Partitioning of the Mediterranean basin has so far mainly focused on surface waters, relying on biogeochemical and hydrological data while the Mediterranean seafloor has received much less attention. Bioregions are essential units for conservation planning, as they provide a framework for designing representative networks of protected areas. Therefore, seafloor-specific bioregions are needed to support the management and conservation of benthic ecosystems. While benthic habitat mapping is generally based on macrofaunal patterns, we propose the first mesoscale partitioning of the Mediterranean seabed based on epibenthic megainvertebrate communities. Benthic records from the MEDITS programme (International Mediterranean Bottom Trawl Survey) were used to partition the Mediterranean soft bottoms. Using k-means clustering combined with Random Forest modelling, we grouped sites according to similarities in biotic composition and predicted their distribution in relation to environmental variables. The analysis was conducted independently across four sub-basins: the Western Mediterranean, the Central Mediterranean, the Adriatic Sea, and the Aegean Sea. This approach identified 16 distinct bioregions, each characterized by unique epibenthic megainvertebrate communities. The partitioning revealed a pronounced bathymetric gradient, with deep-sea bioregions showing a more homogeneous set of indicator taxa and greater similarity across regions compared to the more distinct communities found on the shelf and slope. These coherent bioregions can serve as spatial units to enhance the representativeness of conservation priority networks and provide a valuable complement to the existing EUNIS seabed habitat classification, which does not explicitly account for vulnerable epibenthic megainvertebrate communities.

Animal movement underpins critical ecological processes and shapes ecosystem resilience. In marine systems, understanding the spatial ecology and connectivity of exploited species is essential for informing conservation and sustainable fisheries management. Despite their ecological and economic importance, the spatio-temporal movement of gilthead seabream (Sparus aurata) in the Mediterranean Sea remains poorly understood. We leveraged the largest acoustic telemetry dataset ever collected in the Mediterranean as part of the project CONNECT-MED and RESMED, tracking 222 tagged seabream over three years (2019–2022). Using an array of more than 180 strategically positioned acoustic receivers across the Gulf of Lion in both lagoons and the sea, we analysed over 700,000 detections spanning a longitudinal gradient of 200 km. Using individual-based spatial network analysis, we quantified movement dynamics, space use, and connectivity. Seabream showed strong seasonal migrations, with wide (> 180 km for some individuals) spatial dispersal during spawning (October–March) and localized movements whilst foraging (April–September). Eastward and southward migration linked lagoon nurseries/foraging areas to offshore spawning areas. The Marseille area (Calanques National Park and Côte Bleue Marine Park) was identified as a major spawning region used by fish across the Gulf of Lion. Movement varied with fish size, with larger fish having more complex and dynamic networks. Autumn saw synchronous lagoon emigration and aggregation at spawning sites, with multi-year site fidelity. Our findings demonstrate size-dependent movement strategies in gilthead seabream and reveal structured connectivity linking lagoon foraging areas to offshore spawning grounds. The concentration of spawning activity near Marseille identifies a key regional hotspot of ecological and management importance. Incorporating these connectivity patterns, ontogenetic shifts, and spatial behaviours into fisheries management will be essential for sustaining seabream populations across the northwestern Mediterranean.

Fish quantity has long been the most needed information for stock management as the main source of uncertainty for the fishing sector. However, as the rate of global environmental change accelerates, degradation of fish quality has become a new source of concern. Indeed, evidence is accumulating on a general decrease in fish size and fat content and on the increase of the occurrence of various contaminants. Small pelagic fishes (SPFs) are valuable food rich in fatty acids but, for this reason, are also prone to the accumulation of organic pollutants. While environmental impacts on fish quality are increasingly documented, knowledge on how these propagate to the fishing industry is still very limited. In our study we explored how the various components of the SPF French social-ecological system, from plankton to fish to fishers to the canning industry and the market, interact in their response to global change. First, by analysing the national catches of sardine and anchovy from 2000 to 2024 across the three French maritime regions, we highlighted the strong seasonal dynamics of both fisheries and the strong interannual trends over the period. Second, focusing on Bay of Biscay sardines, we revealed that on both seasonal and interannual scales, the fishing sector was caught between a bottom-up environmental control through its effects on fish quality, namely fat content and size, and a top-down control resulting from canning industry strategies in provisioning and marketing, ultimately mediated by the preferences of consumers. The fishing fleets appeared as the most vulnerable component in the system, while the processing industry appeared more flexible. Our results indicate that a decrease in fish quality can threaten an entire fishing industry. We recommend collaborative efforts between scientists and stakeholders to co-construct adaptation strategies aiming at strengthening the resilience of fisheries social-ecological systems in the face of global change.

