The effects of landscape change on behaviour and risk perceptions of predator and prey communities on a heterogeneous landscape in Alberta and British Columbia, Canada

(1)

by

Gillian Chow-Fraser B.Sc., Trent University, 2015

A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of

MASTER OF SCIENCE in the School of Environmental Studies

ã Gillian Chow-Fraser, 2018 University of Victoria

(2)

Supervisory Committee

The effects of landscape change on behaviour and risk perceptions of predator and prey communities on a heterogeneous landscape in Alberta and British Columbia, Canada

by

Gillian Chow-Fraser B.Sc., Trent University, 2018

Supervisory Committee

Dr. Jason T. Fisher (School of Environmental Studies) Co-Supervisor

Dr. John P. Volpe (School of Environmental Studies) Co-Supervisor

(3)

Abstract

Supervisory Committee

Dr. Jason T. Fisher (School of Environmental Studies) Co-Supervisor

Dr. John P. Volpe (School of Environmental Studies) Co-Supervisor

Habitat selection is assumed to be informed by prior knowledge of the costs and benefits associated with habitat patches on heterogeneous landscapes. Ultimately, species should select habitat that maximizes resources acquired, and minimizes risks to mortality. However, landscape change alters the distribution of resources and, therefore, the energetic trade-offs that drive habitat selection. I investigated how landscape change, through anthropogenic disturbance features, affects behavioural decisions within the predator and prey community, and how those choices affect fitness in the boreal forests and foothills of west-central Alberta and east-central British Columbia. In my first data chapter, I investigated how interspecific interactions within the predator community changed across a gradient of anthropogenic disturbances, focusing on the habitat selection of wolverine (Gulo gulo). I used a novel temporally-explicit approach with camera trap data that modelled weekly co-occurrence of species. I found that anthropogenic features facilitated increased competition between wolverine and coyote, which I suggest is the mechanism that drives broad-scale declines of

wolverine on disturbed landscapes. In my second chapter, I tested how woodland caribou evaluated risks and rewards associated with predation risk, disturbance features, and forage habitat during the calving period in two herds on landscapes with differing degrees of disturbance. I compared drivers of resource selection between mothers whose calves survived and mothers whose calves died in either herd. I found that resource selection for mothers on the lesser disturbed landscape was driven by a trade off between predation risk and forage habitat, wherein mothers whose calves eventually died prioritized selection of forage habitat over predation risk. However, all mothers on the more

(4)

disturbed landscape prioritized their resource selection around disturbance features. Mothers whose calves died appeared to select sites closer to well sites, but more strongly avoided cut blocks and recent wildfire burns. I suggest that disturbance features introduce novel costs and rewards that are not traditionally evaluated on undisturbed landscapes, wherein caribou are required to effectively evaluate risks attributed to unique features with consequences for calf survival. More broadly, my research links the mechanisms that drive changes in habitat selection on changing landscapes with implications for species distributions, population dynamics, and evolutionary changes.

(5)

List of Tables

Table 2.1 Comparison of mean ±SE for natural, abiotic, and disturbance features at camera sites in Willmore Wilderness Park, the undisturbed landscape, and Kananaskis Country, the disturbed landscape. Means of natural and disturbance features were derived from proportion of features within a 5000-m buffer around the camera site. Ratio refers to the ratio of mean of KC to mean WW features. ... 46 Table 2.2 Hypotheses for drivers of weekly wolverine habitat selection and the corresponding models and model variables for testing each hypothesis. ... 50 Table 2.3 Comparison of AIC, delta AIC scores, and associated weights for hypotheses-models in this study. Core model (CM), snow cover, was included in every model to account for baseline abiotic drivers of weekly habitat selection. ... 52 Table 2.4 Estimated b-parameters for variables in best model explaining weekly wolverine habitat selection through inclusion of coyote co-occurrence and their interaction with linear features (coyote absence = 0, coyote presence = 1). ... 53 Table 2.5 Number of camera-trap detections for all species in a cumulative detection dataset

(n=152) and separately for the undisturbed (Willmore Wilderness Area; n=65) and disturbed (Kananaskis Country; n=89) landscapes. The final models were run with the pooled dataset from both landscapes. ... 55 Table 2.6 AIC scores for candidate sets of the most ecologically meaningful models excluding anthropogenic features and biotic interactions. Top model explaining the most variance was

determined within each set, and used to build a cumulative model. The model based on snow cover is bolded to indicate it explained the most variance and was used as the core model for all successive hypothesis testing. ... 56 Table 3.1 Sampling periods during either winter or summer months on both the undisturbed

landscape (UDL) and the disturbed landscape (DSL), with total number of camera sites in each array. The best survey—the survey that yielded the highest number of detections—is indicated for each species on either landscape. ... 87 Table 3.2 Explanatory covariates predicted to affect predator distributions in the undisturbed landscape (UDL) and the disturbed landscape (DSL). Land cover classification adapted from Nijland et al. (2015). ... 89 Table 3.3 Factors hypothesized to affect adult female caribou resource selection: forage (FOR), predation risk (PRED), and disturbance features (DIST). ... 96 Table 3.4 AIC scores for candidate sets of female adult caribou resource selection models for both the lower disturbance range (LDR) and the higher disturbance range (HDR) by calf fate. Most supported hypotheses are shaded in grey determied by the lowest AIC score and highest AIC

(8)

weight. (FOR = Forage hypothesis, PRED = Predation risk hypothesis, DIST = Disturbance

features hypothesis) ... 98 Table 3.5 Resource selection functions model estimates for most supported hypothesis for good mothers (calves survived calving season) and bad mothers (calves died during calving season) in lesser distubed ranges (LDR) and higher disturbed ranges (HDR). (FOR = Forage hypothesis, PRED = Predation risk hypothesis, DIST = Disturbance features hypothesis) ... 99 Table 3.6 Model estimates, standard errors (SE) and significance levels for most-supported predator distribution models on either undisturbed landscapes (UDL) or disturbed landscapes (DSL) derived from camera trap datasets. The characteristic ‘scale of selection’ indicates the spatial scale of the strongest model, and is reflective of the size of buffer surrounding each camera site. Models were validated by calculating percentage of deviance explained by the model. ... 102 Table 3.7 Camera detections for all predator species sampled on undisturbed landscape (UDL) and a disturbed landscape (DSL). ... 104

(9)

List of Figures

Figure 2.2.1 Camera trap sites in the Willmore Wilderness Park (WW) (top panel) and Kananaskis Country (KC) (bottom panel). WW was considered the undisturbed landscape, and KC was

considered the disturbed landscape, based on the degree of human footprint on the landscape. ... 45 Figure 2.2.2 Interaction term of strongest model predicting weekly wolverine occurrence showing probability of wolverine occurrence as a function of proportion of linear features in the absence or presence of coyote (n = 2790 weeks of observation across 152 camera sites). ... 53 Figure 2.2.3 Distribution of proportion of linear features at sites with species occurrences and co-occurrences, for wolverine and coyote across both disturbed and undisturbed landscapes. Middle bar is the median, with black dots as outliers. Average proportion of linear features was significantly different between only and coyote-only sites (p < 0.001), only and wolverine-coyote co-occurrence sites (p < 0.05), and wolverine-coyote-only and wolverine-wolverine-coyote co-occurrence sites (p < 0.10). ... 54 Figure 3.1 Range extents for mother caribou in the lower disturbance range (LDR; Narraway) and higher disturbance range (HDR; Redrock-Prairie Creek) during the calving period. Camera trap arrays were used in the Willmore Wilderness Park (WW) and Kananaskis Country (KC) to predict predator distributions in LDR and HDR. ... 83 Figure 3.2 Mother caribou response to landscape features, as determined by resource selection function model with the most support. A) Resource selection for good mothers and bad mothers on higher disturbance range (HDR) was strongly explained by disturbance features, though mothers differed in responses to wildfire burns, distance to well sites, and distance to cut block. B) Resouce selection for good mothers in lower disturbed range (LDR) was explained by relative predation risk. C) Resource selection for bad mothers in the LDR was explained by natural land cover features. . 100 Figure 3.3 Relative probability of predator occurrence (0-1) in the Narraway and Redrock-Prairie Creek herd home ranges during the calving period for A) black bear, B) grizzly bear, C) wolverine, D) grey wolf, E) coyote, and F) cougar. ... 105 Figure A.1 Scaled residual plots for top model explaining wolverine habitat selection using the DHARMa package in R specifically designed to validate models with random effects by creating randomized bins to visually validate models. Residuals are standardized between 0 and 1, similar to residuals of a linear regression model. ... 143 Figure B.1 Residuals of top model explaining caribou resource selection in the Redrock-Prairie Creek herd for mothers whose calves eventually died during calving period. Scaled residual plots were created using the DHARMa package in R designed to validate models with random effects. Residuals can be interpretted in the same ways as residuals of a linear regression. ... 144 Figure B.2 Residuals of top model explaining caribou resource selection in the Redrock-Prairie Creek for mothers whose calves survived the calving period. Scaled residual plots were created using

(10)

the DHARMa package in R designed to validate models with random effects. Residuals can be interpretted in the same ways as residuals of a linear regression. ... 145 Figure B.3 Residuals of top model explaining caribou resource selection in Narraway herd for mothers whose calves survived the calving period. Scaled residual plots were created using the DHARMa package in R designed to validate models with random effects. Residuals can be

interpretted in the same ways as residuals of a linear regression. ... 146 Figure B.4 Residuals of top model explaining caribou resource selection in Narraway herd for mothers whose calves eventually died during the calving period. Scaled residual plots were created using the DHARMa package in R designed to validate models with random effects. Residuals can be interpretted in the same ways as residuals of a linear regression. ... 147

(11)

Acknowledgements

I am deeply appreciative and indebted to a vast community of people who have supported me and inspired me throughout this degree. Without my community, this thesis would not be in existence.

