Abstract

Abstract. Plankton form the base of the marine food web and are sensitive indicators of environmental change. Plankton time series are therefore an essential part of monitoring progress towards global biodiversity goals, such as the Convention on Biological Diversity Aichi Targets, and for informing ecosystem-based policy, such as the EU Marine Strategy Framework Directive. Multiple plankton monitoring programmes exist in Europe, but differences in sampling and analysis methods prevent the integration of their data, constraining their utility over large spatio-temporal scales. The Plankton Lifeform Extraction Tool brings together disparate European plankton datasets into a central database from which it extracts abundance time series of plankton functional groups, called “lifeforms”, according to shared biological traits. This tool has been designed to make complex plankton datasets accessible and meaningful for policy, public interest, and scientific discovery. It allows examination of large-scale shifts in lifeform abundance or distribution (for example, holoplankton being partially replaced by meroplankton), providing clues to how the marine environment is changing. The lifeform method enables datasets with different plankton sampling and taxonomic analysis methodologies to be used together to provide insights into the response to multiple stressors and robust policy evidence for decision making. Lifeform time series generated with the Plankton Lifeform Extraction Tool currently inform plankton and food web indicators for the UK's Marine Strategy, the EU's Marine Strategy Framework Directive, and for the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) biodiversity assessments. The Plankton Lifeform Extraction Tool currently integrates 155 000 samples, containing over 44 million plankton records, from nine different plankton datasets within UK and European seas, collected between 1924 and 2017. Additional datasets can be added, and time series can be updated. The Plankton Lifeform Extraction Tool is hosted by The Archive for Marine Species and Habitats Data (DASSH) at https://www.dassh.ac.uk/lifeforms/ (last access: 22 November 2021, Ostle et al., 2021). The lifeform outputs are linked to specific, DOI-ed, versions of the Plankton Lifeform Traits Master List and each underlying dataset.

Highlights

  • Plankton form the foundation of the marine food web, help to regulate ocean chemistry, and provide approximately half of the world’s oxygen (Capuzzo et al, 2018; Falkowski, 2012)

  • Large-scale trends in the abundance of individual species are challenging to compare across multiple time series due to difficulties in sampling and in counting at the species level, at the limits of the geographic range of a species

  • Our method to aggregate at the level of functional groups provides a tractable approach to reveal meaningful information at an intermediate level of organization that is still ecologically relevant

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Summary

Introduction

Plankton form the foundation of the marine food web, help to regulate ocean chemistry, and provide approximately half of the world’s oxygen (Capuzzo et al, 2018; Falkowski, 2012). The International Group of Marine Ecological Time Series (IGMETS, https://igmets.net, last access: 22 November 2021; O’Brien et al, 2017) represents valuable progress towards this goal: it provides a global-scale compilation of pelagic time series, with a tool to summarize visualizations of trends across a variety of temporal and spatial scales. This initiative summarizes time trends of highly aggregated variables (e.g. total zooplankton) for multiple sites. The tool is a key step towards transparent and standardized assessment, allowing the integration of information from multiple datasets at multiple spatial and temporal scales

Plankton datasets
Plankton sampling and analysis methodology
Spatio-temporal data distribution
Plankton lifeforms
Plankton Lifeform Extraction Tool functionality
Lifeform outputs
Discussion
5636 Appendix A
Findings
5638 Appendix B
Full Text
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