Understanding risks to terrestrial wildlife species from exposure to chemicals in the environment requires knowledge of how species make habitat decisions and how subsequent exposure events occur. Heterogeneity of chemical distribution and of habitat quality can influence exposure. Previous studies in birds have shown that individually based, spatially explicit models can be useful in predicting exposure and risk; however, studies investigating these influences in small mammals with limited ranges have been lacking. Here we test a spatially explicit, individually based exposure model (Spatially Explicit Exposure Model [SEEM]) in which model predictions based on life history traits, habitat preferences, and varying soil Pb concentrations are used and compared to those with field‐collected blood or tissue Pb concentrations in small (e.g., Peromyscus, Blarina spp.) and medium‐sized mammalian species (e.g., Lepus spp.) at 3 Pb‐contaminated sites. These species were chosen because they were expected to be present in suitable habitat, and Pb was modeled when adequate tissue‐based toxicity thresholds were available. Oral exposure estimates from SEEM were compared with a traditional deterministic model and with field‐collected tissue Pb concentrations using ecological hazard quotients (EHQs) to normalize between oral and real‐time tissue Pb concentrations. Ecological hazard quotients at the 90% population effect level (for SEEM) and at the 95% upper confidence level (assuming a single Pb concentration with no consideration of habitat quality in the deterministic model) were compared with maximum EHQs developed from blood or tissue Pb concentrations. Deterministic estimates and SEEM were similar for small mammal species, yet slightly overpredicted risk compared to field tissue or blood Pb data. Estimates for hares (medium‐sized mammals) using SEEM provided more accurate predictions compared with field tissue data. These data suggest that spatially explicit models may be sensitive to grain size, given that small mammals experience the environment in limited spatial contexts, a scale at which habitat may not change significantly. Integr Environ Assess Manag 2021;17:259–272. Published 2020. This article is a US Government work and is in the public domain in the USA. KEY POINTS: Spatially explicit exposure models allows for improved estimates of exposure for wildlife using space and habitat preferences within a landscape.Improvement of risk estimates are somewhat dependent upon resolution of soil chemistry results and movement of small mammalian species.Exposure estimates improve with wide‐ranging species. [ABSTRACT FROM AUTHOR]
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