My supervisors, Dr. Jason Fisher and Dr. John Volpe, were invaluable in providing guidance and support throughout my degree. It was a big jump to move across the country to join a small quirky lab, and I am eternally grateful that you both were so welcoming. As a mentor, teacher, and friend, I could not have asked for a more caring and enthusiastic supervisor in Jake. Thank you for passing on all your knowledge and helping me become a better ecologist. John, I appreciate you putting up with my shenanigans. Your steadfast patience with me will not be soon forgotten.

For the laughs and thoughtful discussions, I am extremely grateful for my lab comrades: F. Stewart, S. Frey, S. Darlington, S. Gorgopa, D. Bulger, G. Daniels, L. Burke, J. Burgar, R. Boxem, and E. Tattersall. I know I can always count on all of you pick up my spirits on even the darkest of days. And you are all brilliant! Special thanks to my cohort, my Ginnies, who made my time at UVic very special. I especially grateful for fostering the lifelong friendships with D. Cook and C.

O’Manique, who push me to expand my thinking and my heart with unwavering moral compasses. You are also brilliant!

I am deeply appreciative of the financial support and guidance provided by fRI Research, specifically L. Finnegan and B. Nobert. Collaborative work is made all the more meaningful and

(12)

rewarding when working with supportive partners, such as fRI Research. I hope my work can help meet some conservation goals that align with the Caribou Program.

I am lucky enough to re-purpose data collected by previous researchers from many sources. John Paczkowski and Nikki Heim at Alberta Environment and Parks generously provided the data from the Kananaskis. Camera trap data in the Willmore were collected and processed by InnoTech Alberta and many hard-working volunteers. The caribou GPS-collar data used in the third chapter analysis were collected as part of a collaboration between Alberta Environment and Parks and Weyerhaeuser Co. Ltd. Spatial data for the linear disturbance features used in the Narraway and Redrock-Prairie Creek herd ranges was provided by N. DeCesare and M. Hebblewhite.

Thank you to the staff of the Environmental Studies department for minimizing all

administrative headaches: E. Hopkins, L. Erb, D. Janess, and A. Fisher. I would never know how to wade through the administrative bogs without you. Elaine, thank you for the unending number of hugs every time we met.

And finally, my extreme gratitude for my family in Victoria, Edmonton, New York, and Hamilton, who have supported me always. To my partner, M. Harris, who had to deal with my weeping person more than anyone I know, thank you. I promise to get it together now. My parents, N. Fraser and P. Chow-Fraser, were invaluable in helping me thrive during this process. Mom. Dad. I did it!

(13)

Chapter 1 An introduction to habitat selection on a heterogeneous landscape,

the boreal forest and mountains of Alberta and British Columbia

1.1 Introduction

Habitat selection, one of the principle processes determining an individuals survival, is a complex behavioural response that varies across populations, landscapes, and species (Wiens et al. 1993; Dunning, Danielson, and Pulliam 1992). Mediated by not only landscape heterogeneity, but also interactions with interspecifics and intraspecifics (Pulliam and Danielson 1991), it predicts population-level processes such as species distributions, abundance, and ultimately, coexistence (Morris 1992; Morris 1987; Pulliam, Dunning, and Liu 1992; Boyce et al. 2016). Habitat selection is reflected by individual perceptions of preferred and risky habitat types, which promotes overall individual fitness, as defined by their lifetime reproductive success and survival (McGraw and Caswell 1996).

Habitat selection is hypothesized to be informed by prior knowledge of habitat quality, as individuals should distribute themselves across patches differing in their resources, so that each patch maximizes fitness of all individuals within it (Fretwell and Lucas 1970; Zimmerman, LaHaye, and Gutiérrez 2003). However, the distribution of individuals is affected by many external factors that affect individual abilities access to resources and the resource quality, most notably predation risk (Gilliam and Fraser 1987; Lima and Dill 1990; Brown 1999), competition with interspecific species (Rosenzweig 1981; Morris 2003), and heterogeneity of patches (Morris 1992). Perceptions of these factors variably affect probability of selection, and therefore, individual fitness will vary across heterogeneous landscapes.

(14)

Habitat selection demands effective perception of the true costs and benefits of a

combination of biotic and abiotic factors. An individual that effectively weighs different factors—or energetic trade-offs—should benefit from high fitness rewards (e.g.: higher lifetime reproduction (McLoughlin, Dunford, and Boutin 2005), reproductive rates (Fisher, Wheatley, and Mackenzie 2014), survivorship (Zimmerman, LaHaye, and Gutiérrez 2003)). Evaluation of these trade-offs varies; for instance, individuals might avoid an area of relatively high-quality resources due to perceived fitness losses associated with higher predation risk in those areas (Festa-Bianchet 1988), and in other cases the fitness gains of accessing high-quality resources might out-weigh risks of predation (David D Gustine et al. 2006). Habitat selection is considered maladaptive in the particular case wherein selection decisions result in decreased fitness (Weldon and Haddad 2005).

Evolutionary dynamics should favour the persistence of traits that increase fitness over the long term. It is important to understand the mechanisms that affect individual perceptions of risks and rewards that drive habitat selection and impact fitness.

Habitat selection is dynamic to reflect the ways in which energetic trade-offs change as the environmental conditions change; such as the ways in which habitat selection changes with the seasons (?citation). However, rapid landscape change makes effective habitat selection even more costly, as there is a need to quickly evaluate the risks or rewards associated with novel features. Landscape change affects the availability of resources, and potentially indirectly, the strength of interspecific interactions (Amarasekare and Nisbet 2001). As we find ourselves in the era of the Anthropocene, the rapid rate of anthropogenic landscape change has become one of the most prominent types of landscape change with variable effects on resource availability (Pickell et al. 2015; Pickell, Andison, and Coops 2013), and known effects on interactions between species (Latham,

(15)

Latham, McCutchen, et al. 2011; Dorresteijn et al. 2015; Kuijper et al. 2016). Although impacts of anthropogenic features are commonly understood as direct changes to the landscape through fragmentation and habitat loss (Fahrig 2003), there are less understood complex indirect effects concurrently caused by anthropogenic disturbance features (Courbin et al. 2014; Berger 2007; Fisher and Burton 2018).

Anthropogenic landscape change directly and indirectly affects fitness as anthropogenic land-use drives global changes of biodiversity (Butchart et al. 2010), and is the strongest contributor to species declines (Maxwell et al. 2016); while facilitating the expansion of some species that are capable of exploiting landscape changes (Latham, Latham, Knopff, et al. 2013; Dickie et al. 2017; Hody and Kays 2018). Though shifts in population dynamics, such as population declines, are often linked to anthropogenic features, it is poorly understood the ways in which landscape change alters the mechanisms driving these changes. To address this knowledge gap, I investigate the ways in which anthropogenic features affect interspecific interactions, and the interplay between predation risk, risk associated with disturbance features, and habitat selection. It is important to identify ways in which species adapt their behaviour in response to disturbance features, as human disturbances shift selection pressures and favour those species which learn to effectively exploit novel resources, while pushing species to extirpation if adpatation cannot occur quick enough (Otto 2018).

Though testing these spatial relationships across multiple species and across broad landscapes is usually limited by logistical difficulties, I capitalize on existing camera traps datasets that remotely monitor occurrence of multiple species and telemetry data of a highly-mobile prey species. I examine these changes in a model study system, the Rocky Mountains of west-central Alberta and the mountains of east-central British Columbia, where habitat heterogeneity hosts an

(16)

array of predator and prey species. Here, the landscape is variably composed of intact protected areas nestled within a matrix of anthropogenic disturbances; from linear features, such as highways, logging roads, pipelines, or seismic lines, or larger irregular features, such as cut blocks or well pads. Species variably respond to these features with broad-scale implications for changes in population dynamics within the boreal forest (Fisher and Burton 2018; Toews, Juanes, and Burton 2018). The type and rate of landscape change seen in the Rockies is representative of industrial and recreational landscape change in many parts of the world. By understanding species responses to disturbances and the ways in which communities are re-structured, we learn to anticipate and understand similar mechanisms that may affect species responses to landscape change elsewhere.

