代表性启发
自然资本
环境资源管理
中国
地理
自然保护区
比例(比率)
生态系统服务
生态学
生态系统
环境科学
地图学
数学
统计
生物
考古
作者
Yihe Lü,Liwei Zhang,Yuan Zeng,Bojie Fu,Charlotte Whitham,Shuguang Liu,Bingfang Wu
摘要
Abstract Traditional means of assessing representativeness of conservation value in protected areas depend on measures of structural biodiversity. The effectiveness of priority conservation areas at representing critical natural capital (CNC) (i.e., an essential and renewable subset of natural capital) remains largely unknown. We analyzed the representativeness of CNC‐conservation priority areas in national nature reserves (i.e., nature reserves under jurisdiction of the central government with large spatial distribution across the provinces) in China with a new biophysical‐based composite indicator approach. With this approach, we integrated the net primary production of vegetation, topography, soil, and climate variables to map and rank terrestrial ecosystems capacities to generate CNC. National nature reserves accounted for 6.7% of CNC‐conservation priority areas across China. Considerable gaps (35.2%) existed between overall (or potential) CNC representativeness nationally and CNC representation in national reserves, and there was significant spatial heterogeneity of representativeness in CNC‐conservation priority areas at the regional and provincial levels. For example, the best and worst representations were, respectively, 13.0% and 1.6% regionally and 28.9% and 0.0% provincially. Policy in China is transitioning toward the goal of an ecologically sustainable civilization. We identified CNC‐conservation priority areas and conservation gaps and thus contribute to the policy goals of optimization of the national nature reserve network and the demarcation of areas critical to improving the representativeness and conservation of highly functioning areas of natural capital. Moreover, our method for assessing representation of CNC can be easily adapted to other large‐scale networks of conservation areas because few data are needed, and our model is relatively simple.
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