). Shape legend for Number of larvae corresponds to panels (B) and (C) only. .................... 48 Figure 3.13 Non-metric multidimensional scaling (NMDS) ordination of leaf pack taxa community assemblages showing dissimilarities of taxa in treatments with no stonefly predators present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species. Taxa are from >1 % of the total macroinvertebrate abundance. Stress= 0.155, non-metric fit R2 = 0.976, linear fit R2 = 0.907, dimensions (k) = 2. 49 Figure 3.14 Shredder abundance in leaf packs in treatments with no stonefly predators present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species in (A) treatment categorical comparisons, or regressed against (B) C. californica biomass (mg) and (C) H. pacifica biomass (mg). Shape legend for Number of larvae corresponds to panels (B) and (C) only.............................................................................. 50 Figure 3.15 (A) Chlorophyll-a (mg/m2) and (B) periphyton biomass (g/m2) in aquaria with no stonefly predators present (control) or with predator guild assemblages of 1, 2, or 4 C. californica (Cc), H. pacifica (Hp), or a combination of the two species (Cc+Hp). ..................... 51 xii Figure 3.16 Decomposition rate (AFDM mg/day) of leaf packs in aquaria with no stonefly predators present (control) or with predator guild assemblages of 1, 2, or 4 C. californica (Cc), H. pacifica (Hp), or a combination of the two species (Cc+Hp). ................................................. 52 Figure A.1 Specific growth rate (SGR) of weight change (mg) of C. californica individuals’ across experimental treatments containing 1 – 4 C. californica. Boxplots display the median, 25th and 75th percentiles whiskers (1.5 times the IQR) for this and all subsequent boxplots. Data points (dots) correspond to individual larvae growth and not average within a replicate……….94 Figure A.2 Final abundance of prey in aquaria containing 0 - 4 C. californica. The red box depicts aquarium with no stonefly larvae present, while blue boxes correspond to treatments with larvae present, for this and all subsequent plots where control treatments are depicted………...96 Figure A.3 Observed proportion of prey depleted (effect size) in treatments with 2, 3, or 4 C. californica individuals. Dotted lines indicate expected prey depletion calculated using multiplicative models based on single individual treatments. Error bars depict the standard error around the mean………………………………………………………………………………….97 Figure A.4 Pielou’s evenness of invertebrate taxa in treatments with 0 - 4 C. californica……...98 Figure A.5 Non-metric multidimensional scaling (NMDS) ordination of taxa community assemblages showing dissimilarities of taxa between aquaria containing 0 - 4 C. californica. Taxa are from >1 % of the total macroinvertebrate abundance. Stress= 0.185, non-metric fit R2 = 0.979, linear fit R2 = 0.898, dimensions (k) = 2. AmBa corresponds to Ameletus and Baetidae grouped together, PrChlorPerlidae, to predatory Chloroperlidae and Perlidae, and C.G.Chiro are collector-gatherer chironomids (Chironomini and Orthocladiinae)……………………………..99 Figure A.6 Final periphyton biomass in aquaria with 0 - 4 C. californica. Note 1 outlier removed from figure as it was 5.3 times higher than the next highest value left in the dataset……….....100 Figure A.7 Final chlorophyll-a content of periphyton in aquarium with 0 - 4 C. californica….101 Figure A.8 Leaf decomposition rates in treatments with 0 - 4 C. californica………………….102 Figure A.9 Number of (A) collector-gatherers, (B) collector-filterers, (C) predators, (D) shredders, and (E) scrapers remaining in treatments with 0 (n = 4), 1 (n = 3), 2 (n = 2), 3 (n = 2) and 4 (n = 3) C. californica…………………………………………………………………..…108 xiii Figure B.1 Number of benthic invertebrates remaining (log transformed) in treatments with 0 - 4 stonefly predators consisting of C. californica, H. pacifica, or a combination of the two regressed against C. californica biomass (mg) and H. pacifica biomass (mg)……………………………111 Figure B.2 Number of benthic invertebrates remaining in treatments with no predators (control, red) or with predator guild assemblages consisting of 1, 2 or 4 C. californica (Cc, light blue), H. pacifica (Hp, green), or a combination of the two (Cc+Hp, yellow). (B) Number of benthic invertebrates in control aquaria with no stonefly predators added (n = 3, red) and aquaria with stonefly predator additions (n = 26, dark blue)…………………………………………………112 Figure B.3 Number of benthic invertebrates remaining in treatments with no stonefly predators (controls) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two regressed against (A) C. californica biomass (mg) or (B) H. pacifica biomass (mg). …………………………………………………………………………………..113 Figure B.4 Number of invertebrates in the benthos that belong to the (A) shredder, (B) collector-gatherer, and (C) predator functional feeding groups (FFG) in treatments with no stonefly predator present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species………………………………….114 Figure B.5 Number of invertebrates within leaf packs in treatments with 0 - 4 stonefly predators consisting of C. californica, H. pacifica, or a combination of the two regressed against C. californica biomass (mg) and H. pacifica biomass (mg). ……………………………………...115 Figure B.6 Pielou’s evenness in leaf pack taxa in treatments with 0 - 4 stonefly predators consisting of C. californica, H. pacifica, or a combination of the two regressed against C. californica biomass (mg) and H. pacifica biomass (mg)……………………………………….116 Figure B.7 Non-metric multidimensional scaling (NMDS) ordination of leaf pack taxa community assemblages showing dissimilarities of taxa in aquarium with (A) predator guild assemblages consisting of C. californica (blue) or H. pacifica (green) larvae and between treatments with(B) 0 – 4 predatory stoneflies. Taxa are from >1 % of the total macroinvertebrate abundance. Stress= 0.155, non-metric fit R2 = 0.976, linear fit R2 = 0.907, dimensions (k) = 2…………………………………………………………………………………………………117 Figure B.8 Number of invertebrates in the leaf packs that belong to the (A) collector-filterer, (B) collector-gatherer, and (C) predator functional feeding groups (FFG) in treatments with no xiv neither species present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species. ………………………………...118 Figure B.9 Collector-gatherer (CG) functional feeding group (FFG) abundance within leaf packs in treatments with 0 - 4 stonefly predators consisting of C. californica, H. pacifica, or a combination of the two regressed against C. californica biomass (mg) and H. pacifica biomass (mg)……………………………………………………………………………………………..119 Figure B.10 Chlorophyll-a content (mg/m2) of periphyton in aquarium with no stonefly predators (controls) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two regressed against (A) C. californica biomass (mg) or (B) H. pacifica biomass (mg)……………………………………………………………………………………120 xv List of Abbreviations AFDM: Ash-free dry mass AIC: Akaike information criterion ANOVA: Analysis of variance CF: Collector-filterer CG: Collector-gatherer FFG: Functional feeding group MKRF: Malcolm Knapp Research Forest MPE: Multiple predator effect NMDS: Non-metric multidimension scaling SD: Standard deviation SGR: Specific growth rate Tukey’s HSD: Tukey’s honest significant difference xvi Acknowledgements Firstly, I would like to thank my supervisor, John Richardson, for being an exceptional mentor. I am grateful for the tremendous amount of support, guidance, and encouragement you have given me through the years. I would also like to thank my committee members, Christopher Harley and Katie Marshall, for their insightful and helpful feedback on my thesis. In addition, I extend my gratitude to thank Karlee Orvis, Grace Melchers, Paulina Chalmers, Joanna Griggs, and Jennifer Fischer as well all the others that helped along the way. For my funding, I thank my supervisor, the Natural Sciences and Engineering Research Council (NSERC), the Faculty of Forestry, and the Department of Graduate and Postdoctoral Studies. Additionally, I am extremely grateful for the undying support of my family, my friends, and my terrific lab mates, without you this would have never been possible. 1 1. Introduction Ecology aims to understand how abiotic and biotic factors interact to influence population dynamics, community structure, and the ecosystem functioning we see in the natural world (Sutherland et al., 2013). Within these ecosystems, coexisting species interact in a particular place and time, which we call ecological communities (Stroud et al., 2015). Within these communities, organisms can be grouped multiple ways, whether it be into assemblages of taxonomically related groups of species, or into guilds of organisms that exploit similar resources in a similar way (Stroud et al., 2015). For example, when considering communities within streams, fish within Salmonidae could be grouped together within an assemblage, while simultaneously belonging to a guild of predators that may contain fish from other families as well as predatory aquatic invertebrates (Fauth et al., 1996; Stroud et al., 2015). Ecological communities typically have multiple species at each level of the food web (Stroud et al., 2015). As demonstrated in the biodiversity and ecosystem function relationship, having multiple species performing similar roles may allow for ecosystems to have higher stability and resiliency when faced with perturbations (Cardinale et al., 2006). For instance, when species loss occurs there is the capacity to buffer and mitigate detrimental impacts to other levels if there are remaining species within the guild that can compensate and maintain the ecosystem function (Cardinale et al., 2006). However, most species that comprise a guild will not be wholly equivalent and redundant in their abilities to perform an ecosystem function (Downing & Leibold, 2002). A meta-analysis of biodiversity ecosystem function experiments, determined that often the ecosystem function achieved by the most productive taxa was similar to the cumulative function achieved from a diverse community (Cardinale et al., 2006). For instance, an experimental manipulation in artificial ponds showed that guild composition had as strong an influence on productivity, respiration, and decomposition rates as that caused by species richness alone (Downing & Leibold, 2002). The importance of diversity for maintaining and influencing ecosystem function has long been studied; however, it has been identified that more work is needed to understand the role that specific species and community composition may play. 2 Guilds can be structured into trophic levels which shows the feeding position the organism holds within the food web. Food webs show the trophic (feeding) relationships in a community and typically are depicted as a tiered system with predators at the top, that consume herbivores below, and herbivores feed on primary producers at the bottom (Power, 1992). However, communities are highly complex and rarely take on a tidily stratified food web structure. Complexities arise as most food webs are comprised of more than three basic trophic levels with an array of consumer levels and additionally many species may be omnivorous and feed from multiple different levels (Power, 1992). The food web within a community can be influenced by both bottom-up and top-down processes (Bowlby & Roff, 1986; Power, 1992; Warren et al., 1964). Bottom-up processes result from changes in the abundance or quality of the basal resources and can drive food web structure by controlling the amount of nutrients and energy available for the levels higher up (Warren et al., 1964). Conversely, top-down processes result from consumption or behavioural-mediated effects from higher levels on lower trophic levels (Peckarsky et al., 2008). 1.1 Predator-prey dynamics and community-level processes Top-down controls within systems are often understood as apex predators controlling community composition and abundance through direct consumption during predation (Brooks & Dodson, 1965; Hairston et al., 1960; Paine, 1966). Top-down controls within systems can have dramatic effects on food webs. A foundational example of these effects was demonstrated through the experimental removal of predatory Pisaster starfish that altered top-down control on the system. The removal of Pisaster allowed for the drastic increase in their primary prey resource, the Mytilus mussels. These mussels were competitively dominant and crowded out other invertebrates and algae resulting in decreased species richness and abundance (Paine, 1966). Changes to the composition of food webs can lead to unexpected outcomes as they can alter species co-existence mechanisms and predator-prey interactions, which can destabilize communities (Rezende et al., 2021). 3 The number of prey consumed by a predator may vary as a function of the abundance or density of the prey population (Holling, 1959). First coined by Holling (1959), the functional response of predators, described as the per capita consumption rate as a function of prey density, can be depicted as either a Type I, II, or III curve depending on predator satiation, handling time, and search time (Anderson et al., 2015; Dunn & Hovel, 2020). The curves depict different predator-prey interaction mechanisms, with Type I representing a linear relationship between prey density and consumption, Type II depicting an asymptotic relationship where there is decreasing per capita risk to prey with increasing prey density, and Type III curve representing a sigmoidal relationship where prey switching impacts predation rates (Dunn & Hovel, 2020). The functional response is a factor of many different components and can vary widely depending on predator behaviour, type, body size and condition, as well as functions of environmental variables that dictate metabolism and feeding efficiency and prey refuge through habitat complexity (Anderson et al., 2015; Dunn & Hovel, 2020; Sentis et al., 2017). For example, within a single species of salamander it was found that the functional response varied between Type I and II depending on the individual’s age, which dictated the predator’s attack rate and handling time (Anderson et al., 2015). Studies have demonstrated that grouping predators within a guild may not provide adequate information on how different predator species differentially impact the community. In a study comparing predaceous crustaceans and fishes, it was found that functional responses varied between the invertebrate and vertebrate predators but also within the crustacean and fish groupings, highlighting the need to study how different predators impact food webs (Dunn & Hovel, 2020). Predators not only impact prey through direct consumption but also through non-consumptive and non-lethal prey behaviour modifications (Peckarsky et al., 2008). In the presence of predators, prey species may exhibit predator evasion and avoidance behaviour to minimize predation risk that can result in altered habitat use, growth, and survival (Bo et al., 2010; Peckarsky et al., 2008). Experimental manipulations of larvae of the stonefly Perla marginata (Perlidae) showed that their prey may switch from preferred leaf habitats to less desirable pebble microhabitats; however, the switch was not observed for all prey species (Bo et al., 2010). 4 Whether it be through consumption or behavioural modification, it has been well documented that predators impact prey communities; however, the degree to which they may elicit control can vary between environment and predatory species. Predators not only have the ability to impact their prey, they also can impact organisms on trophic levels further below through trophic cascades (Carpenter et al., 1985). Trophic cascades are often triggered through the removal or addition of top predators in a system that can release or suppress the trophic level below them through changes in predation risk. For example, when predators are added to a community there is increased predation on prey species, thereby reducing prey abundance. With decreases in prey species abundance, there is a release of consumptive pressure on basal resources resulting in increased abundance (Carpenter et al., 1985; Paine, 1966). The foundational example from Carpenter et al. (1985), describes how changes in the presence and abundance of piscivores (top fish predators) cascaded through food webs in lake communities to cause changes to algal biomass three trophic levels below. Trophic cascades can also be a result of changes to prey behaviour that can result in decreased consumption of their food source. An example of this behavioural modification was found through laboratory manipulations of a predatory marine snail (Catalán et al., 2021). Trophic cascades in this system were found to arise from non-consumptive effects, where predator presence and cues caused decreased feeding by mussels to reduce detection that cascaded to impact barnacles, bivalves, and algal biomass (Catalán et al., 2021).. The occurrence and strength of trophic cascades is not the same across all systems. Through a meta-analysis, Shurin et al. (2002) found that trophic cascades and predator effects are stronger within aquatic food webs as compared to terrestrial. However, there was high variation across aquatic systems, with lentic and marine benthos having strong predator effects and marine plankton having the weakest (Shurin et al., 2002). Their findings suggest that within aquatic systems the occurrence of trophic cascades may be a function of the susceptibility of prey to predation and the strength of the link between prey and primary producers (Shurin et al., 2002). Additionally, anthropogenic influences may alter the strength of predator-prey interactions and the cascading effect (Su et al., 2021). Within freshwater systems, alterations to temperature and 5 eutrophication can modify the prevalence and strength of cascading top-down controls (Su et al., 2021). Therefore, continuing to study top-down controls in food webs within different community contexts can help us to understand the key processes and organisms that impact community structure. Within the predator guild there are also mid trophic-level predators known as mesopredators, whose influence within food webs is often overlooked and not well understood. Mesopredators are typically smaller-bodied than the apex predators with which they coexist, and many can be omnivores with broad, generalist diets (Prugh et al., 2009). The definition of mesopredators can be quite arbitrary and an organism that is a mesopredator within one system may be an apex predator in another (Klecka & Boukal, 2012; Prugh et al., 2009). For terrestrial systems, coyotes may be seen as mesopredators where wolves are apex predators, while in other communities devoid of wolves, they assume the status of apex predator (Prugh et al., 2009). Due to their broad dietary abilities and central position within the food web as prey for apex predators and predators of lower levels, mesopredators are seen to be highly interconnected and may play an integral role in community and ecosystem stability (Wallace & Webster, 1996). Ecosystems also often contain multiple trophic levels of mesopredators, such as coyotes, foxes, and raccoons, and these species may compete for resources. However, these co-existing species can partition the niche through slight differences in terms of prey preference, habitat use, and behaviour (Sheldon, 1980). Often the determination of co-existence of species within each guild may depend on differences in morphological traits linked to resources acquisition which can impact diet composition allowing for reductions in the occurrence of interspecific interactions (Lancaster, 2021). Co-existence of mesopredators may also be a function of abiotic conditions that determine the availability of suitable habitat that may limit encounter rates between species (Goldberg et al., 2022). Understanding mesopredator interactions and the external factors that impact them may help us to better understand their role in structuring communities through top-down controls. 