In my second chapter, I test the hypothesis that anthropogenic features affect interspecific interactions within the predator community in the Rockies. In particular, I model the habitat selection of wolverine (Gulo gulo), a large-bodied meso-predator that has experienced range contractions throughout its native range in North America, with causes of declines linked to anthropogenic features (Heim et al. 2017; Stewart et al. 2016; Fisher et al. 2013). With the goal of disentangling how anthropogenic features might be driving wolverine declines, I tested how disturbance features might be changing energetic trade-offs associated with changes in interspecific interactions. I hypothesized that wolverine structured their fine-scale habitat selection in response interspecific interactions with coyote (Canis latrans), red fox (Vulpes vulpes), grey wolf (Canis lupus), cougar (Puma concolor), and/or lynx (Lynx canadensis), and further, that these interactions are mediated by disturbance features. Using novel statistical methods to model weekly co-occurrence of wolverine and interspecific predators, I link wolverine population declines on disturbed landscapes to

increased competition with coyote, which I propose is facilitated at sites with high proportions of linear features.

(17)

In my third chapter, I examine habitat selection of adult female woodland caribou (Rangifer tarandus) with calves in two herds, the Narraway and Redrock-Prairie Creek ranges. I test how they evaluate risk on a disturbed and undisturbed landscape, and how variable evaluation of risks affects calf survival. During the calving season, calves are at heel for the first 4-6 weeks following birth, at which time mothers must effectively minimize predation risk and maximize resource acquisition. I hypothesize that mother caribou habitat selection is predominantly driven by 1) predation risk, 2) risk associated with anthropogenic features, or 3) forage habitat, and that these drivers will differ between mothers whose calves survive—“good mothers”—and mothers whose calves died during the calving period—“bad mothers”. Moreover, I hypothesize that selection strategies will change between mothers on undisturbed and higher disturbed landscapes. I build resource selection

functions (RSF) models to test how caribou select habitat, and compare selection strategies between good mothers and bad mothers, and between herds. I find that caribou mothers on lesser disturbed landscapes selected habitat that traded off predation risk and forage habitat, with the prioritization of predation risk resulting in calf survival. On higher disturbed landscapes, anthropogenic features shifted all mothers selection strategies to prioritize risk from anthropogenic features, with fitness success related to the strength of response to unique disturbance features.

The final chapter summarizes the findings from each data chapter, and contextualizes the results with implications for future research and further understanding cumulative effects of landscape change.

(18)

Literature Cited:

Alberta Woodland Caribou Recovery Team. 2005. Alberta Woodland Caribou Recovery Plan 2004/05 - 2013/14. Time.

http://www.srd.alberta.ca/BiodiversityStewardship/SpeciesAtRisk/RecoveryProgram/docume nts/final_caribou_recovery_plan_photo_cover_July_12_05.pdf.

Alley, Thomas R. 1982. “Competition Theory, Evolution, and the Concept of an Ecological Niche.” Acta Biotheoretica 31 (3): 165–79. doi:10.1007/BF01857239.

Amarasekare, Priyanga. 2003. “Competitive Coexistence in Spatially Structured Environments: A Synthesis.” Ecology Letters 6 (12): 1109–22. doi:10.1046/j.1461-0248.2003.00530.x.

Amarasekare, Priyanga, and Renato M. Coutinho. 2014. “Effects of Temperature on Intraspecific Competition in Ectotherms.” The American Naturalist 184 (3): E50–65. doi:10.1086/677386. Amarasekare, Priyanga, and Roger M. Nisbet. 2001. “Spatial Heterogeneity, Source-Sink Dynamics,

and the Local Coexistence of Competing Species.” The American Naturalist 158 (6): 572–84. Andrén, Henrik, Jens Persson, Jenny Mattisson, and Anna C. Danell. 2011. “Modelling the

Combined Effect of an Obligate Predator and a Facultative Predator on a Common Prey: Lynx (Lynx Lynx) and Wolverine (Gulo Gulo) Predation on Reindeer (Rangifer Tarandus).” Wildlife Biology 17 (1): 33–43. doi:10.2981/10-065.

Apps, Clayton D., Bruce N. McLellan, and John G. Woods. 2006. “Landscape Partitioning and Spatial Inferences of Competition between Black and Grizzly Bears.” Ecography 29 (4): 561–72. doi:10.1111/j.0906-7590.2006.04564.x.

Armstrong, Robert A., and Richard McGehee. 1976. “Coexistence of Species Competing for Shared Resources.” Theoretical Population Biology 9 (3): 317–28. doi:10.1016/0040-5809(76)90051-4. Aubry, Keith B., Kevin S. McKelvey, and Jeffrey P. Copeland. 2007. “Distribution and Broadscale

(19)

Management 71 (7): 2147–58. doi:10.2193/2006-548.

Basille, Mathieu, Daniel Fortin, Christian Dussault, Guillaume Bastille-Rousseau, Jean Pierre Ouellet, and Réhaume Courtois. 2015. “Plastic Response of Fearful Prey to the Spatiotemporal

Dynamics of Predator Distribution.” Ecology 96 (10): 2622–31. doi:10.1890/14-1706.1.

Berger, Joel. 2007. “Fear, Human Shields and the Redistribution of Prey and Predators in Protected Areas.” Biol. Lett 3: 620–23. doi:10.1098/rsbl.2007.0415.

Berger, Kim Murray, and Eric M Gese. 2007. “Does Interference Competition with Wolves Limit the Distribution and Abundance of Coyotes ?” Journal of Animal Ecology 76: 1075–85.

doi:10.1111/j.1365-2656.2007.01287.x.

Boonstra, Rudy. 2013. “Reality as the Leading Cause of Stress: Rethinking the Impact of Chronic Stress in Nature.” Functional Ecology 27 (1): 11–23. doi:10.1111/1365-2435.12008.

Boonstra, Rudy, David Hik, Grant R Singleton, and Alexander Tinnikov. 1998. “The Impact of Predator-Induced Stress on the Snowshoe Hare Cycle.” Ecological Monographs 68 (3): 371–94. Bowman, Jeff, Justina C Ray, Audrey J Magoun, Devin S Johnson, and F Neil Dawson. 2010.

“Roads , Logging , and the Large-Mammal Community of an Eastern Canadian Boreal Forest.” Canadian Journal of Zoology 88: 454–67. doi:10.1139/Z10-019.

Boyce, Mark S., Chris J. Johnson, Evelyn H. Merrill, Scott E. Nielsen, Erling J. Solberg, and Bram van Moorter. 2016. “Can Habitat Selection Predict Abundance?” Journal of Animal Ecology 85 (1): 11–20. doi:10.1111/1365-2656.12359.

Boyce, Mark S, Pierre R Vernier, Scott E Nielsen, and Fiona K A Schmiegelow. 2002. “Evaluating Resource Selection Functions.” Ecological Modelling 157: 281–300.

https://ac.els- cdn.com/S0304380002002004/1-s2.0-S0304380002002004-main.pdf?_tid=c88e57fe-6022-4205-b559-969ced8be0cc&acdnat=1527631596_dd1a57432db48c799e612363a7f51949. Brodeur, R. D., C. L. Suchman, D. C. Reese, T. W. Miller, and E. A. Daly. 2008. “Spatial Overlap

(20)

and Trophic Interactions between Pelagic Fish and Large Jellyfish in the Northern California Current.” Marine Biology 154 (4): 649–59. doi:10.1007/s00227-008-0958-3.

Brodie, Jedediah F., and Eric Post. 2010. “Nonlinear Responses of Wolverine Populations to Declining Winter Snowpack.” Population Ecology 52 (2): 279–87. doi:10.1007/s10144-009-0189-6.

Brown, Joel S. 1999. “Vigilance , Patch Use and Habitat Selection : Foraging under Predation Risk.” Evolutionary Ecology Research 1: 49–71.

Burgar, Joanna M., A. Cole Burton, and Jason T. Fisher. 2018. “The Importance of Considering Multiple Interacting Species for Conservation of Species-at-Risk.” Conservation Biology. doi:10.1111/cobi.13233.

Butchart, Stuart, Matt Walpole, Ben Collen, Arco van Strien, Jorn P. W. Scharlemann, and Et Al. 2010. “Global Biodiversity : Indicators of Recent Declines.” Science 328 (May): 1164–69. doi:10.1126/science.1187512.

Casanovas, Jorge G, Joan Barrull, Isabel Mate, Juan M Zorrilla, Jordi Ruiz-Olmo, Joaquimgosà Lbez, and Miquel Salicruhaping. 2012. “Shaping Carnivore Communities by Predator Control:

Competitor Release Revisited.” Ecol Res 27: 603–14.

Chesson, Peter. 1985. “Coexistence of Competitors in Spatially and Temporally Varying

Environments: A Look at the Combined Effects of Different Sorts of Variability.” Theoretical Population Biology 28 (3): 263–87. doi:10.1016/0040-5809(85)90030-9.

———. 2000. “General Theory of Competitive Coexistence in Spatially-Varying Environments.” Theoretical Population Biology 58: 211–37.

Connell, Joseph H. 1961. “The Influence of Interspecific Competition and Other Factors on the Distribution of the Barnacle Chthamalus Stellatus.” Source: Ecology 42 (4): 710–23.

