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Assessing Local and Surrounding Threats to the Protected Area Network in a Biodiversity Hotspot: The Hengduan Mountains of Southwest China.

By Xin Ye, Guohua Liu, Zongshan Li, Hao Wang and Yuan Zeng

Abstract

Protected areas (PAs) not only serve as refuges of biodiversity conservation but are also part of large ecosystems and are vulnerable to change caused by human activity from surrounding lands, especially in biodiversity hotspots. Assessing threats to PAs and surrounding areas is therefore a critical step in effective conservation planning. We apply a threat framework as a means of quantitatively assessing local and surrounding threats to different types of PAs with gradient buffers, and to main ecoregions in the Hengduan Mountain Hotspot of southwest China. Our findings show that national protected areas (NPAs) have lower and significantly lower threat values (p<0.05) than provincial protected areas (PPAs) and other protected areas (OPAs), respectively, which indicates that NPAs are lands with a lower threat level and higher levels of protection and management. PAs have clear edge effects, as the proportion of areas with low threat levels decline dramatically in the 5-kilometer buffers just outside the PAs. However, NPAs suffered greater declines (58.3%) than PPAs (34.8%) and OPAs (33.4%) in the 5-kilometer buffers. Moreover, a significant positive correlation was found between the size of PAs and the proportion of areas with low threat levels that they contained in both PAs and PA buffers (p<0.01). To control or mitigate current threats at the regional scale, PA managers often require quantitative information related to threat intensities and spatial distribution. The threat assessment in the Hengduan Mountain Hotspot will be useful to policy makers and managers in their efforts to establish effective plans and target-oriented management strategies

Topics: Medicine, R, Science, Q
Publisher: Public Library of Science (PLoS)
DOI identifier: 10.1371/journal.pone.0138533
OAI identifier: oai:doaj.org/article:e9eb701b8733440685900160baf491cd
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