Abstract
AbstractAccurate estimates of demographic parameters are critical to the management of wildlife populations, including management programs focused on controlling the spread of zoonotic diseases. Rabies managers in the United States Department of Agriculture (USDA) have applied a simple raccoon (Procyon lotor) abundance index (RAI) based on cumulative catch of unique raccoons per unit area to determine vaccine‐bait distribution densities. This approach was designed to allow for both the collection of biological samples and to index raccoon abundance to determine bait densities for oral rabies programs. However, post‐baiting surveillance data indicate that, on average, only 30% of raccoons sampled have vaccine induced rabies antibody titers, suggesting that bait densities may not be well calibrated to raccoon densities. We trapped raccoons using both capture‐mark‐recapture (CMR) and the standard RAI to evaluate the accuracy of the current index‐based methodology for estimating raccoon density. We then developed a resource selection function from spatial data collected from radio‐collared raccoons to standardize trap placement within the existing RAI protocol, and evaluated the performance of this modified RAI approach relative to CMR for estimating raccoon population size. Both abundance and density estimates derived using the RAI consistently underestimated raccoon population sizes compared with CMR methods. Similarly, although the use of resource selection models to inform trap placement appeared to improve the accuracy of the RAI, the effectiveness of this method was inconsistent because of an inability to account for variance in detection probabilities. Despite the logistical advantages of using indices to estimate population parameters to determine vaccine bait distribution densities, our results suggest that adjustments may be necessary to more accurately quantify raccoon abundance, which should improve the effectiveness of rabies management in the United States. In particular, estimates of detection probabilities are needed to more precisely quantify abundance estimates and ensure appropriate vaccine coverage rates. © 2012 The Wildlife Society.
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