6 Globally, large apex predators are facing higher risks of extinction than other organisms with major threats resulting in drastic population declines of 90-99%, within aquatic and terrestrial systems respectively (Ritchie & Johnson, 2009). When this occurs, there is the potential for mesopredators to increase in abundance, through mesopredator release. The occurrence of this release was documented in chaparral systems devoid of coyotes, which experienced higher levels of subordinate mesopredators, such as foxes (Soulé et al., 1988). This increase in fox abundance also resulted in a trophic cascade that caused a decline in bird populations (Soulé et al., 1988). The loss of apex predators leads to trophic downgrading, by which the top trophic level is removed, and it has been found that this removal can lead to the decrease in community stability partially attributed to mesopredator release (Rezende et al., 2021). As central levels within food webs, mesopredators are highly important, but their roles and what regulates their impacts is poorly understood (Wallace & Webster, 1996). Through habitat loss and human interference, we continue to disproportionately impact top predator abundance, and the degree to which mesopredators exhibit top-down effects will be of high importance. Although still predators, mesopredator consumption rates and impacts may not be similar to those of apex predators and therefore may not be functionally equivalent (Prugh et al., 2009). Therefore, knowing to what degree these lower-trophic level predators may impact communities will give us insight into our conservation efforts. By knowing the consumptive abilities of mesopredators and the interactions between them in the absence of top-predators we can begin to plan for the future consequences and adapt strategies to mitigate large increases in mesopredator abundance that may arise through mesopredator release. 1.2 Predator-Predator Interactions Historically, studies of top-down effects on communities have considered the impacts from a single predatory individual or species. More recently, focus has turned to understanding how interactions between predators can result in non-independent combined predation outcomes (Sih et al., 1998). As predation is a strong regulating factor within communities, understanding how predators interact with one another to influence this regulation can be important for predicting community wide consequences. Predators can interact with one another through trophic 7 interactions such as predation and cannibalism, or non-trophic competitive or facilitative interactions (Holomuzki et al., 2010). These interactions arise between individuals of different species (interspecific) as well as between individuals of the same species (intraspecific) can result in unexpected Multiple Predator Effects (MPEs) on their shared prey (Livernois et al., 2019; Palacios et al., 2018; Sih et al., 1998; Vance-Chalcraft & Soluk, 2005). The outcome of combined predator consumption can be additive, antagonistic, or synergistic (Figure 1.1), with the strength and direction contingent on the environment, predator identity, and predator guild diversity (Sih et al., 1998). Additive effects typically occur when predators are able to either spatially or temporally partition shared prey in a way that allows for no predator-predator interactions or exhibit differences in foraging mode and morphological traits associated with foraging (Lancaster, 2021; Schmitz, 2007; Sih et al., 1998). The outcome of additive MPEs on prey abundance is simply the combined per capita predation ability of each predator independently. However, additive outcomes can also occur if one predator is dominant and can account for most of the combined predator outcomes as opposed to the subordinate that has lower per capita consumption as found with a pairing of active hunting reef fishes (Palacios et al., 2018). Conversely, if predators interact through facilitation or competition, the MPEs will typically be non-additive. Facilitation between predators results in one or both individuals benefitting and having higher predation success. This type of interaction results in synergistic MPEs, where larger numbers of prey are consumed than expected based on independent predator foraging abilities (Sih et al., 1998). Although not commonly found, facilitation typically arises when one predator's foraging results in modifications to prey making them more susceptible to predation (Fodrie et al., 2008; Soluk, 1993). Facilitation has been demonstrated in marine communities, where stone crabs breech oyster valves making them more vulnerable and easier targets for southern oyster drills (Fodrie et al., 2008). Competition occurs when predators cannot partition the shared prey resource and results in antagonistic MPEs, where fewer prey are consumed by the predators than expected based on independent feeding abilities (Schmitz, 2007). 8 Competition can be either exploitative, i.e. one predator reducing prey so that it is not available, or through interference, where there are direct negative interactions (Holdridge et al., 2016). Additionally, the strength of predator-predator interactions can be density-dependent whereby increasing numbers of predatory individuals leads to increased competition for shared resources (Elton, 1949; Holomuzki et al., 2010). There may be some threshold density, where predator numbers have become sufficiently high leading to increased probability of encounter as well as higher rates of prey depletion limiting the amount of prey available for each predator, resulting in competition (Elton, 1949). Additionally, For example, predatory protozoans shift from exploitative to interference competition as the number of predators within the system increase (Holdridge et al., 2016). Competition may not impact all involved species equally and one species may be negatively impacted while the other is unaffected, resulting in asymmetrical competition (amensalism). This has been documented within terrestrial invertebrate communities, where it has been found that asymmetric competition is the more common outcome of competitive interactions where a dominant and subordinate species are established (Lawton & Hassell, 1981). In some instances this can occur due to size-dependent competitive interactions, where large individuals have superior competitive strengths (Anaya-Rojas et al., 2021). In addition to predator body size, predator foraging mode and behaviour can impact interaction strength, predator-prey dynamics, as well as predator growth and survival (Laskowski et al., 2021). In the instance of active mobile predators there is a higher chance of encounters that may increase the likelihood of competition and antagonistic interactions (Björkman & Liman, 2005). Work on intraspecific interactions has found that this can arise in MPEs that can impact the foraging efficiency of mobile crabs and decrease the predation risk to their prey community (Liu et al., 2019). For a given species the type and strength of interaction may also vary between intra and interspecific pairings as studies have found that individuals may interact differently with conspecific versus heterospecific individuals. A study utilizing three fish species (bluegill sunfish, banded tilapia, and southern mouthbrooder) found that tilapia and the mouthbrooder exhibited competitive interspecific interactions that negatively impacted predator abilities, while in intraspecific pairings of bluegill no impacts to predation abilities were observed. However, 9 when bluegill was in interspecific pairings with tilapia, lower predation rates were observed (Wasserman et al., 2016). Therefore, identifying how predators interact in intra and interspecific pairs can help to understand how different species may respond to and be impacted by density and species diversity within their guild. Understanding and predicting MPEs has proven difficult and may be further complicated when considering interactions between species that historically did not co-exist. The nature of mesopredator interactions between native and introduced species has been shown to vary with species identity and have varying impacts to the predators involved and the broader community (Everling & Johansson, 2022; Mofu et al., 2019). In studies assessing functional curves of a native and invasive fish, found that in treatments with both species interference occurred and the native fish was negatively impacted while the invasive species had higher feeding rates (Mofu et al., 2019). However, this interaction was found to have negligible impacts to the prey community of chironomids suggesting that although competitive interactions occur, species will be differentially impacted (Mofu et al., 2019). Understanding how predator specie’s identity and guild richness affects ecosystem functions can have implications for biogeochemical cycles and climate change. In experiments in bromeliads using beetles and damselflies, their abilities to impact prey community through consumption as well as cause trophic cascades to impact to CO2 emissions differed (Atwood et al., 2014b). Moreover, in treatments involving both species together, antagonistic interspecific interactions occurred that resulted in competitive displacement, which eliminated trophic cascades from occurring. (Atwood et al., 2014b). Therefore, not only is understanding intra and interspecific interactions between predators important for the species themselves, but outcomes of these interactions could have larger-scale implications for broader ecosystem dynamics. As we continue to see species additions and losses there will be a continued need for studies of predator-predator interactions across different ecosystems in an attempt to formulate generalizations regarding implications to food webs and ecosystems. 10 1.3 Stream communities Stream communities are comprised of an array of organisms, such as fishes, amphibians, invertebrates, and algae, among others. The food webs of these communities are typically structured with large-bodied organisms such as fish or amphibians as the top predators, aquatic invertebrates as intermediate consumers and with algae and terrestrial detrital inputs as the basal resources. The capacity of predators to elicit top-down controls within streams has been well documented, including the interactions between predatory individuals and their MPE outcomes. Work has been done to understand the MPEs that arise between interactions of fish apex predators and invertebrate mesopredators. Although less commonly reported among predators that share a common prey resource, it was documented that facilitation between cutthroat trout and stonefly larvae within field mesocosms could increase prey susceptibility to fish predation (Soluk & Richardson, 1997). Trout growth was higher in the presence of stonefly larvae, which was attributed to behavioural modification of prey, causing them to increase movements causing them to be easier to capture (Soluk & Richardson, 1997). A study looking at predatory interactions between salamander and sculpin found that interference and exploitative competition may arise but vary seasonally (Cecala et al., 2020). They found that in spring months sculpins impacted salamander growth through both modes of competition, while in fall months the competition strength between species was equal, with salamanders being able to impact sculpin growth through prey reduction (Cecala et al., 2020). There is high biodiversity within small-order streams, with much of the diversity in the form of invertebrates, particularly the aquatic insects (Richardson, 2019). Within headwater systems, small invertebrates may also take on apex predator roles where large-bodied predators cannot persist (Meyer et al., 2007; Richardson, 2019). Stonefly larvae can elicit top-down controls that can directly impact their prey community and cause trophic cascades that indirectly impact ecosystem processes (Lecerf & Richardson, 2011). It has also been found that small Chloroperlidae stoneflies not only impacted prey through predation, but also caused habitat modification that reduced the amount of suitable habitat for detritivores on leaf packs (Majdi et al., 2015). Additionally, studies have explored the outcomes of interactions between mesopredator aquatic invertebrates. When identifying the mechanism by which predatory 11 dragonfly larvae interact, the per capita feeding rate decreased in the presence of both heterospecific and conspecific individuals (Sentis et al., 2017). However, the effect size of competition also varied as a factor of the identity of the predators paired together, temperature and prey density (Sentis et al., 2017). Larvae of perlid stoneflies (Plecoptera, Perlidae) are a common family of predatory aquatic insects in streams (Meyer et al., 2007), and within western North America there are many co-existing species, two of which are Calineuria californica and Hesperoperla pacifica (Peckarsky, 1979). These stoneflies are semivoltine with a 2 – 3 year life cycle where the larval stages are aquatic and the adult stage is terrestrial (Thorpe, et al, 2009). C. californica and H. pacifica spend the majority of their life as larvae and live within cool, coarse-grained riffle sections of streams (Peckarsky, 1979; Sheldon, 1980). Populations of both species are size-structured and larvae go through progressive instars as they grow, reaching sizes of approximately 35 mm and 40 mm, respectively (personal obsv.), making them some of the largest benthic, predaceous macroinvertebrates (Siegfried & Knight, 1976). Within reaches of the streams of coastal British Columbia they can be found at densities of 2.66 individuals/m2 (Lecerf & Richardson, 2011). Additionally, some populations have seasonal variation in density and in areas of Nevada have been found at densities of 159 to 4 individuals/m2 in summer and winter months respectively (Siegfried & Knight, 1978). These two species have a high degree of niche overlap, with only minor differentiation in prey and microhabitat preference (Peckarsky, 1979; Sheldon, 1980). Both species are predominantly carnivorous (Peckarsky, 1979), but during earlier instars (Sheldon, 1969) and when algae is in high abundance, they may show some signs of herbivory (Siegfried & Knight, 1976). They are generalist predators that have an active-searching foraging mode, where they use their antennae to seek out prey as they crawl along benthic substrate (Peckarsky, 1979). Stonefly larvae are gape limited, and feed only on macroinvertebrates that they are capable of fitting within their jaws (Sheldon, 1969). However, there is some evidence that C. californica and H. pacifica have some prey preference which may shift within increasing larval size (Peckarsky, 1979). Both species have been shown to prefer baetid nymphs (Ephemeroptera) (Johnson, 1983; Peckarsky, 12 1979), while C. californica may also consume higher amounts of chironomid (Peckarsky, 1979) and H. pacifica may have some preference for hydropsychids and lepidopterans (Sheldon, 1980). Additionally, studies have found that there is some shifts from caddisfly, to mayflies and finally dipterans with increasing stonefly larvae size (Peckarsky, 1979). Many studies have analyzed the feeding ecology and life history of perlid larvae (Sheldon, 1969; Siegfried & Knight, 1976) as well as their abilities to elicit top-down controls on stream food webs. For instance, in experimental channels, the addition of H. pacifica led to lower invertebrate biomass, increased primary producer biomass, and a subsequent decrease in CO2 emissions as compared to control channels (Atwood et al., 2014a). Additionally, a similar experimental study assessing the impacts of large predators used Doroneuria baumanii in conjunction with H. pacifica, and found that filtering invertebrate biomass, algae biomass, and rates of alder leaf litter mass decomposition was lower in their presence (Lecerf & Richardson, 2011). The high degree of niche overlap between C. californica and H. pacifica suggests that throughout the juvenile stages there is potential for competition interactions, but the intra- and interspecific interactions and implications to stream food webs has not been assessed. To date, there have been no studies using C. californica or H. pacifica that have sought to identify the type of inter and intraspecific interactions and the implications for their foraging efficiency, growth, and the resulting outcomes to the prey community. Many studies of similar stonefly larvae have found that interactions between co-existing pairs of perlids or perlodids may result in individuals displaying evasive, and occasionally aggressive, behaviour that reduced time spent eating, number of prey attacks, and time spent searching (Elliott, 2003a; Peckarsky & Penton, 1985). Additionally, in experiments using a predatory stonefly, Kogotus nonus (Perlodidae), in a single prey system (Baetis tricaudatus), increases in the density of the predator led to increased stationary behaviour of predators, resulting in decreased prey encounter rates (Walde & Davies, 1984). The decreased rate of prey capture and consumption due to predator-predator interactions between stonefly larvae can lead to reduced growth and fecundity which could have additional long-term implications for community structure (Peckarsky & Cowan, 1991). 13 Studies have shown that intraspecific interactions between some species of stonefly larvae led to additive and antagonistic MPEs to the prey community, due to competitive and neutral interactions that impacted feeding, capture, and handling of prey (Elliott, 2003a; Peckarsky & Cowan, 1991; Walde & Davies, 1984) This interference can impact prey consumption rates (Elliott, 2003b) and species’ body size, prey density, as well as sex, impact the strength and occurrence of both inter and intraspecific interactions and their outcomes (Peckarsky, 1991; Peckarsky & Penton, 1985). These previous studies demonstrate that differences in outcomes may also be a factor of species-specific behaviour, prey preference, or the establishment of a dominance hierarchy (Elliott, 2003a; Peckarsky & Cowan, 1991), but no generalizations have yet to be formulated. More work is needed on the analysis and comparison of inter and intraspecific interactions between stonefly mesopredators so that broader consensuses can be formed to help assess impacts to prey community and ecosystem function. Small-scale model systems of invertebrate communities can provide useful tools to understand effects and also create generalizations of MPE outcomes that can be applied to other ecological systems (Ledger et al., 2009). The data collected from the experimental manipulation of predatory stonefly larvae of C. californica and H. pacifica will help demonstrate the importance of understanding how interactions between multiple predators can result in unexpected, non-independent combined predation outcomes that can impact food webs and ecosystem function. If successful, such information will lend insight into how MPEs can directly impact benthic communities and indirectly impact key ecosystem processes. As humans continue to negatively impact systems and cause apex predator extinctions, having a knowledge of the role mesopredators play in structuring communities will become increasingly important. 1.4 Objectives and hypothesis My objective was to evaluate and quantify the outcome of intra- and interspecific interactions of C. californica and H. pacifica on stream food webs. The alternative hypotheses that I tested were: 14 a) Additive MPE hypothesis: I hypothesize that stonefly larvae partition their niche which allows for predators to have weak or no interactions between individuals. If this hypothesis is true, I predict this will result in a combined prey depletion equivalent to the sum of each larvae’s per capita consumption rate independently (Additive MPE; Figure 1.2). Additionally, I predict the decrease in prey numbers will release consumptive pressure on lower basal resources and they will increase proportionally with the sum of effects in single predator systems (note: H1 is the null/expected model with which other hypothesis outcomes are compared). b) Antagonistic MPE hypothesis: I hypothesize that stonefly larvae do not partition their niche and have a high degree of overlap in habitat and resources leading to competition for prey. If this hypothesis is true, I predict this will result in the combined prey depletion increasing less than the addition of each predator’s independent per capita consumption (Antagonistic MPE; Figure 1.2). Additionally, I predict this will result in a trophic cascade where basal resources will not decrease to the extent as expected if no interference occurred. c) Synergistic MPE hypothesis: Although unlikely, I hypothesize that stonefly larvae cause behavioural modification of their prey leading to facilitation where the presence of another predator individual enhances their ability to capture and consume prey. If this hypothesis is true, I predict this will result in higher combined prey depletion where the sum is more than each predatory individual's independent per capita consumption (Synergistic MPE; Figure 1.2). Additionally, I predict this effect will cause trophic cascades that will impact basal resources leading to higher amounts than expected due to the high release of consumptive pressure from the prey community. Additionally, alternative hypotheses of combined predation outcomes relate to stonefly larvae identity and density. I hypothesize that due to the larger size and more aggressive behavior of H. pacifica (Peckarsky, 1979) that inter- and intraspecific interactions that involve this species result in stronger competition. Therefore I predict this will lead to greater and more apparent Antagonistic MPEs as described above. I also hypothesize that the effects of competition increase with increasing larvae density due to reduction in prey availability (exploitative 15 competition) and increases in predator encounter rates (interference competition). Therefore, I predicted that for both inter and intraspecific pairings as density increases fewer prey than expected will be consumed (Antagonistic MPEs) with cascading impacts to basal resources. The competing hypotheses were tested by taking measures of stonefly larvae growth and survival, community abundance and composition, and measures of basal resource standing stock. Through these studies, my main aim was to identify the strength and direction of MPE outcomes from interactions of perlid stonefly larvae and determine if these will impact all levels of the food web, which could have implications for ecosystem function. 