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Among-year variation in deer population density index estimated from road count surveys
Authors:Inoue Mizuki  Shota Sakaguchi  Keitaro Fukushima  Masaru Sakai  Atsushi Takayanagi  Daisuke Fujiki  Michimasa Yamasaki
Institution:1. Laboratory of Forest Science, Faculty of Bioresource Sciences, Akita Prefectural University, Akita, 010-0195, Japan
2. Laboratory of Forest Biology, Graduate School of Agriculture, Kyoto University, Kyoto, Japan
3. Field Science Education and Research Center, Kyoto University, Kyoto, Japan
4. Graduate School of Global Environmental Studies, Kyoto University, Kyoto, Japan
5. Institute of Natural and Environment Science, University of Hyogo, Tanba, Japan
Abstract:A method for obtaining a relative deer population density index with low cost and effort is urgently needed in wildlife protection areas that need their own deer management guidelines. We recorded the number of deer sighted during our daily trips on forest roads by car in Ashiu Forest at Kyoto University, Japan, beginning in 2006. We used generalized additive mixed models (GAMMs) to estimate among-year trends in the number of deer sighted. We applied models for the total number of deer (TND), number of adults (NA), and number of fawns (NF) sighted, which included both current-year and 1-year-old fawns. Full models included the terms of year (2007, 2008, 2009, and 2010), weather (fine, cloudy, and rain/snow), and nonlinear effects of season (date) and time (time). The optimal GAMMs for TND, NA, and NF did not include the effect of weather but included those of time, date, and year. The detected among-year trends in deer population may be influenced by differences in snow environments among the years. The modeling of road count data using GAMM quantitatively determined among-year variation in the number of deer sighted. This trend was similar to that of the population density estimated using a block count survey conducted in Ashiu Forest.
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