(21)

Copeland, J. P., K. S. McKelvey, K. B. Aubry, A. Landa, J. Persson, R. M. Inman, J. Krebs, et al. 2010. “The Bioclimatic Envelope of the Wolverine ( Gulo Gulo ): Do Climatic Constraints Limit Its Geographic Distribution?” Canadian Journal of Zoology 88 (3): 233–46. doi:10.1139/Z09-136. Courbin, N., D. Fortin, C. Dussault, and R. Courtois. 2014. “Logging-Induced Changes in Habitat

Network Connectivity Shape Behavioral Interactions in the Wolf-Caribou-Moose System.” Ecological Monographs 84 (2): 265–85. doi:10.1890/12-2118.1.

Courtois, R, J.-P. Ouellet, L Breton, A Gingras, and C Dussault. 2007. “Effects of Forest Disturbance on Density, Space Use, and Mortality of Woodland Caribou.” Ecoscience 14 (4): 491–98. doi:10.2980/1195-6860(2007)14[491:eofdod]2.0.co;2.

Creel, Scott, and David Christianson. 2008. “Relationships between Direct Predation and Risk Effects.” Trends in Ecology and Evolution 23 (4): 194–201. doi:10.1016/j.tree.2007.12.004. Creel, Scott, David Christianson, Stewart Liley, and John A. Winnie. 2007. “Predation Risk Affects

Reproductive Physiology and Demography of Elk.” Science 315 (5814): 960. doi:10.1126/science.1135918.

Creel, Scott, John Winnie, Bruce Maxwell, Ken Hamlin, and Michael Creel. 2005. “Elk Alter Habitat Selection As an Antipredator Response To Wolves.” Ecology 86 (12): 3387–97.

Cristescu, Bogdan, Gordon B. Stenhouse, and Mark S. Boyce. 2014. “Grizzly Bear Ungulate Consumption and the Relevance of Prey Size to Caching and Meat Sharing.” Animal Behaviour 92. Elsevier Ltd: 133–42. doi:10.1016/j.anbehav.2014.03.020.

DeCesare, Nicholas J. 2012. “Separating Spatial Search and Efficiency Rates as Components of Predation Risk.” Proceedings of the Royal Society B: Biological Sciences 279 (1747): 4626–33. doi:10.1098/rspb.2012.1698.

Decesare, Nicholas J, Mark Hebblewhite, Fiona Schmiegelow, David Hervieux, Gregory J. McDermid, Lalenia Neufeld, Mark Bradley, et al. 2012. “Transcending Scale Dependece in

(22)

Identifying Habitat with Resource Selection Functions.” Ecology 22 (4): 1068–83. doi:10.1890/11-1610.1.

DeMars, Craig A. 2015. “Calving Behavior of Boreal Caribou in a Multi-Predator, Multi-Use Landscape.” University of Alberta.

DeMars, Craig A., Marie Auger-M Eth E, Ulrike E Schlagel, and Stan Boutin. 2013. “Inferring Parturition and Neonate Survival from Movement Patterns of Female Ungulates: A Case Study Using Woodland Caribou.” Ecology and Evolution. doi:10.1002/ece3.785.

DeMars, Craig A., and Stan Boutin. 2017. “Nowhere to Hide: Effects of Linear Features on

Predator–Prey Dynamics in a Large Mammal System.” Journal of Animal Ecology 87 (1): 274–84. doi:10.1111/1365-2656.12760.

Dickie, Melanie, Robert Serrouya, R Scott Mcnay, and Stan Boutin. 2017. “Faster and Farther : Wolf Movement on Linear Features and Implications for Hunting Behaviour.” Journal of Applied Ecology 54: 253–63. doi:10.1111/1365-2664.12732.

Dorresteijn, Ine, Jannik Schultner, Dale G Nimmo, Joern Fischer, Jan Hanspach, Tobias

Kuemmerle, Laura Kehoe, and Euan G Ritchie. 2015. “Incorporating Anthropogenic Effects into Trophic Ecology: Predator– Prey Interactions in a Human-Dominated Landscape.” Proc. R. Soc. B 282: 20151602. doi:10.1098/rspb.2015.1602.

Dunning, John B, Brent J Danielson, and H Ronald Pulliam. 1992. “Ecological Processes That Affect Populations in Complex Landscapes.” Oikos 65 (1): 169–75. doi:Doi 10.2307/3544901. Dussault, Christian, Véronique Pinard, pierre Ouellet, Réhaume Courtois, Daniel Fortin,

Jean-pierre Ouellet, Christian Dussault, and Daniel Fortin. 2012. “Avoidance of Roads and Selection for Recent Cutovers by Threatened Caribou : Fitness-Rewarding or Maladaptive Behaviour.” Proc. R. Soc. B 279: 4481–88. doi:10.1098/rspb.2012.1700.

(23)

Development by Woodland Caribou.” The Journal of Wildlife Management 65 (3): 531–42. Eggers, Sönke, Michael Griesser, Magdalena Nystrand, and Jan Ekman. 2006. “Predation Risk

Induces Changes in Nest-Site Selection and Clutch Size in the Siberian Jay.” Proceedings. Biological Sciences / The Royal Society 273 (1587): 701–6. doi:10.1098/rspb.2005.3373.

Elbroch, L Mark, Heiko U Wittmer, and Martin Krkosek. 2013. “Nuisance Ecology: Do Scavenging Condors Exact Foraging Costs on Pumas in Patagonia?” PLoS ONE 8 (1).

doi:10.1371/journal.pone.0053595.

Elith, Jane, Catherine H Graham, Robert P Anderson, Miroslav Dudík, Simon Ferrier, Antoine Guisan, Robert J Hijmans, et al. 2006. “Novel Methods Improve Prediction of Species’ Distributions from Occurrence Data.” Ecography 29: 129–51.

Elith, Jane, John R Leathwick, Jane Elith1, and John R Leathwick2. 2009. “Species Distribution Models: Ecological Explanation and Prediction Across Space.” Source: Annual Review of Ecology, Evolution, and Systematics Annu. Rev. Ecol. Evol. Syst 40 (40). doi:10.1146/annurev.ecolsys.l. Engler, R, A Guisan, and L Rechsteiner. 2004. “An Improved Approach for Predicting the

Distribution of Rare and Endangered Species from Occurrence and Pseudo-Absence Data.” Journal of Applied Ecology 41 (2): 263–74. doi:10.1111/j.0021-8901.2004.00881.x.

Environment Canada. 2012. “Recovery Strategy for the Woodland Caribou (Rangifer Tarandus Caribou), Boreal Population in Canada.” Ottawa.

Erb, Peter L, William J Mcshea, and Robert P Guralnick. 2012. “Anthropogenic Influences on Macro-Level Mammal Occupancy in the Appalachian Trail Corridor.” PLoS ONE 7 (8). doi:10.1371/journal.pone.0042574.

Fahrig, Lenore. 2003. “Effects of Habitat Fragmentation on Biodiversity.” Annu. Rev. Ecol. Evol. Syst 34: 487–515. doi:10.1146/annurev.ecolsys.34.011802.132419.

(24)

“Background Level of Risk and the Survival of Predator-Naive Prey: Can Neophobia Compensate for Predator Naivety in Juvenile Coral Reef Fishes?” Proc. R. Soc. B. 282 (20142197). doi:10.1098/rspb.2014.2197.

Festa-Bianchet, M., J.C. Ray, S. Boutin, S.D. Côté, and A. Gunn. 2011. “Conservation of Caribou (Rangifer Tarandus) in Canada: An Uncertain Future.” Canadian Journal of Zoology 89 (5): 419– 34. doi:10.1139/z11-025.

Festa-Bianchet, M. 1988. “Seasonal Range Selection in Bighorn Sheep: Conflicts between Forage Quality, Forage Quantity, and Predator Avoidance.” Oecologia 75: 580–86.

Finnegan, Laura, Karine E. Pigeon, Jerome Cranston, Mark Hebblewhite, Marco Musiani, Lalenia Neufeld, Fiona Schmiegelow, Julie Duval, and Gordon B. Stenhouse. 2018. “Natural

Regeneration on Seismic Lines Influences Movement Behaviour of Wolves and Grizzly Bears.” PLoS ONE 13 (4). doi:10.1371/journal.pone.0195480.

Fisher, Jason T., Brad Anholt, Steve Bradbury, Matthew Wheatley, and John P Volpe. 2012. “Spatial Segregation of Sympatric Marten and Fishers: The Influence of Landscapes and Species-Scapes.” Ecography 35: 001–009. doi:10.1111/j.1600-0587.2012.07556.x.

Fisher, Jason T., Brad Anholt, and John P. Volpe. 2011. “Body Mass Explains Characteristic Scales of Habitat Selection in Terrestrial Mammals.” Ecology and Evolution 1 (4): 517–28.

doi:10.1002/ece3.45.

Fisher, Jason T., S. Bradbury, B. Anholt, L. Nolan, L. Roy, J. P. Volpe, and M. Wheatley. 2013. “Wolverines (Gulo Gulo Luscus) on the Rocky Mountain Slopes : Natural Heterogeneity and Landscape Alteration as Predictors of Distribution.” Research Press 91 (August): 706–16. doi:10.1139/cjz-2013-0022.

