Abstract
We examined environmental and anthropogenic factors drive range loss in large mammals, using presence data of Amur tigers opportunistically collected between 2000 and 2012, and anthropogenic and environmental variables to model the distribution of the Amur tiger in northeastern China. Our results suggested that population distribution models of different subregions showed different habitat factors determining tiger population distribution patterns. Where farmland cover was over 50 km2 per pixel (196 km2), distance was within 15 km to the railway in Changbaishan and road density (length per pixel) increased in Wandashan, the relative probability of Amur tiger occurrence exhibited monotonic avoidance responses; however, where distance was within 150 km of the Sino-Russia border, the occurrence probability of Amur tiger was relatively high. We analyzed the avoidance or preference responses of Amur tiger distribution to elevation, snow depth and Viewshed. Furthermore, different subregional models detected a variety of spatial autocorrelation distances due to different population clustering patterns. We found that spatial models significantly improved model fits for non-spatial models and made more robust habitat suitability predications than that of non-spatial models. Consequently, these findings provide useful guidance for habitat conservation and management.





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Acknowledgments
We thank the support of the Fundamental Research Funds for the Central Universities of China (2572014EA06), “National Natural Science Foundation of China (1272336)” and the “New Century Excellent Talent Plan of the Ministry of Education of China (NCET-10-0310)”. We thank Dr. M. Hebblewhite for his useful comments on improving the quality of this paper. The authors declare no conflict of interest. In addition, we appreciate the funding and coordinating support of WWF–China Tiger Conservation Program.
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Jiang, G., Sun, H., Lang, J. et al. Effects of environmental and anthropogenic drivers on Amur tiger distribution in northeastern China. Ecol Res 29, 801–813 (2014). https://doi.org/10.1007/s11284-014-1160-3
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DOI: https://doi.org/10.1007/s11284-014-1160-3