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In order to assist fisheries managers, ecological indicators are needed to evaluate the effects of fishing activities on marine ecosystems and to improve communication of these effects in both public and scientific contexts. Finding appropriate indicators is challenging given the complexity of marine food webs as well as the ecosystem response to fishing pressure. In this study, an end-to-end model developed in the Gulf of Gabes ecosystem (Tunisia) was used to compare the performance of a set of ecosystem indicators in assessing the impact of fishing. This end-to-end model aimed to represent the ecosystem functioning by coupling two existing sub-models, the multispecies individual-based model OSMOSE, representing the dynamics of exploited species and the biogeochemical model Eco3M-Med. The aim of the indicator selection method is to evaluate the sensitivity of a set of ecological indicators regardless the fishing management plan. This method was performed in two major steps. The first step consisted in simulating three simple contrasted fishing strategies in the OSMOSE model exploiting target species (i.e. high trophic level, low trophic level or all species) and then applying a fishing effort multiplier for each fishing strategy to the focus target species. In the second step, three paradigms defining the desirable properties of an ecological indicator have been specified: i/the indicator decreases with increasing fishing pressure, ii/the indicator responds linearly to an increase in fishing pressure and iii/the indicator responds consistently across different fishing strategies. Our results highlighted that the majority of indicators have quite similar performance regarding the trend and the linearity of their responses. However, the size-based indicators seem to be the most robust to track ecosystem effects of fishing when the fishing strategy changes. A focus on size-based indicators showed that Large Fish Indicators (40 cm) derived from demersal or all surveyed

The end-to-end OSMOSE-GoL model parameterized, calibrated and evaluated for the Gulf of Lions ecosystem (Northwestern Mediterranean Sea) has been used to investigate the effects of introducing two-ways coupling between the dynamics of Low and High Trophic Level groups. The use of a fully dynamic two-ways coupling between the models of Low and High Trophic Levels organisms provided some insights in the functioning of the food web in the Gulf of Lions. On the whole microphytoplankton and mesozooplankton were found to be preyed upon by High Trophic Levels planktivorous groups at rates lower than 20% and 30% of their respective natural mortality rates, but these relatively low rates involved some important alterations in the infra-seasonal and annual cycles of both High and Low Trophic Levels groups. They induced significant changes in biomass, fisheries landings and food web interactions by cascading effects. Spatial differential impacts of High Trophic Levels predation on plankton are less clear except in areas in which primary productivity is high. Higher predation rates on plankton groups were encountered within the area of the Rhone river's influence and in areas associated to the presence of mesoscale eddies in the Northwestern part of the Gulf of Lions, especially. Generally, the pressure of the High Trophic Levels predation was the highest in areas of highest biomass whatever the plankton group considered. The two-ways coupling between Low and High Trophic Levels models revealed both bottom-up and top-down controls in the ecosystem with effects on planktivorous species similar to those observed in the field. The use of the end-to-end model enabled to propose a set of potential mechanisms that may explain the observed decrease in small pelagic catches by the French Mediterranean artisanal fisheries over the last decade.

The human impact on life on Earth has increased sharply since the 1970s, driven by the demands of a growing population with rising average per capita income. Nature is currently supplying more materials than ever before, but this has come at the high cost of unprecedented global declines in the extent and integrity of ecosystems, distinctness of local ecological communities, abundance and number of wild species, and the number of local domesticated varieties. Such changes reduce vital benefits that people receive from nature and threaten the quality of life of future generations. Both the benefits of an expanding economy and the costs of reducing nature's benefits are unequally distributed. The fabric of life on which we all depend-nature and its contributions to people-is unravelling rapidly. Despite the severity of the threats and lack of enough progress in tackling them to date, opportunities exist to change future trajectories through transformative action. Such action must begin immediately, however, and address the root economic, social, and technological causes of nature's deterioration.

