Managing the fishing industry is crucial to maintain a balance between the exploitation of marine resources and their natural ability to recover. To achieve such a goal, stock assessment models are built to combine commercial catches and population abundance time series. These approaches can often handle only single-species, losing the information regarding the ecological interactions affecting the dynamics of the species. Moreover, conventional stock assessment models are based on explicit deterministic equations, which can fail to represent the ecological interactions between the species and its environment. In this paper we present Maelstrom, a multispecies predictive model based on neural networks that can interpret fishery-dependent and -independent data to return a forecast of stock abundance considering variations in fishing effort. Although neural networks-based forecasting of ecological and fisheries time series is well established, we present a customizable Shiny tool in which a multi-species, age-structured framing is integrated and devised to be applied in real management frameworks. Namely, we set up five scenarios of increasing complexity in which three commercial species are considered. To assess the model's reliability, we conducted a benchmark test comparing Maelstrom to a routinely used stock assessment tool, the a4a model framework, using RMSE and MAE for validation. The results, besides showing a good degree of accuracy of Maelstrom to classical stock assessment models, endorse the potential of a multi-species approach even when working on shorter time-series. The Shiny application returns statistics, plots, and a report of all the operations conducted during the stock assessment.

The Moroccan Mediterranean region has experienced significant development in various sectors, including tourism, fishing, industry, agriculture, and construction. However, the trophic functioning of its ecosystem and its vulnerability to these developments remain largely unexplored. To address this gap, an in-depth examination of the Moroccan Mediterranean Sea ecosystem was conducted using the Ecopath with Ecosim modelling approach from 2000 to 2003. This study aimed to describe the structure, functioning and state of the system. The model incorporated 40 functional groups, including 21 fish, 12 invertebrates, 2 primary producers, and 2 detritus groups, as well as individual groups for marine mammals, seabirds, and turtles. Analysis revealed that the functional groups were organized into five trophic levels, with swordfish and bluefin tuna occupying the highest level. Results also indicated that the ecosystem structure relies heavily on high flows into detritus and exports. Transfer efficiencies values are within the typical range for aquatic environments. The model’s pedigree scored of 0.49 indicates that it was built from data of generally acceptable quality- a notable achievement given the limited availability of data for the Mediterranean Sea in Morocco. Across the entire study area, the total biomass of the modeled ecosystem (excluding detritus) was estimated at 93 t · km− 2. Indicators of omnivory showed low values across most groups. Pelagic sharks, large pelagic fish, and hake were identified as ecologically important groups within the ecosystem.

Marine ecosystems are healthy with a high degree of biodiversity. Assessing how factors affect spatial and temporal patterns of biodiversity is an essential task for the Ecosystem Based Management approach. In this work, we investigated the effect of fisheries disturbance and ocean variables in determining α- and β-diversity of Mediterranean demersal assemblages. Generalized additive mixed models were used to explain the spatio-temporal variability of diversity indices from 2014 to 2020 in three Mediterranean subregions as a function of covariates. An in-depth analysis also made it possible to decouple the effects of bottom trawling from the other covariates. The results show that several fishing activities and environmental variables influence biodiversity, but the direction of change depends on the subregion considered. Bottom trawling instead has a quasi-linear erosion effect on α- and β-diversity in all areas. Valuable commercial species and threatened rays and sharks importantly characterized the sites with low fishing impact. Results are a step towards the development of conservation and management strategies, particularly in the context of the Marine Strategy.

