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Tardy O.,Laval University | Masse A.,Direction de la Biodiversite et des Maladies de la Faune | Pelletier F.,Universite de Sherbrooke | Fortin D.,Laval University

Isodar theory can be used to evaluate fitness consequences of density-dependent habitat selection by animals. A typical habitat isodar is a regression curve plotting competitor densities in two adjacent habitats when individual fitness is equal. Despite the increasing use of habitat isodars, their application remains largely limited to areas composed of pairs of adjacent habitats that are defined a priori. We developed a resampling method that uses data from wildlife surveys to build isodars in heterogeneous landscapes without having to predefine habitat types. The method consists in randomly placing blocks over the survey area and dividing those blocks in two adjacent sub-blocks of the same size. Animal abundance is then estimated within the two sub-blocks. This process is done 100 times. Different functional forms of isodars can be investigated by relating animal abundance and differences in habitat features between sub-blocks. We applied this method to abundance data of raccoons and striped skunks, two of the main hosts of rabies virus in North America. Habitat selection by raccoons and striped skunks depended on both conspecific abundance and the difference in landscape composition and structure between sub-blocks. When conspecific abundance was low, raccoons and striped skunks favored areas with relatively high proportions of forests and anthropogenic features, respectively. Under high conspecific abundance, however, both species preferred areas with rather large corn-forest edge densities and corn field proportions. Based on random sampling techniques, we provide a robust method that is applicable to a broad range of species, including medium- to large-sized mammals with high mobility. The method is sufficiently flexible to incorporate multiple environmental covariates that can reflect key requirements of the focal species. We thus illustrate how isodar theory can be used with wildlife surveys to assess density-dependent habitat selection over large geographic extents. © 2015 Tardy et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Source

Turgeon G.,Universite de Sherbrooke | Wal E.V.,Universite de Sherbrooke | Masse A.,Direction de la Biodiversite et des Maladies de la Faune | Pelletier F.,Universite de Sherbrooke
Canadian Journal of Zoology

Human-driven environmental changes affect behavior, morphology, life history, and population dynamics of wild species. Artificial food sources in anthropogenic environments benefit some species and may lead to faster somatic growth and larger body size, which affects survival and reproduction, thus contributing to a species’ success in modified environments. Using raccoons (Procyon lotor (L., 1758)) as a model, we documented age-specific body-mass pattern and evaluated the influence of human activities (human density, area with artificial food sources, edges of forested area bordering corn (Zea mays L.) fields) and weather (index of winter severity and mean annual precipitation) on body-mass variation at multiple spatial scales. The effect of human-driven changes on raccoon mass varied with age, sex, and spatial scale, suggesting that anthropogenic changes affect raccoons differentially according to gender and life stages. Human activity had consistently opposing effects between the sexes. Weather covariates represented >50% of the total variance in body mass explained by our models. Previous winter severity and mean annual precipitation affected body mass negatively and positively, respectively. Our results emphasize the importance of multiscale, sex- and age-specific analyses when studying influences of human activity on wildlife. © 2015, National Research Council of Canada.All rights reserved. Source

Tardy O.,Laval University | Masse A.,Direction de la Biodiversite et des Maladies de la Faune | Pelletier F.,Universite de Sherbrooke | Mainguy J.,Direction de la Biodiversite et des Maladies de la Faune | Fortin D.,Laval University

Spatio-temporal variations in conspecific density and resource availability are two of the main factors responsible for plasticity in habitat selection. Despite the need for habitat selection models that can accurately predict animal distribution given the plasticity in the selection process, no study has assessed the synergistic effects of these factors on habitat selection. We investigated density-dependent functional responses by raccoons (Procyon lotor) and striped skunks (Mephitis mephitis), two of the main hosts of the rabies virus in North America. We monitored 54 raccoons and 12 striped skunks with Global-Positioning- System collars in a landscape dominated by corn fields and forest patches. We built resource selection functions to evaluate if the selection of corn fields varied with conspecific density and corn field availability within 100% minimum convex polygons. Raccoons altered their selection of corn fields depending on both conspecific density and corn-forest edge density or corn field proportion. In areas of low corn-forest edge densities and a low corn field proportion, raccoons showed stronger selection for corn fields when few conspecifics were present. At high conspecific densities, the selection of corn fields was stronger in areas with high corn-forest edge densities and a low corn field proportion. For striped skunks, we did not detect any synergistic effect of density-dependence and functional responses. Unlike raccoons, striped skunks displayed a selection that was strongest for agricultural corridors. We show that functional responses in habitat selection can be density-dependent. In a context of infectious disease dynamics, modeling densitydependence in functional responses increases the ability to predict spatio-temporal variations in the distribution of reservoir species and thus, to delineate areas at high animal densities where the risk of disease outbreaks is relatively high. For example, the omission of density-dependence in functional responses underestimated the relative probability of raccoon occurrence in corn fields, while overestimating the relative probability of occurrence in anthropogenic areas and wetlands. Our study underscores the relevance of considering the complexity of habitat selection by all hosts of a zoonosis. Costeffective control and prevention programs used to limit disease spread can benefit from accounting for density-dependent functional responses of a multi-host disease system. © 2014 Tardy et al. Source

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