Movement patterns offer a rich source of information on animal behaviour and the ecological significance of landscape attributes. This is especially useful for species occupying remote landscapes where direct behavioural observations are limited. In this study, we fit a mechanistic model of animal cognition and movement to GPS positional data of woodland caribou (Rangifer tarandus caribou; Gmelin 1788) collected over a wide range of ecological conditions. The model explicitly tracks individual animal informational state over space and time, with resulting parameter estimates that have direct cognitive and ecological meaning. Three biotic landscape attributes were hypothesized to motivate caribou movement: forage abundance (dietary digestible biomass), wolf (Canis lupus; Linnaeus, 1758) density and moose (Alces alces; Linnaeus, 1758) habitat. Wolves are the main predator of caribou in this system and moose are their primary prey. Resulting parameter estimates clearly indicated that forage abundance is an important driver of caribou movement patterns, with predator and moose avoidance often having a strong effect, but not for all individuals. From the cognitive perspective, our results support the notion that caribou rely on limited sensory inputs from their surroundings, as well as on long-term spatial memory, to make informed movement decisions. Our study demonstrates how sensory, memory and motion capacities may interact with ecological fitness covariates to influence movement decisions by free-ranging animals.
Summary1. Although local variation in territorial predator density is often correlated with habitat quality, the causal mechanism underlying this frequently observed association is poorly understood and could stem from facultative adjustment in either group size or territory size. 2. To test between these alternative hypotheses, we used a novel statistical framework to construct a winter population-level utilization distribution for wolves (Canis lupus) in northern Ontario, which we then linked to a suite of environmental variables to determine factors influencing wolf space use. Next, we compared habitat quality metrics emerging from this analysis as well as an independent measure of prey abundance, with pack size and territory size to investigate which hypothesis was most supported by the data. 3. We show that wolf space use patterns were concentrated near deciduous, mixed deciduous/ coniferous and disturbed forest stands favoured by moose (Alces alces), the predominant prey species in the diet of wolves in northern Ontario, and in proximity to linear corridors, including shorelines and road networks remaining from commercial forestry activities. 4. We then demonstrate that landscape metrics of wolf habitat quality -projected wolf use, probability of moose occupancy and proportion of preferred land cover classes -were inversely related to territory size but unrelated to pack size. 5. These results suggest that wolves in boreal ecosystems alter territory size, but not pack size, in response to local variation in habitat quality. This could be an adaptive strategy to balance trade-offs between territorial defence costs and energetic gains due to resource acquisition. That pack size was not responsive to habitat quality suggests that variation in group size is influenced by other factors such as intraspecific competition between wolf packs.
One of the most challenging tasks in wildlife conservation and management is to clarify how spatial variation in land cover due to anthropogenic disturbance influences wildlife demography and longterm viability. To evaluate this, we compared rates of survival and population growth by woodland caribou (Rangifer tarandus caribou) from 2 study sites in northern Ontario, Canada that differed in the degree of anthropogenic disturbance because of commercial logging and road development, resulting in differences in predation risk due to gray wolves (Canis lupus). We used an individual-based model for population viability analysis (PVA) that incorporated adaptive patterns of caribou movement in relation to predation risk and food availability to predict stochastic variation in rates of caribou survival. Field estimates of annual survival rates for adult female caribou in the unlogged (¯= x 0.90) and logged (¯= x 0.76) study sites recorded during 2010-2014 did not differ significantly (P > 0.05) from values predicted by the individual-based PVA model (unlogged:x = 0.87; logged:¯= x 0.79). Outcomes from the individual-based PVA model and a simpler stage-structured matrix model suggest that substantial differences in adult survival largely due to wolf predation are likely to lead to long-term decline of woodland caribou in the commercially logged landscape, whereas the unlogged landscape should be considerably more capable of sustaining caribou. Estimates of population growth rates (λ) for the 2010-2014 period differed little between the matrix model and the individual-based PVA model for the unlogged (matrix modelx = 1.01; individual-based modelx = 0.98) and logged landscape (matrix modelx = 0.88; individual-based modelx = 0.89). We applied the spatially explicit PVA model to assess the viability of woodland caribou across 14 woodland caribou ranges in Ontario. Outcomes of these simulations suggest that woodland caribou ranges that have experiencedThis is an open access article under the terms of the Creative Commons Attribution-NonCommercial License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes. significant levels of commercial forestry activities in the past had annual growth rates <0.89, whereas caribou ranges that had not experienced commercial forestry operations had population growth rates >0.96. These differences were strongly related to regional variation in wolf densities. Our results suggest that increased wolf predation risk due to anthropogenic disturbance is of sufficient magnitude to cause appreciable risk of population decline in woodland caribou in Ontario.
The ideal free distribution assumes that animals select habitats that are beneficial to their fitness. When the needs of dependent offspring differ from those of the parent, ideal habitat selection patterns could vary with the presence or absence of offspring. We test whether habitat selection depends on reproductive state due to top‐down or bottom‐up influences on the fitness of woodland caribou (Rangifer tarandus caribou), a threatened, wide‐ranging herbivore. We combined established methods of fitting resource and step selection functions derived from locations of collared animals in Ontario with newer techniques, including identifying calf status from video collar footage and seasonal habitat selection analysis through latent selection difference functions. We found that females with calves avoided predation risk and proximity to roads more strongly than females without calves within their seasonal ranges. At the local scale, females with calves avoided predation more strongly than females without calves. Females with calves increased predation avoidance but not selection for food availability upon calving, whereas females without calves increased selection for food availability across the same season. These behavioral responses suggest that habitat selection by woodland caribou is influenced by reproductive state, such that females with calves at heel use habitat selection to offset the increased vulnerability of their offspring to predation risk.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.