Spatial measures are often used to support fisheries management. The European Union, for example, has emphasized the importance of the spatial aspect to protect overfished stocks and to find a better approach to fisheries management. Nevertheless, careful selection of which marine areas to manage with greater precaution is essential to optimize their benefits. In this work, we estimated hot spots of aggregation using a species distribution model developed with template model builder (sdmTMB) on density indices (number of individuals/km2) for blackspot seabream (Pagellus bogaraveo) for two length ranges (< = 20 cm and > 20 cm). We applied the model to scientific bottom trawl surveys conducted in the Alboran Sea (western Mediterranean) and to a dataset of georeferenced commercial catches (CPUE, Catch Per Unit Effort or fishery-dependent data) in the Strait of Gibraltar. In addition, the effects of oceanographic variables on the distribution of species was tested. The identified best distributions for both length ranges are used to determine hot spots of aggregation for the two size classes from 1994 to 2021 in northern Alboran Sea, from 2018 to 2021 in southern Alboran Sea and from 2005 to 2009 in the Strait of Gibraltar area. Identified persistent hot spots (as an hotspot area across all years of the time series) represent key ecological areas for the species that might be considered in future management plans. In the Northern Alboran Sea, 5 ecologically important areas were identified for smaller size individuals and 2 for the larger sized individuals. The overlap with the current effort estimates revealed two areas (one for smaller and one for larger specimens) off Cabo de Gata and Almeria that could have significant ecological impacts with minimal socio-economic disadvantages if further protected. These could be two future management areas (e.g. Fisheries Restricted Area - FRA) that could be important for stock dynamics. The results confirm the ecological preferences of the species that were disentangled by Species Distribution Models (SDMs) as well as its useful contribution to support the management of this depleted species in the Mediterranean sea.

Ocean warming can affect plankton both directly, through altered metabolic activities, and indirectly, modifying the physical-chemical properties of the water column, with possible effects on ecosystem functioning. To evaluate the combined action of warming-related physiological responses and environmental changes on plankton functioning, we carried out a long-term analysis (from 1994 to 2019) of the Bermuda Atlantic Timeseries Study (BATS) dataset where ocean warming and stratification have driven a decrease in the net primary production over the last decade. Using the time series of plankton observations, we assembled 1000 replicates of a food web model for each year. We observed that the total flow of matter through the model remained constant over time, despite the increased oligotrophication, due to global warming, after 2014. In fact, the plankton food web remained robust through re-modulated trophic interactions with an increased detritivory to herbivory ratio of the food web over time. However, it was problematic to re-establish the trophic connections of the food web broken by ocean warming, as remarked by the increased relative internal ascendency. Thanks to trophic plasticity, the reduced zooplankton dependence on herbivory was compensated by a significant increase in the reliance on carnivory and detritivores, highlighting the crucial role of trophic interactions in buffering significant environmental short-term changes.

Certification schemes are increasingly applied in fisheries and aquaculture to promote sustainability, traceability, and responsible sourcing. However, their application to the management and exploitation of edible aquatic invasive species (AIS) remains largely unexplored. This study represents the first attempt to assess how a regional certification framework, the Adriatic Responsible Fisheries Management (ARFM) scheme, can be adapted to a fishery targeting an AIS in the Mediterranean. We focus on the case of the Atlantic blue crab (Callinectes sapidus), an invasive predator that has recently proliferated in the coastal lagoons of the northern Adriatic Sea, causing considerable ecological and economic damage, particularly to clam farming systems. To evaluate whether C. sapidus fishery aligns with ARFM certification criteria, we gathered knowledge through interviews with smallscale fishers who have developed and implemented innovative gears to control and commercially exploit the species. Our assessment found that, under current management, the C. sapidus fishery does not meet all ARFM certification requirements. Certification could only be achieved if an action plan is adopted addressing key challenges such as the absence of dedicated regulations, the need for harvest control rules, and the implementation of systematic data collection and monitoring. Our findings highlight both the opportunities and obstacles in integrating an edible AIS into responsible seafood markets, and illustrate how the ARFM scheme can guide necessary improvements towards sustainable and certified exploitation. This case study provides a valuable model for developing adaptive harvest strategies for edible AIS in the Mediterranean, where biological invasions are increasingly reshaping coastal fisheries.