The Mediterranean Sea is one of the main hotspots of marine biodiversity in the world. The combined pressures of fishing activity and climate change have also made it a hotspot of global change amidst increasing concern about the worsening status of exploited marine species. To anticipate the impacts of global changes in the Mediterranean Sea, more integrated modelling approaches are needed, which can then help policymakers prioritize management actions and formulate strategies to mitigate impacts and adapt to changes. The aim of this study was to develop a holistic model of marine biodiversity in the Mediterranean Sea with an explicit representation of the spatial, multispecies dynamics of exploited resources subject to the combined influence of climate variability and fishing pressure. To this end, we used the individual-based OSMOSE model (Object-oriented Simulator of Marine ecOSystEms), including 100 marine species (fish, cephalopods and crustaceans) representing about 95% of the total declared catch, at a high spatial resolution (400 km2) and a large spatial scale (the entire Mediterranean basin) – the first time such a resolution and scale have been modelled. We then combined OSMOSE with the NEMOMED 12 physical model and the Eco3M-S biogeochemical low trophic level model to build the end-to-end model, OSMOSE-MED. We fitted OSMOSE-MED model with observed or estimated biomass and commercial catch data using a likelihood approach and an evolutionary optimization algorithm. The outputs of OSMOSE-MED were then verified against observed biomass and catch data, and compared with independent datasets (MEDITS data, diet composition and trophic levels). The model results – at different hierarchical levels, from individuals to the scale of the ecosystem – were consistent with current knowledge of the structure, functioning and dynamics of the ecosystems in the Mediterranean Sea. While the model could be further improved in future iterations, all the modelling steps – the

Moving toward ecosystem-based fisheries management (EBFM) necessitates a suite of ecological indicators that are responsive to fishing pressure, capable of tracking changes in the state of marine ecosystems, and related to management objectives. In this study, we employed the gradient forest method to assess the performance of 14 key ecological indicators in terms of specificity, sensitivity and the detection of thresholds for EBFM across ten marine ecosystems using four modelling frameworks (Ecopath with Ecosim, OSMOSE, Atlantis, and a multi-species size-spectrum model). Across seven of the ten ecosystems, high specificity to fishing pressure was found for most of the 14 indicators. The indicators biomass to fisheries catch ratio (B/C), mean lifespan and trophic level of fish community were found to have wide utility for evaluating fishing impacts. The biomass indicators, which have been identified as Essential Ocean Variables by the Global Ocean Observing System (GOOS), had lower performance for evaluating fishing impacts, yet they were most sensitive to changes in primary productivity. The indicator B/C was most sensitive to low levels of fishing pressure with a generally consistent threshold response around 0.4*FMSY (fishing mortality rate at maximum sustainable yield) across nine of the ten ecosystems. Over 50% of the 14 indicators had threshold responses at, or below ∼0.6* FMSY for most ecosystems, indicating that these ecosystems would have already crossed a threshold for most indicators when fished at FMSY. This research provides useful insights on the performance of indicators, which contribute to facilitating the worldwide move toward EBFM.

Systematic Conservation Planning (SCP) is a widely-used approach to develop networks of protected areas. A crucial step in the SCP process is to set conservation targets for biodiversity features (explicit goals that quantify the minimum amount of each biodiversity feature to be covered by the protected areas). When the biodiversity features are different habitats occurring in the planning region, a relevant approach, based on the Species-Area Relationship (SAR), defines targets so as to maximize biodiversity representation within each habitat type. While many formulations of the SAR exist, their application remains dominated by the log-transformation of Power-law model. However, documented habitat-related and taxonomic idiosyncrasies in the shape of the SAR question the effectiveness of a given ubiquitous model in fitting data compared to others. Here, using 13 SAR functional forms, we investigate whether the habitat-related SAR uncertainties propagate across the entire conservation planning process and lead to both divergent conservation targets and conservation solutions for six habitats in the Mediterranean sea. Results revealed uncertainties in model selection across habitats, which leads to different SAR habitat-targets. Constraining a systemic conservation planning tool (Marxan) with those targets provided contrasted sets of priority areas for different SAR scenario. Our study demonstrated that restraining to one particular SAR model is inappropriate at fitting all SAR datasets, providing consequently conservation targets diverging markedly from data-driven SAR inferences. More importantly, corresponding reserve networks are either inefficient or overstated for the protection of habitats, leading to waste of scarce conservation resources that should be used sparingly. Therefore, we suggest to evaluate different SAR models and, when appropriate to carry out a multi-model inference to provide robust habitat-specific conservation targets.

