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Using distance sampling and hierarchical models to improve estimates of Dall's sheep abundance

Authors


  • Associate Editor: Joshua Millspaugh.

Abstract

Management of large mammal populations has often been based on aerial minimum count surveys that are uncorrected for incomplete detection and lack estimates of precision. These limitations can be particularly problematic for Dall's sheep (Ovis dalli dalli) due to the high cost of surveys and variation in detection probability across time and space. The limitations of these methods have been recognized for some time, but previously proposed alternatives for sheep surveys proved to be too costly and logistically unfeasible in most circumstances (Udevitz et al. 2006). We assessed the potential for a combination of distance sampling surveys and a hierarchical modeling approach to provide a more efficient means for estimating Dall's sheep abundance by conducting aerial contour transect surveys over all sheep habitat in Gates of the Arctic National Park and Preserve (GAAR), Alaska in 2009 and 2010. We estimated the population of Dall's sheep was 8,412 (95% CI: 6,517–11,090) and 10,072 (95% CI 8,081–12,520) in 2009 and 2010, respectively. Abundance within the Itkillik Preserve area within GAAR was 1,898 (95% CI: 1,421–2,578) and 1,854 (95% CI: 1,342–2,488) in 2009 and 2010, respectively. Estimates of lamb abundance in 2010 were more than double those of 2009 after correcting for detection bias related to group size, suggesting that the apparent estimate of lambs in the population may be biased in some years depending on the degree of aggregation. Overall, the contour transect surveys were feasible logistically, cost 70–80% less than minimum count surveys, and produced precise estimates of abundance, indicating that the application of these methods could be used effectively to increase the statistical rigor and spatial extent of Dall's sheep abundance surveys throughout Alaska. These methods could be used to improve the assessment of long-term trends in populations and productivity and provide valuable information for harvest management at both local and landscape scales at reduced costs in comparison to traditional minimum count surveys. © 2011 The Wildlife Society.

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