Spatially-explicit models are invaluable tools for analyzing the species-environment interactions, even at scales beyond that of direct observations. In fisheries context, the observations on species usually consist of data derived from survey campaigns, such as the Mediterranean International Bottom Trawl Surveys (MEDITS) programme. MEDITS survey foresees the use of a standardized protocol for data acquisition on demersal species, such as the blue and red shrimp Aristeus antennatus and the giant red shrimp Aristaeomorpha foliacea. These two species are recognized as highly valuable marked resources accounting for about 5 % of the trawl fishing income in the Mediterranean basin. Here, we developed a modeling framework for the analysis of the MEDITS data on those species. Within our modeling framework we aimed at detecting the existence of a divergence in the spatial patterns that could guide the definition of targeted management actions for those two valuable fishing resources. A Random Forest (RF) machine learning approach has been used to model both the occurrence (i.e., presence/ absence) and the biomass index (kg/km2) of both species in four Geographical SubAreas (GSAs) located in the central part of the Mediterranean and the Ionian Sea. The RF showed high level of accuracy (i.e., K=0.83 and K=0.88, for A. antennatus and A. foliacea, respectively) in modeling species occurrence, and good level of performance (i.e., R2=0.63 and R2=0.74, respectively) in modeling their biomass index (kg/km2). The niche overlap and statistical analyses we performed on the models outputs revealed the existence of a significant divergence in the spatial patterns between these species. This provides crucial ecological knowledge for the definition of targeted (i.e., species-related) management actions. Afterwards, the models have been extrapolated at the spatial scale of the Mediterranean Sea based on an approach we defined, called hyperspace. The hyperspace approach, while showing technical and ecological soundness, was meant to guarantee the reliability of model predictions in unknown areas. It reduces the need for a proper interpretation of "what is beyond a predicted value", offering a straightforward method for model extrapolation. Our effort aims to provide insights for prioritizing key areas in conservation strategies and marine spatial planning. It also represents an important contribution towards adopting an ecosystem-based approach to fishery resource management in the Mediterranean basin.

Spatial fisheries management is widely used to reduce overfishing, rebuild stocks, and protect biodiversity. However, the effectiveness and optimization of spatial measures depend on accurately identifying ecologically meaningful areas, which can be difficult in mixed fisheries. To apply a method generally to a range of target species, we developed an ensemble of species distribution models (e-SDM) that combines general additive models, generalized linear mixed models, random forest, and gradient-boosting machine methods in a training and testing protocol. The e-SDM was used to integrate density indices from two scientific bottom trawl surveys with the geopositional data, relevant oceanographic variables from the three-dimensional physical-biogeochemical operational model, and fishing effort from the vessel monitoring system. The determined best distributions for juveniles and adults are used to determine hot spots of aggregation based on single or multiple target species. We applied e-SDM to juvenile and adult stages of 10 marine demersal species representing 60% of the total demersal landings in the central areas of the Mediterranean Sea. Using the e-SDM results, hot spots of aggregation and grounds potentially more selective were identified for each species and for the target species group of otter trawl and beam trawl fisheries. The results confirm the ecological appropriateness of existing fishery restriction areas and support the identification of locations for new spatial management measures.

Marine ecosystems associated with mid-oceanic elevations harbour unique pelagic and benthic biodiversity and sustain food webs critical for Nature’s contributions to people (NCP). The United Nations Sustainable Development Goals and the Convention on the Law of the Sea recognize the need to implement ecosystem-based management approaches to conserve the structure and functioning of oceanic and deep-sea ecosystems within sustainable reference points. However, uncertainties regarding the interactions between multiple drivers of change, and their impacts on the state of these ecosystems and the NCP, present significant challenges to effective management. Trophic models offer a holistic approach to identify the main drivers affecting the dynamics of marine ecosystems. Here, we used a food web model of the open-ocean and deep-sea environments of the Azores for identifying the drivers that best explain historical biomass trends of demersal fish of high commercial value. Our hindcast simulations suggested that historical trends can be explained by the combined effects of deep-sea fisheries exploitation and variability in environmental conditions, likely dominated by primary productivity anomalies. In particular, deficits in primary production and high levels of fishing exploitation might have contributed to the pronounced decline in biomass observed between 2008 and 2012. These findings reinforce that failure to consider environmental factors in ecosystem-based management may result in shortfalls at achieving biodiversity conservation and sustainability objectives, particularly in the context of climate change.

A collection of papers presented at the 4th International Conference on Community Ecology. (4th ComEc, Trieste, Italy) is presented.

