Taxonomic aggregation does not alleviate the lack of consistency in analysing diversity in long‐term phytoplankton monitoring data: a rejoinder to Pomati et al. (2015)
Taxonomic aggregation does not alleviate the lack of consistency in analysing diversity in long‐term phytoplankton monitoring data: a rejoinder to Pomati et al. (2015)
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分类聚合并不能缓解长期浮游植物监测数据多样性分析缺乏一致性的问题：对 Pomati 等人的反驳（2015）
DOI：
10.1111/fwb.12552
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发表时间：
2015
影响因子：
2.7
通讯作者：
R Kümmerlin
中科院分区：
文献类型：
--
作者：
Straile D;Jochimsen M C ;R Kümmerlin
长期浮游植物监测为研究环境变化对群落的影响和检验生态假设提供了重要资源。然而，由于识别困难，很难长期保持数据的一致性。通常认为，当只有一个分类学家负责整个过程时，和/或当数据被汇总到一个粗略的分类级别时，一致性会得到改善。这两个假设都没有得到严格的检验。我们处理Pomatiet等人的评论。（2015年）在我们的早期意见文件（Straileet al，2013）并使用苏黎世湖的长期数据测试这些假设。我们表明，聚集到较粗的分类水平并不能提高数据集的一致性，因为：（i）分类错误的比例效应不太可能通过将分类群归为一组来减少，因为分类错误越少，影响的分类群的总体数量就越少，这是比例效应是恒定的，（ii）因为检测限的变化将影响所有分类水平成比例。我们还表明，虽然一个单一的分类学家监督浮游植物记录，数据的一致性受到破坏：（i）通过与其他分类学家交流和参加分类学讲习班学习，（ii）降低物种的检测极限，可能是由于分类学家数量的增加（允许增加每个样品的处理时间）。由于（i）检测限的降低，（ii）确认的分类学学习和（iii）分类学聚集未能提高一致性，我们的新证据加强了苏黎世湖数据集存在一致性问题的观点，以及对Pomatiet等人的结论进行批判性审查的必要性。（2012）和马修斯& Pomati（2012）。
Long‐term phytoplankton monitoring provides an important resource for studying the effects of environmental change on communities and testing ecological hypotheses. However, because of identification difficulties, maintaining consistency in the data over long periods is extremely difficult. It is usually assumed that consistency is improved when only one taxonomist is responsible throughout, and/or when data are aggregated to a coarser taxonomic level. Neither assumption has been critically tested. We address the comment of Pomatiet al. (2015) on our earlier Opinion paper (Straileet al, 2013) and test these assumptions with the long‐term data from Lake Zurich.We show that aggregation to coarser taxonomic levels does not improve data set consistency because: (i) the proportional effect of misclassification is unlikely to be reduced by lumping taxa since the fewer misclassifications affect the dynamics of an overall lower number of taxa, that is the proportional effect is constant, and (ii) because changes in detection limits will affect all taxonomic levels proportionally.We also show that, although a single taxonomist supervised phytoplankton recordings, data consistency is undermined by: (i) learning via exchange with other taxonomists and participation in taxonomic workshops, and (ii) a reduction in detection limits of species, presumably due to an increase in the number of taxonomists (allowing an increased processing time per sample).As a consequence of (i) a reduction in detection limits, (ii) the confirmed taxonomic learning and (iii) the failure of taxonomic aggregation to improve consistency, our new evidence strengthens the view that there are consistency problems in the Lake Zurich data set, and the need for a critical review of the conclusions of Pomatiet al. (2012) and Matthews & Pomati (2012).
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影响因子：
3.4
作者：
F. Pomati;B. Matthews;J. Jokela;A. Schildknecht;B. Ibelings
通讯作者：
F. Pomati;B. Matthews;J. Jokela;A. Schildknecht;B. Ibelings
解释苏黎世湖（瑞士）浮游植物多样性长期变化的挑战和前景
DOI：
--
发表时间：
2015
期刊：
影响因子：
--
作者：
F. Pomati;C. Tellenbach;B. Matthews;P. Venail;B. Ibelings;R. Ptáčník
通讯作者：
R. Ptáčník
使用长期监测数据研究浮游生物多样性：瑞士两个湖泊的警示故事
DOI：
--
发表时间：
2013
期刊：
影响因子：
--
作者：
D. Straile;M. Jochimsen;R. Kümmerlin
通讯作者：
R. Kümmerlin
20 世纪 80 年代末气候变化对瑞士河流和湖泊的物理影响
DOI：
--
发表时间：
2013
期刊：
影响因子：
--
作者：
Ryan P. North;D. Livingstone;Renata E. Hari;O. Köster;Pius Niederhauser;R. Kipfer
通讯作者：
R. Kipfer