4.7 Article

High spatial variability biases the space-for-time approach in environmental monitoring

期刊

ECOLOGICAL INDICATORS
卷 10, 期 6, 页码 1202-1205

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.ecolind.2010.03.012

关键词

Bioassessment; Benthic invertebrates; Season; Stream; Water quality

资金

  1. Hesse's Ministry of Higher Education, Research, and the Arts

向作者/读者索取更多资源

The space-for-time approach is widely used in fundamental and applied ecology but assemblages from some habitats are highly variable. For example, streams may show marked spatio-temporal changes in the taxonomic composition of the macroinvertebrate assemblages. We exemplify the effect of the temporal component 'season' on some assemblage-derived stream quality assessment metrics under the assumptions of the space-for-time and the replicated samples approaches. Benthic macroinvertebrates were sampled in spring, summer, and fall from two stream types, namely streams in the Pleistocene sediments of the alpine foothills and small fine substrate dominated siliceous highland rivers in southern and central Germany. As exemplified for ASPT and the German multimetric index (MMI), the data showed no effect of season when samples were regarded as independent, whereas stream quality decreased between spring and fall in the replicated samples approach. The transformation of MM I to rank-ordered stream quality classes depicted a decrease in perceived stream quality in 29% and 54% of the sites by summer and early fall, respectively, when compared to spring samples. We thus suggest (1) to test seemingly robust metrics in a repetitive measures approach for other stream types and regions, and (2) to standardize the sampling season for ecological quality assessment. Based on this example, we assume that many subtle, but significant, environmental trends are still to be detected in highly heterogeneous habitats from various ecosystems. (C) 2010 Elsevier Ltd. All rights reserved.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据