16 Figure 1.1 Visual representation of the proportion of prey consumed by individual predators A and B in independent isolated systems and the additive (blue), antagonistic (red), and synergistic (green) Multiple Predator Effects (MPEs) that may arise due to intra- and interspecific pairings. Note, units of prey consumed are arbitrary and are used for ease of interpretation of MPEs. 17 Figure 1.2 Predicted outcomes to prey abundance (solid lines) and periphyton and detritus amounts (dashed lines) of the (1) Additive MPE hypothesis (blue), (2) Antagonistic MPE hypothesis (red), and (3) Synergistic MPE hypothesis (green) with increasing perlid larvae density. 18 2. Methods 2.1 Experimental design I conducted a 22-day laboratory experiment between 5 - 27 September 2021 manipulating the identity (C. californica and H. pacifica), density (0, 1, 2, 4 individuals) and richness (single versus multiple species) of the predator guild within 36 microcosms. Microcosms were constructed similar to Chará-Serna (2018) using 37.85 L aquarium (50 cm × 5 cm × 30 cm) divided into an upper and lower section with a glass sheet (25 cm × 30 cm) stacked up on 3.5 cm tall ceramic tiles (Figure 2.1). Each aquarium had air pumped in at one end with a plastic deflector positioned to allow for oxygenated water to be circulated throughout. Aquaria were filled with 12 L of water, 2 L of rinsed sediment, and 3 large rocks (grain size ~ 7.5 cm) collected from UBC’s Malcolm Knapp Research Forest (MKRF). Aquaria were held under light conditions (10.67 ± 4.03 μmol s-1 m-2) similar to that found in shaded small-order streams in MKRF (Kiffney et al., 2004) using Sunblaster T5HO nanotechnology grow lights (Sunblaster Holdings ULC, Langley, BC, Canada) on a 12:12 h light:dark cycle. During the experiment, water levels within the microcosms were maintained at about 12 L by adding water from either MKRF or distilled water every 2-3 days when levels dropped. Sediment grain size ranged from 0.4 to 1.2 cm and was arranged to an approximate average depth of 1.5 cm. One of the large rocks was used as both a weight to hold down leaf packs (description below), as well as refuge for stonefly larvae and other benthic invertebrates. Each aquarium had a temperature logger to track changes in temperature throughout the duration of the experiment and water quality measures were taken on the start and end days of the experiment using a YSI ProODO and YSI Pro 1030 water quality probes. Pre-experiment water quality measures showed microcosms had similar temperature (20.5 ± 0.2 °C), dissolved oxygen (9.02 ± 0.03 mg/L), conductivity (0.0506 ± 0.0055 mS/cm), and pH (7.52 ± 0.14). Microcosm conditions were also similar to those found in streams in MKRF in late summer months. To establish a natural prey community, I inoculated microcosms with equal amounts of prey collected from Spring Creek and Marion Creek in MKRF. Thirty-six Surber samples (243 μm mesh with sampling area of 0.09 m2) were collected from each location (72 samples total) and 19 pooled into four 16 L buckets. Large predatory and large-bodied organisms, such as Pteronarcys californica and tadpoles, were removed from the samples as these could either consume prey or have been found to impact prey behaviour (Lecerf & Richardson, 2011). Back in the laboratory the contents of each bucket were randomly distributed to each aquarium so that each received 2.67 L of prey inoculation (2 Surber samples per aquarium). Prey were added 2 days prior to the start of the experiment to allow for acclimation prior to the addition of stonefly predators. Five additional Surber samples were collected from each stream to establish the counts and community structure of the initial prey community within each aquarium. Samples were stored in 70% ethanol and sorted using a dissecting microscope to later be enumerated and identified as described below. To measure predator effects to ecosystem processes, measures of leaf litter decomposition and periphyton growth and chlorophyll-a content were used. To measure leaf litter decomposition, air-dried senesced red alder leaves collected from beneath trees on UBC Vancouver campus were used. Two leaves weighing 2 g total dry weight (± 0.04g) were soaked in tap water for 12 hours to leach soluble organic compounds (DOM) from the leaves that would make the visibility of the water too murky. Leaves were then added into coarse mesh bags to serve as leaf packs (1 cm x 0.7 cm openings) and were weighed down with a large rock one day prior to the start of the experiment. To measure effects on periphyton, unglazed ceramic tiles (7.5 cm x 7.5 cm) were placed into experimental channels within UBC’s MKRF two weeks prior to the start of the experiment to inoculate them with an adequate standing stock of periphyton. Two days prior to the start of the experiment the tiles were collected and transported back to the laboratory in buckets filled with cool water. Tiles were placed in the furthest side from the air stone and not under the glass or deflector to ensure full exposure to the grow lights. C. californica and H. pacifica larvae were collected over a period of a week prior to the start of the experiment due to the time it took to find an adequate number of similarly sized individuals. Larvae were placed within holding tanks with natural stream bottom substrate (grain size 2-7.5 cm) in MKRF and were supplied with a flow of water from Mayfly Creek allowing for a continuous flow of oxygenated water and drifting prey while being housed. Two to three days 20 prior to the start of the experiment larvae were placed in individual fine mesh bags (2 mm x 2 mm openings) to eliminate interactions and ensure equal levels of starvation and transported back to UBC Vancouver campus. Before the start of the experiment, larvae were kept within insulated coolers with stream water from Spring Creek and multiple air stones to ensure cool, well-oxygenated water. Larvae were weighed, measured, and marked the day of or the day prior to the start of the experiment. Using calipers (Empire 2784 5” Vernier Caliper, India), total length was measured from the anal gills to the tip of the mouthparts, to the nearest mm. Headwidth was measured to the nearest 0.1 mm as the distance from the outer edge of the compound eyes. Weight was determined by first blotting each larva dry then using a compact precision balance model EJ-303 (A&D Company Limited, Tokyo, Japan) with a precision of 1 mg. Larvae were marked with individual bee tags using super glue on the pronotum slightly off-center to avoid gluing the midline together and to allow larvae to molt as they grew. Larvae used weighed 135 ± 19 mg, had lengths of 17.3 ± 2.12 mm, and headwidths of 4.3 ± 0.23 mm. Larvae were randomly assigned to 1 of 8 predator treatments: 1 C. californica (n = 4), 1 H. pacifica (n = 4), 2 C. californica (n = 3), 2 H. pacifica (n = 5), 1 C. californica + 1 H. pacifica (n = 3), 4 C. californica (n = 4), 4 H. pacifica (n = 4), 2 C. californica + 2 H. pacifica (n = 4). There were also four control aquaria that contained neither species of stonefly larvae. 2.2 Response parameters Stonefly larvae growth At the end of the experiment, larvae were removed from the aquaria and immediately weighed and measured using the same methods as described above. Most larvae survived the duration of the experiment and retained tags, but in instances of tag loss individual ID was verified using species identity and pre-experiment measurements and body condition notes. Once individuals were identified, Specific Growth Rate (SGR) of weight change was calculated. SGR was not calculated for headwidth and length as these were found to have negligible change or slightly decreased (~1 mm) indicating potential minor errors in measurements or no change. To 21 determine mass change of the stonefly larvae the following specific growth rate formula was used: 𝑆𝐺𝑅 =ln(𝑊𝐹) − ln⁡(𝑊𝐼)22⁡𝑑𝑎𝑦𝑠× ⁡100 Where the growth rate (%/day) was determined by the difference between the natural logarithm of the final (WF) and the initial (WI) weight divided by the length of the experiment (22 days). A positive SGR indicates increasing weight (gain) while a negative value corresponds to decreasing mass (loss) during the experiment. Once larvae were weighed and measured, they were placed into 70% ethanol to be preserved. Ecosystem processes (leaf litter decomposition and periphyton standing stock) I removed the leaf packs on day 22 using an aquarium net and placed them into plastic bags which were immediately put into a refrigerator at 6 °C. The leaves were rinsed the following day using alternating cool and warm tap water baths to remove any invertebrates from the leaf surface. The water was poured over a 63 μm sieve and the invertebrates were stored in 70% ethanol to be later processed similarly to the benthic invertebrates described below. The leaves were then placed in a drying oven at 60 °C for 2 – 4 days. Dry weights were taken and then leaves were burned in a furnace at 500 °C for 5 hours to determine ash-free dry mass (AFDM). The remaining AFDM (mg) was subtracted from the initial dry mass and divided by 22 to give a measure of AFDM leaf decomposition rates (mg/day). I removed tiles and wrapped each in tinfoil and placed them into a freezer at -10 °C to be processed 7 days later. Under low light conditions tiles were removed from the freezer to warm to room temperature. Tiles were scraped with a toothbrush and the algae biofilm slurry was collected onto glass microfiber filters (Whatman™ GF/F: 47 mm diameter, 0.7 μm particle retention) using a Buchner funnel vacuum filtration method. The filters were cut in half and one half was placed into a drying oven at 60 °C for periphyton biomass analysis and the other half was placed into falcon tubes with 5 ml of 90% acetone, wrapped in aluminum foil, and placed into a refrigerator at 6 °C for chlorophyll-a analysis using the Welshyer method. To determine 22 AFDM (g/m2) of the periphyton, filters were removed from the drying oven 48-hours later and then burned at 500 °C for 4 hours. For chlorophyll-a analysis samples remained in the refrigerator for 36 hours and were taken out 30 minutes before fluorometry to reduce condensation on the glass tubes. One ml of the slurry was combined with 5 ml of 90% acetone in a 13 mm x 100 mm glass tube and placed into a fluorometer (TD-700™ Laboratory Fluorometer Turner Designs) to obtain readings of chlorophyll-a (ug/L). If readings were above the 200 μg/L fluorometer limit, the sample was diluted by 25% by taking 1.5 ml of the diluted sample and combining it with 4.5 ml of 90% acetone. To calculate mg/m2 the following equations were used: 𝐶ℎ𝑙𝑜𝑟𝑜𝑝ℎ𝑦𝑙𝑙 − 𝑎⁡ (𝑚𝑔𝑚2) = ⁡𝐶ℎ𝑙𝑎(𝑢𝑔)1⁡𝑚𝑙×𝑠𝑜𝑙𝑢𝑡𝑖𝑜𝑛⁡(𝑚𝑙)𝑡𝑖𝑙𝑒⁡𝑎𝑟𝑒𝑎⁡(𝑚2)× 𝑑𝑖𝑙𝑢𝑡𝑖𝑜𝑛⁡(𝑚𝑙) × ⁡2 Macroinvertebrate community Once larvae, tiles, and leaves were removed, I collected all benthic material from each aquarium and divided it into 3 fractions, a coarse fraction (> 4 mm), intermediate fraction (2 – 4 mm), and fine fraction (75 µm - 2 mm). Each fraction was preserved in 70% ethanol to be sorted later with a dissecting microscope to pick out all invertebrates visible at 16 times magnification. The coarse fraction was sorted in entirety to ensure larger, and potentially rarer, organisms were not missed. Coarse fractions from 25 aquaria were separated using elutriation (Rosenberg et al., 1998). Elutriation entails rinsing the sediment with water and lightly rubbing the rocks, this allows for the macroinvertebrates to float, which can then be poured off with the water onto a 63 μm sieve (Rosenberg et al., 1998). The efficiency of this method was determined to be 100% using 3 aquaria and was therefore deemed appropriate to speed up processing. The intermediate fraction was sorted in entirety under a dissecting microscope and the fine fraction was subsampled in halves and one half was then sorted. The count from the fine fraction was then multiplied to determine approximate number of individuals in each aquarium. During the collection period fine fraction benthic samples from two aquarium were accidently combined and therefore were 23 excluded from the benthic invertebrate community analysis. All organisms from the benthic samples and leaf packs were then identified down to the lowest possible taxonomic level, usually family or genus using taxonomic keys (Merritt et al., 2008). Organisms were also assigned to a functional feeding group (FFG – scraper, shredder, predator, collector-gatherer [CG], and collector-filterer [CF]) so that total abundance and abundance of FFGs could be compared. I was predominantly looking for differences in the number of scrapers and shredders as these are the FFGs that feed on the periphyton and leaf litter, respectively. When determining the abundance of the predator FFG the marked C. californica and H. pacifica larvae were not included in these counts. Additionally, Pielou’s evenness for taxa was calculated to assess differences in relative abundance within the community. 2.3 Statistical analysis For statistical analysis, I used R 4.1.2 (R Core Team, 2021). To assess the outcomes of intra and interspecific interactions to stream food webs, I analyzed the data two ways, (1) using treatment as a categorical fixed predictor variable, and (2) regressions using C. californica and H. pacifica biomass as continuous fixed predictor variables. It is common in studies assessing MPEs to analyze data using discrete categorical variables, however, this does not account for differences in predator biomass within treatments. Predator biomass is known to affect predation rates, as larger-bodied individuals will consume higher amounts of prey as compared to smaller individuals (Hill & Weissburg, 2013). Within this study, biomass of individual stonefly predators ranged from 95 mg to 176 mg, making the largest individual 54% heavier than the smallest. Attempts were made to standardize biomass between and within treatments and replicates, but due to the low availability of similarly sized individuals this could not be done perfectly. Analyzing data using biomass as continuous variables also removes the confounding effect of predator density with having multiple species that often occurs with traditional analysis of MPEs (Aukema et al., 2004). As previously stated, at the end of the experiment not all stonefly larvae were recovered and additionally, during the collection of benthic samples two aquaria were combined. To determine 24 the most appropriate subset of data to use for response variables I analyzed linear models of benthic invertebrate abundance using three subsets of data and then compared them using AICc and comparisons of each model’s adjusted R2. The three subsets of data were (1) the full dataset including all aquaria (minus the two that had combined benthic samples, n = 34), (2) a reduced subset to remove one outlier in the control treatment which was found to be 4 times lower than the next lowest count (~100 remaining individuals) (n = 33), and (3) a reduced subset that removed all aquaria where stonefly mortality occurred and the outlier in the control (n = 29). Models including the low outlier in the control treatment were excluded as they could not meet model assumptions regardless of the transformation employed. The final reduced dataset had the lowest AICc and second highest adjusted R2 value (Table B.1) and was therefore deemed the most appropriate subset of data. For leaf AFDM, chlorophyll-a, and periphyton biomass the reduced subset of data was used, but the data from the two aquaria missing benthic samples could be included (n = 31). For leaf invertebrate community responses, the reduced dataset was also used as the number of benthic invertebrates would influence the number of invertebrates within leaf packs, however, six additional leaf invertebrate samples dried-up to the point that they could not be rehydrated and therefore could not be included in the analysis (n = 23). For linear models with each species’ biomass as continuous predictor variables, the interaction term was included, as when the interaction term is significant it indicates the presence of interspecific MPEs (Aukema et al., 2004). When the interaction term was not significant it was dropped from the model before further analyses were conducted (e.g. model coefficient comparisons). To determine if predators are substitutable and equal in their effects on the response variables, coefficients from the multiple regression model were compared using the linearHypothesis function in the car package (Fox, 2019). A significant outcome indicates that coefficients are not equivalent and therefore the two species are not substitutable in their effects. The relationship between response variables and C. californica and H. pacifica biomass were plotted in 2-dimensional and 3-dimensional figures. The trend lines within the 2-dimensional plots represent a linear model of response variables regressed against a single species biomass and do not depict the true intercept or slope from the multiple regression linear models. Although these figures do not depict the true relationship, they are presented within the results section for 25 ease of interpretation as they show the general trends. I present the 3-dimensional plots with the true multiple regression model outputs with the interaction term within Appendix B. To determine if the presence of any stonefly larvae impacted benthic and leaf invertebrate abundance, I performed linear models using predator presence versus absence as a categorical fixed predictor variable to determine if there were differences between controls (no predator) and all other aquaria containing any density or species of stonefly larvae. To test for differences in survival of stonefly larvae between treatments, a Fisher’s exact test was performed to assess if the frequencies of recovered and not recovered (dead) larvae differed. All models were tested to ensure they met the assumptions of linearity, normality, and homogeneity using Q-Q plots, Residuals vs Fitted diagnostic plots, as well as the Shapiro-Wilks test. When assumptions were violated, response variables were transformed. Count data (benthic and leaf pack invertebrates) was log transformed and stonefly larvae growth (SGR %/day) was transformed using a log + 1 transformation to meet model assumptions. For linear models with treatment as the categorical predictor variable, significance was determined using analysis of variance (ANOVA) with type III sums of squares due to the unbalanced design, and for all models, significance was determined at p < 0.05. When there were significant differences between treatments, TukeyHSD analyses were performed. To determine the types of MPEs that arose in treatments with two and four stonefly larvae, the observed predator effect size (proportion of prey depleted) in the benthos first needed to be calculated for all aquarium with stonefly larvae present. The proportion of prey depleted within the xth aquarium (Px) was calculated as: 𝑃𝑥 =⁡(𝑛𝑐 − 𝑛𝑓)𝑛𝑐⁄ where nc is the average number of benthic prey remaining in the control treatments (1100 individuals) and nf is the final number of prey within the xth aquarium. Typically, final counts would be subtracted from initial prey abundance and not the controls, however, the pre-experiment Surber samples collected to determine these initial numbers were taken from the 26 streams after they had been extensively disturbed. This resulted in inadequate samples that were lower in total abundance than many final counts within the aquaria. However, by using the control treatments I was able to account for natural mortality that occurred during the experiment (Vance-Chalcraft & Soluk, 2005). Unfortunately, by using the controls this resulted in three aquaria