Fishing has significant trophodynamic impacts on marine communities, including reductions in the mean trophic position (TP) of the ecosystem resulting from a decrease in the abundance and size of species and individuals with high TPs. This study demonstrates the erosion of fish TP, an additional process that results in lower TP of individuals of a given size, which may exacerbate the effects of fishing on the food web. A stable isotope approach based on the tRophicPosition Bayesian method was used to quantify the TP of 12 target marine species at a given length, and compare their TP between fishery-restricted areas and trawled areas. The results show a difference in the TP of six benthic and apical nekto-benthic predators, which feed in the median at about 0.5 TP lower in trawled areas. It appears that current ‘fishing down marine food webs’ analyses may underestimate the trophic effects of fishing. Accounting for changes in trophodynamics of individuals at a given size is important to detect indirect effects through food web interactions. The application of a trawling ban may lead to the restoration of lost trophic structure; however, trophic changes may occur more slowly than changes in biomass. This article is part of the theme issue ‘Connected interactions: enriching food web research by spatial and social interactions’.

Predicting the ocean state in a reliable and interoperable way, while ensuring high-quality products, requires forecasting systems that synergistically combine science-based methodologies with advanced technologies for timely, user-oriented solutions. Achieving this objective necessitates the adoption of best practices when implementing ocean forecasting services, resulting in the proper design of system components and the capacity to evolve through different levels of complexity. The vision of OceanPrediction Decade Collaborative Center, endorsed by the UN Decade of Ocean Science for Sustainable Development 2021-2030, is to support this challenge by developing a “predicted ocean based on a shared and coordinated global effort” and by working within a collaborative framework that encompasses worldwide expertise in ocean science and technology. To measure the capacity of ocean forecasting systems, the OceanPrediction Decade Collaborative Center proposes a novel approach based on the definition of an Operational Readiness Level (ORL). This approach is designed to guide and promote the adoption of best practices by qualifying and quantifying the overall operational status. Considering three identified operational categories - production, validation, and data dissemination - the proposed ORL is computed through a cumulative scoring system. This method is determined by fulfilling specific criteria, starting from a given base level and progressively advancing to higher levels. The goal of ORL and the computed scores per operational category is to support ocean forecasters in using and producing ocean data, information, and knowledge. This is achieved through systems that attain progressively higher levels of readiness, accessibility, and interoperability by adopting best practices that will be linked to the future design of standards and tools. This paper discusses examples of the application of this methodology, concluding on the advantages of its adoption as a reference tool to encourage and endorse services in joining common frameworks.

The advancement of ecosystem-based management of aquatic ecosystems should no longer be limited by a lack of tools. However, a lack of comprehensive understanding of the capabilities of existing tools can form a barrier for uptake. With this chapter, we strive to more fully describe one of these tools, the spatial-temporal ecosystem model Ecospace, which is part of the Ecopath with Ecosim (EwE) ecosystem modeling approach and software. Changes and developments in Ecospace have been faster than documented in recent years. Many features of Ecospace, including the most recent that have not been described before, are detailed in this chapter. The applications highlighted showcase the multitude of uses of the spatial application of EwE, which, especially due to expansion of the capabilities to incorporate the effects of environmental change, has facilitated its use outside of fisheries management to protection of biodiversity, ecosystem restoration and environmental impact assessment. New applications of Ecospace can truly contribute to advance modeling of cumulative impacts and management alternatives in marine ecosystems, and can be of interest to inform sectoral and intersectoral policy.