Moving toward ecosystem-based fisheries management (EBFM) necessitates a suite of ecological indicators that are responsive to fishing pressure, capable of tracking changes in the state of marine ecosystems, and related to management objectives. In this study, we employed the gradient forest method to assess the performance of 14 key ecological indicators in terms of specificity, sensitivity and the detection of thresholds for EBFM across ten marine ecosystems using four modelling frameworks (Ecopath with Ecosim, OSMOSE, Atlantis, and a multi-species size-spectrum model). Across seven of the ten ecosystems, high specificity to fishing pressure was found for most of the 14 indicators. The indicators biomass to fisheries catch ratio (B/C), mean lifespan and trophic level of fish community were found to have wide utility for evaluating fishing impacts. The biomass indicators, which have been identified as Essential Ocean Variables by the Global Ocean Observing System (GOOS), had lower performance for evaluating fishing impacts, yet they were most sensitive to changes in primary productivity. The indicator B/C was most sensitive to low levels of fishing pressure with a generally consistent threshold response around 0.4*F (fishing mortality rate at maximum sustainable yield) across nine of the ten ecosystems. Over 50% of the 14 indicators had threshold responses at, or below ∼0.6* F for most ecosystems, indicating that these ecosystems would have already crossed a threshold for most indicators when fished at F. This research provides useful insights on the performance of indicators, which contribute to facilitating the worldwide move toward EBFM

While the physical dimensions of climate change are now routinely assessed through multimodel intercomparisons, projected impacts on the global ocean ecosystem generally rely on individual models with a specific set of assumptions. To address these single-model limitations, we present standardized ensemble projections from six global marine ecosystem models forced with two Earth system models and four emission scenarios with and without fishing. We derive average biomass trends and associated uncertainties across the marine food web. Without fishing, mean global animal biomass decreased by 5% (±4% SD) under low emissions and 17% (±11% SD) under high emissions by 2100, with an average 5% decline for every 1 °C of warming. Projected biomass declines were primarily driven by increasing temperature and decreasing primary production, and were more pronounced at higher trophic levels, a process known as trophic amplification. Fishing did not substantially alter the effects of climate change. Considerable regional variation featured strong biomass increases at high latitudes and decreases at middle to low latitudes, with good model agreement on the direction of change but variable magnitude. Uncertainties due to variations in marine ecosystem and Earth system models were similar. Ensemble projections performed well compared with empirical data, emphasizing the benefits of multimodel inference to project future outcomes. Our results indicate that global ocean animal biomass consistently declines with climate change, and that these impacts are amplified at higher trophic levels. Next steps for model development include dynamic scenarios of fishing, cumulative human impacts, and the effects of management measures on future ocean biomass trends

Measurements of the status and trends of key indicators for the ocean and marine life are required to inform policy and management in the context of growing human uses of marine resources, coastal development, and climate change. Two synergistic efforts identify specific priority variables for monitoring: Essential Ocean Variables (EOVs) through the Global Ocean Observing System (GOOS), and Essential Biodiversity Variables (EBVs) from the Group on Earth Observations Biodiversity Observation Network (GEO BON) (see Data Sheet 1 in Supplementary Materials for a glossary of acronyms). Both systems support reporting against internationally agreed conventions and treaties. GOOS, established under the auspices of the Intergovernmental Oceanographic Commission (IOC), plays a leading role in coordinating global monitoring of the ocean and in the definition of EOVs. GEO BON is a global biodiversity observation network that coordinates observations to enhance management of the world's biodiversity and promote both the awareness and accounting of ecosystem services. Convergence and agreement between these two efforts are required to streamline existing and new marine observation programs to advance scientific knowledge effectively and to support the sustainable use and management of ocean spaces and resources. In this context, the Marine Biodiversity Observation Network (MBON), a thematic component of GEO BON, is collaborating with GOOS, the Ocean Biogeographic Information System (OBIS), and the Integrated Marine Biosphere Research (IMBeR) project to ensure that EBVs and EOVs are complementary, representing alternative uses of a common set of scientific measurements. This work is informed by the Joint Technical Commission for Oceanography and Marine Meteorology (JCOMM), an intergovernmental body of technical experts that helps international coordination on best practices for observing, data management and services, combined with capacity development expertise. Characterizing bi

