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Development of a spatially universal framework for classifying stream assemblages with application to conservation planning for Great Lakes lotic fish communities

机译:开发一种空间通用的框架,用于对溪流集合进行分类,并将其应用于大湖地区鱼类种群的保护规划

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摘要

Classifications are typically specific to particular issues or areas, leading to patchworks of subjectively defined spatial units. Stream conservation is hindered by the lack of a universal habitat classification system and would benefit from an independent hydrology-guided spatial framework of units encompassing all aquatic habitats at multiple spatial scales within large regions. We present a system that explicitly separates the spatial framework from any particular classification developed from the framework. The framework was constructed from landscape variables that are hydrologically and biologically relevant, covered all space within the study area, and was nested hierarchically and spatially related at scales ranging from the stream reach to the entire region; classifications may be developed from any subset of the 9 basins, 107 watersheds, 459 subwatersheds, or 10,000s of valley segments or stream reaches. To illustrate the advantages of this approach, we developed a fish-guided classification generated from a framework for the Great Lakes region that produced a mosaic of habitat units which, when aggregated, formed larger patches of more general conditions at progressively broader spatial scales. We identified greater than 1,200 distinct fish habitat types at the valley segment scale, most of which were rare. Comparisons of biodiversity and species assemblages are easily examined at any scale. This system can identify and quantify habitat types, evaluate habitat quality for conservation and/or restoration, and assist managers and policymakers with prioritization of protection and restoration efforts. Similar spatial frameworks and habitat classifications can be developed for any organism in any riverine ecosystem.
机译:分类通常是特定于特定问题或区域的,导致主观定义空间单位的拼凑。缺乏通用的生境分类系统阻碍了河流的养护,并将受益于一个独立的水文指导的单位空间框架,该单位涵盖了大区域内多个空间尺度上的所有水生生境。我们提出了一个系统,该系统将空间框架与从该框架开发的任何特定分类明确分离。该框架由与水文和生物学相关的景观变量构建而成,涵盖了研究区域内的所有空间,并且嵌套了层次结构和空间相关性,范围从小溪到整个区域不等;可以从9个盆地,107个集水区,459个子集水区或10,000个谷段或河段的任何子集进行分类。为了说明这种方法的优势,我们开发了一种由大湖区框架生成的鱼类指导分类,该分类产生了栖息地单位的镶嵌图,这些栖息地单位在聚合时形成了逐渐扩大的空间尺度上的更一般条件的较大斑块。我们在山谷段尺度上确定了1,200多种不同的鱼类栖息地类型,其中大多数是罕见的。可以在任何规模上轻松检查生物多样性和物种组合的比较。该系统可以识别和量化栖息地类型,评估栖息地质量以进行保护和/或恢复,并协助管理人员和决策者确定保护和恢复工作的优先顺序。可以为任何河流生态系统中的任何生物开发相似的空间框架和栖息地分类。

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