Justus James, Fuller Trevon, Sarkar Sahotra
Biodiversity and Biocultural Conservation Laboratory, Section of Integrative Biology, University of Texas at Austin, Austin, TX 78712-1180, USA.
Conserv Biol. 2008 Jun;22(3):673-82. doi: 10.1111/j.1523-1739.2008.00928.x. Epub 2008 Apr 25.
Systematic conservation planning typically requires specification of quantitative representation targets for biodiversity surrogates such as species, vegetation types, and environmental parameters. Targets are usually specified either as the minimum total area in a conservation-area network in which a surrogate must be present or as the proportion of a surrogate's existing spatial distribution required to be in the network. Because the biological basis for setting targets is often unclear, a better understanding of how targets affect selection of conservation areas is needed. We studied how the total area of conservation-area networks depends on percentage targets ranging from 5% to 95%. We analyzed 12 data sets of different surrogate distributions from 5 regions: Korea, Mexico, Québec, Queensland, and West Virginia. To assess the effect of spatial resolution on the target-area relationship, we also analyzed each data set at 7 spatial resolutions ranging from 0.01 degrees x 0.01 degrees to 0.10 degrees x 0.10 degrees. Most of the data sets showed a linear relationship between representation targets and total area of conservation-area networks that was invariant across changes in spatial resolution. The slope of this relationship indicated how total area increased with target level, and our results suggest that greater surrogate representation requires significantly more area. One data set exhibited a highly nonlinear relationship. The results for this data set suggest a new method for setting targets on the basis of the functional form of target-area relationships. In particular, the method shows how the target-area relationship can provide a rationale for setting targets solely on the basis of distributional information about surrogates.
系统性保护规划通常需要为生物多样性替代指标(如物种、植被类型和环境参数)指定定量的代表性目标。目标通常指定为保护区网络中必须存在替代指标的最小总面积,或者指定为替代指标现有空间分布中需要包含在网络中的比例。由于设定目标的生物学基础往往不明确,因此需要更好地理解目标如何影响保护区的选择。我们研究了保护区网络的总面积如何取决于5%至95%的百分比目标。我们分析了来自韩国、墨西哥、魁北克、昆士兰和西弗吉尼亚5个地区的12个不同替代指标分布的数据集。为了评估空间分辨率对目标面积关系的影响,我们还在从0.01度×0.01度到0.10度×0.10度的7种空间分辨率下分析了每个数据集。大多数数据集显示,代表性目标与保护区网络总面积之间存在线性关系,且这种关系在空间分辨率变化时保持不变。这种关系的斜率表明总面积如何随目标水平增加,我们的结果表明,更高的替代指标代表性需要显著更多的面积。一个数据集呈现出高度非线性关系。该数据集的结果提出了一种基于目标面积关系的函数形式设定目标的新方法。特别是,该方法展示了目标面积关系如何能够仅基于替代指标的分布信息为设定目标提供依据。