School of Environmental and Forest Sciences, University of Washington, Seattle, WA, USA.
Department of Applied Economics and Department of Ecology Evolution, and Behavior, University of Minnesota, St. Paul, MN, USA.
Ecol Lett. 2012 Nov;15(11):1249-1256. doi: 10.1111/j.1461-0248.2012.01847.x. Epub 2012 Aug 23.
Efficient conservation planning requires knowledge about conservation targets, threats to those targets, costs of conservation and the marginal return to additional conservation efforts. Systematic conservation planning typically only takes a small piece of this complex puzzle into account. Here, we use a return-on-investment (ROI) approach to prioritise lands for conservation at the county level in the conterminous USA. Our approach accounts for species richness, county area, the proportion of species' ranges already protected, the threat of land conversion and land costs. Areas selected by a complementarity-based greedy heuristic using our full ROI approach provided greater averted species losses per dollar spent compared with areas selected by heuristics accounting for richness alone or richness and cost, and avoided acquiring lands not threatened with conversion. In contrast to traditional prioritisation approaches, our results highlight conservation bargains, opportunities to avert the threat of development and places where conservation efforts are currently lacking.
高效的保护规划需要了解保护目标、对这些目标的威胁、保护成本以及额外保护工作的边际回报。系统保护规划通常只考虑到这一复杂难题的一小部分。在这里，我们使用投资回报率 (ROI) 方法，按优先顺序为美国本土的县一级土地制定保护计划。我们的方法考虑了物种丰富度、县面积、物种分布范围已受保护的比例、土地转化的威胁和土地成本。与仅考虑丰富度或丰富度和成本的启发式方法选择的区域相比，使用我们的完整 ROI 方法的基于互补性的贪婪启发式方法选择的区域，每花费一美元就能避免更多的物种损失，并且避免获得没有受到转化威胁的土地。与传统的优先级排序方法相比，我们的结果突出了保护的优势、避免发展威胁的机会以及当前缺乏保护努力的地方。
