IUCN / SSC Cat Specialist Group - Digital Cat Library |
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| Zhenxin, L.; Zimmermann, F.; Hebblewhite, M.; Purekhovsky, A.; M”rschel, F.; Chunquan, Z.; Miquelle, D. | |
| Study on the potential tiger habitat in the Changbaishan area, China | |
| 2010 Full Book | |
The Amur tiger (Panthera tigris altaica) is extremely endangered in Northeast China, where it was historically widely distributed. However, there still exist vast tracts of forests - the essential base of good habitat for the Amur tiger - situated throughout eastern Jilin and Heilongjiang provinces. Adjacent forested habitat in the Russian Far East holds a population of 430-500 tigers. Although there is no evidence that a stable, reproducing population exists in Northeast China, there are regular reports of tigers in this region, and confirmed reports of tigers regularly crossing the border between Russia and China. Therefore, re-colonization of previously occupied tiger habitat in Northeast China is a very real possibility if steps are taken to identify and manage these landscapes in an appropriate manner. The goals and objectives for this project were defined as follows: Contribute to the development of a landscape conservation strategy and action plan for tigers in the Changbaishan landscape involving key stakeholders by: Defining potential tiger habitat as tiger conservation priority areas for short-term, medium-term, and long-term effective protection and management to recover tigers; Identifying ecological corridors between large patches of potential tiger habitat Identifying critical priority areas for immediate actions to address the main threats as the base for tiger recovery in the Changbaishan landscape; Providing basic recommendations to guide development of a full tiger conservation strategy and action plan. To try and predict where potential habitat for tigers exists in the Changbaishan landscape, we relied on three types of spatially-explicit modeling approaches. An ecological niche factor analysis model (ENFA) compares use (or an indication of animal presence) to the suite of available resources in the environment, and conducts a factor-analysis to quantify the relationship of biotic and abiotic variables to tiger presence. Resource selection functions (RSF) also attempt to predict tiger distribution based on a suite of environmental variables, but the RSF approach uses logistic regression which provides the opportunity to determine which variables are most useful in predicting where suitable habitat might exist. The third approach, expert-based modeling, relies on expert knowledge and up to date available data and information of Amur tiger and its habitat to define key variables and determine what constitutes suitable habitat. All three approaches have their benefits and disadvantages, and therefore we averaged the results of these models to derive the most robust prediction of where potential tiger habitat exists in the Changbaishan landscape. |
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