Sustained observations of marine biodiversity and ecosystems focused on specific conservation and management problems are needed around the world to effectively mitigate or manage changes resulting from anthropogenic pressures. These observations, while complex and expensive, are required by the international scientific, governance and policy communities to provide baselines against which the effects of human pressures and climate change may be measured and reported, and resources allocated to implement solutions. To identify biological and ecological essential ocean variables (EOVs) for implementation within a global ocean observing system that is relevant for science, informs society, and technologically feasible, we used a driver-pressure-state-impact-response (DPSIR) model. We (1) examined relevant international agreements to identify societal drivers and pressures on marine resources and ecosystems, (2) evaluated the temporal and spatial scales of variables measured by 100+ observing programs, and (3) analysed the impact and scalability of these variables and how they contribute to address societal and scientific issues. EOVs were related to the status of ecosystem components (phytoplankton and zoo-plankton biomass and diversity, and abundance and distribution of fish, marine turtles, birds and mammals), and to the extent and health of ecosystems (cover and composition of hard coral, seagrass, mangrove and macroalgal canopy). Benthic invertebrate abundance and distribution and microbe diversity and biomass were identified as emerging EOVs to be developed based on emerging requirements and new technologies. The temporal scale at which any shifts in biological systems will be detected will vary across the EOVs, the properties being monitored and the length of the existing time-series. Global implementation to deliver useful products will require collaboration of the scientific and policy sectors and a significant commitment to improve human and infrastructure cap

There is an increasing need to understand community-level or whole-ecosystem responses to multiple stressors since the impacts of multiple stressors on marine systems depend not only on species- level responses, but also on species interactions and ecosystem structure. In this study, we used a multi-model ecosystem simulation approach to explore the combined effects of fishing and primary productivity on different components of the food-web across a suite of ecosystems and a range of model types. Simulations were carried out under different levels of primary productivity and various fishing scenarios (targeting different trophic levels). Previous work exploring the effects of multiple stressors often assumed that the combined effects of stressors are additive, synergistic or antagonis- tic. In this study, we included a fourth category “dampened”, which refers to less negative or to less positive impacts on a given ecosystem component compared to additive effects, and in contrast to pre- vious studies, we explicitly considered the direction of the combined effects (positive or negative). We focused on two specific combined effects (negative synergism and positive dampened) associ- ated with the ecological risk of resultant lower fish biomass than expected under additive effects. Through a meta-analysis of the multi-models’ simulation results, we found that (i) the risk of negative synergism was generally higher for low-trophic-level (LTL) taxa, implying that following an increase of fishing pressure on a given LTL stock, the subsequent decrease of biomass under low primary productivity would be higher than expected when fishing is the sole driver and (ii) the risk of pos- itive dampened effects was generally higher for high-trophic-level (HTL) taxa, implying that given a management measure aimed at reducing the impact of fishing on HTL stocks, the subsequent rebuild- ing of these stocks would be slower than expected if only fishing were considered. Our approach to ca

Developing enduring capacity to monitor ocean life requires investing in people and their institutions to build infrastructure, ownership, and long-term support networks. International initiatives can enhance access to scientific data, tools and methodologies, and develop local expertise to use them, but without ongoing engagement may fail to have lasting benefit. Linking capacity development and technology transfer to sustained ocean monitoring is a win-win proposition. Trained local experts will benefit from joining global communities of experts who are building the comprehensive Global Ocean Observing System (GOOS). This two-way exchange will benefit scientists and policy makers in developing and developed countries. The first step toward the GOOS is complete: identification of an initial set of biological Essential Ocean Variables (EOVs) that incorporate the Group on Earth Observations (GEO) Essential Biological Variables (EBVs), and link to the physical and biogeochemical EOVs. EOVs provide a globally consistent approach to monitoring where the costs of monitoring oceans can be shared and where capacity and expertise can be transferred globally. Integrating monitoring with existing international reporting and policy development connects ocean observations with agreements underlying many countries' commitments and obligations, including under SDG 14, thus catalyzing progress toward sustained use of the ocean. Combining scientific expertise with international capacity development initiatives can help meet the need of developing countries to engage in the agreed United Nations (UN) initiatives including new negotiations for the conservation and sustainable use of marine biological diversity of areas beyond national jurisdiction, and the needs of the global community to understand how the ocean is changing.

