Abstract
There is a growing awareness that ecological risk assessments (ERAs) could be improved if they made better use of ecological information. In particular, landscape features that determine the quality of wildlife habitat can have a profound influence on the estimated exposure to stressors incurred by animals when they occupy a particular area. Various approaches to characterizing the quality of habitat for a given species have existed for some time. These approaches fall into three generalized categories: (1) entirely qualitative as in suitable or unsuitable, (2) semiquantitative as in formalized habitat suitability index models, or (3) highly quantitative site-specific characterization of population demographic data such as matrix population models or multiple regression models. Such information can be used to generate spatially explicit estimates of exposure to chemicals or other environmental stressors, e.g., invasive species, physical perturbation, that take into account the magnitude of co-occurrence of the animals and stressors as they forage across a landscape. In this way, greater ecological realism is provided in the ERA and more informed management decisions can be attained.
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