I addressed the need for a statistically rigorous, logistically feasible method of abundance estimation for Amur tigers in the Russian Far East by comparing six candidate methods. Additionally, I investigated how to increase precision of the preferred method.;My primary objective was to systematically rank candidate methods for abundance estimation based on three broad criteria of performance: logistics, statistics, and cost. Because of logistical difficulties inherent in the region, it was especially important to consider not just the precision of each method, but its feasibility under the biological, environmental, and social constraints of the Russian Far East. I found the traditional Russian track survey to be the most promising method in terms of logistics and cost, although it was one of the poorer methods in terms of statistical properties. In contrast, camera trapping was deemed the most promising method statistically, although it performed poorly under logistical and cost concerns. In light of these results, I recommended that double sampling be employed to monitor population trends of Amur tigers, with broad implementation of track surveys and more focused implementation of camera trapping in areas of critical importance to tiger conservation.;Based on the recommendation that camera trapping be employed in the Russian Far East, I conducted logistic regressions to determine which physical features were most likely to increase precision of abundance estimates when associated with camera traps. I found that roads and mark trees were both likely to increase precision of camera trapping studies of Amur tigers in the Russian Far East when compared against trail sites and non-mark tree sites.
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