having negative prey depletion and therefore were dropped as they could not be included in the calculations or determination of MPEs. This included one replicate from each of the following treatments, 1 C. californica, 1 H. pacifica, and 4 H. pacifica. To determine the type of MPEs that arose I compared the observed prey depletion in each aquarium to the expected prey depletion which was calculated using the multiplicative risk model (Sih et al., 1998; Soluk & Collins, 1988). Based on the multiplicative risk model, the effect size (proportion depleted) for interspecific treatments with two individuals (EC+H) were calculated as: 𝐸𝐶+𝐻 = 𝑃𝐶 + 𝑃𝐻 − (𝑃𝐶𝑃𝐻) Where PC and PH were calculated as the average proportion of prey depleted in the single C. californica treatment and single H. pacifica treatment, respectively (Soluk & Collins, 1988). For intraspecific treatments (just C. californica or just H. pacifica) the expected effect size (EC+C or EH+H) was calculated using the respective average proportion depleted in single individual treatments. As the equation for 4 predator individuals is unknown, to calculate the expected outcomes in the high-density treatments the expected effect size for two individuals was used. For interspecific treatments the expected effect size (ECC+HH) were calculated as: 𝐸𝐶𝐶+𝐻𝐻 =⁡𝐸𝐶+𝐻 +⁡𝐸𝐶+𝐻 − (𝐸𝐶+𝐻𝐸𝐶+𝐻) Again, for intraspecific interactions the respective effect size and proportion was calculated using only the calculated proportions from the appropriate species. However, calculating the expected effect size using the low density (two individual) effect size may result in inaccurate estimates, many studies devoid of a single individual treatment use the lowest density treatment to calculate depleted proportions and expected outcomes (Greig et al., 2013). Therefore, it was deemed an appropriate method to calculate expected effect size. To determine if the observed 27 proportion of prey depleted differed from the expected additive proportion of prey depleted, one-sample t-tests were performed separately for each treatment. This was done by setting the mean to be compared with as the calculated expected outcome and determining if the true mean of the observed outcomes was equal. To detect shifts in taxa structure within communities Non-Metric Dimensional Scaling (NMDS) was performed using the “vegan” package and metaMDS function (Oksanen et al., 2013). For this analysis the taxa that comprised more than 1% of the total abundance were used and any unidentified juveniles or pupae were not included. To help meet these requirements for taxa some groups were combined and aggregated to high levels, for example, all genera under Heptageniidae were condensed into one group. Data were transformed with either a Wisconsin double standardization (for common abundance class scales >9) or square root transformed (for common abundance class scales >50) which allows all groupings to have similar weightings for ordination (Oksanen, et al., 2020). A Bray-Curtis dissimilarity index was used, with dimensions (k) selected at k = 2. To determine the linear and non-metric fits as well as the stress a Shepard plot was created. 28 Figure 2.1 (A) Photo of 36 aquarium microcosms used. (B) Birdseye view of a single aquarium, where the red arrow points to the plastic deflector with the airstone underneath. 1 corresponds to leaf packs used to measure leaf litter decomposition rates, 2 corresponds to the tile used to weigh down temperature dataloggers, and 3 corresponds to the unglazed ceramic tile used to quantify impacts to periphyton standing stock. 29 3. Results 3.1 Larval growth and survival At the end of the experiment, I recovered 94.3% of the stonefly larvae that were added as predators (Table 3.1). Of the four that were not recovered, three were C. californica and one was H. pacifica, with none belonging to the same replicate. Two of the C. californica larvae belonged to a 1 C. californica + 1 H. pacifica treatment, while the other was from a 4 C. californica treatment. The H. pacifica larvae belonged to a 4 H. pacifica treatment replicate. The remaining treatments had full survival in all replicates (Table 3.1). There was no statistically significant difference in the survival rate among treatments (p = 0.21). For the specific growth rate (SGR) dataset, two larvae were removed, one from the 2 C. californica treatment and one from the 4 H. pacifica treatment, as models could not meet assumptions of normality regardless of transformations employed. With these two larvae removed, there was no significant difference in the SGR of larval weight attributed to treatment (F7,57 = 1.08, p = 0.39; Figure 3.1) or to initial C. californica or H. pacifica biomass (F3,61 = 1.59, p = 0.20). Additionally, there was no significant interaction term between species’ biomasses, and the coefficients were found to be equivalent (F1,61 = 0.02, p = 0.89). Overall, larvae had positive growth (0.11 ± 0.15 %/day SD) with only 11 larvae experiencing negative SGR and four having zero SGR (Figure 3.1). The larvae in the 2 C. californica treatment had the highest mean SGR (0.22 ± 0.26 %/day), which corresponded to 1.29 times more weight gain than the next highest treatment, i.e. 1 H. pacifica (0.17 ± 0.08 %/day) (Figure 3.1). Although not statistically significant, H. pacifica larvae on average had higher SGR (0.12 ± 0.15 %/day SD) than C. californica larvae (0.09 ± 0.14 %/day). Additionally, larvae in treatments with 4 stonefly larvae had lower SGR (0.08 ± 0.13 %/day) than treatments with 2 larvae (0.15 ± 0.18 %/day) or one stonefly predator (0.14 ± 0.11 %/day), regardless of species. 30 3.2 Benthic invertebrate community Using the treatments as fixed categories, there was no significant difference in total remaining invertebrates in the benthos (F8,20 = 1.38, p = 0.26, Figure 3.2) among treatments. However, treatments with stonefly predators present (755 ± 196 individuals) had significantly fewer benthic invertebrates than control treatments (1100 ± 480 individuals) with no stonefly predators (F1,27 = 5.22, p = 0.03, Figure 3.3). Aquaria with stonefly predator additions had approximately 46% fewer remaining benthic invertebrates as compared to the controls with no stonefly present. Using the multiple regression analysis with C. californica and H. pacifica biomass as continuous predictor variables, there was a significant decrease in the numbers of remaining benthic invertebrates (F2,25 = 3.02, p = 0.049, Figure 3.4). I found that C. californica biomass (Figure 3.4A) was a significant predictor of the decline in benthic invertebrates (Figure 3.4A). Additionally, I found that when the interaction term was included in the model, H. pacifica biomass (Figure 3.4B) was not a significant predictor, but when the interaction term was dropped it was. However, comparison of C. californica and H. pacifica regression coefficients (F1,26 = 0.33, p = 0.57) determined that predators were substitutable in their impacts to benthic community abundance. For every 1 mg increase in C. californica biomass there was a 0.08% decrease in benthic macroinvertebrate abundance while for a 1 mg increase in H. pacifica there was a 0.06% decrease in the number of individuals when the other predictor is held constant. Additionally, there was no significant interaction between the biomass of the stonefly predators suggesting no emergent interspecific multiple predator effects resulting from mixed assemblage pairings (Figure B.1). In the benthic invertebrate counts there was one large outlier in the control treatments (Figure 3.3, 3.4) and when removed (Figure B.2, B.3) there was still was no significant difference among treatments (F8,19 = 1.02, p = 0.46). However, there was no longer a significant difference between aquaria with stoneflies present or absent (F1,26 = 0.46, p = 0.50) or with changes in C. californica or H. pacifica biomass (F3,24 = 2.41, p = 0.13). Treatments with no stonefly larvae (823 ± 21) and one larva (878 ± 259) had similar remaining invertebrates, while treatments with two (722 ± 113) and four (667 ± 116) larvae had less benthic invertebrates (Figure B.2). Although there was a large outlier in the control tank, and this datapoint potentially had high 31 leverage, the remainder of the analyses for other response variables includes this aquarium, so caution should be taken when interpreting results. I found that the difference between observed and expected prey depletion within treatments with multiple predators varied with predator guild identity and density. The observed proportion of prey depleted within multiple predator treatments containing two stonefly predators did not differ from expected outcomes for the single species treatment with C. californica (t = -4.12, p = 0.15), but did for single species treatments with H. pacifica (t = -3.39, p = 0.04, Figure 3.5). The combined predator treatment containing one of each species could not be tested due to there being a single replicate for this treatment. There were significant differences in observed and expected prey depletion for all four predator treatments regardless of predator guild assemblage (C. californica: t = -6.34, p = 0.02; H. pacifica: t = - 16.56, p = 0.004; C. californica + H. pacifica: t = -4.96, p = 0.02). The expected and observed prey depletion was highest for C. californica treatments compared to H. pacifica treatments. Additionally, the observed prey depletion was similar between treatments with two and four predatory stonefly larvae (Figure 3.5). As previously stated in the methods, three replicates were found to have negative prey depletion and were removed analysis. To determine if the removal impacted the results, I performed calculations of expected and observed prey depletion with the negative depletion values included. I found that the observed proportion of prey depleted when two C. californica were present still did not significantly differ from expected (t = -1.57, p = 0.36) and the observed outcomes when 1 C. californica + 1 H. pacifica were present still could not be tested. However, using the negative prey depleted values, I found that when two H. pacifica were present observed prey was no longer significantly different from expected (t = 3.27, p = 0.19). I also found that prey depletion in all four predator treatments were still significantly lower than expected MPEs (C. californica: t = -9.05, p = 0.01; H. pacifica: t = -14.03 p = 0.005; C. californica + H. pacifica: t = -5.60, p = 0.01). 32 Analysis of benthic invertebrate taxa community structure revealed no significant difference in Pielou’s evenness among treatments (F8,20 = 0.46, p = 0.87, Figure 3.6A) or with changes in C. californica or H. pacifica biomass (F2,26 = 1.03, p = 0.37, Figure 3.6B and C). Additionally, there was no emergent interspecific MPE detected as the interaction term was not significant. Treatments with 1 C. californica had the lowest evenness (0.63 ± 0.12) and the 4 C. californica treatment had the highest evenness (0.73 ± 0.05). Based on non-metric multidimensional scaling (NMDS) ordination it was found there were no dissimilarities in taxa community assemblage between treatments, stonefly larvae identity, predator guild richness, or with the number of stonefly larvae added to each aquarium (Figure 3.7), however some taxa were found be clustered within the ordination plot. Chironomini and Cladocera were grouped and more distant from the other remaining taxa. Paraleptophlebia spp. was more distant from the other Ephemeroptera (Ameletus, Baetidae, Heptageniidae) taxa that were grouped together. I found no difference in the number of scrapers (F8,20 = 1.20, p = 0.35, Figure 3.8A), collector-gatherers (CGs) (F8,20 = 0.95, p = 0.50, Figure B.4A), shredders (F8,20 = 0.22, p = 0.98, Figure B.4B), or predators (F8,20 = 0.39, p = 0.92, Figure B.4C) in the benthos among treatments. Additionally, changes in C. californica and H. pacifica biomass caused no significant difference in scrapers (F3,25 = 1.57 p = 0.22, Figure 3.8B and C), CGs (F3,25 = 1.96, p = 0.15), shredders (F3,25 = 0.17, p = 0.92), or predators (F3,25 = 0.81, p = 0.50). The abundance of the collector-filterer (CF) functional feeding group (FFG) was signficantly different among treatments (F8,20 = 4.82, p = 0.002, Figure 3.9A). From the TukeyHSD comparisons it was found that the control (7.33 ± 27.7) had a signficantly higher number of CFs as compared to the 2 C. californica (p = 0.04), 4 C. californica (p = 0.04), 4 H. pacifica (p = 0.03), and 2 C. californica + 2 H. pacifica (p = 0.02) treatments. Additionally the 1 H. pacifica treatment had sginficantly more CFs than the 2 C. californica + 2 H. pacifica treatment (p = 0.03). Control treatments had the highest number of CFs while the 2 C. californica had the lowest (390 ± 2.12). The CF FFG also significantly declined with increasing biomass of both C. californica and H. pacifica (F3,25 = 5.30, p = 0.005, Figure 3.9B and C). The biomass of both species were good predictors of the decline in abundance and were equal in their effects (F1,26 = 0.30, p = 0.59). Additionally, there was no significant interaction indicating no emergent interspecific MPEs. 33 3.3 Leaf pack invertebrate community I found no significant difference among treatments in the number of invertebrates within leaf packs (F8,15 = 1.79, p = 0.16, Figure 3.10). The treatment with 2 C. californica +2 H. pacifica had the highest number of invertebrates (110 ± 15) while the 4 H. pacifica had the lowest with 54 (no SD, single replicate). Treatments with no predator present (63 ± 31 invertebrates) did not have a significantly different number of invertebrates within leaf packs in comparison to aquaria with any amount of stonefly predator (77 ± 29 invertebrates) (F1,22 = 0.58, p = 0.45). Multiple regression analysis showed that there was a significant difference in total number of invertebrates in leaf packs (F3,20 = 5.21, p = 0.01, Figure 3.11). There was no significant interaction between C. californica and H. pacifica biomass (Figure B.5). Additionally, I found that C. californica biomass (Figure 3.11A), but not that of H. pacifica (Figure 3.11B), was a good predictor of the increase in leaf invertebrates. Comparison of the C. californica and H. pacifica coefficients determined they were significantly different and not substitutable in their impacts on leaf invertebrate abundance (F1,21 = 5.13, p = 0.03). For every 1 mg increase in C. californica biomass there was a 0.11 increase in the number of leaf pack invertebrates, while for H. pacifica there was no increase. The model containing both predator biomasses and the interaction term explained 35% of the variance in leaf invertebrate abundance. There was a significant difference in Pielou’s evenness of the invertebrate community taxa within leaf packs among treatments (F8,15 = 5.24, p = 0.003, Figure 3.12A). The 2 C. californica + 2 H. pacifica had significantly lower evenness than the control (p = 0.006), 1 H. pacifica (p = 0.005), and the 1 C. californica (p=0.02) treatments. Additionally, the 2 C. californica had significantly lower evenness than the 1 H. pacifica treatment (p = 0.04). The regression model significantly explained 43% of the decline in evenness (F3,20 = 6.79, p = 0.002) and this was driven by the significant interaction term, indicating emergent interspecific MPEs (Figure B.6). Neither C. californica or H. pacifica biomass alone were good predictors of Pielou’s evenness and comparisons of coefficients found they were similar (F1,20 = 2.36, p = 0.14, Figure 3.12B and C). 34 Based on non-metric multidimensional scaling (NMDS) ordination there were some dissimilarities in community assemblage of taxa on leaf packs based on treatment, number of stonefly larvae, and species identity (Figure 3.13, Figure B.7). When considering dissimilarities in treatments, the communities in the control were different from treatments with 1 H. pacifica, 2 H. pacifica, and 4 C. californica, while these treatments were more similar to one another and all other treatment communities. The 4 H. pacifica treatment and 1 C. californica + 1 H. pacifica each only had one replicate and therefore it was not clear if these communities were dissimilar from each other or any other treatments. Based on species identity in the predator guild, control treatments were marginally dissimilar from treatments with just H. pacifica and treatments with H. pacifica and C. californica combined (Figure B.7A). Additionally, observations from treatments with no stonefly larvae (controls) were found to be further away and more dissimilar from treatments containing four stonefly larvae (Figure B.7B). I found no significant difference in shredder abundance among treatments (F8,15 = 0.52) or with changes in C. californica and H. pacifica biomass (F3,20 = 0.73, p = 0.55) (Figure 3.14). Additionally, no FFG differed as a function of treatment (predators F8,15 = 1.28, p = 0.32; CF F8,15 = 0.21, p = 0.98; CG F8,15 = 1.57, p = 0.22), (Figure B.8) and CFs (F3,20 = 0.28, p = 0.84) and predators (F3,20 = 2.48, p = 0.09) did not differ as a function of stonefly larvae biomass. I found an increase in CGs using multiple regression that was driven by a significant interaction term (Figure B.9) (F3,20 = 4.60, p = 0.01). Both C. californica and H. pacifica biomass were insignificant and equivalent in their effects on CG abundance (F1,21 = 0.23, p = 0.63). The scraper FFG was not analyzed as there were only 10 individuals in total. 3.4 Ecosystem function Periphyton biomass (F8,22 = 0.402, p = 0.91) and chlorophyll-a (F8,22 = 1.5, p = 0.14) did not differ significantly among treatments (Figure 3.15). Additionally, I found neither differed as a function of predator stonefly biomass (periphyton biomass F3, 27 = 0.40, p = 0.67; chlorophyll-a F3,27 = 1.45, p = 0.25) and there was no significant interaction term. Based on comparison of biomass coefficients of the two species they were not significantly different from one another in 35 their effects on periphyton biomass (F1,28 = 0.80, p = 0.38) or chlorophyll-a (F1,28 = 2.17, p = 0.15) indicating substitutability in impacts. Although not statistically significant there was a slight increasing trend in chlorophyll-a with increasing C. californica biomass (Figure B.10). Chlorophyll-a was highest in treatments with 2 C. californica (122.85 ± 42.53 mg/m2) and lowest in treatments with 2 H. pacifica (46.29 ± 26.31 mg/m2). Additionally, chlorophyll-a was highest in treatments with C. californica present (94.70 ± 33.17 mg/m2) and lowest in treatments with H. pacifica (63.16 ± 36.64 mg/m2). Treatments with no stonefly larvae present had slightly lower periphyton biomass (0.31 ± 0.17 g/m2) than aquaria with any larvae present (0.31 ± 0.16 g/m2) and were not significantly different from one another (F1,29 < 0.01, p = 0.96). Treatments containing H. pacifica were found to have the lowest average biomass (0.26 ± 0.12) while treatments with C. californica had the highest (0.36 ± 0.14). There was no significant difference in leaf decomposition rates among treatments (F8,22 = 0.71, p = 0.68, Figure 3.16) or as a function of C. californica or H. pacifica biomass (F2,28 = 0.63, p = 0.54). The 2 H. pacifica treatment had the highest loss of leaf (2.49 ± 0.45 mg/day) and the lowest was the 1 C. californica treatment (1.98 ± 0.49 mg/day). There was no significant interaction between species biomass and comparisons of coefficients were not significant (F1,28 = 1.20, p =0.28) indicating no emergent interspecific MPEs. Treatments with and without stonefly larvae were not significantly different (F1,29 = 0.11, p = 0.75) and had similar leaf decomposition rates (2.25 ± 0.36 mg/day, 2.32 ± 0.16 mg/day respectively). Based on predator guild assemblage, leaf decomposition rates were lowest in treatments with only C. californica (2.08 ± 0.36 mg/day) and highest with both species present (2.35 ± 0.36 mg/day). 36 Table 3.1 The number of larvae at the beginning of the experiment, and those recovered from each treatment, as well as the total percentage recovery and precent of successful replicates per treatment. Treatment abbreviations correspond to 1 C. californica (1Cc), 1 H. pacifica (1Hp), 2 C. californica (2Cc), 2 H. pacifica (2Hp), 1 C. californica + 1 H. pacifica (1Cc1Hp), 4 C. californica (4Cc, 4 H. pacifica (4Hp), and 2 C. californica + 2 H. pacifica (n = 4). Treatment Starting Recovered Survival (%) Successful replicates (%) 1Cc 4 4 100 100 (out of n = 4) 1Hp 5 5 100 100 (out of n = 5) 2Cc 6 6 100 100 (out of n = 3) 2Hp 10 10 100 100 (out of n = 5) 1Cc1Hp 6 4 66.7 33 (out of n = 3) 4Cc 16 16 100 100 (out of n = 4) 4Hp 16 15 93.7 75 (out of n = 4) 2Cc2Hp 16 16 100 100 (out of n = 4) Total 79 75 94.3 85.4 (out of n = 32) 37 Figure 3.1 Specific growth rate (SGR) of C. californica and H. pacifica weight (%/day) in aquaria containing 1 - 4 stoneflies in predator guild assemblages of single and multiple species. Boxplots display the median, 25th and 75th percentiles whiskers (1.5 times the IQR) for this and all subsequent boxplots. Data points correspond to individual stonefly predators and not averages within a replicate, individuals depicted are from aquaria with no mortality. Dotted line corresponds to no change in mass, while above the line corresponds to increasing weight (gain) and below to decreasing weight (loss). 