Department of Ecology and Evolutionary Biology and National Institute for Mathematical and Biological Synthesis, University of Tennessee, 569 Dabney Hall, 1416 Circle Dr, Knoxville, Tennessee, 37996, USA.
Department of Ecology and Evolutionary Biology, University of Tennessee, 569 Dabney Hall, 1416 Circle Dr, Knoxville, Tennessee, 37996, USA.
Ecol Appl. 2020 Sep;30(6):e02118. doi: 10.1002/eap.2118. Epub 2020 May 5.
Spatial optimization approaches that were originally developed to help conservation organizations determine protection decisions over small spatial scales are now used to inform global or continental scale priority setting. However, the different decision contexts involved in large-scale resource allocation need to be considered. We present a continuous optimization approach in which a decision-maker allocates funding to regional offices. Local decision-makers then use these funds to implement habitat protection efforts with varying effectiveness when evaluated in terms of the funder's goals. We illustrate this continuous formulation by examining the relative priority that should be given to different counties in the coterminous United States when acquiring land to establish new protected areas. If weighting all species equally, counties in the southwest United States, where large areas can be bought cheaply, are priorities for protection. If focusing only on species of conservation concern, priorities shift to locations rich in such species, particularly near expanding exurban areas facing high rates of future habitat conversion (e.g., south-central Texas). Priorities for protection are sensitive to what is assumed about local ecological and decision-making processes. For example, decision-makers who doubt the efficacy of local land protection efforts should focus on a few key areas, while optimistic decision-makers should disperse funding more widely. Efforts to inform large-scale conservation priorities should reflect better the types of choice that decision-makers actually face when working over these scales. They also need to report the sensitivity of recommended priorities to what are often unstated assumptions about local processes affecting conservation outcomes.
最初开发用于帮助保护组织在小空间尺度上做出保护决策的空间优化方法，现在被用于为全球或大陆尺度的优先级设置提供信息。然而，需要考虑到大尺度资源分配中涉及的不同决策背景。我们提出了一种连续优化方法，其中决策者将资金分配给区域办事处。当地决策者然后使用这些资金来实施栖息地保护工作，根据资助者的目标评估，这些工作的有效性各不相同。我们通过检查在美国大陆不同县在获得土地以建立新的保护区时应给予的相对优先级，来说明这种连续的方案。如果平等对待所有物种，美国西南部的县（那里可以廉价购买大面积土地）是保护的优先事项。如果只关注受关注的物种，那么优先级就会转移到这些物种丰富的地方，特别是在面临未来栖息地转换率高的不断扩大的城市郊区附近（例如，德克萨斯州中南部）。保护的优先级取决于对当地生态和决策过程的假设。例如，怀疑当地土地保护工作效果的决策者应该集中在少数几个关键领域，而乐观的决策者应该更广泛地分散资金。为告知大尺度保护优先级而进行的努力应该更好地反映决策者在这些尺度上实际面临的选择类型。它们还需要报告建议的优先级对影响保护结果的当地过程的经常未说明假设的敏感性。
