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无物种的物种分布模型描述了保护区网络的宏观生态特性。

Species-free species distribution models describe macroecological properties of protected area networks.

作者信息

Robinson Jason L, Fordyce James A

机构信息

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.

出版信息

PLoS One. 2017 Mar 16;12(3):e0173443. doi: 10.1371/journal.pone.0173443. eCollection 2017.

Abstract

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.

摘要

保护区内动植物物种保护面临的最大挑战之一是快速变化的气候带来的威胁。气候变化给改进保护区网络的管理带来了挑战,也带来了机遇。越来越多地,诸如物种分布建模等定量工具被用于在预测框架内评估保护区的表现,并预测物种群体对气候变化的潜在反应。在更大的地理区域和尺度上,保护区网络单元具有空间地理气候属性,这些属性可以在通常用于测量或汇总物种地理分布的差距分析中描述(堆叠物种分布模型,即S-SDM)。我们扩展了物种分布建模技术的应用,以便对分布在美国本土48个州且由美国国家公园管理局管理的保护区网络内各个保护区的气候包络(或“足迹”)进行建模。在我们的方法中,我们将每个保护区视为一个假设的特有物种的地理范围,然后使用最大熵模型(MaxEnt)和5个不相关的生物气候变量来模拟与每个保护区单元相关的气候包络的地理分布(将公园单元的地理区域建模为一个物种的范围)。我们描述了由163个保护区组成的大型网络预测的单个和汇总的气候包络,并简要说明了如何从我们对保护区景观生态背景的分析中得出地理多样性的宏观生态指标。为了估计保护区网络内气候特征时间分布的变化轨迹,我们将当前条件下保护区的气候包络投影到预测的未来气候条件数据集上。我们的结果表明,一些公园的气候包络可能在局部是独特的,或者地理分布狭窄,因此在当前气候下,这些公园未来的气候条件可能会发生变化。在其他情况下,一些公园与公园周围的大地理区域大致相似,或者其气候包络可能会持续到近期的气候变化。在当前条件下,较大的公园预测的气候包络更大,但在我们的单一未来条件情景中,预测的气候包络平均面积较小。保护区网络中的各个单元在气候适应潜力方面可能存在差异,该网络的适应性管理策略应考虑各个单元内地理多样性或气候多样性的景观背景。包括维持连通性、评估辅助迁移的可行性以及其他景观恢复或增强措施在内的保护策略,可以通过分析方法进行优化,以评估生物地理和宏观生态背景下保护区网络的空间属性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/788b/5354291/c1a7e9bec51e/pone.0173443.g001.jpg

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