Resource selection addresses how individuals or populations choose the spatial environment in which they conduct activities, including where and when they forage, rest, or reproduce. The spatial-temporal area over which these activities take place defines the ecological habitat of an organism or population, and these models are therefore often applied in terms of habitat selection. Habitat selection models can assist in chemical risk assessments by examining spatial-temporal intersections of receptors and chemical contaminants in the environment. Inputs to such models can include a wide variety of environmental parameters, including behavioral data (e.g., home range size as gained by telemetry or direct observations), geospatial data (e.g., distance to water or distribution of dens or roosts), and foraging resource data (e.g., abundance of a preferred prey item). Using such data, habitat resource selection can be modeled with respect to exposure and/or effects deterministically, for example, by overlaying a discrete habitat area on an area of known contamination, or probabilistically across a landscape; or by using a Monte Carlo simulation to estimate likelihood of exposure and contaminant uptake weighted by probability of resource selection. The increasing availability of large geospatial data sets and the diversity of ways to integrate these data sets with toxicological response models provide growing opportunities to increase the accuracy of models to assess ecological risk in the framework of wildlife habitat selection.
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