Algorithm improvements and applications for biological conservation security patterns

CHEN Jie1 ZHOU Nianxing1 TAO Zhuomin1

(1.School of Geography Science, Nanjing Normal University, Nanjing 210023)

【Abstract】Using biological movement as a basis, landscape security patterns are an effective approach to biological conservation. This study probed the recognition technique to buffer zones with the aid of utility formulas, and improved the method of recognition of ecological corridors with the help of gradient descent algorithms. These habit islets, which are located within low-resistance areas outside the buffer zone and of a certain distance from suitable sources for the subsistence of targeted protected species, can be considered source candidates. Regions, which are situated within high-resistance areas inside the buffer zone and close to unsuitable sources for maintaining targeted protected species, can be categorized in ecological restoration areas. The intersection between ecological corridors and high-resistance areas should be identified as a key point for ecological restoration. Taking the Wulingyuan Scenic and Historic Interest Area (WSA) as an empirical case, the study formulated the landscape security pattern of Macaca mulatta, in which the core area of the reserve was comprised of four discrete source Macaca mulatta habitats and is supplemented by three source candidates. A few ecological corridors and connections between sources that aimed to improve connectivity of the inter-population were delimited, and the strategic points of ecological restoration are discerned. This study not only identified buffer zones and ecological corridors in landscape security patterns but also attached great practical significance to biological conservation exemplified by the Macaca mulatta population in WSA.

【Keywords】 landscape security pattern; algorithm; Wulingyuan Scenic and Historic Interest Area; Macaca mulatta;

【DOI】

【Funds】 National Natural Science Foundation of China (41671140, 41271150)

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This Article

ISSN:1005-0094

CN: 11-3247/Q

Vol 26, No. 01, Pages 36-43

January 2018

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Article Outline

Abstract

  • 1 Algorithm improvement
  • 2 Application case
  • 3 Results
  • 4 Conclusion
  • References