Recherche

Dryad Translation missing: fr.blacklight.search.logo
Data from: Space-use behavior of woodland caribou based on a cognitive movement model
Dryad
Avgar, Tal; Brown, Glen S.; Thompson, Ian; Rodgers, Art R.; Mosser, Anna; Fryxell, John M.; Patterson, Brent R.; Newmaster, Steven G.; Reid, Doug E. B.; Turetsky, Merritt; Hagens, Jevon S.; Reid, Douglas E. B.; Shuter, Jennifer; Baker, James A.; Kittle, Andrew M.; Mallon, Erin E.; McGreer, Madeleine T.; Street, Garrett M.; Turetsky, Merritt J. — 2016-01-20 1. 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. 2. 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. 3. 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.
Dryad Translation missing: fr.blacklight.search.logo
Data from: Diel movement patterns influence daily variation in wolf kill rates on moose
Dryad
Vander Vennen, Lucas M.; Patterson, Brent R.; Rodgers, Arthur R.; Moffatt, Scott; Anderson, Morgan L.; Fryxell, John M. — 2016-12-15 Variation in predation can have important consequences for predators and prey, but little is known about associated mechanisms. Diel interactions between predators and prey are commonly assumed to be influenced by movement speeds of both predators and prey individuals, sensu the ideal gas model, but the influencing factors of diel predation dynamics have yet to be empirically examined. In this study, we apply principles of the ideal gas model to predict diel variation in kill frequency of moose (Alces alces) by wolves (Canis lupus) in northern Ontario, Canada based on GPS radio-telemetry data combined with field verification of kills. We used GPS telemetry data from wolves and moose combined with a unique data set on the diel pattern of wolf kills to test whether predator movement rate, prey movement rate, and ambient light condition influence diel variation in kill rates of wolves on moose. Our results indicate that the kill rate between wolves and moose was principally related to the effective movement rate of predators and prey, as predicted by the ideal gas model. We found little evidence that light conditions had any effect on kill rates, but rather the majority of kill rate variation corresponded to wolf movement rate, which was over an order of magnitude higher than that of moose.
Dryad Translation missing: fr.blacklight.search.logo
Data from: Patchy distribution and low effective population size raise concern for an at-risk top predator
Dryad
Rutledge, Linda Y.; Desy, Glenn; Fryxell, John M.; Middel, Kevin; White, Bradley N.; Patterson, Brent R. — 2017-10-12 Aim: Understanding carnivore distribution is important for management decisions that aim to restore naturally-regulated ecosystems and preserve biodiversity. Eastern Wolves, a species at risk in Canada, are centralized in Algonquin Provincial Park and their ability to disperse and establish themselves elsewhere is limited by human-caused mortality associated with hunting, trapping, and vehicle collisions. Here, we refine our understanding of Eastern Wolf distribution and provide the first estimates of their effective population size. Location: Southern Ontario and Gatineau Quebec. Methods: We used noninvasive samples, as well as blood samples archived from other research projects, collected between 2010 – 2014 to generate autosomal microsatellite genotypes at 12 loci for 98 Canis individuals. We utilized Bayesian and multivariate clustering analyses to identify Eastern Wolves in regions that were previously unsampled. Both linkage disequilibrium and temporal approaches were used to estimate effective population size of Eastern Wolves. Results: Assignment tests identified 34 individuals as Eastern Wolves, primarily in or near two provincial parks: Killarney and Queen Elizabeth II Wildlands. Eastern Coyotes were identified in Bon Echo Provincial Park, Frontenac Provincial Park, and Gatineau Park, whereas many of the samples were admixed among the different Canis types. Effective population size (Ne) estimates ranged from 24.3 – 122.1 with a harmonic mean of 45.6. Main Conclusions: The identification of Eastern Wolves in the regions of Killarney and Queen Elizabeth II Wildlands Provincial Parks extends the range of Eastern Wolves north of the French River and southward into previously unidentified regions. The effective population size is low and raises concerns for long-term persistence of this threatened carnivore; values are dangerously close to critical values recommended for short-term persistence. These results provide important information for upcoming Eastern Wolf recovery plans associated with federal and provincial endangered species legislation.

Instructions pour la recherche cartographique

1.Activez le filtre cartographique en cliquant sur le bouton « Limiter à la zone sur la carte ».
2.Déplacez la carte pour afficher la zone qui vous intéresse. Maintenez la touche Maj enfoncée et cliquez pour encadrer une zone spécifique à agrandir sur la carte. Les résultats de la recherche changeront à mesure que vous déplacerez la carte.
3.Pour voir les détails d’un emplacement, vous pouvez cliquer soit sur un élément dans les résultats de recherche, soit sur l’épingle d’un emplacement sur la carte et sur le lien associé au titre.
Remarque : Les groupes servent à donner un aperçu visuel de l’emplacement des données. Puisqu’un maximum de 50 emplacements peut s’afficher sur la carte, il est possible que vous n’obteniez pas un portrait exact du nombre total de résultats de recherche.

(auteur : Fryxell, John M.)

Limiter par :

Effacer tout

au