Fisher, Jason T., and Steve Bradbury. 2014. “A Multi-Method Hierarchical Modeling Approach to Quantifying Bias in Occupancy from Noninvasive Genetic Tagging Studies.” Journal of Wildlife

(25)

Management 78 (6): 1087–95. doi:10.1002/jwmg.750.

Fisher, Jason T., and Cole A. Burton. 2018. “Wildlife Winners and Losers in an Oil Sands Landscape.” Frontiers in Ecology and the EnvironmentI. doi:10.1002/fee.1807.

Fisher, Jason T., Chris Pasztor, Amanda Wilson, John P. Volpe, and Bradley R. Anholt. 2014. “Recolonizing Sea Otters Spatially Segregate from Pinnipeds on the Canadian Pacific Coastline: The Implications of Segregation for Species Conservation.” Biological Conservation 177. Elsevier Ltd: 148–55. doi:10.1016/j.biocon.2014.06.025.

Fisher, Jason T., Matthew Wheatley, and Darryl Mackenzie. 2014. “Spatial Patterns of Breeding Success of Grizzly Bears Derived from Hierarchical Multistate Models.” Conservation Biology 28 (5): 1249–59. doi:10.1111/cobi.12302.

Fisher, Jason T., and Lisa Wilkinson. 2005. “The Response of Mammals to Forest Fire and Timber Harvest in the North American Boreal Forest.” Mammal Rev 35 (1): 51–81.

http://www.jasontfisher.ca/uploads/6/1/0/0/61006329/fisherandwilkinson2005.pdf. Flagel, David G, Gary E Belovsky, Michael J Cramer, Dean E Beyer, and Katie E Robertson. 2016.

“Fear and Loathing in a Great Lakes Forest: Cascading Effects of Competition between Wolves and Coyotes.” Journal of Mammalogy, 1–8. doi:10.1093/jmammal/gyw162.

Fretwell, Stephen DeWitt, and Henry L Jr Lucas. 1970. “On Territorial Behavior and Other Factors Influencing Habitat Distribution in Birds I. Theoretical Development.” Acta Biotheoretica 19: 16–36. doi:10.1007/BF01601953.

Frey, Sandra. 2018. “Evaluating the Impacts of Human-Mediated Disturbances on Species’ Behaviour and Interactions.” University of Victoria.

Furness, R. W. 1984. “Seabird Colony Distributions Suggest Competition for Food Supplies during the Breeding Season.” Nature 311: 655–56. doi:10.1038/311525a0.

(26)

a Model with Foraging Minnows.” Ecology 68 (8): 1856–62.

Godsoe, William, and Luke J Harmon. 2012. “How Do Species Interactions Affect Species Distribution Models ?” Ecography, no. 35: 811–20. doi:10.1111/j.1600-0587.2011.07103.x. Gompper, Matthew. 2002. “Top in the Carnivores Suburbs? Ecological by Colonization of

North-Eastern North America by Coyotes.” BioScience 52 (2): 185–90.

Griffin, Kathleen A., Mark Hebblewhite, Hugh S. Robinson, Peter Zager, Shannon M. Barber-Meyer, David Christianson, Scott Creel, et al. 2011. “Neonatal Mortality of Elk Driven by Climate, Predator Phenology and Predator Community Composition.” Journal of Animal Ecology 80 (6): 1246–57. doi:10.1111/j.1365-2656.2011.01856.x.

Guisan, Antoine, and Wilfried Thuiller. 2005. “Predicting Species Distribution: Offering More than Simple Habitat Models.” Ecology Letters 8 (9): 993–1009. doi:10.1111/j.1461-0248.2005.00792.x. Gustine, D D, and K L Parker. 2008. “Variation in the Seasonal Selection of Resources by

Woodland Caribou in Northern British Columbia.” Can. J. Zool. 86: 812–25. doi:10.1139/Z08-047.

Gustine, David D, Katherine L Parker, Roberta J Lay, P Michael, and Douglas C Heard. 2006. “Calf Survival of Woodland Caribou in a Multi-Predator Ecosystem Calf Survival of Woodland Caribou in a Multi-Predator Ecosystem.” Wildlife Monographs, no. 165: 1–32. doi:10.2193/0084-0173(2006)165.

Hebblewhite, M., E. H. Merrill, and T. L. McDonald. 2005. “Spatial Decomposition of Predation Risk Using Resource Selection Functions: An Example in a Wolf-Elk Predator-Prey System.” Oikos 111 (1): 101–11. doi:10.1111/j.0030-1299.2005.13858.x.

Hebblewhite, M, E H Merrill, T L Mcdonald, and Esa Ranta. 2005. “Spatial Decomposition of Predation Risk Using Resource Selection Functions: An Example in a Wolf-Elk Predator-Prey System.” Oikos 111 (1): 101–11.

(27)

Hebblewhite, Mark, and Evelyn H. Merrill. 2007. “Multiscale Wolf Predation Risk for Elk: Does Migration Reduce Risk?” Oecologia 152 (2): 377–87. doi:10.1007/s00442-007-0661-y.

Hebblewhite, Mark, Clifford A White, Clifford G Nietvelt, John A Mckenzie, Tomas E Hurd, John M Fryxell, Suzanne E Bayley, and Paul C Paquet. 2005. “Human Activity Mediates a Trophic Cascade Caused by Wolves.” Ecology 86 (8): 2135–44.

Heim, Nicole A. 2015. “Complex Effects of Human-Impacted Landscapes on the Spatial Patterns of Mammalian Carnivores By.”

Heim, Nicole A., Jason T. Fisher, Anthony Clevenger, John Paczkowski, and John Volpe. 2017. “Cumulative Effects of Climate and Landscape Change Drive Spatial Distribution of Rocky Mountain Wolverine ( Gulo Gulo L.).” Ecology and Evolution, 1–12. doi:10.1002/ece3.3337. Hervieux, Dave, M Hebblewhite, N. J. DeCesare, M. Russell, K. Smith, and S. Robertson. 2013.

“Widespread Declines in Woodland Caribou (Rangifer Tarandus Caribou) Continue in Alberta.” Can. J. Zool. 91: 872–82.

Hervieux, Dave, Mark Hebblewhite, Dave Stepnisky, Michelle Bacon, and Stan Boutin. 2014. “Managing Wolves ( Canis Lupus ) to Recover Threatened Woodland Caribou ( Rangifer Tarandus Caribou ) in Alberta.” Canadian Journal of Zoology 92 (12): 1029–37. doi:10.1139/cjz-2014-0142.

Hody, James W., and Roland Kays. 2018. “Mapping the Expansion of Coyotes (Canis Latrans) across North and Central America.” ZooKeys 759: 81–97. doi:10.3897/zookeys.759.15149. Holt, Robert D, and Gary A Polis. 1997. “A Theoretical Framework for Intraguild Predation.” The

American Naturalist 149 (4): 745–64.

Huey, Raymond B, and Eric R Pianka. 1981. “Ecological Consequences of Foraging Mode.” Ecology 62 (4): 991–99.

(28)

Niche: Linking Reproductive Chronology, Caching, Competition, and Climate.” Journal of Mammalogy 93 (3): 634–44. doi:10.1644/11-MAMM-A-319.1.

Inman, Robert M., Mark L. Packila, Kristine H. Inman, Anthony J. McCue, Gary C. White, Jens Persson, Bryan C. Aber, et al. 2012. “Spatial Ecology of Wolverines at the Southern Periphery of Distribution.” Journal of Wildlife Management 76 (4): 778–92. doi:10.1002/jwmg.289.

James, Adam R. C., and A. Kari Stuart-Smith. 2016. “Distribution of Caribou and Wolves in Relation to Linear Corridors.” The Journal of Wildlife Management 64 (1): 154–59.

Johnson, Chris J., Libby P W Ehlers, and Dale R. Seip. 2015. “Witnessing Extinction - Cumulative Impacts across Landscapes and the Future Loss of an Evolutionarily Significant Unit of Woodland Caribou in Canada.” Biological Conservation 186. Elsevier Ltd: 176–86.

doi:10.1016/j.biocon.2015.03.012.

Johnson, D W, and A Dunk. 2018. “A Large-Scale Study of Competition of Two Temperate Reef Fishes: Temperature, Functional Diversity, and Regional Differences in Dynamics.” Marine Ecology Progress Series 593: 97–109. doi:10.3354/meps12472.

Johnson, H E, S W Breck, S Baruch-Mordo, D L Lewis, C W Lackey, K R Wilson, J Broderick, J S Mao, and J P Beckmann. 2015. “Shifting Perceptions of Risk and Reward: Dynamic Selection for Human Development by Black Bears in the Western United States.” Biological Conservation 187: 164–72. doi:10.1016/j.biocon.2015.04.014.

Knopff, Aliah Adams, Kyle H. Knopff, Mark S. Boyce, and Colleen Cassady St. Clair. 2014.

