Increasing the quality, comparability and accessibility of phytoplankton species composition time-series data. (5th September 2015)

• Record Type: Journal Article
• Authors: Zingone, Adriana; Harrison, Paul J.; Kraberg, Alexandra; Lehtinen, Sirpa; McQuatters-Gollop, Abigail; O'Brien, Todd; Sun, Jun; Jakobsen, Hans H.
• Is Part Of: Estuarine, coastal and shelf science. Volume 162(2015)
• Page Start: 151
• Page End: 160
• Publication Date: 2015-09-05
• Subjects: phytoplankton -- Long Term Ecological Research (LTER) -- metadata -- methodology -- quality assurance -- quality control -- time series; Estuarine oceanography -- Periodicals; Coasts -- Periodicals; Estuarine biology -- Periodicals; Seashore biology -- Periodicals; Coasts; Estuarine biology; Estuarine oceanography; Seashore biology; Periodicals; 551.461805
• DOI: 10.1016/j.ecss.2015.05.024
• Languages: English
• ISSNs: 0272-7714

Abstract

Abstract: 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 complementary 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. Highlights: Phytoplankton time-series (PTS) are invaluable for the assessment of the environmental status and of its changes over time. There is a broad variability in the methods used to produce PTS and a generalised lack of metadata and QC procedures. A list of information on different phases of data production is proposed as a first step towards a QC manual for PTS. Metadata and QC procedures increase quality, accessibility and comparability of PTS, ensuring their long-term exploitation.