Identifying priority areas for bioclimatic representation under climate change: a case study for Proteaceae in the Cape Floristic Region, South Africa
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- 作者：Pyke ; Christopher R. ; Andelman ; Sandy J. ; Midgley ; Guy
- 关键词：Climate change ; Biodiversity ; Systematic conservation planning ; Reserve design and selection ; Bioclimatic representation
- 刊名：Biological Conservation
- 出版年：2005
- 出版时间：September, 2005
- 年：2005
- 卷：125
- 期：1
- 页码：1-9
- 全文大小：382 K
文摘
Biological reserves are established to protect natural resources and represent the diversity of environments found within a region. Unfortunately, many systems of protected areas do not proportionally capture the range of environmental conditions occupied by species and communities. Combinations of habitat loss and climate change may exacerbate these representational biases, and result in future distributions of environmental conditions that bare little resemblance to historic patterns. New protected areas need to be established to correct existing biases, and create conservation networks that remain representative despite climate change, habitat loss, and changes in species distributions. We demonstrate a new method to identify and prioritize habitat based on its value for improving bioclimatic representation. We assessed representation provided by existing protected areas for 301 Proteaceae species under historic and projected 2050 climate across the Cape Floristic Region in South Africa. The existing reserve system has relatively modest biases with respect to current species distributions and climate. However, if the system is not supplemented, protected areas in 2050 will capture an increasingly skewed sample of climatic conditions occupied by Proteaceae. These biases can be repaired through the systematic establishment of new protected areas, and many of the most valuable areas coincide with high priority ecosystem components and irreplaceable elements identified in the Cape Action for People and the Environmental conservation plan. Protecting these areas achieves nearly the best possible improvement in climatic representation while also meeting biodiversity representation goals.