There is an increasing need to understand ecosystem responses to multiple stressors in that such complex responses depend not only on species-level responses, but also on species interactions and ecosystem structure. In this study, we used a multi-model ecosystem simulation approach to explore the combined effects of fishing and primary productivity on different components of the food-web across a suite of ecosystems and a range of model types. Simulations were carried out under different levels of primary productivity and various fishing scenarios. In addition to exploring synergistic, additive or antagonistic combined effects of multiple stressors, we included a fourth category “dampened”, which refers to less negative or less positive impacts compared to additive ones, and in contrast to previous studies, we explicitly considered the direction (positive or negative) of the combined effects. We focused on two specific combined effects (negative synergism and positive dampened) associated with the risk of resultant lower fish biomass than expected under additive effects. Through a meta-analysis of the multi-models' simulation results, we found that (i) the risk of negative synergism was generally higher for low-trophic-level (LTL) taxa, implying that following an increase of fishing pressure on a given LTL stock, the subsequent decrease of biomass under low primary productivity would be larger than expected under additive effects and (ii) the risk of positive dampened effects was generally higher for high-trophic-level (HTL) taxa, implying that given a management measure aimed at reducing the impact of fishing on HTL stocks, the subsequent rebuilding of these stocks would be slower than expected. Our approach to categorizing and exploring cumulative effects can be applied to evaluate other community properties, and provide guidance for fisheries management

Ecological indicators are widely used to characterise ecosystem health. In the marine environment, indicators have been developed to assess the ecosystem effects of fishing to support an ecosystem approach to fisheries. However, very little work on the performance and robustness of ecological indicators has been carried out. An important aspect of robustness is that indicators should respond specifically to changes in the pressures they are designed to detect (e.g. fishing) rather than changes in other drivers (e.g. environment). We adopted a multi-model approach to compare and test the specificity of commonly used ecological indicators to capture fishing effects in the presence of environmental change and under different fishing strategies. We tested specificity in the presence of two types of environmental change: “random” representing interannual climate variability and “directional” representing climate change. We used phytoplankton biomass as a proxy of the environmental conditions, as this driver was comparable across all ecosystem models, then applied a signal-to-noise ratio analysis to test the specificity of indicators with random environmental change. For directional change, we used mean gradients to apportion the quantity of change in the indicators due to fishing and the environment. We found that depending on the fishing strategy and environmental change, ecological indicators could range from high to low specificity to fishing. As expected, the specificity of indicators to fishing almost always decreased as environmental variability increased. In 55–76% of the scenarios run with directional change in phytoplankton biomass across fishing strategies and ecosystem models, indicators were significantly more responsive to changes in fishing than to changes in phytoplankton biomass. This important result makes the tested ecological indicators good candidates to support fisheries management in a changing environment. Among the indicators, the catch over bioma

Fisheries have had major negative impacts on marine ecosystems, and effective fisheries management and governance are needed to achieve sustainable fisheries, biodiversity conservation goals and thus good ecosystem status. To date, the IndiSeas programme (Indicators for the Seas) has focussed on assessing the ecological impacts of fishing at the ecosystem scale using ecological indicators. Here, we explore fisheries Management Effectiveness' and Governance Quality' and relate this to ecosystem health and status. We developed a dedicated expert survey, focused at the ecosystem level, with a series of questions addressing aspects of management and governance, from an ecosystem-based perspective, using objective and evidence-based criteria. The survey was completed by ecosystem experts (managers and scientists) and results analysed using ranking and multivariate methods. Results were further examined for selected ecosystems, using expert knowledge, to explore the overall findings in greater depth. Higher scores for Management Effectiveness' and Governance Quality' were significantly and positively related to ecosystems with better ecological status. Key factors that point to success in delivering fisheries and conservation objectives were as follows: the use of reference points for management, frequent review of stock assessments, whether Illegal, Unreported and Unregulated (IUU) catches were being accounted for and addressed, and the inclusion of stakeholders. Additionally, we found that the implementation of a long-term management plan, including economic and social dimensions of fisheries in exploited ecosystems, was a key factor in successful, sustainable fisheries management. Our results support the thesis that good ecosystem-based management and governance, sustainable fisheries and healthy ecosystems go together.