“Flexible Habitat Selection by Cougars in Response to Anthropogenic Development.” Biological Conservation 178. Elsevier Ltd: 136–45. doi:10.1016/j.biocon.2014.07.017.

Kuijper, D P J, E Sahlén, B Elmhagen, S Chamaillé-Jammes, H Sand, K Lone, and J P G M Cromsigt. 2016. “Paws without Claws? Ecological Effects of Large Carnivores in

(29)

Laliberte, Andrea S., and William J. Ripple. 2004. “Range Contractions of North American Carnivore and Ungulates.” BioScience 54 (2): 123–38. doi:10.1641/0006-3568(2004)054. Lamb, Clayton T, Garth Mowat, Bruce N Mclellan, Scott E Nielsen, and Stan Boutin. 2017.

“Forbidden Fruit : Human Settlement and Abundant Fruit Create an Ecological Trap for an Apex Omnivore.” Journal of Animal Ecology 86: 55–65. doi:10.1111/1365-2656.12589.

Latham, A. David M., M. C. Latham, and M. S. Boyce. 2011. “Habitat Selection and Spatial

Relationships of Black Bears (Ursus Americanus) with Woodland Caribou (Rangifer Tarandus Caribou) in Northeastern Alberta.” Canadian Journal of Zoology 89: 267–77. doi:10.1139/Z10-115. Latham, A. David M., M. Cecilia Latham, Mark S. Boyce, and Stan Boutin. 2011. “Movement

Responses by Wolves to Industrial Linear Features and Their Effect on Woodland Caribou in Northeastern Alberta.” Ecological Applications 21 (8): 2854–65. doi:10.1890/11-0666.1.

———. 2013. “Spatial Relationships of Sympatric Wolves ( Canis Lupus ) and Coyotes ( C .

Latrans ) with Woodland Caribou ( Rangifer Tarandus Caribou ) during the Calving Season in a Human-Modified Boreal Landscape.” Wildlife Research, no. May 2013. doi:10.1071/WR12184. Latham, A. David M., M. Cecilia Latham, Kyle H. Knopff, Mark Hebblewhite, and Stan Boutin.

2013. “Wolves, White-Tailed Deer, and Beaver: Implications of Seasonal Prey Switching for Woodland Caribou Declines.” Ecography 36 (12): 1276–90.

doi:10.1111/j.1600-0587.2013.00035.x.

Latham, A. David M., M. Cecilia Latham, Nicole A. McCutchen, and Stan Boutin. 2011. “Invading White-Tailed Deer Change Wolf-Caribou Dynamics in Northeastern Alberta.” Journal of Wildlife Management 75 (1): 204–12. doi:10.1002/jwmg.28.

Latombe, Guillaume, Daniel Fortin, and Lael Parrott. 2014. “Spatio-Temporal Dynamics in the Response of Woodland Caribou and Moose to the Passage of Grey Wolf.” Journal of Animal Ecology 83 (1): 185–98. doi:10.1111/1365-2656.12108.

(30)

Leblond, Mathieu, Christian Dussault, Jean Pierre Ouellet, Martin Hugues St-Laurent, and Navinder Singh. 2016. “Caribou Avoiding Wolves Face Increased Predation by Bears: Caught between Scylla and Charybdis.” Journal of Applied Ecology 53 (4): 1078–87. doi:10.1111/1365-2664.12658. Leclerc, Martin, Christian Dussault, and Martin Hugues St-Laurent. 2014. “Behavioural Strategies

towards Human Disturbances Explain Individual Performance in Woodland Caribou.” Oecologia 176 (1): 297–306. doi:10.1007/s00442-014-3012-9.

Lei, Guangchun, and Ilkka Hanski. 1998. “Spatial Dynamics of Two Competing Specialist Parasitoids in a Host Metapopulation.” Journal of Animal Ecology 67 (3): 422–33. doi:10.1046/j.1365-2656.1998.00204.x.

Lele, Subhash R., Evelyn H. Merrill, Jonah Keim, and Mark S. Boyce. 2013. “Selection, Use, Choice and Occupancy: Clarifying Concepts in Resource Selection Studies.” Journal of Animal Ecology 82 (6): 1183–91. doi:10.1111/1365-2656.12141.

Lima, Steven L, and Lawrence M Dill. 1990. “Behavioral Decisions Made under the Risk of Predation: A Review and Prospectus.” Can. J. Zool. 68: 619–40.

Linnell, John D C, and Olav Strand. 2000. “Interference Interactions , Co-Existence and Conservation of Mammalian Carnivores,” 169–76.

Losier, Chrystel L., Serge Couturier, Martin Hugues St-Laurent, Pierre Drapeau, Claude Dussault, Tyler Rudolph, Vincent Brodeur, Jerod A. Merkle, and Daniel Fortin. 2015. “Adjustments in Habitat Selection to Changing Availability Induce Fitness Costs for a Threatened Ungulate.” Journal of Applied Ecology 52 (2): 496–504. doi:10.1111/1365-2664.12400.

Mackenzie, Darryl I., Larissa L. Bailey, and James D. Nichols. 2004. “Investigating Species Co-Occurrence Patterns When Species.” Journal of Animal Ecology 73: 546–55.

Macnearney, Doug, Karine Pigeon, Gordon Stenhouse, Wiebe Nijland, Nicholas C. Coops, and Laura Finnegan. 2016. “Heading for the Hills? Evaluating Spatial Distribution of Woodland

(31)

Caribou in Response to a Growing Anthropogenic Disturbance Footprint.” Ecology and Evolution 6 (18): 6484–6509. doi:10.1002/ece3.2362.

Manly, Bryan, Lyman McDonald, and Dana Thomas. 1993. Resource Selection By Animals. First. London: Chapman & Hall.

Massé, Ariane, and Steeve D. Coté. 2009. “Habitat Selection of a Large Herbivore At High Density and Without Predation : Trade-Off Between Forage and Cover ?” Journal of Mammalogy 90 (4): 961–70. doi:10.1644/08-MAMM-A-148.1.

Mattisson, Jenny. 2011. “Interactions between Eurasian Lynx and Wolverines in the Reindeer Husbandry Area.” Swedish University of Agricultural Sciences.

Mattisson, Jenny, Henrik Andrén, Jens Persson, and Peter Segerström. 2011. “Influence of Intraguild Interactions on Resource Use by Wolverines and Eurasian Lynx.” Journal of Mammalogy 92 (6): 1321–30. doi:10.1644/11-MAMM-A-099.1.

Maxwell, Sean L., Richard A. Fuller, Thomas M. Brooks, and James E. M. Watson. 2016. “The Ravages of Guns, Nets and Bulldozers.” Nature 536 (August): 146–145. doi:10.1038/536143a. McDermid, G J, R J Hall, G A Sanchez-Azofeifa, S E Franklin, G B Stenhouse, T Kobliuk, and E F

Ledrew. 2009. “Remote Sensing and Forest Inventory for Wildlife Habitat Assessment.” Forest Ecology and Management 257: 2262–69. doi:10.1016/j.foreco.2009.03.005.

McGraw, James B., and Hal Caswell. 1996. “Estimation of Individual Fitness from Life-History Data.” The American Naturalist 147 (1): 47–64. doi:10.1086/285839.

McKay, Tracy, Ellinor Sahlén, Ole-Gunnar Støen, Jon E. Swenson, and Gordon B. Stenhouse. 2014. “Wellsite Selection by Grizzly Bears Ursus Arctos in West—Central Alberta.” Wildlife Biology 20 (5): 310–19. doi:10.2981/wlb.00046.

McKenzie, Hannah W., Evelyn H. Merrill, Raymond J. Spiteri, and Mark a. Lewis. 2012. “How Linear Features Alter Predator Movement and the Functional Response.” Interface Focus 2 (2):

(32)

205–16. doi:10.1098/rsfs.2011.0086.

McLoughlin, Philip D., Jesse S. Dunford, and Stan Boutin. 2005. “Relating Predation Mortality to Broad-Scale Habitat Selection.” Journal of Animal Ecology 74 (4): 701–7. doi:10.1111/j.1365-2656.2005.00967.x.

McLoughlin, Philip D., E. Dzus, B. Wynes, and S. Boutin. 2016. “Declines in Populations of Woodland Caribou.” The Journal of Wildlife Management 67 (4): 755–61.

Metz, Matthew C, Cyril Milleret, Aimee Tallian, Camilla Wikenros, Douglas W Smith, Daniel R Stahler, Jonas Kindberg, Daniel R Macnulty, Petter Wabakken, and Jon E Swenson. 2017. “Competition between Apex Predators ? Brown Bears Decrease Wolf Kill Rate on Two Continents.”

Miller, Jennifer R B, Yadvendradev V Jhala, and Jyotirmay J Jena. 2016. “Livestock Losses and Hotspots of Attack from Tigers and Leopards in Kanha Tiger Reserve, Central India.” Reg Enviro Change 16: 17–29.

Morris, Douglas. 1987. “Ecological Scale and Habitat Use.” Ecology 68 (2): 362–69.