38 Figure 3.2 Number of benthic invertebrates remaining in treatments with no stonefly predators (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica (Cc), H. pacifica (Hp), or a combination of the two (Cc+Hp). Black dots correspond to observations from independent aquarium. 39 Figure 3.3 Number of benthic invertebrates in control aquaria with no stonefly predators added (n = 3, red) and aquaria with stonefly predator additions (n = 26, blue). 40 Figure 3.4 Number of benthic invertebrates remaining in treatments with no stonefly predators (controls) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two regressed against (A) C. californica biomass (mg) or (B) H. pacifica biomass (mg). Trend lines are based on linear models of only C. californica or H. pacifica as sole predictor variables. 41 Figure 3.5 Observed proportion of prey depleted (effect size) by (A) two or (B) four predatory stonefly individuals in predator guild assemblages consisting of just C. californica (Cc, blue), just H. pacifica (Hp, green), or a mixed assemblage with both species (CcHp, yellow). Dotted lines indicate expected prey depletion calculated using multiplicative models based on single individual treatments. Asterisks indicate a significant difference between observed and expected prey depletion (* p < 0.05). nt denotes no statistical test performed due to inadequate number of replicates to perform one-sample t-test. 42 Figure 3.6 Pielou’s eveness of benthic taxa treatments with neither no stonefly predators present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species in (a) treatment categorical comparisons, or regressed against (B) C. californica biomass (mg) and (C) H. pacifica biomass (mg). Shape legend for Number of larvae corresponds to panels (B) and (C) only. 43 Figure 3.7 Non-metric multidimensional scaling (NMDS) ordination of benthic community assemblages showing dissimilarities of taxa in treatments with no stonefly predators present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species. Taxa included each comprise >1 % of the total macroinvertebrate abundance. Stress= 0.216, non-metric fit R2 = 0.953, linear fit R2 = 0.78, dimensions (k) = 2. Panel A is a zoomed-out representation to depict taxa while B is a close-up version (note different axis scales) to more accurately show differences between observations. 44 Figure 3.8 Number of invertebrates in the benthos that belong to the scraper functional feeding group (FFG) in treatments with neither species present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species in (a) treatment categorical comparisons, or regressed against (B) C. californica biomass (mg) and (C) H. pacifica biomass (mg). Shape legend for Number of larvae corresponds to panels (B) and (C) only. 45 Figure 3.9 Number of invertebrates in the benthos that belong to the collector-filterer (CF) functional feeding group in treatments with no stonefly predators present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species in (A) treatment categorical comparisons, or regressed against (B) C. californica biomass (mg) and (C) H. pacifica biomass (mg). Shape legend for Number of larvae corresponds to panels (B) and (C) only. 46 Figure 3.10 Number of invertebrates found within leaf packs in aquaria with no stonefly predators present (control) or with predator guild assemblages of 1, 2, or 4 C. californica (Cc), H. pacifica (Hp), or a combination of the two species. 47 Figure 3.11 Number of invertebrates within leaf packs in treatments with no stonefly predators (controls) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two regressed against (A) C. californica biomass (mg) or (B) H. pacifica biomass (mg). Trend lines are based on linear models of only C. californica or H. pacifica as sole predictor variables. 48 Figure 3.12 Pielou’s eveness of leaf pack invertebrate taxa in treatments with no stonefly predators present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species in (A) treatment categorical comparisons, or regressed against (B) C. californica biomass (mg) and (C) H. pacifica biomass (mg). Shape legend for “Number of larvae” corresponds to panels (B) and (C) only. 49 Figure 3.13 Non-metric multidimensional scaling (NMDS) ordination of leaf pack taxa community assemblages showing dissimilarities of taxa in treatments with no stonefly predators present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species. Taxa are from >1 % of the total macroinvertebrate abundance. Stress= 0.155, non-metric fit R2 = 0.976, linear fit R2 = 0.907, dimensions (k) = 2. 50 Figure 3.14 Shredder abundance in leaf packs in treatments with no stonefly predators present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species in (A) treatment categorical comparisons, or regressed against (B) C. californica biomass (mg) and (C) H. pacifica biomass (mg). Shape legend for Number of larvae corresponds to panels (B) and (C) only. 51 Figure 3.15 (A) Chlorophyll-a (mg/m2) and (B) periphyton biomass (g/m2) in aquaria with no stonefly predators present (control) or with predator guild assemblages of 1, 2, or 4 C. californica (Cc), H. pacifica (Hp), or a combination of the two species (Cc+Hp). 52 Figure 3.16 Decomposition rate (AFDM mg/day) of leaf packs in aquaria with no stonefly predators present (control) or with predator guild assemblages of 1, 2, or 4 C. californica (Cc), H. pacifica (Hp), or a combination of the two species (Cc+Hp). 53 4. Discussion 4.1 Impacts to benthic invertebrate abundance and MPEs In general, I found that predatory stonefly larvae impact communities through top-down controls, and inter and intraspecific interactions, as well as predator identity, could lead to unexpected, non-linear outcomes to stream food webs. I found that adding stonefly larvae resulted in a 46% lower abundance of macroinvertebrates within the benthos compared to controls. Similarly, a previous study using artificial channels found that the presence of H. pacifica at naturally occurring densities resulted in 48% lower invertebrate biomass (Atwood et al., 2014a). Another study using similar large-bodied Perlidae larvae, Acroneuria carolinensis and Agnetina capitata, found that in cages within streams their presence resulted in macroinvertebrate densities being 50% and 46% lower, respectively, as compared to control cages with no stonefly larvae (Peckarsky, 1985). Therefore, my findings are in line with previous studies and provide further evidence to demonstrate that macroinvertebrate mesopredators can exert top-down controls on stream food webs. Based on multiple regressions analyses, I found a significantly lower number of benthic prey as a result of increasing biomass of C. californica. However, H. pacifica impacts were more complicated, and when interaction terms were dropped from the models, H. pacifica was a significant predictor, while with the interaction term included it was not. I found that using either model, both species were statistically equivalent and substitutable in their impacts on the prey community. To further investigate the effects of H. pacifica to the prey community, I analyzed the data based on number of individuals of each species (Aukema et al., 2004), opposed to biomass. I found that the numbers of both species were significant predictors of the decline in prey community and equivalent in their effects. These analyses show that it is likely that increasing density of H. pacifica in this study causes decreases in the prey community similar to previous studies (Atwood et al., 2014a; Lecerf & Richardson, 2011), just to a weaker extent than does changes in C. californica density. 54 Increasing perlid biomass decreased the benthic macroinvertebrate and for every 1 mg increase in stonefly biomass there was a corresponding ~0.07% decrease in prey numbers. For an average-sized stonefly utilized in this study (approx. 130 mg) this would correspond to a decline of ~ 9.1% in single individual treatments. Although this may be a small decline in the prey community, studies utilizing Kogotus modestus found that they consumed ~2 Baetis per day, even in the absence of any competitors (Peckarsky & Cowan, 1991). Similar studies assessing the degree to which K. modestus presence impacted Baetis abundance found comparable declines, with predation by this species resulting in 1.6 – 9.5% decrease (Kerans et al., 1995). Additionally, studies assessing the consumption rate of C. californica between seasons and across a temperature gradient found that larvae held at similar temperatures to the current study (~20 °C) in August-September consume approximately 20 mg/g dry weight per day (Heiman & Knight, 1975). These studies help to show that stonefly larvae may have a low capacity to consume large quantities of prey and help to explain the low proportion of prey at any predator biomass. Although both species caused declines in the prey community, the type of multiple predator effect (MPE) varied with species identity as well as predator density. When considering intraspecific MPEs within assemblages of C. californica, I found that with two individuals, additive MPEs arose, however, at four individuals the observed prey depletion significantly differed from expected depletion suggesting antagonistic outcomes (Sih et al., 1998). This suggests density-dependence in competition, and C. californica individuals are either weakly or not interacting with one another at low densities, while at higher densities there is some form of competition that decreases per capita prey consumption. This trend was found to occur in a study using Rhantus beetles, where prey consumption was found to be lower than expected (antagonistic) at the highest treatment densities (Greig et al., 2013). For intraspecific pairings of H. pacifica individuals, I found lower than expected numbers of benthic prey were depleted in both the two and four individual treatments. This result partially supports my hypothesis that H. pacifica larvae would potentially compete more strongly due to their more aggressive nature and larger size (Peckarsky, 1979). However, I found that observed prey depletion did not differ from expected depletion in the two H. pacifica treatment when incorporating the replicates that 55 experienced negative depletion. This was potentially due to the large negative depletion in one of the replicates of the 1 H. pacifica treatment that was used to calculate the expected prey depletion. This replicate was found to have 325 more individuals than the controls, which may be attributed to the high number of chironomini (Chironomidae) within the sample. No other study has utilized these two species of perlid stoneflies, but as mentioned in the introduction, others utilizing different predatory stoneflies have found that the nature of intraspecific MPEs varies with species (Elliott, 2003a). For example, Elliott (2003a) found that Isoperla grammatica (Perlodidae) individuals consumed the same amount of prey in single individual treatments as they did with low (3) and high (5) densities of conspecifics. In contrast, with Perlodes microcephalus (Perlodidae), increasing densities of conspecifics resulted in drastic reductions of the amount of prey captured per individual. The authors were able to observe the encounters between these species, and found that the duration and nature (non-aggressive versus aggressive) of predator-predator encounters explained the effect on prey capture rates (Elliott, 2003a). Additionally, they found some evidence for density-dependent effects, as increasing from 1 to 2 individuals minorly altered attack rates but further increases (3, 4, or 5 individuals) caused more drastic and decreasing impacts. For interspecific pairings of C. californica and H. pacifica, I found no significant interaction term from multiple regression analyses indicating that no emergent MPEs occurred (Aukema et al., 2004). This indicates that increasing biomass of one species does not have an impact on the effect caused by the other species. However, when calculating expected prey depletion for interspecific pairings, statistical tests could not confirm that at low density (2 individuals) that this value differed from expected prey depletion. If expected depletion did not differ from observed depletion, this would indicate that additive MPEs arose at low interspecific densities (Soluk, 1993). This finding goes against my original hypothesis that any treatment involving H. pacifica would result in stronger competition and antagonistic MPEs at all densities. This may have occurred due to mechanisms by which predators may spatially or temporally partition their niche to reduce competitive encounters (Garvey et al., 2021). In studies of terrestrial mammals, mesopredators may temporally shift their feeding to reduce encounters with larger, more 56 aggressive apex predators and decreasing the likelihood of interference competition (Garvey et al., 2021). Although it is unlikely that either stonefly larvae would temporally shift feeding times, as stoneflies are typically nocturnal (Johnson, 1983), there is the chance at low densities they may spatially partition their environment. This may be likely as many species of stonefly larvae exhibit submissive or evasive behaviour that may lead to decreased future encounters but not decreased capacity to capture and consume prey (Peckarsky & Penton, 1985). In this study I found that as density of perlid larvae increased in interspecific treatments the type of interactions between larvae changed, indicating the occurrence of density-dependent competition (Nilsson, 2001). In treatments with two individuals of each species (four individuals total) I found the outcome of having multiple species resulted in similar amounts of prey being depleted compared to single species treatments. Therefore, this suggests that interspecific competition is the same as intraspecific competition at higher densities and results in antagonistic MPEs. For some species of stonefly larvae, e.g. Acroneuria carolinensis, the impact of interactions with conspecifics and heterospecifics may yield similar interaction strength, while for other species, i.e. Agnetina capitata, they may be more negatively impacted by heterospecifics (Peckarsky & Penton, 1985). At high densities, intra and interspecific competition may be similar as both species and all individuals have a high degree of niche overlap for habitat and prey (Sheldon, 1980). In studies using dragonfly and hellgrammite larvae, antagonistic MPEs arose in both inter and intraspecific treatments (Vance-Chalcraft et al., 2004). Additionally, they found that the antagonistic MPEs were of similar magnitude between inter and intraspecific treatments, indicating that competition was similar between and within species pairings. I found that increasing the density of stonefly larvae led to lower than expected reduction of the benthic community due to competition. However, it cannot be determined if competition arose due to direct interference between larvae or an indirect effect through exploitation of prey leaving less available to other larvae (Holdridge et al., 2016; Holomuzki et al., 2010). At the end of the experiment, aquaria with stoneflies present had an average of 755 (± 192) remaining benthic invertebrates which corresponds to 6,040 (± 1,536) invertebrates/m2. Based on estimates 57 of macroinvertebrate densities in Oregon streams this is comparable with natural stream macroinvertebrate abundance (Li et al., 2001). This suggests that densities were high enough to ensure that prey were unlikely to be a limit on encounter rates (Kratz, 1996). Therefore, this may support the interpretation that interference, rather than exploitative competition occurred. Additionally, most studies of stonefly predator interactions have found evidence to suggest it arises due to interference (Elliott, 2003b; Peckarsky & Penton, 1985; Walde & Davies, 1984). In studies of Kogustus nonus, the authors designed experiments to eliminate the potential of exploitative competition by ensuring prey densities remained at high densities (Walde & Davies, 1984). They found that stonefly larvae decreased the time spent moving and number of prey encounters as predator density increased. Although I cannot definitively conclude what the specific mechanism is, it seems likely that interference, rather than exploitative competition ensued. Although the number of remaining invertebrates may have been sufficiently high, there is the possibility that those remaining at the end may have been small and therefore more difficult to find. Stonefly larvae have been found to shift in prey preference to larger individuals as they themselves grow (Sheldon, 1969), suggesting that the larger individuals used in the experiment may first exploit larger prey. Although remaining prey were not measured at the end of the experiment, based on qualitative notes of relative body size of remaining prey taken during the identification, I found a weak trend to suggest larger organisms were left in aquarium with no stonefly or single predator treatments. This is consistent with work analyzing the size structure of Cladocera in lakes with and without Alosa aestivalis (blueback herring) (Brooks & Dodson, 1965). The authors found that the presence of fish led to decreases in the size of remaining prey, however, if this had consequences for predator foraging is unknown. Additionally, size-shifts in prey may not have occurred, as other studies have found that although stonefly consume progressively larger prey as they grow they still include small prey and instead have a broader range of prey sizes consumed (Feminella & Stewart, 1986). I observed a potential weak trend of decreases in prey size, however this trend was also highly variable, as I found high proportions of large prey in some high predator density treatments. 58 In my benthic invertebrate community results, there was a large outlier within the control treatments, and with its removal, benthic counts were still higher in controls compared to aquaria with stonefly larva, however, it was not significantly different. The high benthic invertebrate counts within the outlier aquarium may have resulted from an unusual abundance of newly hatched or Ephemeroptera (mayfly) that were not found in any other aquaria. The mayfly nymphs were small (1-2 mm), did not have gills and were just starting to develop definitive mayfly appearances, indicating they had recently hatched (Anderson, 1969). We counted ~ 230 early stage Ephemeroptera in one control sample, and if they were excluded from the counts would have resulted in 1430 invertebrates which was comparable to counts from two other aquaria from different treatments containing stonefly predators. However, while this control replicate may have resulted in this aquarium leveraging benthic invertebrate counts, the general decreasing trend in benthic invertebrate abundance with increasing predator biomass and density is still apparent. 