Description: Combining the existing knowledge on links between functional characteristics of phytoplankton taxa and food web functioning with the methods from long-term data analysis, we present an approach for using phytoplankton monitoring data to draw conclusions on potential effects of phytoplankton taxonomic composition on the next trophic level. This information can be used as a part of marine food web assessments required by the Marine Strategy Framework Directive of the European Union. In this approach, both contemporary taxonomic composition and recent trends of changes are used to assess their potential consequences for food web functioning. The approach consists of four steps: (1) long-term trend analysis of class-level and total phytoplankton biomass using generalized additive models (GAMs) and calculating average biomass share of each phytoplankton class from the total phytoplankton biomass, (2) comparing the current phytoplankton community composition and its long-term changes with non-metric ordination analysis (NMDS) of genus-level biomass, (3) describing which taxa (the most accurate taxonomic level) are primarily responsible for forming the biomass and for causing the possible changes, and (4) interpretation of the phytoplankton results to assess the potential effects on the next trophic level. Within step 4, special attention is given to the following characteristic of taxa: potential suitability or quality as food for grazers, harmfulness, size, and trophy. These characteristics are selected based on existing scientific knowledge on their relevance to the higher trophic levels. In this article, we present the concept of the suggested approach and demonstrate the phytoplankton analyses with multi-decadal monitoring data from the northern Baltic Sea. We also discuss the future development of the approach toward a food web index by combining or replacing the taxonomic analyses with functional trait-based approaches.

Description: A Catalogue of Marine Biodiversity Indicators was developed with the aim of providing the basis for assessing the environmental status of the marine ecosystems. Useful for the implementation of the Marine Strategy Framework Directive (MSFD), this catalogue allows the navigation of a database of indicators mostly related to biological diversity, non-indigenous species, food webs, and seafloor integrity. Over 600 indicators were compiled, which were developed and used in the framework of different initiatives (e.g., EU policies, research projects) and in national and international contexts (e.g., Regional Seas Conventions, and assessments in non-European seas). The catalogue reflects the current scientific capability to address environmental assessment needs by providing a broad coverage of the most relevant indicators for marine biodiversity and ecosystem integrity. The available indicators are reviewed according to their typology, data requirements, development status, geographical coverage, relevance to habitats or biodiversity components, and related human pressures. Through this comprehensive overview, we discuss the potential of the current set of indicators in a wide range of contexts, from large-scale to local environmental programs, and we also address shortcomings in light of current needs. Developed by the DEVOTES Project, the catalogue is freely available through the DEVOTool software application, which provides browsing and query options for the associated metadata. The tool allows extraction of ranked indicator lists best fulfilling selected criteria, enabling users to search for suitable indicators to address a particular biodiversity component, ecosystem feature, habitat, or pressure in a marine area of interest. This tool is useful for EU Member States, Regional Sea Conventions, the European Commission, non-governmental organizations, managers, scientists, and any person interested in marine environmental assessment. It allows users to build, complement or adjust monitoring programs and has the potential to improve comparability and foster transfer of knowledge across marine regions.

Description: Highlights: • A simple quantitative method for choosing ecological indicators and target ranges is proposed. • Sustainable use of ecosystems requires freedom of usage choice for each generation. • Sustainability so limits any state indicator to the range from which timely recovery is feasible. • Relevant state indicators are those that anthropogenic pressure might drive out of this range. • The method extends to pressure- and auxiliary indicators, and suites of indicators. Abstract: Wide-ranging, indicator-based assessments of large, complex ecosystems are playing an increasing role in guiding environmental policy and management. An example is the EU’s Marine Strategy Framework Directive, which requires Member States to take measures to reach “good environmental status” (GES) in European marine waters. However, formulation of indicator targets consistent with the Directive’s high-level policy goal of sustainable use has proven challenging. We develop a specific, quantitative interpretation of the concepts of GES and sustainable use in terms of indicators and associated targets, by sharply distinguishing between current uses to satisfy current societal needs and preferences, and unknown future uses. We argue that consistent targets to safeguard future uses derive from a requirement that any environmental state indicator should recover within a defined time (e.g. 30 years) to its pressure-free range of variation when all pressures are hypothetically removed. Within these constraints, specific targets for current uses should be set. Routes to implementation of this proposal for indicators of fish-community size structure, population size of selected species, eutrophication, impacts of non-indigenous species, and genetic diversity are discussed. Important policy implications are that (a) indicator target ranges, which may be wider than natural ranges, systematically and rationally derive from our proposal; (b) because relevant state indicators tend to respond slowly, corresponding pressures should also be monitored and assessed; (c) support of current uses and safeguarding of future uses are distinct management goals, they require different types of targets, decision processes, and management philosophies.

Description: Vital processes relevant for exploited stocks, for example growth, predation and recruitment are closely related to the environmental conditions. Here, we present a generic method to include state of the art knowledge on environmental impacts and environmental forecasting into short-term predictions and the formulation of environment-based harvest control rules for exploited stocks. The method consists of three elements: First, the linkage between environmental parameters and stock dynamics, second the short-term prediction of both environment and stock dynamics, and third the scaling of otherwise constant reference values for fishing mortality in accordance with the environmental situation. The method is exemplified for Eastern Baltic cod. Recruitment is treated as dependent on oxygen conditions, and the formulation of the proposed fishing intensity is accounting for the actual oxygen conditions and predicted conditions for the year following the assessment year. Finally, the resulting advice is compared to advice that has been given not accounting for the oxygen conditions.

Description: Ecosystem-based management requires understanding of food webs. Consequently, assessment of food web status is mandatory according to the European Union’s Marine Strategy Framework Directive (MSFD) for EU Member States. However, how to best monitor and assess food webs in practise has proven a challenging question. Here, we review and assess the current status of food web indicators and food web models, and discuss whether the models can help addressing current shortcomings of indicator-based food web assessments, using the Baltic Sea as an example region. We show that although the MSFD food web assessment was designed to use food web indicators alone, they are currently poorly fit for the purpose, because they lack interconnectivity of trophic guilds. We then argue that the multiple food web models published for this region have a high potential to provide additional coherence to the definition of good environmental status, the evaluation of uncertainties, and estimates for unsampled indicator values, but we also identify current limitations that stand in the way of more formal implementation of this approach. We close with a discussion of which current models have the best capacity for this purpose in the Baltic Sea, and of the way forward towards the combination of measurable indicators and modelling approaches in food web assessments.

Description: Machine learning covers a large set of algorithms that can be trained to identify patterns in data. Thanks to the increase in the amount of data and computing power available, it has become pervasive across scientific disciplines. We first highlight why machine learning is needed in marine ecology. Then we provide a quick primer on machine learning techniques and vocabulary. We built a database of & SIM;1000 publications that implement such techniques to analyse marine ecology data. For various data types (images, optical spectra, acoustics, omics, geolocations, biogeochemical profiles, and satellite imagery), we present a historical perspective on applications that proved influential, can serve as templates for new work, or represent the diversity of approaches. Then, we illustrate how machine learning can be used to better understand ecological systems, by combining various sources of marine data. Through this coverage of the literature, we demonstrate an increase in the proportion of marine ecology studies that use machine learning, the pervasiveness of images as a data source, the dominance of machine learning for classification-type problems, and a shift towards deep learning for all data types. This overview is meant to guide researchers who wish to apply machine learning methods to their marine datasets.