———. 1992. “Scales and Costs of Habitat Selection in Heterogeneous Landscapes.” Evolutionary Ecology 6 (5): 412–32. doi:10.1007/BF02270701.

———. 2003. “Toward an Ecological Synthesis: A Case for Habitat Selection.” Oecologia 136 (1): 1– 13. doi:10.1007/s00442-003-1241-4.

Morris, Lillian R, Kelly M Proffitt, and Jason K Blackburn. 2016. “Mapping Resource Selection Functions in Wildlife Studies: Concerns and Recommendations.”

doi:10.1016/j.apgeog.2016.09.025.

Muhly, Tyler B., Christina Semeniuk, Alessandro Massolo, Laura Hickman, and Marco Musiani. 2011. “Human Activity Helps Prey Win the Predator-Prey Space Race.” PLoS ONE 6 (3): 1–8. doi:10.1371/journal.pone.0017050.

(33)

Mumma, Matthew A., Michael P. Gillingham, Katherine L. Parker, Chris J. Johnson, and Megan Watters. 2018. “Predation Risk for Boreal Woodland Caribou in Human-Modified Landscapes: Evidence of Wolf Spatial Responses Independent of Apparent Competition.” Biological

Conservation 228 (September). Elsevier: 215–23. doi:10.1016/j.biocon.2018.09.015. Munro, R. H M., Scott E. Nielsen, M. H. Price, G. B. Stenhouse, and Mark S. Boyce. 2006.

“Seasonal and Diel Patterns of Grizzly Bear Diet and Activity in West-Central Alberta.” Journal of Mammalogy 87 (6): 1112–21. doi:10.1644/05-MAMM-A-410R3.1.

Murrell, David J., and Richard Law. 2003. “Heteromyopia and the Spatial Coexistence of Similar Competitors.” Ecology Letters 6 (1): 48–59. doi:10.1046/j.1461-0248.2003.00397.x.

Nielsen, Scott E., Mark S. Boyce, and Gordon B. Stenhouse. 2004. “Grizzly Bears and Forestry: I. Selection of Clearcuts by Grizzly Bears in West-Central Alberta, Canada.” Forest Ecology and Management 199 (1): 51–65. doi:10.1016/j.foreco.2004.04.014.

Nijland, W, N C Coops, S E Nielsen, and G Stenhouse. 2015. “Integrating Optical Satellite Data and Airborne Laser Scanning in Habitat Classification for Wildlife Management.” International Journal of Applied Earth Observations and Geoinformation 38: 242–50. doi:10.1016/j.jag.2014.12.004. Nobert, B. R., S. Milligan, G. B. Stenhouse, and L. Finnegan. 2016. “Seeking Sanctuary: The

Neonatal Period among Central Mountain Caribou (Rangifer Tarandus Caribou).” Can. J. Zool. 94: 837–51. doi:10.2135/cropsci2015.10.0632.

Northrup, Joseph M., Justin Pitt, Tyler B. Muhly, Gordon B. Stenhouse, Marco Musiani, and Mark S. Boyce. 2012. “Vehicle Traffic Shapes Grizzly Bear Behaviour on a Multiple-Use Landscape.” Journal of Applied Ecology 49 (5): 1159–67. doi:10.1111/j.1365-2664.2012.02180.x.

Otto, Sarah P. 2018. “Adaptation, Speciation and Extinction in the Anthropocene.” Proc. R. Soc. B. 285: 20182047. doi:10.1098/rspb.2018.2047.

(34)

American Naturalist 153 (5): 492–508.

Pasher, Jon, Evan Seed, and Jason Duffe. 2013. “Development of Boreal Ecosystem Anthropogenic Disturbance Layers for Canada Based on 2008 to 2010 Landsat Imagery Development of Boreal Ecosystem Anthropogenic Disturbance Layers for Canada Based on 2008 to 2010 Landsat Imagery.” Canadian Journal of Remote Sensing 39 (1): 42–58. doi:10.5589/m13-007. Persson, Jens, Per Wedholm, and Peter Segerström. 2010. “Space Use and Territoriality of

Wolverines (Gulo Gulo) in Northern Scandinavia.” European Journal of Wildlife Research 56 (1): 49–57. doi:10.1007/s10344-009-0290-3.

Pickell, Paul D, David W Andison, and Nicholas C Coops. 2013. “Characterizations of

Anthropogenic Disturbance Patterns in the Mixedwood Boreal Forest of Alberta, Canada.” Forest Ecology and Management 304: 243–53. doi:10.1016/j.foreco.2013.04.031.

Pickell, Paul D, David W Andison, Nicholas C Coops, Sarah E Gergel, and Peter L Marshall. 2015. “The Spatial Patterns of Anthropogenic Disturbance in the Western Canadian Boreal Forest Following Oil and Gas Development.” Can. J. For. Res. 45: 732–43. doi:10.1139/cjfr-2014-0546.

Pinard, Véronique, Christian Dussault, Jean Pierre Ouellet, Daniel Fortin, and Réhaume Courtois. 2012. “Calving Rate, Calf Survival Rate, and Habitat Selection of Forest-Dwelling Caribou in a Highly Managed Landscape.” Journal of Wildlife Management 76 (1): 189–99.

doi:10.1002/jwmg.217.

Polis, Gary A, Christopher A Myers, and Robert D Holt. 1989. “The Ecology and Evolution of Intraguild Predation: Potential Competitors That Eat Each Other.” Annu. Rev. Ecol. Syst 20: 297–330.

Pulliam, Ronald H, and Brent J Danielson. 1991. “Sources, Sinks, and Habitat Selection: A Landscape Perspective on Population Dynamics.” The American Naturalist 137: 50–66.

(35)

Pulliam, Ronald H, John B Dunning, and Jianguo Liu. 1992. “Population Dynamics in Complex Landscapes a Case Study.” Ecological Applications 2: 165–77. doi:1868-7083-4-20

[pii]\r10.1186/1868-7083-4-20.

Richmond, Orien M W, James E. Hines, and Steven R. Beissinger. 2010. “Two-Species Occupancy Models: A New Parameterization Applied to Co-Occurrence of Secretive Rails.” Ecological Applications 20 (7): 2036–46. doi:10.1890/09-0470.1.

Riley, Shawn J, Stephen D DeGloria, and Robert Elliot. 1999. “A Terrain Ruggedness Index That Qauntifies Topographic Heterogeneity.” Intermountain Journal of Sciences 5 (1–4): 23–27. doi:citeulike-article-id:8858430.

Ripple, William J, and Robert L Beschta. 2006. “Linking a Cougar Decline, Trophic Cascade, and Catastrophic Regime Shift in Zion National Park.” Biological Conservation 133: 397–408. doi:10.1016/j.biocon.2006.07.002.

Ripple, William J, Thomas M Newsome, Christopher Wolf, Rodolfo Dirzo, Kristoffer T Everatt, Mauro Galetti, Matt W Hayward, et al. 2015. “Collapse of the World’s Largest Herbivores.” Ecology, 1–12. doi:10.1126/sciadv.1400103.

Rosenzweig, Michael L. 1981. “A Theory of Habitat Selection.” Ecology 62 (2): 327–35.

Saher, D Joanne. 2005. “Woodland Caribou Habitat Selection during Winter and along Migratory Routes in West-Central Alberta.” University of Alberta. doi:10.16953/deusbed.74839.

Schuette, Paul, Aaron P. Wagner, Meredith E. Wagner, and Scott Creel. 2013. “Occupancy Patterns and Niche Partitioning within a Diverse Carnivore Community Exposed to Anthropogenic Pressures.” Biological Conservation 158: 301–12. doi:10.1016/j.biocon.2012.08.008.

Scrafford, Matthew A., and Mark S. Boyce. 2018. “Temporal Patterns of Wolverine (Gulo Gulo Luscus) Foraging in the Boreal Forest.” Journal of Mammalogy 99 (3): 693–701.

(36)

Scrafford, Matthew A, Tal Avgar, Bill Abercrombie, Jesse Tigner, and Mark S Boyce. 2017. “Wolverine Habitat Selection in Response to Anthropogenic Disturbance in the Western Canadian Boreal Forest.” Forest Ecology and Management 395. Elsevier B.V.: 27–36.

doi:10.1016/j.foreco.2017.03.029.

Seip, Dale R. 1992. “Factors Limiting Woodland Caribou Populations and Their Interrelationships with Wolves and Moose in Southeastern British Columbia.” Canadian Journal of Zoology 70 (8): 1494–1503. doi:10.1139/z92-206.

Sheriff, Michael J., Charles J. Krebs, and Rudy Boonstra. 2009. “The Sensitive Hare: Sublethal Effects of Predator Stress on Reproduction in Snowshoe Hares.” Journal of Animal Ecology 78 (6): 1249–58. doi:10.1111/j.1365-2656.2009.01552.x.

Sih, Andrew, Maud C O Ferrari, and David J. Harris. 2011. “Evolution and Behavioural Responses to Human-Induced Rapid Environmental Change.” Evolutionary Applications 4 (2): 367–87. doi:10.1111/j.1752-4571.2010.00166.x.