4.2 Leaf pack invertebrates – consumptive vs behavioural impacts Prey species may be consumed by predators, but they may also evade predators by changing habitats or seeking refuges from predation (Peckarsky & Dodson, 1980). I found relatively more invertebrates in leaf packs with increasing biomass of C. californica, but not H. pacifica. This suggests that although both predator species cause a decline in benthic invertebrates, the mechanism by which they impact invertebrate abundance differs. As H. pacifica caused a decline of invertebrates in the benthos, but no increase in the number within leaf packs, this suggests it was caused by predation (consumptive impact). However, with C. californica, although they caused a comparable decline in the benthic community, they also caused an increase in invertebrates within leaf packs, suggesting some sort of non-consumptive effect (Peckarsky et al., 2008). I found that the number of invertebrates in the leaf packs increased by 37 individuals from the control to the 4 C. californica, while the number in benthos decreased by 462. This indicates that although C. californica was causing a behavioural modification of prey they also were decreasing the prey abundance through consumption. Additionally, I found that the number of invertebrates within leaf packs in interspecific treatments was similarly high to treatments 59 with intraspecific pairings of C. californica. This suggests that in interspecific treatments both non-consumptive and consumptive impacts are occurring due to the presence of C. californica. This has been observed in a predatory newt and dragonfly larvae predator guild assemblage where they found that dragonfly larvae caused non-consumptive effects in tadpole prey to move to leaf packs, resulting in decreased consumptive abilities of the newts (Davenport & Chalcraft, 2013). The increase of invertebrates within leaf packs suggests that prey are using predator avoidance tactics to avoid being predated upon (McIntosh & Peckarsky, 1999). Although the mesh bags holding the leaves had openings that stonefly larvae were capable of fitting within, leaf packs still provide some refuge as stonefly larvae typically do not go into them (Richardson & Chauvet, 2019). Prey behaviour shifts in the presence of stoneflies has been well documented and the literature suggest that stonefly larvae cause prey to either emigrate or drift (Lancaster, 1990), or to utilize alternative microhabitats (Peckarsky & Dodson, 1980). Studies within artificial channels showed that the presence of a similar stonefly predator, Doroneuria baumanni, led to increased drift of prey, but the response was not seen for all prey species (Lancaster, 1990). Additionally, the finding that C. californica may be causing a behavioural modification of the prey is consistent with previous studies, as it has previously been documented that C. californica can cause an increased drift response in prey that additionally may lead to indirect facilitation with trout (Soluk & Richardson, 1997). Studies utilizing Acroneuria lycorias, found that they were capable of causing shifts in prey distributions and also causing decreases in overall abundance through predation (Peckarsky & Dodson, 1980), similar to my results of C. californica. Therefore, my findings provide more evidence that many species of stonefly may cause prey to shift to alternative habitats to reduce predation risks (Bo et al., 2010; Peckarsky & Dodson, 1980). 4.3 Community structure When considering invertebrate taxa community structure (i.e. composition and evenness) benthic communities were similar regardless of stonefly larvae presence, identity, density or predator 60 guild assemblage. This suggests that C. californica and H. pacifica may be opportunistic predators and did not show evidence of having strong prey species-specific selection within this study. Although some previous studies have shown there is potentially some degree of prey preference (Johnson, 1983), if C. californica and H. pacifica were to exhibit this I would have expected to see a difference in community structure and richness between controls and aquaria with stoneflies as well as between guild assemblages. Therefore, this study helps to demonstrate that both species are most likely generalist predators (Peckarsky, 1979). I found differences in functional feeding groups within the benthos, that is, collector-filterers (CFs) were lower in high density treatments as compared to controls and that increasing the biomass of either species contributed to this decrease. This decrease is similar to that observed in experimental manipulations of large-bodied detritivores and predators in artificial channels. One study found that channels containing H. pacifica had ten-fold lower biomass of CFs as compared to channels devoid of predators (Lecerf & Richardson, 2011). Atwood et al. (2014a) found that H. pacifica presence caused a significant decline in the biomass of grazers and detritivores compared to control treatments. However, I did not observe this trend, but this could be partially attributed to my experiment being conducted in a closed system opposed to an open system (Cooper et al., 1998). In the open channel experiments (Atwood et al. 2014a; Lecerf & Richardson, 2011), declines in prey abundances may be a factor of emigration and drift (Cooper et al., 1998). Therefore, in the closed aquaria I performed my experiment in, I may not have detected declines in prey as they could not emigrate from the system. When considering leaf pack communities, I found evenness was lower and the abundance of the collector-gatherer (CG) FFG was higher in mixed predator guilds, while single species guilds were similar regardless of density. The significant interaction term between C. californica and H. pacifica biomass suggests that when both predator species are present, there is an interspecific emergent effect on macroinvertebrates in leaf packs (Aukema et al., 2004). Additionally, based on NMDS plots of taxa within leaf packs I found that control tanks were grouped closely together and dissimilar from treatments with just H. pacifica or a mixed predator assemblage, as well as further away from aquaria with high density treatments. The visual inspection of the plot showed that control treatments had more Ameletus and Baetidae, while the treatments with just 61 H. pacifica, mixed predator assemblage, and four predators had more Chironomini. Therefore, the decrease in evenness in interspecific treatments may have arisen from the increase of Chironomidae in the CG FFG. Chironomids are a common prey source for both perlid species (Peckarsky, 1979), and I would expect that their abundance would decrease in the presence of stonefly larvae. Additionally, as I found competition was similar between inter and intraspecific pairings, the per capita risk to chironomid larvae would have gone up proportionally in all high-density treatments, not just interspecific treatments. However, it is not surprising that chironomids experience behavioural modification in the presence of predators, as some studies have found that certain species may dig deeper burrows to evade fish predators (Hölker & Stief, 2005). Alternatively, the shift in microhabitat may be driven more by resource availability rather than as a consequence of predation risk (Baker & Ball, 1995). This is corroborated by studies finding that collector-gatherers may be more highly associated with leaf packs if there is a higher proportion of organic matter and algae to use as a food resource (Nelson, 2000). Therefore, although significant, I do not have evidence to conclude the mechanisms by which interspecific interactions between C. californica and H. pacifica, but not intraspecific interactions, cause changes to CGs and evenness. 4.4 Impacts to stonefly larvae growth and survival At the end of the experiment only 4 stonefly larvae, 3 C. californica and 1 H. pacifica, were not recovered and differences in survival were not attributable to treatment, nor was it different between species. Mortality may have resulted from cannibalism rather than due to competition for prey resources (Rudolf & Armstrong, 2008). Although, cannibalism is common among macroinvertebrates, this typically occurs when larger individuals predate on smaller individuals as many macroinvertebrate predators are gape-limited and feed on prey they are capable of fitting in their jaws (Woodward & Hildrew, 2002). In this study, stonefly larvae were of similar size, however, two of the four larvae that died were the smallest individual within the treatment. Additionally, I did not locate the remains or the tags of these larvae at the end of the experiment. 62 Although these findings could suggest cannibalism may have occurred, it cannot be conclusively determined as stomach contents were not analyzed, nor were encounters between larvae observed. Although I found stonefly larvae consumed fewer prey than expected with increasing density, this did not have negative impacts to their survival. There was also no significant difference in growth rates between treatments or between species, and increases in mass were exceptionally low (0.1% per day). Studies on C. californica have found in July the percentage of consumed food that gets converted to growth is lower than at other times of year. They found that the majority of prey consumed is allocated to respiration (46%) and egestion (19.2%) with only 23.4% converted to growth (Heiman & Knight, 1975). Additionally, based on the time of year of my study (August-September) and temperatures within the microcosms, growth rates for C. californica may be as low as 2 mg/g dry weight per day (approx. 0.01 % per day, wet weight) (Heiman & Knight, 1975). Alternatively, studies utilizing other stonefly larvae found growth rates to be higher with average growth per day corresponding to 2-5% (Peckarsky & Cowan, 1991). Although these rates are substantially higher, in their experiment prey abundance was maintained at a high abundance ensuring larvae had sufficient access to food resources. Although the growth rate observed within my study was low, it was consistent with other experiments with stonefly larvae, and due to the short duration of the experiment changes in mass may have been minimal and not detectable (Lieske & Zwick, 2008). Some studies have found that growth of stonefly larvae may not be impacted by the presence of a competitor. Peckarsky and Cowan (1991) found that stonefly larvae growth in multiple predator treatments did not differ from single predator treatments, even when the feeding rates were found to be lower in multiple predator treatments. They also documented high variability in growth between individuals in their multiple predator treatments. They suggested this could be attributed to due to the establishment of a dominant individual that gained more weight than the subordinate or to individuals allocating nutrients to other processes than growth (Peckarsky & Cowan, 1991). In the current study, although not statistically significant, there was a trend towards decreasing growth with increasing predator density regardless of species and guild 63 assemblage. Treatments with four individuals had the lowest growth (0.08 %/day) and also had eight of the eleven larvae that experienced mass losses. This suggests that if the experiment persisted for a longer duration there may have been a more noticeable decline in mass (Lieske & Zwick, 2008). Additionally, I found that H. pacifica individuals had higher growth rates compared to C. californica. This is consistent with the findings that H. pacifica was decreasing the prey community primarily through consumptive pressures and consuming higher amounts of prey than C. californica individuals. 4.5 Trophic cascades Although trophic cascades are typically stronger in lotic systems (Shurin et al., 2002), I found no evidence to suggest that the presence of stonefly larvae or the interactions between them cascaded to impact basal resources. Previous studies have found that stonefly presence can impact both leaf litter decomposition (Atwood et al., 2014a) and periphyton standing stocks through decreases in the abundance of the prey community (Lecerf & Richardson, 2011). In my study, I found that C. californica caused more invertebrates to enter leaf packs, but this did not result in higher rates of decomposition. This could be attributed to the overall low number of shredders within aquaria, as well as abundance being similar between treatments. Although not statistically significant, I did find a weak, decreasing trend in chlorophyll-a with increasing C. californica biomass. This suggests a potential weak effect though the primary producer side of the food web, which is similar to findings from a previous study (Lecerf & Richardson, 2011). Additionally, although H. pacifica caused lower abundance of invertebrates in aquaria, there was no subsequent decrease in decomposition rates or higher amounts of periphyton standing stock. This too could be attributed to scraper abundance which remained relatively low and similar between treatments. Trophic cascades may not have occurred because of behavioural modifications of the prey (Reynolds & Bruno, 2013). It has been found that amphipods in marine systems decrease grazing rates in presence of predators to decrease the risk of detection and consumption. Additionally, trophic cascades may also not have occurred because of the low abundance of periphyton. 64 Studies utilizing the artificial channels the tiles were inoculated in have found that periphyton biomass was 200-300 mg/m2 depending on the amount of canopy shading (Kiffney et al., 2004). To determine if starting biomass was low, or if it became low during the course of the experiment, I processed reference tiles that I had placed in MKRF when treatment tiles were added. Based on these reference tiles, I found that starting standing stock of periphyton may have been highly variable and low initially (0.14 – 0.39 mg/m2) and not drastically depleted during the experiment. This finding shows that bottom-up controls through low amounts of periphyton (Power, 1992) may have made detecting trophic cascades difficult. 65 5. Limitations and future directions Although this study showed how inter and intraspecific interactions between stonefly larvae may impact stream food webs, there were some limitations. Firstly, the experiment was aimed at understanding the interactions between mesopredators and its implications, yet these experiments were conducted in the absence of top predators. In larger streams with fish or amphibians, stonefly larvae may interact with prey and each other differently (Soluk & Collins, 1988). For example, the amount of prey captured by an assemblage of five Agnetina capitata (Perlidae) larvae was lower in the presence of sculpins than in aquaria where the fish predator was absent (Soluk & Collins, 1988). Similar to how stonefly larvae may elicit behavioural modifications in their prey resources, fish may also cause the same responses in stonefly larvae. In an experiment in field enclosures, fish not only decreased the density of larvae of the stonefly Paragnetina media through consumption, they also elicited a drift response that caused stonefly larvae to emigrate from the system (Feltmate & Williams, 1989). Additionally, they found that stonefly larvae may be less active when fish are present, either residing within interstitial spaces of substrate or other refuge habitat, leading to decreased consumption of prey by stoneflies (Feltmate & Williams, 1989; Soluk & Collins, 1988). Alternatively, studies assessing the impacts of trout on whitebait fish (Galaxiidae) have also found that the presence of a larger predator (trout) can lead to reduced foraging; however, in some instances trout presence led to increased growth of whitebait, suggesting some form of facilitation (McIntosh et al., 2010). Therefore, although I found that C. californica and H. pacifica can elicit top-down controls, this may be altered in natural systems with larger apex predators present The presence of apex predators may impact the interactions and the degree to which competition occurs between stonefly larvae. It is postulated that if predators cause their prey to concentrate in refuge areas, then competition within their prey may be increased (Mittelbach, 1986). Therefore, in the presence of apex predators, this likely would increase intraspecific competition by stonefly larvae, and potentially interspecific competition if C. californica and H. pacifica have the same predator avoidance tactics. Studies of dragonfly larvae found that not all species responded the same to fish predators (Pierce, 1988). Pierce (1988) found that two species, Tetragoneuria cynosure and Lapdona deplanata, shifted microhabitat use to reduce predation risk, while a third 66 species, Sympetrum semicinctum, did not shift habitat use and remained on more exposed surfaces of substrate. Therefore, to better understand the role of C. californica and H. pacifica and the implication of their interactions for stream food webs, future work should be aimed at identifying the mode of predator avoidance tactics and the consequences of this for stonefly interaction strengths. Stream communities have a high biodiversity of macroinvertebrates (Richardson, 2019), many of which may be co-occurring mesopredators (Klecka & Boukal, 2012). In the current study, I only focused on a mesopredator assemblage of two species and did not incorporate any additional predatory species that may further compete with Perlidae stonefly larvae for a shared prey resource. Within lotic systems macroinvertebrate mesopredators may have a high degree of niche overlap (Klecka & Boukal, 2012). In streams in MKRF, some species of predatory caddisfly may have a high degree of dietary overlap, and consume similar prey (Baetis) to that of perlid larvae (Dudgeon & Richardson, 1988). Therefore, this suggests that in the presence of additional mesopredators, the top-down controls and interactions between stonefly larvae may be altered. When considering the consumptive effects of two predator species, having an understanding of differences in metabolic capacity may be of importance (Ruesink & Srivastava, 2001). Body size, as well as many other factors, are known to be determinants of a species’ consumption rate (Fielding & DeFoliart, 2008). In my experiment C. californica and H. pacifica were of similar size, indicating that they had similar per capita consumptive abilities. However, when trying to understand differences in consumption between additional mesopredator species with different body size, having a more general understanding of differences in metabolic capacity may be needed. Mesopredators may also predate on one another, resulting in intraguild predation (McPeek, 2014), which may further complicate our understanding of mesopredator roles in top-down controls. Many mesopredators that co-occur with stonefly larvae, such as Odonate larvae, are aggressive predators and have been frequently reported to engage in intraguild predation and cannibalism (Rudolf & Armstrong, 2008). Studies have found that prey experience risk reduction when intraguild predation occurs between mesopredators (Schmitz, 2007). Understanding how 67 dragonfly larvae interact with other mesopredators may be particularly important, as in streams where C. californica and H. pacifica are found there are large larvae of the dragonfly Cordulegaster dorsalis (Marczak et al., 2006). Additionally, stonefly larvae have size-structured populations (Sheldon, 1980), which could impact the type and strength of interaction as well as the MPE outcome. Therefore, in natural systems prey may experience changes to risk reduction due to the inter and intraspecific competition between stoneflies and other macroinvertebrate mesopredators. To have a better understanding of increasing mesopredator guild richness, future studies should aim to incorporate a larger array of species of mesopredators as well as different age classes to further our understanding of the role and interactions between the numerous mesopredators. The interactions between predators can have implications for both predator and prey population dynamics. In my study, I did not measure how interactions between stonefly impacted emergence or fecundity and therefore, the longer-term impacts of inter and intraspecific competition between C. californica and H. pacifica is unknown. Little work has been done to understand the implications of stream macroinvertebrate interactions to long-term population dynamics (Little, 2022; McIntosh et al., 2022). More recently, one field-based experiment assessed how density-dependent feedbacks with caddisfly larvae can regulate populations open to emigration and immigration during a 2-year life cycle (McIntosh et al., 2022). Through this work it was apparent that there are multiple mechanisms of population regulation (i.e. stochastic and density-dependence) that may impact multiple life stages differently (Little, 2022). Although I found that competition may arise between and within C. californica and H. pacifica, the long-term consequences this may have to growth and survival at later life stages, as well as the further implications to the prey community, are unknown. Some work has been done to understand how interactions between stonefly predators can impact the fitness of the predators themselves (Peckarsky & Cowan, 1991), as well as how predation pressure may also impact the prey fitness (Peckarsky & McIntosh, 1998). Studies have found that increased competition results in smaller, less fecund female stoneflies and that the presence of stonefly larvae led to smaller female Baetis larvae that are predicted to be less fecund (Peckarsky & Cowan, 1991; Peckarsky & McIntosh, 68 1998). However, within streams in the PNW the extent to which this may influence future generations and community composition and abundance has not been studied. Within the current study there was high variability in all response variables. At the predator level variability in growth could be attributed to differences in sex, body size, behaviour type, as well as the formation of dominance hierarchies in multiple predator treatments (Peckarsky & Cowan, 1991; Peckarsky & McIntosh, 1998). A study measuring growth of stonefly in intraspecific pairings