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A freshwater classification approach for biodiversity conservation planning

机译:一种用于生物多样性保护规划的淡水分类方法

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Freshwater biodiversity is highly endangered and faces increasing threats worldwide. To be complete, regional plans that identify critical areas for conservation must capture representative components of freshwater biodiversity as well as rare and endangered species. We present a spatially hierarchical approach to classify freshwater systems to create a coarse filter to capture representative freshwater biodiversity in regional conservation plans. The classification framework has four levels that we described using abiotic factors within a zoogeographic context and mapped in a geographic information system. Methods to classify and map units are flexible and can be automated where high-quality spatial data exist, or can be manually developed where such data are not available. Products include a spatially comprehensive inventory of mapped and classified units that can be used remotely to characterize regional patterns of aquatic ecosystems. We provide examples of classification procedures in data-rich and data-poor regions from the Columbia River Basin in the Pacific Northwest of North America and the upper Paraguay River in central South America. The approach, which has been applied in North, Central, and South America, provides a relatively rapid and pragmatic way to account for representative freshwater biodiversity at scales appropriate to regional assessments.
机译:淡水生物多样性受到高度威胁,在世界范围内面临越来越多的威胁。为了完整起见,确定关键保护区的区域计划必须捕获淡水生物多样性以及稀有和濒危物种的代表性组成部分。我们提出了一种空间分层方法来对淡水系统进行分类,以创建一个粗滤器,以捕获区域保护计划中代表性的淡水生物多样性。分类框架有四个级别,我们在动物地理环境内使用非生物因素对其进行了描述,并在地理信息系统中进行了映射。单位分类和制图的方法非常灵活,可以在存在高质量空间数据的情况下自动进行,也可以在没有此类数据的情况下手动进行开发。产品包括对所映射和分类的单位进行全面的空间盘点,可远程用于表征水生生态系统的区域格局。我们提供了来自北美西北太平洋的哥伦比亚河盆地和南美洲中部巴拉圭河上游的数据丰富和数据贫乏地区的分类程序示例。该方法已在北美洲,中美洲和南美洲使用,它提供了一种相对迅速和务实的方式,以适合区域评估的规模来解释代表性的淡水生物多样性。

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