Studies in parts of Europe, New Zealand, and North America indicate uptake of anticoagulant rodenticides (ARs) by predatory mammals to be widespread and common, with proximity to urban and agricultural areas being an important driver of exposure. Yet, little is known regarding the patterns and drivers of AR exposure in predatory mammals within more forest-dominated landscapes. Across the forest-dominated northeastern United States (US), a region spanning Pennsylvania to Maine, we tested livers from 597 fisher (Pekania pennanti) obtained from the legal harvest for 11 anticoagulant rodenticide compounds. We used kriging to determine potential hot zones (within or among states) and used regression models to test agricultural land use, developed landscapes, and protected areas as potential drivers of exposure patterns. We detected 8 AR compounds, with 78.6% of sampled individuals testing positive for ≥1 compound. The highest rate of exposure was observed in New Hampshire and Vermont at 93.3 and 100.0% and the lowest in Maine at 52.8%. The majority of individuals (55.3%) tested positive for 2-6 different compounds rather than a single compound (23.3%) or none (21.4%), indicating repeated and chronic levels of exposure among fisher. Spatial interpolation revealed a hot region of exposure spanning southern New Hampshire, Vermont, and southeastern New York. Regression models indicated the proportion of wildland-urban intermix (low density buildings within a largely forest-dominated landscape) as a consistent and strong predictor of AR exposure, with marginal and inconsistent relationships observed between AR exposure and the amount of agricultural land use, and with no apparent benefit conferred by protected areas in the region. Given that northeastern states support the highest rural human population density in the nation, with individual homes interspersed throughout a forested matrix, residential use of ARs is implicated as potentially the main driver of exposure for forest carnivores in this region. However, surveillance of a broader suite of species, and greater knowledge of AR use in commercial forestry operations, will be necessary to understand the generality of our observations.
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