found that one individual may become the “dominant” individual and the other the “subordinate” leading to large differences in the growth by each individual (Peckarsky & Cowan, 1991). Additionally, in other studies “bold” versus “shy” predators have been found to have differences in consumptive abilities that can dictate the capacity for growth and survival (Everling & Johansson, 2022). Within the community there may be high variability due to complex interactions within the community itself. Predators are not the only FFG that compete with one another, and other FFGs, such as scrapers and CFs, that share a food resource may have some level of competition occurring (Hemphill, 1991; Kohler, 1992). These studies found that intra and interspecific competition resulted in changes in abundance and growth rates, which could result in impacts to prey numbers and the basal resources they consume (Kohler, 1992). A final consideration that may impact the outcome of predator-predator interactions are abiotic factors and prey abundance. As demonstrated in my trial study (Appendix A), aspects such as low prey availability, seasonality, and temperature may complicate results. Studies have found that prey abundance is highly influential in dictating the nature of trophic and also non-trophic interactions (Sentis et al., 2017). With increasing density of prey, interactions between predators may be reduced as they are no longer resource limited and can reach satiation, limiting the occurrence of competition (Cuthbert et al., 2021). Additionally, temperature mediates movement and metabolism in ectothermic organisms (Gillooly et al., 2001), and at increased temperatures may lead to increased encounter rates with other predators, but also increased metabolic demand leading to higher bouts of prey searching (Sentis et al., 2017). When considering seasonality, predators may be less active at different months, partially due to the temperature effect (Heiman & Knight, 1975). Therefore, future studies should continue to identify the factors that influence 69 consumptive rates and predator interactions which can give as a better understanding of top-down controls in stream food webs. 70 6. Conclusions This work demonstrated that predator guild identity, density, and richness are important factors in determining the type and strength of MPEs. Through this research, my aim was to evaluate and quantify the outcome of intra- and interspecific interactions of C. californica and H. pacifica on stream food webs. Generally, I found that consistent with the literature both C. californica and H. pacifica impacted communities through top-down controls (Atwood et al., 2014a). I found that both caused minor decreases in the prey community (0.07% per mg), which may be explained by the low consumptive capacities of Perlidae stonefly larvae (Peckarsky & Cowan, 1991). Interestingly, I found that although these two species are quite similar, the mechanism by which they impact the prey community appears to differ. The more voracious species, H. pacifica, elicited stronger consumptive controls on the prey community, while C. californica, caused prey to shift habitats to leaf packs. Through this experiment I found evidence to support my hypotheses that antagonistic MPEs would arise, and that the presence of H. pacifica as well as increasing density would impact the degree of competition and strength of antagonism. I found that inter and intraspecific C. californica pairings had density-dependent competition, and when C. californica was present at low densities, predator assemblages were found to decrease the benthic community to the expected calculated proportion (additive MPE). However, antagonistic MPEs arose due to competition at high densities of intraspecific C. californica and interspecific pairings, and for all densities of intraspecific H. pacifica treatments. I also found no evidence of predator effects or the implications of predator-predator competition causing trophic cascades to impact lower basal resources. The findings from this work have implications for conservation and management as well as for general understanding of the role of mesopredator interactions in structuring communities. Small macroinvertebrate communities act as model systems (Ledger et al., 2009) and may help us to create generalizations about what aspects of predator guilds may be important in dictating community composition. Utilizing these types of model systems will be useful for providing insights into the outcomes of predator additions and removals, and helping conservation managers understand the implications to community changes. Apex predators are disproportionately being threatened with extinction (Ritchie & Johnson, 2009) which may lead to 71 mesopredator release (Prugh et al., 2009) and posing the question of how these mesopredators and the interactions between them may dictate community structure. In some instances it is suggested that if there is strong competition regulating mesopredators, the removal of top predators may have little effect on communities (McPeek, 2014). However, when apex predator controls dictate mesopredator behaviour and abundance, their removal can lead to unexpected consequences. Information gained from this study can help to identity what aspects of predator traits (i.e. behaviour, size, foraging) may dictate the outcome of predator interactions. This study also provides insights into the effects this may have on the prey community as well as the extent to which these impacts may extend to alter ecosystem processes and functionality. 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Earlier work using this species of stonefly larvae has found that they can elicit top-down controls that directly impact prey abundance and behaviour, and indirectly impact leaf litter decomposition and periphyton standing stock through trophic cascades (Atwood et al., 2014a; Soluk & Collins, 1988). However, to-date no study has aimed to understand how interactions between individuals of C. californica result in Multiple Predator Effects (MPEs) to their prey community. Therefore, to better understand the role of C. californica and predator-predator interactions in structuring stream food webs, I performed a trial experiment to evaluate the outcomes of intraspecific interactions of C. californica larvae on stream food webs across a density gradient. Although this study provides little information on the nature of these interactions, insights were gained to better understand how prey abundance, seasonality, and temperature may complicate the detection of predator impacts. My objectives were (1) to quantify the impacts of intraspecific interactions to the prey community, (2) to determine if C. californica can elicit trophic controls that impact lower-level basal resources, and (3) to determine and quantify if increases in the density of C. californica alters the outcomes. If my results coincided with additive MPEs, I predicted that the decrease in prey community would be equal to the sum of each larva’s independent per capita effect and would propagate to see the same trend in leaf litter decomposition and periphyton standing stock. If my results were consistent with antagonistic MPEs, I predicted that overall consumption would still increase but that the total decrease in prey community would be less than the sum of each larva’s independent per capita effect and there would be higher leaf litter decomposition 85 and lower periphyton standing stock as compared to additive models. Lastly, if my results were in line with synergistic MPEs, I predicted there would be lower prey abundance and leaf litter decomposition and higher periphyton standing stock as compared to the additive model. I hypothesized that the effects of intraspecific interactions will increase with increasing C. californica density due to increased encounters and stronger intraspecific interactions that would impact the prey community and cause trophic cascades that will impact lower basal level resources. Methods Experimental design I conducted a 14-day experiment between 11 to 25 February 2021 manipulating the presence and density of C. californica from 0 to 4 individuals within 24 microcosms. Microcosm design was the same as that outlined in thesis section 2 (Methods) and pictured in Figure 2.1 with minor modifications. Aquaria contained 10 L of stream water obtained from MKRF’s Spring Creek as opposed to 12 L and one large rock (grain size 7.4 cm) instead of 3. I measured water quality on the start day of the experiment using YSI 556 mps and YSI ProODO water quality probes. All aquaria were similar in terms of temperature (18.21 ± 0.22 °C, mean ± standard deviation), dissolved oxygen (9.55 ± 0.42 mg O2/L), and conductivity (12.13 ± 2.00 µS/cm). Due to apparatus failures pH could not be taken. To inoculate the microcosms with the natural benthic stream community, I collected Surber samples (243 μm mesh with sampling area of 0.09 m2) from Spring Creek in MKRF. Once again. large predatory and large-bodied organisms were removed from the samples to reduce the consumption of prey by other predators or behavioural modifications that can occur due to other large macroinvertebrates (Lecerf & Richardson, 2011). Four buckets were filled with 12 Surber samples each and topped up to 16 L. Once back in the laboratory 500 ml was taken from each bucket and randomly placed into the aquaria. The remaining contents of each bucket were combined and then equally divided and randomly assigned to the aquarium so that each 86 aquarium had 2.67 L of prey inoculation added. Surber samples were added two days prior to the start of the experiment to allow for prey to acclimate before C. californica addition. During prey inoculation four aquaria received approximately 100 ml less which may impact the starting community abundance and structure. Further details on impacts and implications for data analysis are presented below in Methods Statistical analysis. I took measures of leaf litter decomposition and periphyton standing stock (AFDM and chlorophyll-a) to detect impacts to ecosystem functions. Each aquarium was given two senesced airdried red alder leaves weighing 2 g total dry weight (± 0.04g) that were collected beneath trees on the UBC campus. Leaves were then soaked for 13 hours prior to the start of the experiment to leach dissolved organic carbon that could result in browning of the water. We placed the leaves into coarse mesh bags (1 cm x 0.7 cm openings) and weighted them down with the large rock. Fourteen days prior to the start of the experiment, I placed unglazed ceramic tiles into artificial channels in MKRF to inoculate them with similar levels of periphyton standing stock. Tiles were then collected two days prior to the start of the experiment, and randomly placed one within each aquarium. One day prior to the start of the experiment, we captured C. californica larvae from small-order streams within UBC’s MKRF. Larvae were placed in individual fine mesh bags (2 mm x 2 mm openings) to ensure equal levels of starvation and to reduce the interactions between larvae before the start of the experiment. We weighed, measured, and marked the larvae either the day prior to the start of the experiment or the day of. Stoneflies were measured and marked using the same methods outlined in thesis section 2. The larvae used weighed 0.175 ± 0.029 g, were 19.3 ± 1.0 mm long and had headwidths of 4.5 ± 0.3 mm. On the start day of the experiment larvae were randomly assigned to treatments (1, 2, 3, or 4 larvae per aquarium) and microcosms. Treatments with 0, 1, 2, or 4 individuals had 5 replicates and treatments with 3 individuals had 4 replicates 87 Response variables C. californica growth On the final day of the experiment, we located the C. californica larvae and immediately weighed and measured them using the same methods as previously described. Similar to outcomes in thesis section 2, larvae were found to have negligible or slight increases in headwidth and length, indicating measurement errors and therefore were not used in generating estimates of growth. Using the Specific Growth Weight (SGR) formula, the change (%/day) of larvae weight was calculated to assess potential impacts of intraspecific interactions to C. californica growth. Ecosystem processes (leaf decomposition and periphyton standing stock) On the final day of the experiment, I removed tiles using aquarium nets, wrapped each in tinfoil and placed them into a freezer at -10 °C. The tiles were then processed using the methods outlined in section 2 to determine periphyton biomass (g/m2) and chlorophyll-a content (mg/m2). Leaves were also removed using aquarium nets and placed into plastic bags in a 6 °C refrigerator until the following day. Leaves were processed using methods outlined in section 2 to determine the AFDM decomposition rate of leaf pack (mg/day) and to collect and preserve invertebrates found within leaf packs. The leaves were then placed in a drying oven at 60 °C for 83 days. Leaves were left in the drying oven for an extended duration due to lack of access to a furnace to burn leaves. Invertebrates from the leaf packs were then identified down to the lowest possible taxonomic level and assigned to a functional feeding group (FFG) so that counts of total abundance and differences in the proportion of certain taxa and FFGs could be determined. Benthic community Once larvae, leaves, and tiles were removed from the aquaria I scooped out all the benthic material into metal trays. The sediment was rinsed with tap water and elutriation was performed 88 to remove macroinvertebrates. This was performed 3 to 5 times until the water coming out of the tray was clear and devoid of floating organisms and debris and everything captured was then preserved in 70% ethanol. I retained all the sediment with grain sizes between 6.3 mm and 63 μm and stored it in 70% ethanol. Using a dissecting microscope any invertebrates visible at 16 times magnification were removed and preserved in 70% ethanol to later be identified to the lowest possible taxonomic level, usually family or genus, and FFGs were identified. Statistical analysis For statistical analysis, I used R 4.1.2 (R Core Team, 2021). As previously stated, during the inoculation of the prey community, 4 aquaria were given less of the combined prey Surber samples, and additionally I did not recover all larvae at the end of the experiment. To determine if these factors influenced the outcome of the results 4 different subsets of data were created to determine the best and most reliable subset for analyses. One dataset was the full set of observations (n = 24), a second consisted of a set of observations from aquaria that had full survival (n = 16), a third set for aquaria that received the full allocation of prey (n = 20), and a fourth subset of data that consisted of observations with full larvae survival and proper allocation of prey (n = 14). As the prey abundance response measure would influence the outcome of all the response parameters (e.g. growth of stonefly, consumption of leaf, etc.), a linear model with treatment as the fixed effect for each of the subsets was created and compared using AICc. It was determined that the fourth dataset containing observations from aquaria with full survival and prey allocation had the lowest AICc value (Table A.3). The results presented pertain to this dataset unless otherwise stated. When there are deviations in terms of mean, standard deviation, statistical analysis, it will be stated To test for differences in survival of C. californica between treatments, I performed a Fisher’s exact test. For changes to stonefly larvae growth (SGR) I used general linear mixed effects models (glmms), with treatment as the categorical fixed predictor variable and aquaria as a random variable. Due to the low number of prey recovered within the leaf packs, benthic and leaf macroinvertebrates recovered were compiled into one data set to determine impacts to the prey 89 community. For taxa and FFG abundance, evenness, as well as periphyton AFDM (g/m2), chlorophyll-a (mg/m2) and leaf litter decomposition (AFDM mg/day) linear models (LMs) with treatment as the fixed predictor variable were used. Models were tested to ensure they met the assumptions of linearity, normality, and homogeneity. When assumptions were violated, they were log transformed. In one instance for chlorophyll-a data could not be transformed to meet the assumption of homogeneity, but due to the high overlap in means and standard deviations between treatments no further transformations were performed as biologically there were no differences between treatments. Significance was determined using analysis of variance (ANOVA) with type III sums of squares due to the unbalanced design, with significance determined at p < 0.05. To assess for changes in community composition of taxa Non-Metric Dimensional Scaling (NMDS) was performed and the same protocols outlined in section 2 were used. To determine if MPEs arose in treatments with 2-4 C. californica, the observed proportion of prey depleted was determined by subtracting the final from the initial (~ 208.5 individuals) prey abundance. I then compared observed prey depletion to expected outcomes, which were calculated using the multiplicative risk model and the average observed depletion in the single C. californica treatment (Sih et al., 1998; Soluk & Collins, 1988). Formulas and calculations are explained in detail in the Statistical Analysis section in the main body of the thesis. Some studies account for natural mortality occurring within the prey community (Vance-Chalcraft et al., 2004), however, those studies focus on a single prey species. As our study included other smaller predators within the prey community, it cannot be determined if mortality in control treatments was attributable to natural mortality or arose due to consumption by small predators. Therefore, I did not account for natural mortality when calculating expected MPEs in this study. To determine if observed proportion of prey depleted differed from the expected additive null hypothesis, one-sample t-tests were performed for each density level. If there were no differences between the expected and observed outcome at 2, 3, or 4 individuals, it was determined to be an additive MPE. 90 Results Growth & Survival At the end of the experiment 8 aquaria had mortality of at least 1 individual, leaving 37 of the initial 47 larvae alive (79%). Two of the unrecovered larvae came from separate aquaria that received lower prey allocated. The mortality was not significantly different between treatments (p = 0.61) with 2 dying in each of the lower density treatments (1 and 2 C. californica) and 6 dying in each of the higher density treatments (with 3 and 4 C. californica) (Table A.1). Of aquaria that experienced some level of mortality only 2 had more than a single individual die, which was observed in the 3 and 4 C. californica treatments. Aquaria with the 4 C. californica treatment had the highest proportion of survival (0.85 ± 0.22, mean ± SD), followed by 2 (0.80 ± 0.27), 3 (0.75 ± 0.32), and the 1 (0.60 ± 0.54) C. californica treatments. When excluding the aquaria with fewer prey allocation, the 4 C. californica treatment then had full survival (100%) and the 2 C. californica treatment now had 75 % survival. Thirteen larvae had negative specific growth rates (SGR), that is, mass loss. Those that experienced mass loss were observed in every treatment and there was no significant difference in growth between treatments (χ2 = 0.24, p = 0.97). Based on the median, SGR showed mass loss for the single C. californica treatment (-0.25 %/day), no growth in the 4 C. californica treatment, 0.12% increase per day for individuals in the 2 C. californica treatment with the highest growth experienced by individuals in the 3 C. californica treatment (0.23 %/day) (Figure A.1). However, based on the mean the 4 C. californica treatment had the lowest average growth (0.04 ± 0.32 %/day). Prey Community The amount of prey remaining at the end of the experiment was low regardless of treatment, ranging from 29 to 186 individuals remaining of the initial 208.5 per aquaria for the subset of data with full larvae survival and proper prey inoculation (Table A.2). In the subset containing all 24 aquaria, one was found to have 25 remaining prey individuals, but this was excluded in the 91 analyzed full prey/full survival subset as it was an aquarium that received less prey. I found no significant differences in the number of prey remaining at the end of 14 days (F4,9 = 0.93, p = 0.49). Based on means, the 4 C. californica treatment had the lowest number of prey remaining (92.67 ± 59.18) and the 3 C. californica treatment had the highest (156 ± 32.53). However, based on the median values, controls had the lowest abundance in contrast