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Improving the description of human activities potentially affecting rural stream ecosystems

机译:改进对可能影响农村河流生态系统的人类活动的描述

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Stressor (or human activity) gradients that quantify variation in the magnitude and type of human activity among sites are an important and widely applicable tool for aquatic monitoring and assessment. These gradients are typically determined from regional land cover data. We predicted that their performance could be improved by incorporating less generalized depictions of human activities. Using data from 479 rural, headwater basins we calculated four human activity gradients (HAGs) that differed in the level of detail (coarse, fine) and spatial explicitness (aspatial, spatial) used to describe human activity. Results demonstrated that the addition of fine detailed information was valuable as it resulted in a HAG that captured subtle differences in the extent of human activity among study units. In comparison, the addition of spatially explicit data added little novel information to the HAG. Analysis of fish and benthic macroinvertebrate samples from 160 of the 479 basins indicated that the addition of fine detailed and spatially explicit information significantly increased the ability of the HAG to predict variation in aquatic assemblages. We concluded that HAGs can better meet the requirements of monitoring and assessment programs if detailed and spatially explicit descriptions of human activity are used along with more typically available land cover data.
机译:量化站点之间人类活动规模和类型变化的应激源(或人类活动)梯度,是一种重要且广泛适用的水生监测和评估工具。这些梯度通常是根据区域土地覆盖数据确定的。我们预测,通过合并不太概括的人类活动描述,可以提高它们的性能。使用来自479个农村水源流域的数据,我们计算了四个人类活动梯度(HAG),它们在描述人类活动的详细程度(粗略,精细)和空间明晰度(空间,空间)方面有所不同。结果表明,添加精细的详细信息非常有价值,因为它导致HAG捕获了研究单位之间人类活动程度的细微差异。相比之下,空间显式数据的添加几乎没有给HAG带来新颖的信息。对来自479个盆地的160个鱼类和底栖大型无脊椎动物样本的分析表明,添加精细的详细信息和空间清晰的信息显着提高了HAG预测水生生物多样性变化的能力。我们得出的结论是,如果使用人类活动的详细且在空间上明确的描述以及更常见的可用土地覆盖数据,HAG可以更好地满足监控和评估计划的要求。

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