Anthropogenic activities have led to the persistent build-up of trace metals and organic pollutants in coastal ecosystems, threatening aquatic life. Gilthead seabream, a commercially valuable species, often inhabits Mediterranean lagoons that function as vital nursery grounds. In this study, we examined 93 juvenile seabreams from three Tunisian lagoons to evaluate contamination levels and their effects on otolith morphology. We measured inorganic and organic contaminants in fish muscle and investigated their potential effects on otolith shape and asymmetry. Clear fish muscle contamination signatures emerged across sites: Tunis Lagoon exhibited the highest levels of contamination, followed by Ghar El Melh, while El Biban Lagoon appeared relatively pristine. Relatively elevated levels of metals (e.g., Pb, Ni, Be) and persistent organic pollutants (e.g., PCBs, DDTs, PBDEs) were observed in the more impacted lagoons. Notably, we found that otolith shape and fluctuating asymmetry were significantly associated with contaminant exposure, even after accounting for natural variables like fish size and lipid content. Specific pollutants, especially Cu, Rb, Sr and DDT, were linked to altered otolith morphology, suggesting disrupted biomineralization. The stronger response of the left otolith suggests that sub-lethal stress impairs developmental stability. Although fish muscle contaminant levels generally fell below food safety thresholds, the observed effects on otolith development raise concerns about functional consequences and underlying physiological stress. Our results highlight otolith asymmetry as a sensitive bioindicator of environmental stress in wild fish. By integrating shape analysis with contaminant profiling, this study offers a powerful tool for assessing pollution impacts in vulnerable Mediterranean nursery habitats.

The need for an ecosystem-based approach to fisheries management is widely recognized. Designing ecosystem models for management purposes requires the identification of key interactions and environmental forcing that drive the dynamics of fish stocks. This can be a very challenging task given the complexity of interactions, which determine the evolution of marine ecosystems. To overcome this difficulty, this study proposes a statistical approach based on multivariate time series analysis to identify the main biotic and abiotic interactions using as a case study of a complex and exploited marine ecosystem, the Gulf of Lions (GOL) in the Mediterranean Sea. To do so, first, pairwise Granger causality tests were performed to detect and select the strongest interactions and drivers, then followed by Multivariate Auto-Regressive (MAR) modelling techniques to evaluate the relevance of the selected causal relationships in a multivariate system. The results led to the identification of three statistical interaction networks (SINs) of moderated complexity. The first showed statistical interactions between blackbellied angler (Lophius budegassa), hake (Merluccius merluccius), grey gurnard (Eutrigla gurnardus), and John dory (Zeus faber), as well as the influence of phosphate concentration. The second focused on blackbellied angler, red mullet (Mullus barbatus), anchovy (Engraulis encrasicolus), under the combined influence of demersal trawlers, Sea Surface Temperature (SST) and nitrate concentration. Horned octopus (Eledone cirrhosa), capelan (Trisopterus capelanus), and sardine (Sardina pilchardus) were also investigated under the influence of nitrate concentration. These SINs can serve as a basis to build models of intermediate complexities to describe the dynamics of the main fish stocks of the GOL.

Crinoid beds of Leptometra phalangium (Müller, 1841) have been identified as sensitive habitats by the General Fisheries Commission for the Mediterranean (GFCM) due to their high vulnerability to bottom trawl fisheries. Poorly resilient to physical damage, L. phalangium has been listed as a potential indicator of Vulnerable Marine Ecosystems (VMEs) in the Mediterranean Sea. If fishing activities represent the main cause of habitat destruction for this species, the ongoing changes in climate conditions may rapidly exacerbate the process. In this study, we developed an ensemble Species Distribution Modeling framework to predict the potential habitat of L. phalangium for present-days in the Mediterranean Sea, and used the model to infer potential changes in its spatial distribution by 2050 under two different climate scenarios (IPCC Representative Concentration Pathways RCP2.6 and RCP8.5). True presence-absence records were used and correlated to a parsimonious set of environmental predictors considered as important drivers of benthic species distribution. In present conditions, L. phalangium seems to be widely distributed along the continental slopes of the western and central Mediterranean. This crinoid is often described as confined to the continental shelf-break (100–200 m), but our results show that it can be found over a wider depth range, between 100 and 500 m. Our predictions obtained for the mid-21st century indicate an important habitat loss for L. phalangium under future climate conditions, mainly in the central and southern basins. Declines of 50 to 70 % in its suitable habitat were predicted under RCP2.6 and RCP8.5 compared to present-day predictions. Climate refugia (i.e., areas where environmental conditions remain suitable for the species in the future) were restricted to the northwestern basin (e.g., Gulf of Lion, the Catalan Sea, the Balearic Sea, Ligurian Sea) and in the southern Adriatic Sea. Provided by a robust statistical framework, climate refugia predictions, along with uncertainty assessments, must support the identification of priority areas for the conservation of VME indicator species by governmental bodies and regional management organizations.

Animal movements are typically influenced by multiple environmental factors simultaneously, and individuals vary in their response to this environmental heterogeneity. Therefore, understanding how environmental aspects, including biotic, abiotic, and anthropogenic factors, influence the movements of wild animals is an important focus of wildlife research and conservation. We apply Exponential Random Graph Models (ERGMs) to analyze movement networks of a bull shark population in a network of acoustic receivers and identify the effects of environmental, social, or other types of covariates on their movements. We found that intra- and interspecific factors often had stronger effects on movements than environmental variables. ERGMs proved to be a potentially useful tool for studying animal movement network data, especially in the context of spatial attribute heterogeneity.