Stachowics, John J. 2001. “Mutualism, Facilitation, and the Structure of Ecological Communities.” BioScience 51 (3): 235–46.

Stewart, Benjamin P., Trisalyn A. Nelson, Michael A. Wulder, Scott E. Nielsen, and Gordon Stenhouse. 2012. “Impact of Disturbance Characteristics and Age on Grizzly Bear Habitat Selection.” Applied Geography 34. Elsevier Ltd: 614–25. doi:10.1016/j.apgeog.2012.03.001. Stewart, Frances E C, Nicole A. Heim, Anthony P. Clevenger, John Paczkowski, John P. Volpe, and

Jason T. Fisher. 2016. “Wolverine Behavior Varies Spatially with Anthropogenic Footprint: Implications for Conservation and Inferences about Declines.” Ecology and Evolution 6 (5): 1493–1503. doi:10.1002/ece3.1921.

Street, Garrett M., Lucas M. Vander Vennen, Tal Avgar, Anna Mosser, Morgan L. Anderson, Arthur R. Rodgers, and John M. Fryxell. 2015. “Habitat Selection Following Recent Disturbance:

(37)

Model Transferability with Implications for Management and Conservation of Moose ( Alces Alces ).” Canadian Journal of Zoology 93 (11): 813–21. doi:10.1139/cjz-2015-0005.

Sunarto, S, M J Kelly, K Parakkasi, and M B Hutajulu. 2015. “Cat Coexistence in Central Sumatra : Ecological Characteristics , Spatial and Temporal Overlap , and Implications for Management” 296: 104–15. doi:10.1111/jzo.12218.

Tigner, Jesse, Erin M. Bayne, and Stan Boutin. 2014. “Black Bear Use of Seismic Lines in Northern Canada.” Journal of Wildlife Management 78 (2): 282–92. doi:10.1002/jwmg.664.

Toews, Mary, Francis Juanes, and A. Cole Burton. 2018. “Mammal Responses to the Human Footprint Vary across Species and Stressors.” Journal of Environmental Management 217 (July): 690–99. doi:10.1016/j.jenvman.2018.04.009.

Verdolin, Jennifer L. 2006. “Meta-Analysis of Foraging and Predation Risk Trade-Offs in Terrestrial Systems.” Behavioral Ecology and Sociobiology 60 (4): 457–64. doi:10.1007/s00265-006-0172-6. Wang, Yiwei, Maximilian L Allen, and Christopher C Wilmers. 2015. “Mesopredator Spatial and

Temporal Responses to Large Predators and Human Development in the Santa Cruz Mountains of California.” Biological Conservation 190. Elsevier Ltd: 23–33.

doi:10.1016/j.biocon.2015.05.007.

Weldon, Aimee J, and Nick M Haddad. 2005. “The Effects of Patch Shape on Indigo Buntings: Evidence for an Ecological Trap.” Ecology 86 (6): 1422–31.

White, Craig G, Peter Zager, and Michael W Gratson. 2010. “Influence of Predator Harvest, Biological Factors, and Landscape on Elk Calf Survival in Idaho.” Journal of Wildlife Management 74 (3): 355–69. doi:10.2193/2007-506.

Whittington, Jesse, Mark Hebblewhite, Nicholas J. Decesare, Lalenia Neufeld, Mark Bradley, John Wilmshurst, and Marco Musiani. 2011. “Caribou Encounters with Wolves Increase near Roads and Trails: A Time-to-Event Approach.” Journal of Applied Ecology 48 (6): 1535–42.

(38)

doi:10.1111/j.1365-2664.2011.02043.x.

Wiens, John A, Nils Chr Stenseth, Beatrice Van Horne, and Rolf Anker Ims. 1993. “Ecological Mechanisms and Landscape Ecology.” Oikos 66 (3): 369–80. doi:10.2307/3544931. Wisz, Mary Susanne, Julien Pottier, W Daniel Kissling, Loïc Pellissier, Christian F Damgaard,

Carsten F Dormann, Mads C Forchhammer, et al. 2013. “The Role of Biotic Interactions in Shaping Distributions and Realised Assemblages of Species : Implications for Species Distribution Modelling” 88: 15–30. doi:10.1111/j.1469-185X.2012.00235.x.

Wittmer, Heiko U, Anthony R E Sinclair, and Bruce N Mclellan. 2005. “The Role of Predation in the Decline and Extirpation of Woodland Caribou.” Population Ecology 144: 257–67.

doi:10.1007/s00442-005-0055-y.

Wolf, Christopher, and William J. Ripple. 2017. “Range Contractions of the World’s Large Carnivores.” R. Soc. Open Sci 4: 170052.

Woodroffe, Rosie. 2000. “Predators and People: Using Human Densities to Interpret Declines of Large Carnivores.” Animal Conservation 3: 165–73.

Zager, Peter, and John Beecham. 2006. “The Role of American Black Bears and Brown Bears as Predators on Ungulates in North America.” Ursus 17 (2): 95–108. doi:10.2192/1537-6176(2006)17[95:TROABB]2.0.CO;2.

Zimmerman, Guthrie S., William S. LaHaye, and R. J. Gutiérrez. 2003. “Empirical Support for a Despotic Distribution in a California Spotted Owl Population.” Behavioral Ecology 14 (3): 433– 37. doi:10.1093/beheco/14.3.433.

Zimmermann, Niklaus E., and Felix Kienast. 1999. “Predictive Mapping of Alpine Grasslands in Switzerland: Species versus Community Approach.” Journal of Vegetation Science 10 (4): 469–82. doi:10.2307/3237182.

(39)

(40)

Chapter 2 Changes in the competitive dynamics between two predators in

heterogeneous environments through the introduction of

anthropogenic features on the landscape

Chapter 2 of thesis is in preparation for publication with co-authors Jason T. Fisher, John P. Volpe, Nicole Heim & John Paczkowski

2.1 Introduction

Biodiversity is declining globally, with terrestrial mammals being some of the most

vulnerable to environmental and landscape change (Butchart et al. 2010; Woodroffe 2000; Ripple et al. 2015; Wolf and Ripple 2017). Anthropogenic disturbances are a principle driver of their declines (Maxwell et al. 2016), but their impacts are often narrowly understood as physical changes to the landscape. Interspecific interactions vary across spatially heterogeneous landscapes as individuals spatially segregate to different habitat patches (Amarasekare 2003), so I would expect landscape changes to affect species distributions, and therefore, interspecific interactions. Differences in habitat selection between species typically allow for competitive coexistence on patchy landscapes (Chesson 2000), as species spatially and temporally segregate to maintain broad-scale coexistence (Armstrong and McGehee 1976; Chesson 1985; Amarasekare 2003). This means that changes in spatially heterogeneous environments and their resources should result in concurrent changes in interspecific interactions between competing species.

Interspecific interactions of diverse predator communities are predominantly the result of competition for shared resources—primarily prey species—while simultaneously constrained by the

(41)

minimiztion of predation risk (Holt and Polis 1997; Connell 1961). Competition for resources can be observed through interference competition wherein competitors directly prevent others from using a resource, or through exploitation competition wherein competitors locate and consume resources faster than others (Polis, Myers, and Holt 1989; Holt and Polis 1997; Palomares and Caro 1999). However, not all interactions between predators must have attributed fitness costs; facilitative interactions benefit at least one of the competitors, while harming neither (Stachowics 2001). These biotic interactions can drive broad-scale spatial and temporal segregation, and conversely, co-occurrence (e.g.: Linnell and Strand 2000; Sunarto et al. 2015; Fisher et al. 2012), depending on the costs of co-occurrence and poorer-quality resources (Festa-Bianchet 1988).

Many interspecific interactions are governed by access to resources; therefore, changes in those resources will variably affect strength and direction of competition and predation within diverse communities (e.g.: Wang, Allen, and Wilmers 2015; Berger 2007; Bowman et al. 2010). In particular, anthropogenic disturbances frequently alter the landscape and introduce novel resources (Maxwell et al. 2016), creating natural observational experiments in which I can test hypotheses regarding interspecific interactions and changing the landscape of competition. However, the effects of anthropogenic features on interspecific interactions and, ultimately, their effects on population fitness and species distributions, are rarely quantified across large landscapes and across multiple species due to logistical difficulties in assessing fitness across multiple species. As a proxy for interspecific interactions, I can instead examine co-occurrences of sympatric species across a gradient of conditions using a temporally-explicit approach, and assume that if two species with similar diets are occurring within the same fine-scale time period at the same location, they are likely competing for the same resource or facilitating acquisition of resources. Conversely, I can assume

The effects of landscape change on behaviour and risk perceptions of predator and prey communities on a heterogeneous landscape in Alberta and British Columbia, Canada

Supervisory Committee

Abstract

Table of Contents

List of Tables

List of Figures

Acknowledgements

Chapter 1

An introduction to habitat selection on a heterogeneous landscape,

the boreal forest and mountains of Alberta and British Columbia

1.1 Introduction

Literature Cited:

Chapter 2

Changes in the competitive dynamics between two predators in

heterogeneous environments through the introduction of

anthropogenic features on the landscape

2.1 Introduction