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Burton, Cole; Beirne, Christopher; Sun, Catherine; Granados, Alys; Procko, Michael; Chen, Cheng; Fennell, Mitchell; Constantinou, Alexia; Colton, Christopher; Tjaden-McClement, Katie; Fisher, Jason; Burgar, Joanna 2022-06-27 <p>Human disturbance directly affects animal populations but indirect effects of disturbance on species behaviors are less well understood. Camera traps provide an opportunity to investigate variation in animal behaviors across gradients of disturbance. We used camera trap data to test predictions about predator-sensitive behavior in three ungulate species (caribou Rangifer tarandus; white-tailed deer, Odocoileus virginianus; moose, Alces alces) across two boreal forest landscapes varying in disturbance. We quantified behavior as the number of camera trap photos per detection event and tested its relationship to predation risk between a landscape with greater industrial disturbance and predator abundance (Algar) and a “control” landscape with lower human and predator activity (Richardson). We also assessed the influence of predation risk and habitat on behavior across camera sites within the disturbed Algar landscape. We predicted that animals in areas with greater predation risk (more wolf activity, less cover) would travel faster and generate fewer photos per event, while animals in areas with less predation risk would linger (rest, forage), generating more photos per event. Consistent with predictions, caribou and moose had more photos per event in the landscape where predation risk was reduced. Within the disturbed landscape, no prey species showed a significant behavioral response to wolf activity, but the number of photos per event decreased for white-tailed deer with increasing line of sight (m) along seismic lines (i.e. decreasing visual cover), consistent with a predator-sensitive response. The presence of juveniles was associated with shorter behavioral events for caribou and moose, suggesting greater predator sensitivity for females with calves. Only moose demonstrated a positive association with vegetation productivity (NDVI), suggesting that for other species influences of forage availability were generally weaker than those from predation risk. Behavioral insights can be gleaned from camera trap surveys and provide information about animal responses to predation risk and the indirect impacts of human disturbances.</p> https://creativecommons.org/publicdomain/zero/1.0/
University of Victoria Dataverse Translation missing: fr.blacklight.search.logo
Borealis
Fisher, Jason; Murray, Sean; Barnas, Andrew; Smith, Rebecca 2024-07-12 Data on boreal mammal communities from Alberta, Canada, conducted for the joint Federal-Provincial Oil Sands Monitoring program (Terrestrial Biological Monitoring group) from 2021–2022. These data are from two different Landscape Units (LU3 and LU2). The data describes the sampling locations of remote infrared camera arrays, the locations of those arrays, the mammal data collected from the cameras, and the landscapes surrounding those arrays.
University of Victoria Dataverse Translation missing: fr.blacklight.search.logo
Borealis
Fisher, Jason; Murray, Jason; Barnas, Andrew 2022-03-30 Data on boreal mammal communities from Alberta, Canada, conducted for the joint Federal-Provincial Oil Sands Monitoring program (Terrestrial Biological Monitoring group). These data are from Landscape Unit 3. The data describes the sampling locations of remote infrared camera arrays, the locations of those arrays, the mammal data collected from the cameras, and the landscapes surrounding those arrays.
Dryad Translation missing: fr.blacklight.search.logo
Dryad
Fisher, Jason 2021-03-02 <p style="margin-bottom:13px;">1. Landscape change is a key driver of biodiversity declines due to habitat loss and fragmentation, but spatially shifting resources can also facilitate range expansion and invasion. Invasive populations are reproductively successful, and landscape change may buoy this success.</p> <p style="margin-bottom:13px;">2. We show how modelling the spatial structure of reproductive success can elucidate the mechanisms of range shifts and sustained invasions for mammalian species with attendant young. We use an example of white-tailed deer (deer; <i>Odocoileus virginianus</i>) expansion in the Nearctic boreal forest, a North American phenomenon implicated in severe declines of threatened woodland caribou (<i>Rangifer tarandus</i>).</p> <p style="margin-bottom:13px;">3. We hypothesized that deer reproductive success is linked to forage subsidies provided by extensive landscape change <i>via</i> resource extraction. We measured deer occurrence using data from 62 camera-traps in northern Alberta, Canada, over three years. We weighed support for multiple competing hypotheses about deer reproductive success using multi-state occupancy models and generalized linear models in an AIC-based model selection framework.</p> <p style="margin-bottom:13px;">4. Spatial patterns of reproductive success were best explained by features associated with petroleum exploration and extraction, which offer early seral vegetation resource subsidies. Effect sizes of anthropogenic features eclipsed natural heterogeneity by two orders of magnitude. We conclude that anthropogenic early seral forage subsidies support high springtime reproductive success, mitigating or exceeding winter losses, maintaining populations.</p> <p style="margin-bottom:13px;"><i>5. Synthesis and Applications</i>. Modelling spatial structuring in reproductive success can become a key goal of remote camera-based global networks, yielding ecological insights into mechanisms of invasion and range shifts to inform effective decision-making for global biodiversity conservation.</p>
University of Victoria Dataverse Translation missing: fr.blacklight.search.logo
Borealis
Fisher, Jason; Barnas, Andrew; Smith, Rebecca; Arthurs, Emerald; Dyck, Marissa; Braun, Megan 2024-07-12 Data on boreal mammal communities from Alberta, Canada, conducted for the joint Federal-Provincial Oil Sands Monitoring program (Terrestrial Biological Monitoring group) from 2022–2023. These data are from four different Landscape Units (LU1, LU13, LU15, and LU21). The data describes the sampling locations of remote infrared camera arrays, the locations of those arrays, the mammal data collected from the cameras, and the landscapes surrounding those arrays.
University of Victoria Dataverse Translation missing: fr.blacklight.search.logo
Borealis
Fisher, Jason; Ladle, Andrew; Boczkulak, Hannah; Boucher, Nicole; Boyce, Mark 2023-05-26 Increasing resource extraction and human activity are reshaping species’ spatial distributions in human-altered landscape and consequently impacting the dynamics of interspecific interactions, such as between predators and prey. To evaluate the effects of industrial features and human activity on the occurrence of wolves (Canis lupus), we deployed an array of 122 remote wildlife camera traps in Alberta's Rocky Mountains and foothills near Hinton, Canada in 2014. Using generalized linear models, we compared the occurrence frequency of wolves at camera sites to natural land cover, industrial disturbance (forestry and oil/gas exploration), human activity (motorized and non-motorized), and prey availability (moose, Alces alces; elk, Cervus canadensis; mule deer, Odocoileus hemionus; and white-tailed deer, Odocoileus virginianus). Industrial block features (well sites and cutblocks) and prey (elk and mule deer) availability interacted to influence wolf occurrences, but models including motorized and non-motorized human activity were not strongly supported. Wolves occurred infrequently at sites with high densities of well sites and cutblocks, except when elk or mule deer were frequently detected. Our results suggest that wolves risk using industrial block features when prey occur frequently to increase predation opportunities, but otherwise avoid them due to risk of human encounters. Effective management of wolves in anthropogenically-altered landscapes thus requires the simultaneous consideration of industrial block features and populations of elk and mule deer.
University of Victoria Dataverse Translation missing: fr.blacklight.search.logo
Borealis
Fisher, Jason; Barnas, Andrew; Murray, Sean 2022-03-29 Data on boreal mammal communities from Alberta, Canada, conducted for the joint Federal-Provincial Oil Sands Monitoring program (Terrestrial Biological Monitoring group). The data describes the sampling locations of remote infrared camera arrays, the locations of those arrays, the mammal data collected from the cameras, and the landscapes surrounding those arrays.

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