Department of Biology, The University of Western Ontario, 1151 Richmond St. N., London, Ontario, Canada, N6A 5B7.
Environ Monit Assess. 2010 Nov;170(1-4):129-40. doi: 10.1007/s10661-009-1221-1. Epub 2009 Nov 10.
Our study develops and demonstrates an objective method for selecting reference sites for the assessment of ecological condition in freshwater ecosystems. The method uses widely available GIS data to group potential sites based on their natural environments. It then establishes the degree and types of human activities each site is exposed to prior to scoring the sites in each group by the relative amount of human activity present. Finally, the sites in each group with the least amount of human activity are categorized as reference sites, with the boundary between reference and test sites defined to maximize the distinctiveness of the two categories with respect to human activity. Application of this technique for the purpose of identifying headwater reference basins in rural areas of southwestern Ontario resulted in the classification of basins into six natural groups based on the dominant texture of the surface geology. Development of a human activity gradient indicated that basins varied according to the amount of exposure to agricultural activities with most basins having at least moderate exposure. Establishment of the reference test boundary indicated that the selected reference basins exhibited substantively lower extents of agricultural activity than test sites for most groups. Because this method uses only widely available GIS data, it enables rapid and cost-effective identification of candidate reference sites, even for large, remote, and understudied regions.
本研究开发并演示了一种客观的方法，用于选择淡水生态系统生态状况评估的参考站点。该方法使用广泛可用的 GIS 数据，根据其自然环境对潜在站点进行分组。然后，在对每组中的站点进行评分之前，根据每个站点所暴露的人类活动的程度和类型，确定每个站点所暴露的人类活动的程度和类型。最后，将每组中人类活动最少的站点归类为参考站点，参考和测试站点之间的边界定义为使两组在人类活动方面的差异最大化。将该技术应用于识别安大略省西南部农村地区的源头参考流域，结果根据地表地质的主要质地将流域分为六个自然组。人类活动梯度的发展表明，流域根据其与农业活动的接触程度而有所不同，大多数流域至少有中度接触。参考测试边界的建立表明，对于大多数群体，所选参考流域的农业活动程度明显低于测试站点。由于该方法仅使用广泛可用的 GIS 数据，因此即使对于大型、偏远和研究不足的地区，也能够快速且经济高效地识别候选参考站点。
