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Increasing the quality, comparability and accessibility of phytoplankton species composition time-series data

机译：提高浮游植物物种组成时间序列数据的质量，可比性和可及性

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Phytoplankton diversity and its variation over an extended time scale can provide answers to a wide range of questions relevant to societal needs. These include human health, the safe and sustained use of marine resources and the ecological status of the marine environment, including long-term changes under the impact of multiple stressors. The analysis of phytoplankton data collected at the same place over time, as well as the comparison among different sampling sites, provide key information for assessing environmental change, and evaluating new actions that must be made to reduce human induced pressures on the environment. To achieve these aims, phytoplankton data may be used several decades later by users that have not participated in their production, including automatic data retrieval and analysis. The methods used in phytoplankton species analysis vary widely among research and monitoring groups, while quality control procedures have not been implemented in most cases. Here we highlight some of the main differences in the sampling and analytical procedures applied to phytoplankton analysis and identify critical steps that are required to improve the quality and inter-comparability of data obtained at different sites and/or times. Harmonization of methods may not be a realistic goal, considering the wide range of purposes of phytoplankton time-series data collection. However, we propose that more consistent and detailed metadata and complementaty information be recorded and made available along with phytoplankton time-series datasets, including description of the procedures and elements allowing for a quality control of the data. To keep up with the progress in taxonomic research, there is a need for continued training of taxonomists, and for supporting and complementing existing web resources, in order to allow a constant upgrade of knowledge in phytoplankton classification and identification. Efforts towards the improvement of metadata recording, data annotation and quality control procedures will ensure the internal consistency of phytoplankton time series and facilitate their comparability and accessibility, thus strongly increasing the value of the precious information they provide. Ultimately, the sharing of quality controlled data will allow one to recoup the high cost of obtaining the data through the multiple use of the time-series data in various projects over many decades. (C) 2015 Elsevier Ltd. All rights reserved.
机译：浮游植物的多样性及其在较长时间内的变化可以回答与社会需求有关的各种问题。其中包括人类健康，海洋资源的安全和持续利用以及海洋环境的生态状况，包括在多重压力影响下的长期变化。随时间推移在同一地点收集的浮游植物数据的分析，以及不同采样点之间的比较，为评估环境变化以及评估为减轻人为环境压力而必须采取的新措施提供了关键信息。为了实现这些目标，几十年后未参与生产的用户可能会使用浮游植物数据，包括自动数据检索和分析。在研究和监测小组中，用于浮游植物种类分析的方法差异很大，而在大多数情况下尚未实施质量控制程序。在这里，我们重点介绍了浮游植物分析所采用的采样和分析程序中的一些主要区别，并确定了提高在不同地点和/或时间获得的数据的质量和可比性所需的关键步骤。考虑到浮游植物时间序列数据收集的广泛目的，方法的统一可能不是一个现实的目标。但是，我们建议记录更一致，更详细的元数据和补充信息，并使之与浮游植物时间序列数据集一起使用，包括对程序和元素的描述，以便对数据进行质量控制。为了跟上分类学研究的进展，需要继续培训分类学家，并支持和补充现有的网络资源，以使浮游植物分类和识别的知识不断提高。改进元数据记录，数据注释和质量控制程序的工作将确保浮游植物时间序列的内部一致性，并促进其可比性和可及性，从而极大地增加了它们提供的宝贵信息的价值。最终，质量控制数据的共享将使人们能够通过数十年来在多个项目中多次使用时间序列数据来弥补获得数据的高昂成本。 （C）2015 Elsevier Ltd.保留所有权利。

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