Ecosystem models are valuable tools for informing fisheries management due to their ability to simulate the spatial dynamics of modelled species, their trophic interactions, and their responses to fishing in an ecosystem context. In this study, we developed an OSMOSE (Objectoriented Simulator of Marine Ecosystems Exploitation) model for the Pacific North Coast Integrated Management Area (PNCIMA) ecosystem off western Canada, which simulated the entire life cycle of six key species and for the first time integrated spatial population structure and "background" taxa. Background taxa are of secondary importance for the study at hand but have the potential to be important prey or predators of the key species. The primary aim of the study was to explore how the population dynamics of the key species differed over time and different management areas, with results focusing on Pacific Herring (Clupea pallasii) and Pacific Cod (Gadus macrocephalus) that have been assessed on a single-species basis in the last 5 years. Results found that the population dynamics of a specific species varied in different management areas due to differences in species interactions particularly in the form of predation mortality, which supports the current areaspecific assessment and management framework. The study also indicated that increasing predation mortality may have caused the decline of the Pacific Cod populations. By contrast, increasing starvation mortality was found to be a limiting factor for the Pacific Herring populations. The discoveries from these OSMOSE simulations provide important information for fisheries management within the PNCIMA ecosystem.

Fisheries have had major negative impacts on marine ecosystems, and effective fisheries management and governance are needed to achieve sustainable fisheries, biodiversity conservation goals and thus good ecosystem status. To date, the IndiSeas programme (Indicators for the Seas) has focussed on assessing the ecological impacts of fishing at the ecosystem scale using ecological indicators. Here, we explore fisheries ‘Management Effectiveness’ and ‘Governance Quality’ and relate this to ecosystem health and status. We developed a dedicated expert survey, focused at the ecosystem level, with a series of questions addressing aspects of management and governance, from an ecosystem-based perspective, using objective and evidence-based criteria. The survey was completed by ecosystem experts (managers and scientists) and results analysed using ranking and multivariate methods. Results were further examined for selected ecosystems, using expert knowledge, to explore the overall findings in greater depth. Higher scores for ‘Management Effectiveness’ and ‘Governance Quality’ were significantly and positively related to ecosystems with better ecological status. Key factors that point to success in delivering fisheries and conservation objectives were as follows: the use of reference points for management, frequent review of stock assessments, whether Illegal, Unreported and Unregulated (IUU) catches were being accounted for and addressed, and the inclusion of stakeholders. Additionally, we found that the implementation of a long-term management plan, including economic and social dimensions of fisheries in exploited ecosystems, was a key factor in successful, sustainable fisheries management. Our results support the thesis that good ecosystem-based management and governance, sustainable fisheries and healthy ecosystems go together

Trophic level (TL)-based indicators are commonly used to track the ecosystem effects of fishing as the selective removal of organisms from the food web may result in changes to the trophic structure of marine ecosystems. The use of a fixed TL per species in the calculation of TL-based indicators has been questioned, given that species’ TLs vary with ontogeny, as well as over time and space. We conducted a model-based assessment of the performance of fixed TL-based indicators vs. variable TL-based indicators for tracking the effects of fishing pressure. This assessment considered three TL-based indicators (the trophic level of the landed catch (TLc), the marine trophic index (MTI) and the trophic level of the surveyed community (TLsc)), three fishing scenarios that targeted specific model groups (the low TL scenario (LTL), the high TL scenario (HTL) and a scenario encompassing broad-scale exploitation (ALL)) and ten contrasting marine ecosystems with four types of ecosystem modelling approaches that differ in their structure and assumptions. Results showed that, overall, variable TL-based indicators have a greater capacity for detecting the effects of fishing pressure than fixed TL-based indicators. Across TL-based indicators, TLsc displayed the most consistent response to fishing whether fixed or variable species' TLs were used, as well as the highest capacity for detecting fishing effects. This result supports previous studies that promote the use of survey-based indicators over catch-based indicators to explore the impacts of fishing on the structure of marine ecosystems. Across fishing scenarios, the low trophic level fishing scenario (LTL) resulted in the lowest consistency between fixed and variable TL-based indicator responses and the lowest capacity of TL-based indicators for detecting fishing effects. Overall, our results speak to the need for caution when interpreting TL-based indicator trends, and knowledge of the broader context, such as fishing strategie