globalchange  > 过去全球变化的重建
DOI: 10.1371/journal.pone.0173443
论文题名:
Species-free species distribution models describe macroecological properties of protected area networks
作者: Jason L. Robinson; James A. Fordyce
刊名: PLOS ONE
ISSN: 1932-6203
出版年: 2017
发表日期: 2017-3-16
卷: 12, 期:3
语种: 英语
英文关键词: Conservation science ; Climate change ; Spatial and landscape ecology ; Biogeography ; Climate modeling ; Forests ; Geographic distribution ; Theoretical ecology
英文摘要: Among the greatest challenges facing the conservation of plants and animal species in protected areas are threats from a rapidly changing climate. An altered climate creates both challenges and opportunities for improving the management of protected areas in networks. Increasingly, quantitative tools like species distribution modeling are used to assess the performance of protected areas and predict potential responses to changing climates for groups of species, within a predictive framework. At larger geographic domains and scales, protected area network units have spatial geoclimatic properties that can be described in the gap analysis typically used to measure or aggregate the geographic distributions of species (stacked species distribution models, or S-SDM). We extend the use of species distribution modeling techniques in order to model the climate envelope (or “footprint”) of individual protected areas within a network of protected areas distributed across the 48 conterminous United States and managed by the US National Park System. In our approach we treat each protected area as the geographic range of a hypothetical endemic species, then use MaxEnt and 5 uncorrelated BioClim variables to model the geographic distribution of the climatic envelope associated with each protected area unit (modeling the geographic area of park units as the range of a species). We describe the individual and aggregated climate envelopes predicted by a large network of 163 protected areas and briefly illustrate how macroecological measures of geodiversity can be derived from our analysis of the landscape ecological context of protected areas. To estimate trajectories of change in the temporal distribution of climatic features within a protected area network, we projected the climate envelopes of protected areas in current conditions onto a dataset of predicted future climatic conditions. Our results suggest that the climate envelopes of some parks may be locally unique or have narrow geographic distributions, and are thus prone to future shifts away from the climatic conditions in these parks in current climates. In other cases, some parks are broadly similar to large geographic regions surrounding the park or have climatic envelopes that may persist into near-term climate change. Larger parks predict larger climatic envelopes, in current conditions, but on average the predicted area of climate envelopes are smaller in our single future conditions scenario. Individual units in a protected area network may vary in the potential for climate adaptation, and adaptive management strategies for the network should account for the landscape contexts of the geodiversity or climate diversity within individual units. Conservation strategies, including maintaining connectivity, assessing the feasibility of assisted migration and other landscape restoration or enhancements can be optimized using analysis methods to assess the spatial properties of protected area networks in biogeographic and macroecological contexts.
URL: http://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0173443&type=printable
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/25676
Appears in Collections:过去全球变化的重建
影响、适应和脆弱性
科学计划与规划
气候变化与战略
全球变化的国际研究计划
气候减缓与适应
气候变化事实与影响

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作者单位: Illinois Natural History Survey, Prairie Research Institute, University of Illinois, Urbana- Champaign. Champaign IL, United States of America;Department of Ecology and Evolutionary Biology, University of Tennessee, Knoxville, TN, United States of America

Recommended Citation:
Jason L. Robinson,James A. Fordyce. Species-free species distribution models describe macroecological properties of protected area networks[J]. PLOS ONE,2017-01-01,12(3)
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