首页> 外文期刊>Environmental Management >A Priori Typology-based Prediction Of Benthic Macroinvertebrate Fauna For Ecological Classification Of Rivers
【24h】

A Priori Typology-based Prediction Of Benthic Macroinvertebrate Fauna For Ecological Classification Of Rivers

机译:基于先验类型学的底栖大型无脊椎动物动物河流生态分类预测

获取原文
获取原文并翻译 | 示例
       

摘要

We evaluated a simple bioassessment method based on a priori river typology to predict benthic macro-invertebrate fauna in riffle sites of rivers in the absence of human influence. Our approach predicted taxon lists specific to four river types differing in catchment area with a method analogous to the site-specific RIVPACS-type models. The reference sites grouped in accordance with their type in NMS ordination, indicating that the typology efficiently accounted for natural variation in macroinvertebrate assemblages. Compared with a null model, typology greatly increased the precision of prediction and sensitivity to detect human impairment and strengthened the correlation of the ratio of observed-to-expected number of predicted taxa (O/E) with the measured stressor variables. The performance of the typology-based approach was equal to that of a RIVPACS-type predictive model that we developed. Exclusion of rarest taxa with low occurrence probabilities improved the performance of both approaches by all criteria. With an increasing inclusion threshold of occurrence probability, especially the predictive model sensitivity first increased but then decreased. Many common taxa with intermediate type-specific occurrence probabilities were consistently missing from impacted sites, a result suggesting that these taxa may be especially important in detecting human disturbances. We conclude that if a typology-based approach such as that suggested by the European Union's Water Framework Directive is required, the O/E ratio of type-specific taxa can be a useful metric for assessment of the status of riffle macroinvertebrate communities. Successful application of the approach, however, requires biologically meaningful river types with a sufficient pool of reference sites for each type.
机译:我们评估了一种基于先验河流类型的简单生物评估方法,以预测在没有人为影响的情况下河流浅滩处的底栖大型无脊椎动物动物。我们的方法使用类似于特定地点的RIVPACS类型模型的方法来预测针对流域不同的四种河流类型的分类单元列表。参考位点按照其在NMS排序中的类型进行分组,表明类型有效地解释了大型无脊椎动物组合的自然变化。与零模型相比,类型学极大地提高了预测的准确性和检测人类损伤的敏感性,并增强了预测分类单元的观察数与预期数之比与测得的应激变量的相关性。基于类型学的方法的性能与我们开发的RIVPACS型预测模型的性能相同。通过所有标准排除出现概率较低的最稀有分类单元可提高两种方法的性能。随着出现概率的包含阈值的增加,尤其是预测模型的敏感性首先增加,然后降低。受影响地点始终缺少许多具有特定类型中间发生概率的常见分类单元,结果表明这些分类单元在检测人为干扰方面可能特别重要。我们得出的结论是,如果需要基于类型的方法(如欧盟《水框架指令》建议的方法),则特定类型的分类单元的O / E比可以作为评估浅滩无脊椎动物群落状况的有用指标。但是,成功应用该方法需要具有生物学意义的河流类型,并且每种类型都有足够的参考站池。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号