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Phytoplankton are crucial to marine ecosystem functioning and are important indicators of environmental change. Phytoplankton data are also essential for informing management and policy, particularly in supporting the new generation of marine legislative drivers, which take a holistic ecosystem approach to management. The Marine Strategy Framework Directive (MSFD) seeks to achieve Good Environmental Status (GES) of European seas through the implementation of such a management approach. This is a regional scale directive which recognises the importance of plankton communities in marine ecosystems; plankton data at the appropriate spatial, temporal and taxonomic scales are therefore required for implementation. The Continuous Plankton Recorder (CPR) survey is a multidecadal, North Atlantic basin scale programme which routinely records approximately 300 phytoplankton taxa. Because of these attributes, the survey plays a key role in the implementation of the MSFD and the assessment of GES in the Northeast Atlantic region. This paper addresses the role of the CPR's phytoplankton time-series in delivering GES through the development and informing of MSFD indicators, the setting of targets against a background of climate change and the provision of supporting information used to interpret change in non-plankton indicators. We also discuss CPR data in the context of other phytoplankton data types that may contribute to GES, as well as explore future possibilities for the use of new and innovative applications of CPR phytoplankton datasets in delivering GES. Efforts must be made to preserve long-term time series, such as the CPR, which supply vital ecological information used to informed evidence-based environmental policy.

Abstract The EU Marine Strategy Framework Directive (MSFD) requires that Good Environmental Status (GEnS), is achieved for European seas by 2020. These may deviate from GEnS, its 11 Descriptors, targets and baselines, due to endogenic managed pressures (from activities within an area) and externally due to exogenic unmanaged pressures (e.g. climate change). Conceptual models detail the likely or perceived changes expected on marine biodiversity and GEnS Descriptors in the light of climate change. We emphasise that marine management has to accommodate 'shifting baselines' caused by climate change particularly during GEnS monitoring, assessment and management and 'unbounded boundaries' given the migration and dispersal of highly-mobile species. We suggest climate change may prevent GEnS being met, but Member States may rebut legal challenges by claiming that this is outside its control, force majeure or due to 'natural causes' (Article 14 of the MSFD). The analysis is relevant to management of other global seas.

Phytoplankton are crucial to marine ecosystem functioning and are important indicators of environmental change. Phytoplankton data are also essential for informing management and policy, particularly in supporting the new generation of marine legislative drivers, which take a holistic ecosystem approach to management. The Marine Strategy Framework Directive (MSFD) seeks to achieve Good Environmental Status (GES) of European seas through the implementation of such a management approach. This is a regional scale directive which recognises the importance of plankton communities in marine ecosystems; plankton data at the appropriate spatial, temporal and taxonomic scales are therefore required for implementation. The Continuous Plankton Recorder (CPR) survey is a multidecadal, North Atlantic–basin scale programme which routinely records approximately 300 phytoplankton taxa. Because of these attributes, the survey plays a key role in the implementation of the MSFD and the assessment of GES in the Northeast Atlantic region. This paper addresses the role of the CPR's phytoplankton time-series in delivering GES through the development and informing of MSFD indicators, the setting of targets against a background of climate change and the provision of supporting information used to interpret change in non-plankton indicators. We also discuss CPR data in the context of other phytoplankton data types that may contribute to GES, as well as explore future possibilities for the use of new and innovative applications of CPR phytoplankton datasets in delivering GES. Efforts must be made to preserve long-term time series, such as the CPR, which supply vital ecological information used to informed evidence-based environmental policy.

Marine environmental legislation is increasingly expressing a need to consider the quality of pelagic habitats. This paper uses the European Union marine strategy framework to explore the concept of good environmental status (GES) of pelagic habitat with the aim to build a wider understanding of the issue. Pelagic ecosystems have static, persistent and ephemeral features, with manageable human activities primarily impacting the persistent features. The paper explores defining the meaning of "good", setting boundaries to assess pelagic habitat and the challenges of considering habitat biodiversity in a moving medium. It concludes that for pelagic habitats to be in GES and able to provide goods and services to humans, three conditions should be met: (i) all species present under current environmental conditions should be able to find the pelagic habitats essential to close their life cycles; (ii) biogeochemical regulation is maintained at normal levels; (iii) critical physical dynamics and movements of biota and water masses at multiple scales are not obstructed. Reference points for acceptable levels of each condition and how these may change over time in line with prevailing oceanographic conditions, should be discussed by knowledge brokers, managers and stakeholders. Managers should think about a habitat hydrography rather than a habitat geography. Setting the bounds of the habitats requires a consideration of dimension, scale and gradients. It is likely that to deal with the challenges caused by a dynamic environment and the relevance of differing spatial and temporal scales, we will need to integrate multidisciplinary empirical data sets with spatial and temporal models to assess and monitor progress towards, or displacement from GES of the pelagic habitat.

Marine environmental legislation is increasingly expressing a need to consider the quality of pelagic habitats. This paper uses the European Union marine strategy framework to explore the concept of good environmental status (GES) of pelagic habitat with the aim to build a wider understanding of the issue. Pelagic ecosystems have static, persistent and ephemeral features, with manageable human activities primarily impacting the persistent features. The paper explores defining the meaning of "good", setting boundaries to assess pelagic habitat and the challenges of considering habitat biodiversity in a moving medium. It concludes that for pelagic habitats to be in GES and able to provide goods and services to humans, three conditions should be met: (i) all species present under current environmental conditions should be able to find the pelagic habitats essential to close their life cycles; (ii) biogeochemical regulation is maintained at normal levels; (iii) critical physical dynamics and movements of biota and water masses at multiple scales are not obstructed. Reference points for acceptable levels of each condition and how these may change over time in line with prevailing oceanographic conditions, should be discussed by knowledge brokers, managers and stakeholders. Managers should think about a habitat hydrography rather than a habitat geography. Setting the bounds of the habitats requires a consideration of dimension, scale and gradients. It is likely that to deal with the challenges caused by a dynamic environment and the relevance of differing spatial and temporal scales, we will need to integrate multidisciplinary empirical data sets with spatial and temporal models to assess and monitor progress towards, or displacement from GES of the pelagic habitat.

Sustainable management and conservation of the world's oceans requires effective monitoring, evaluation, and reporting (MER). Despite the growing political and social imperative for these activities, there are some persistent and emerging challenges that marine practitioners face in undertaking these activities. In 2015, a diverse group of marine practitioners came together to discuss the emerging challenges associated with marine MER, and potential solutions to address these challenges. Three emerging challenges were identified: (i) the need to incorporate environmental, social and economic dimensions in evaluation and reporting; (ii) the implications of big data, creating challenges in data management and interpretation; and (iii) dealing with uncertainty throughout MER activities. We point to key solutions to address these challenges across MER activities: (i) integrating models into marine management systems to help understand, interpret, and manage the environmental and socio-economic dimensions of uncertain and complex marine systems; (ii) utilizing big data sources and new technologies to collect, process, store, and analyze data; and (iii) applying approaches to evaluate, account for, and report on the multiple sources and types of uncertainty. These solutions point towards a potential for a new wave of evidence-based marine management, through more innovative monitoring, rigorous evaluation and transparent reporting. Effective collaboration and institutional support across the science–management–policy interface will be crucial to deal with emerging challenges, and implement the tools and approaches embedded within these solutions.

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 ex�amination 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 in�dicators 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.

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.