The European Union Marine Strategy Framework Directive (MSFD) recognises that maintaining marine food-webs in Good Environmental Status (GES) is fundamental to ensure the long-term provision of essential ecosystem goods and services. However, operationalising food-web assessments is challenging due to difficulties in i) implementing simple but complete monitoring programmes, ii) identifying thresholds in monitoring indicators that inform when perturbations are diverting food-web state from GES and iii) in providing an integrative and complete picture of the (health) status of food-webs. In this context, stability assessments of marine food-webs could be useful to identifying the indicators that best track perturbation-induced changes in food-web state and the threshold boundaries that should not be exceeded to minimise the likelihood of losing stability. Yet, there is still a lack of systematic methods to perform such assessments. Here, we evaluate the potential of a simulation-based protocol to be used as a methodological standard for assessing the stability of marine food-webs. The protocol draws on the principles of ecological stability theory and provides a framework for assessing the trajectories of individual indicators during perturbation regimes and their robustness in detecting stability thresholds for marine food-webs. We tested the protocol on an open-ocean and deep-sea food-web modelled with the Ecopath with Ecosim suite. We concluded that indicators that quantify transfer efficiency through the food-web and measure the average trophic level of the community are optimal proxies for trophic functioning and structure to assess the stability of the system. Furthermore, we show how the approach can be applied to i) determine the impact of a loss of stability on the balance between trophic levels and ii) identify the biological components of the food-web that are most affected in scenarios of stability loss. Our findings could be useful for the ongoing debate on how trophic models and derived indicators can play a concrete and practical role in the food-web assessments in European seas.

AbstractIn December 2017, the United Nation decided to proclaim the United Nations Decade of Ocean Science for Sustainable Development for the 10-year period beginning on 1 January 2021.

Biological invasions are a major threat to biodiversity in species-rich regions. Therefore, it is important to understand mechanisms behind the long-term establishment of non-native fish species in aquatic environments in the Neotropical region. Here, we associated fish biomass, species richness, and the proportion of non-native species (contamination and Kempton’s indices) to quantify the non-native pressure over fish biodiversity in lakes and rivers of the Parana River floodplain, seasonally, from 2000 to 2017. We divided species into native and non-native assemblages sampled in spatio-temporal gradients. Temporal trends were examined using linear regressions and generalised additive models. Fish biomass in gillnets increased for both native and non-native fish species, but their Kempton indices were inversely correlated. Extinction of native species occurred locally with biotic differentiation of non-native species in lakes, rivers, and ecosystem contamination. A constant increase in fish biomass resulted in overwhelming biodiversity of non-natives at the end of the time series evaluated. Native biotic resistance to introductions was not detected in deterministic trends. The observed patterns were consistent with previous studies showing native biotic homogenisation and extinction of species in response to biological invasions, landscape fragmentation, and riverine impoundments. Increases in abundance and species richness of non-native fish were the biodiversity drivers that resulted in non-native species outweighing native species in the Parana floodplain.

Abstract. Understanding and managing marine ecosystems under potential stress from human activities or climate change requires the development of models with different degree of sophistication in order to be capable of predicting changes in living components and environmental variables. Recent advances in ecosystem modelling are the focus of this paper, which reviews numerical approaches to analyse the characteristics of marine conditions in terms of typical units, i.e., individuals, populations, communities and ecosystems. In particular, it examines the current classification of numerical models of increasing complexity – from individuals and population and stock assessment models to models representing the whole ecosystem by covering all trophic levels – and presents examples and their operational maturity, finally demonstrating their use for supporting marine resource management, conservation, planning and mitigation actions.

Predicting range shifts of marine species under different CO2 emission scenarios is of paramount importance to understand spatial potential changes in a context of climate change and to ensure appropriate management, in particular in areas where resources are critical to fisheries. Important tools which use environmental variables to infer range limits and species habitat suitability are the species distribution models or SDMs. In this work, we develop an ensemble species distribution model (e-SDM) to assess past, present and future distributions under Representative Concentration Pathway (RCP) 8.5 of nine demersal species and hotspot areas for their two life stages (adult and juvenile) in the Adriatic and Western Ionian Seas in four time windows (1999-2003, 2014-2018, 2031-2035 and 2046-2050). The e-SDM has been developed using three different models (and sub-models), i.e. (i) generalized additive models (GAM), (ii) generalized linear mixed model (GLMM), (iii) gradient boosting machine (GBM), through the combination of density data in terms of numbers of individuals km2 and environmental variables. Then, we have determined the changes in the aggregation hotspots and distributions. Finally, we assess gains and losses areas (i.e. occupation area) in the future climate change scenario as new potential range shifts for the nine species and their life stages. The results show that densities of some key commercial species, such as Merluccius merluccius (European hake), Mullus barbatus (red mullet), and Lophius budegassa (anglerfish) will be shifting northwards.