The use of long-term monitoring data for studies of planktonic diversity: a cautionary tale from two Swiss lakes
The use of long-term monitoring data for studies of planktonic diversity: a cautionary tale from two Swiss lakes
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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：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
R. Kümmerlin
中科院分区：
文献类型：
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作者：
D. Straile;M. Jochimsen;R. Kümmerlin
摘要1.长期数据被认为是调查环境对生物多样性的影响以及生物多样性对生态系统动态的作用的资源。然而，分析长期数据中生物多样性模式的科学家需要认识到，数十年的时间序列可能会受到方法不一致的影响，这可能会使多样性模式的解释变得非常复杂。不幸的是，这种不一致通常很难发现，因此，不知道它们对得出的结论有多大影响。2.在这里，我们强调了两个长期的数据集采样的一个实验室，分析模式的浮游植物丰富的两个瑞士湖泊，苏黎世湖和湖瓦伦。两个湖泊长期物种丰富度的明显模式来自：（一）物种鉴定的不一致（分类学文献和/或计数人员的分类学专业知识的变化）和（二）分类群检测限的变化。因此，在这两个案例研究的偏见是强大的，足以掩盖任何可能的影响物种丰富的环境变化（富营养化）。3.我们表明，在这两个数据集的情况下，不一致混淆浮游植物丰富度的估计不仅在物种水平，但即使在属和家族水平。这表明，经常针对不一致性提出的解决方案，即在汇总到属或科后重新分析数据，可能是不够的。4.我们建议使用两个诊断图，这可能会被用于其他研究中，无论是长期的时间序列或比较研究，其中几个科学家/实验室的数据采集丰富的模式。这些图说明了时间或空间模式，（i）的百分比分类群确定的属和（ii）在5%百分位数的浓度个别藻类分类群。它们将有助于查明由于（i）分类学专门知识和（ii）检测限度的变化或差异而造成的不一致问题。
SUMMARY 1. Long-term data have been suggested as resources for investigating environmental influences on biodiversity and, in turn, the role of biodiversity for ecosystem dynamics. However, scientists analysing biodiversity patterns in long-term data need to recognise that multidecadal time series are likely to suffer from inconsistencies in methodology, which might strongly complicate the interpretation of diversity patterns. Unfortunately, such inconsistencies are usually difficult to detect, and consequently, it is not known how strongly they affect the conclusions drawn. 2. Here, we highlight two long-term data sets sampled by one laboratory to analyse patterns in phytoplankton richness in two Swiss lakes, Lake Zurich and Lake Walen. Apparent patterns in the long-term species richness in the two lakes arise from: (i) inconsistencies in species identification (changes in taxonomic literature and/or taxonomic expertise of the counting personnel) and (ii) changes in the detection limits of taxa. Hence, bias in these two case studies was strong enough to obscure any possible effects on species richness of environmental change (oligotrophication). 3. We show that in the case of these two data sets, inconsistency confounds estimates of phytoplankton richness not only at the species level but even at the generic and familial levels. This suggests that a solution often proposed for inconsistency, that is, reanalysis of the data after aggregation to genus or family, may be insufficient. 4. We suggest the use of two diagnostic plots, which may be used in other studies examining richness patterns in either long-term time series or comparative studies in which several scientists/laboratories contributed to data acquisition. These plots illustrate temporal or spatial patterns in (i) the percentage of taxa identified only to genus and (ii) in the 5% percentile of the concentrations of individual algal taxa. They will help to identify inconsistency problems due to changes or differences in (i) taxonomic expertise and (ii) detection limits.