to treatments with any number of C. californica larvae (Figure A.2). When comparing the full prey/full survival subset of data to the others, control treatments had either the lowest or second lowest remaining prey while the 3 C. californica treatment always had the highest amount of remaining prey regardless of the subset of data (Table A.2). In all instances there was high variability within treatment outcomes and no observed trend with increasing C. californica density. I found that observed prey depletion did not differ from expected prey depletion for any density of C. californica (2 C. californica, t1 = -2.32, p = 0.26; 3 C. californica, t1 = -4.29, p = 0.15; 4 C. californica, t2 = -1.62, p = 0.25) (Figure A.3). The 3 C. californica treatment had the lowest observed prey depletion (0.25 ± 0.16) and the highest deviation from the expected prey depletion (2.9 times lower). There were no significant differences in taxa evenness (F4,9 = 0.93, p = 0.49) between treatments and values were highest in the high density- 4 C. californica treatment and lowest in the 3 C. californica treatment (Figure A.4). Pielou’s evenness of taxa showed a declining trend with increasing density of C. californica up to 3 individuals but, overall, the difference in evenness was only approximately 0.03 and was highly variable between and within treatments. Based on ordination plots representing the community assemblage of taxa (stress = 0.146), I found there was no difference in community structure of between treatments (Figure A.5). Ordination also showed that the presence or absence (control vs treatments with any C. californica), did not impact prey community structure (Figure A.5). I found that Seratella was more distant from the other Ephemeroptera groups (Ameletus, Baetidae, Paraleptophlebia, and Heptageniidae), and that Elmidae, Lepidostoma and Seratella were grouped and were more distant to the other remaining taxa. 92 Ecosystem Functions I found no statistical differences in biofilm biomass (F4,8 = 1.76, p = 0.23) or chlorophyll-a (F4,9 = 1.09, p = 0.41) between treatments. Biofilm biomass was highest and most variable in the treatment with 1 C. californica (0.64 ± 0.45 g/m2, without outlier removed: 2.12 ± 2.58 g/m2) and on average was 2 times higher than other treatments (Figure A.6). The same occurred for chlorophyll-a, where aquaria with a single C. californica had the highest and most variable amounts (64.4 ± g/m2). The remaining four treatments had similar and less variable final biofilm biomass with aquaria with 4 C. californica (0.33 ± 0.02 g/cm2) having the next highest biomass followed by aquaria with 2 (0.32 ± 0.05 g/cm2), 0 (0.31 ± 0.03 g/cm2), and 3 (0.27 ± 0.08 g/cm2) C. californica, respectively. In the 3 C. californica treatment, I found that the chlorophyll-a response showed a different relationship than what was observed in biofilm biomass. This treatment was found to have the next highest and second most variable amounts of chlorophyll-a as compared to the controls (17.91 ± 18.33 mg/m2), 2 C. californica (10.94 ± 6.93 mg/m2), and 4 C. californica (20.61 ± 10.99 mg/m2) treatments which again had similar and less variable results (Figure A.7). Overall, I found no trend in chlorophyll-a (Figure A.7) or biofilm biomass (Figure A.6) with increasing numbers of C. californica or between treatments with larvae present or absent. Similar to the biofilm response, leaf decomposition rates did not significantly differ between treatments (F4,9 = 0.33, p = 0.84). Aquarium with 3 C. californica had lower rates of decomposition (0.28 ± 0.00 mg/day) when looking at the most reduced dataset, but for the other datasets decomposition rates were similar to that observed in the 4 and 1 C. californica treatments. Variability in decomposition rates was lowest in the controls as compared to any treatment with C. californica present. Overall, I found there was little difference in leaf decomposition rates and all observations were within 0.01 mg/day of each other (Figure A.8). 93 Table A.1 The number of C. californica (Cc) larvae at the beginning of the experiment, and those recovered from treatments with 1, 2, 3, or 4 individuals, as well as the total percentage recovery and precent of successful replicates per treatment. Treatment Starting Recovered Survival (%) Successful replicates (%) 1Cc 5 3 60 60 (out of n = 5) 2Cc 10 8 80 80 (out of n = 5)* 3Cc 12 9 75 75 (out of n = 4) 4Cc 20 17 85 60 (out of n = 5)+ Total 47 37 79 62.5 (out of n = 16) * One successful replicate had lower prey allocation + Two replicates had lower prey allocation 94 Figure A.1 Specific growth rate (SGR) of weight change (mg) of C. californica individuals’ across experimental treatments containing 1 – 4 C. californica. Boxplots display the median, 25th and 75th percentiles whiskers (1.5 times the IQR) for this and all subsequent boxplots. Data points (dots) correspond to individual larvae growth and not average within a replicate. 95 Table A.2 Summary (mean and standard deviation (SD)) of prey abundance for each subset of data in treatments with 0 (control), 1, 2, 3, or 4 C. californica (Cc). Survival/Prey model was the one used for all data analysis (n=14). Treatment Survival/Prey Full Survival Prey Mean SD Mean SD Mean SD Mean SD Control 97.25 29.78 82.80 41.34 82.80 41.34 97.25 29.78 1 Cc 135.67 59.50 125.00 45.95 135.67 59.50 125.00 45.95 2 Cc 126.50 23.33 103.00 32.23 119/33 20.65 102.50 37.19 3 Cc 156.00 32.53 129.50 41.30 156.00 32.53 129.50 41.30 4 Cc 92.67 59.18 89.00 48.00 92.67 59.18 92.67 59.18 96 Figure A.2 Final abundance of prey in aquaria containing 0 - 4 C. californica. The red box depicts aquarium with no stonefly larvae present, while blue boxes correspond to treatments with larvae present, for this and all subsequent plots where control treatments are depicted. 97 Figure A.3 Observed proportion of prey depleted (effect size) in treatments with 2, 3, or 4 C. californica individuals. Dotted lines indicate expected prey depletion calculated using multiplicative models based on single individual treatments. Error bars depict the standard error around the mean. 98 Figure A.4 Pielou’s evenness of invertebrate taxa in treatments with 0 - 4 C. californica. 99 Figure A.5 Non-metric multidimensional scaling (NMDS) ordination of taxa community assemblages showing dissimilarities of taxa between aquaria containing 0 - 4 C. californica. Taxa are from >1 % of the total macroinvertebrate abundance. Stress= 0.185, non-metric fit R2 = 0.979, linear fit R2 = 0.898, dimensions (k) = 2. AmBa corresponds to Ameletus and Baetidae grouped together, PrChlorPerlidae, to predatory Chloroperlidae and Perlidae, and C.G.Chiro are collector-gatherer chironomids (Chironomini and Orthocladiinae). 100 Figure A.6 Final periphyton biomass in aquaria with 0 - 4 C. californica. Note 1 outlier removed from figure as it was 5.3 times higher than the next highest value left in the dataset. 101 Figure A.7 Final chlorophyll-a content of periphyton in aquarium with 0 - 4 C. californica. 102 Figure A.8 Leaf decomposition rates in treatments with 0 - 4 C. californica. 103 Discussion I found no significant difference in C. californica growth and survival, prey community composition and structure, or to basal resources. Additionally, I found there was no difference between expected and observed depletion of prey with increasing density of C. californica, suggesting that MPEs were additive. Consistent with the prey community impacts, there was no differences in biofilm biomass, chlorophyll-a, or leaf litter decomposition. In contrast to my other experiment involving C. californica, in this study I found that larval C. californica do not elicit have top-down control on stream food webs that decrease prey abundance through predation or behavioural modification. This may in part be attributed to by the season and temperature in which the experiment was conducted. Studies on C. californica found that their growth and consumption rates vary with temperature and time of year (Heiman & Knight, 1975). Although macroinvertebrate consumption rates typically increase with increasing temperature (Sentis et al., 2017), laboratory experiments with C. californica in winter months showed growth and consumption is not only the lowest during these months, but is generally not affected by temperature (Heiman & Knight, 1975). The current study was conducted during February and aquarium temperatures were 18.2 ± 0.2 o C for the duration of the 14-day experiment. This suggests top-down controls may not have been observed due to the inherent nature of C. californica to have low consumption during these months and the short duration of the study. Additionally, although temperature has the capacity to increase activity and consumption, the temperature difference between natural streams and the aquarium may have had an impact. Stream temperature in East Creek in MKRF during February typically range from 5 to 8 °C (Leach & Moore, 2014), indicating macroinvertebrates were held at 6 to 12 °C above their typical winter temperatures (Heiman & Knight, 1975). Although these temperatures are within the 30 °C median tolerance levels of C. californica (Heiman & Knight, 1975), many aquatic insects that are held at higher than expected temperatures in winter have been found to reduce growth and fecundity and alter emergence times (Vannote & Sweeney, 1980). Therefore, the growth and survival of C. californica and the other macroinvertebrates in the prey community may have been negatively impacted by residing at higher temperatures during cooler months. 104 Observed consumption did not significantly differ from expected, suggesting that MPEs were additive across all densities of C. californica. However, in the 3 C. californica treatment, there was a large deviation between the expected and observed prey depletion. This observation suggests that there may have been weak competitive interactions that could have led to a decrease in consumption and weak antagonistic MPEs that were not detected in this study (Vance-Chalcraft & Soluk, 2005). Additionally, of the three MPE treatments (2 – 4 C. californica), the 3 larvae treatment saw a slightly higher amount of remaining prey than the others. This also could suggests weak competition occurred between C. californica that decreased their ability to consume prey, which may be a result of decreases in foraging behaviour in the presence of conspecifics as found with similar stoneflies (Peckarsky & Penton, 1985). The starting amount of prey at the beginning of the experiment was exceptionally low (~ 209 individuals). Prey density is a known to impact both predator-prey and predator-predator interactions. The amount of prey within a system can dictate the ability of predators to seek out, capture, and consume prey (Sentis et al., 2017). The effect of prey density on predator interaction strength forms concave up relationship, where sufficiently high and low prey densities leads to decreased predator-predator interactions (Sentis et al., 2017). Therefore, this study demonstrates that having low availability of prey may have made detecting differences in consumption rates difficult. Regardless of predator density prey would have been sufficiently difficult for any C. californica to find, suggesting this may be responsible for there being similar prey abundance and low consumption differences between treatments. Although not statistically significant, control treatments had slightly lower abundance than in treatments containing the large mesopredator. By excluding C. californica there was the potential for smaller predatory individuals to go through mesopredator release and remain at higher numbers due to decreased predation and behavioural suppression by the larger C. californica predator allowing them to consume more prey (Soulé et al., 1988). However, our results showed predator numbers were lowest in the control treatment (Figure A.9). As there were few predatory 105 individuals in controls and those remaining were small bodied, predation on the prey community would not have been high enough to be equivalent or exceed that of C. californica. Some studies have found that by removing the top predator, which in this instance was C. californica, that this can lead to destabilization of the community and unexpected outcomes to species and community dynamics (Rezende et al., 2021). They found that through mesopredator release there was a decrease in species stability and community asynchrony that indirectly decrease community stability suggesting that the loss of top predators (Rezende et al., 2021). Although plausible, it is not expected that either of these processes occurred. Instead, it could be due to the experimental set-up where control treatments may have received slightly lower proportions of initial prey. For this experiment I used the full community assemblage, which would include all biotic interactions that occur between the prey species, which may have attributed to some of the high variability in the observed results. Studies of inter and intraspecific interactions between grazers and shredders in the absence of predators found that this may dictate growth, survival, and consumption rates of these FFGs (Kohler, 1992; Little et al., 2020). Predators are not the only FFG that experiences competition between individuals as demonstrated within these studies. Studies manipulating the density of Baetis and Glossosoma found that there were differences in survival and growth between species and in inter and intraspecific pairings. Baetis survival and growth was more highly impacted by intraspecific competition while Glossosoma survival was unaffected by competition but growth was more impacted by interspecific competition (Kohler, 1992). However, in this instance, some of the competition was attributed to by exploitative competition, which would not have occurred in our system as there was no difference in resources at the end of the experiment. Additionally, studies of intraspecific competition of shredders found that increasing densities lead to decreasing consumption of leaf litter (Little et al., 2020). Overall, this demonstrates that due to the inclusion of the full community that differences in the outcomes could partially be attributed to complex biotic interactions between the prey community that could not be detected in this experiment. 106 The results from my study of the outcomes of C. californica intraspecific interactions on stream food webs are not significant, and have a trend that makes little biological sense. These results might be either artefacts of the winter timing of the aquarium experiment or some other unusual dynamic within the prey community that I could not detect. Although, this experiment may have yielded little information relating to the nature of intraspecific interactions of C. californica it was helpful in understanding external factors that may complicate the detection of such interactions. This study still helps to highlight the complexities of community dynamics and demonstrates the importance of appropriate and thoughtful experimental procedures. Additionally, this work helped to show that predator consumption as well as predator-predator interactions strength and their importance in impacting community structure may vary as a function of seasonality and prey availability. Continued experimental work should aim to understand the external factors that impact predator interactions which may help to construct more extensive generalizations of the roles and impacts of predators in structuring community composition. 107 Appendix A Supplemental Tables and Figures Table A.3 The number of observations, AICc values and weights for the 4 subsets of data used to run models for prey abundance to determine appropriate model to use for all response variables. Model Observations AICc AICc weight Prey/Survival 14 164.23 1 (100%) Survival 16 182.95 0 (0%) Prey 20 219.65 0 (0%) Full 24 259.03 0 (0%) 108 Figure A.9 Number of (A) collector-gatherers, (B) collector-filterers, (C) predators, (D) shredders, and (E) scrapers remaining in treatments with 0 (n = 4), 1 (n = 3), 2 (n = 2), 3 (n = 2) and 4 (n = 3) C. californica. 109 Table A.4 Functional feeding group (FFG) association of all identified taxa. Percentages in parentheses correspond to the relative contribution of each taxon to the associated FFG. Collector-Gatherer Collector-Filterer Predator Scraper Shredder Baetidae (12.0%) Hydropsyche (7.6%) Chloroperlidae -other (15.3%) Drunella (1.3%) Despaxia (6.3%) Seratella (3.3%) Tanytarsini (85.2%) Perlodidae (1.3%) Ironodes (4.7%) Nemouridae (57.7%) Ameletus (2.1%) Copepoda (7.2%) Perlidae (6.7%) Cinygmula (40.1%) Pteronarcys (2.7%) Paraleptophlebia (23.2%) Rhyacophila (11.8%) Cinygma (9.9%) Lepidostoma (29.7%) Elmidae (5.8%) Polycentropus (0.9%) Epeorus (43.5%) Microsema (3.6%) Chironomini (26.0%) Tanypodinae (32.5%) Glossosomatidae (0.4%) Corynoneura (1.0%) Ceratopogonidae (14.7%) Orthocladiinae – other (8.8%) Hexatoma (1.8%) Pericoma (0.1%) Oreogeton (1.1%) Tubificidae (17.6%) Hemerodromia (0.9%) Kathroperla (0.2%) Acaria (12.2%) Agraylea (0.1%) Turbellaria (0.4%) Empididae- other (0.2%) 110 Appendix B: Supplemental figures Table B.1 The number of observations, AICc values and weights, and adjusted R2 for the 3 subsets of data used to run models for prey abundance to determine most appropriate model to use for all response variables. The Full dataset model did not meet model assumptions. Model Observations AICc AICc weight Adj R2 No outlier or mortality 29 24.06 0.87 (87%) 0.098 Full dataset 34 27.82 0.13 (13%) -0.17 No outlier 33 63.92 0.00 (0%) 0.10 111 Figure B.1 Number of benthic invertebrates remaining (log transformed) in treatments with 0 - 4 stonefly predators consisting of C. californica, H. pacifica, or a combination of the two regressed against C. californica biomass (mg) and H. pacifica biomass (mg). 112 Figure B.2 Number of benthic invertebrates remaining in treatments with no predators (control, red) or with predator guild assemblages consisting of 1, 2 or 4 C. californica (Cc, light blue), H. pacifica (Hp, green), or a combination of the two (Cc+Hp, yellow). (B) Number of benthic invertebrates in control aquaria with no stonefly predators added (n = 3, red) and aquaria with stonefly predator additions (n = 26, dark blue). 113 Figure B.3 Number of benthic invertebrates remaining in treatments with no stonefly predators (controls) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two regressed against (A) C. californica biomass (mg) or (B) H. pacifica biomass (mg). 114 Figure B.4 Number of invertebrates in the benthos that belong to the (A) shredder, (B) collector-gatherer, and (C) predator functional feeding groups (FFG) in treatments with no stonefly predator present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species. 115 Figure B.5 Number of invertebrates within leaf packs in treatments with 0 - 4 stonefly predators consisting of C. californica, H. pacifica, or a combination of the two regressed against C. californica biomass (mg) and H. pacifica biomass (mg). 116 Figure B.6 Pielou’s evenness of leaf pack taxa in treatments with 0 - 4 stonefly predators consisting of C. californica, H. pacifica, or a combination of the two regressed against C. californica biomass (mg) and H. pacifica biomass (mg). 117 Figure B.7 Non-metric multidimensional scaling (NMDS) ordination of leaf pack taxa community assemblages showing dissimilarities of taxa in aquarium with (A) predator guild assemblages consisting of C. californica (blue) or H. pacifica (green) larvae and between treatments with (B) 0 – 4 predatory stoneflies. Taxa are from >1 % of the total macroinvertebrate abundance. Stress= 0.155, non-metric fit R2 = 0.976, linear fit R2 = 0.907, dimensions (k) = 2. 118 Figure B.8 Number of invertebrates in the leaf packs that belong to the (A) collector-filterer, (B) collector-gatherer, and (C) predator functional feeding groups (FFG) in treatments with neither species present (control) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two species. 119 Figure B.9 Collector-gatherer (CG) functional feeding group (FFG) abundance within leaf packs in treatments with 0 - 4 stonefly predators consisting of C. californica, H. pacifica, or a combination of the two regressed against C. californica biomass (mg) and H. pacifica biomass (mg). 120 Figure B.10 Chlorophyll-a content (mg/m2) of periphyton in aquarium with no stonefly predators (controls) or with predator guild assemblages consisting of 1, 2 or 4 C. californica, H. pacifica, or a combination of the two regressed against (A) C. californica biomass (mg) or (B) H. pacifica biomass (mg).
Thesis/Dissertation
eng
Forestry
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Richardson, John Stuart
Outcomes of stream invertebrate mesopredator interactions to benthic food webs and ecosystem functions
Text