Ecopath mass-balanced models are widely-used tools to address various challenges in the understanding and protection of ecosystems. To track the continuing improvements in data and the evolving environment (climate change, anthropic pressure), new models are regularly being developed. In this study, we built a Gulf of Lion Ecopath model, focused on the continental shelf, featuring enhanced representation of benthic invertebrates and a realistic assessment of catches, and which takes into account the significant changes observed after 2008–2009 in the trophic structure of this ecosystem as well as related changes in fisheries activities. The model is composed of 68 functional groups, including 6 primary producers, discards and detritus, 27 invertebrate groups, 31 fish groups, dolphins and seabirds. New datasets were taken into account for biomasses, as well as for diets. P/B and Q/B parameters were calculated to include the most recent and geographically closest data. Model results highlight a food web diagram, ranging over 5 trophic levels and placing Prionace glauca, Squalus acanthias and dolphins as top predators. The mixed trophic impact analysis showed that the groups with the highest accumulated negative impacts are, in decreasing order, benthic trawls, nets and carnivorous echinoderms. The groups with the highest accumulated positive impacts are, in decreasing order, detritus, microphytoplankton and nanoplankton. The flux analysis shows that a major part of the flows occurs at trophic level 2 with 35.1% of the model total throughput and 43.8% of the total biomass. The catches have a mean trophic level of 3.47, higher than in previous studies, reflecting the changes in the fisheries activities.

Ecological processes are often spatially and temporally structured, potentially leading to autocorrelation either in environmental variables or species distribution data. Because of that, spatially-biased in-situ samples or predictors might affect the outcomes of ecological models used to infer the geographic distribution of species and diversity. There is a vast heterogeneity of methods and approaches to assess and measure spatial bias; this paper aims at addressing the spatial component of data-driven biases in species distribution modelling, and to propose potential solutions to explicitly test and account for them. Our major goal is not to propose methods to remove spatial bias from the modelling procedure, which would be impossible without proper knowledge of all the processes generating it, but rather to propose alternatives to explore and handle it. In particular, we propose and describe three main strategies that may provide a fair account of spatial bias, namely: (i) how to represent spatial bias; (ii) how to simulate null models based on virtual species for testing biogeographical and species distribution hypotheses; and (iii) how to make use of spatial bias - in particular related to sampling effort - as a leverage instead of a hindrance in species distribution modelling. We link these strategies with good practice in accounting for spatial bias in species distribution modelling.

Small pelagic fish have shown a general decrease in size and body condition over the past two decades in several European regional seas. Although the underlying processes are still not well understood, recent studies point to a bottom-up control. In order to better understand how the environment impacts the main individual life history traits, which themselves control the dynamic of the population, we developed a comparative approach between two species, European anchovy and sardine, and across three regions of the Northeast Atlantic and Mediterra-nean Sea: the English Channel in the north, to the Bay of Biscay and the Gulf of Lion in the south. We developed a bioenergetic modeling framework based on the Dynamic Energy Budget theory (DEB). Our DEB models were forced using two different representations of the lower trophic levels, POLCOMS-ERSEM and SEAPODYM models. Our models were calibrated for the Bay of Biscay and then projected on to the other regions, over the early 2000s (period with bigger fish) and the early 2010s (period with smaller fish). The environment alone, temperature and zooplankton, explained a significant part of the observed regional differences in growth. However, the temporal trends simulated by the lower trophic levels models, when transcribed through bio-energetics, could not explain the strong decrease in length and weight that occurred in the Bay of Biscay (-30 % in weight for anchovy and-20 % for sardine) and in the Gulf of Lion (-30 % for anchovy and-50 % for sardine). Through a scenario approach, we estimated that a decrease in zooplankton quality could be a significant driver of the observed decrease in size both in the Bay of Biscay and in the Gulf of Lion (decrease in assimilable energy of 4 to 5 % and 15 to 17 % in the Bay of Biscay and the Gulf of Lion, respectively). For such a decrease in size, a zooplankton biomass of the same quality should have been reduced by between 17 and 31 % in the Bay of Biscay over a 10-to 15-year period, while no biologically realistic estimations were obtained for the Gulf of Lion. The validity of these proposed changes in biomass and quality is discussed in context of alternative explanations.

Species distribution models (SDMs) provide robust inferences about species-specific site suitability and are increasingly used in systematic conservation planning (SCP). SDMs are subjected to intrinsic uncertainties, and conservation studies have generally overlooked these. The integration of SDM uncertainties in conservation solutions requires the development of a suitable optimization algorithm. Exact optimization algorithms grant efficiency to conservation solutions, but most of their implementations generate a single binary and indivisible solution. Therefore, without variation in their parameterization, they provide low flexibility in the implementation of conservation solutions by stakeholders. Contrarily, heuristic algorithms provide such flexibility, by generating large amounts of sub-optimal solutions. As a consequence, efficiency and flexibility are implicitly linked in conservation applications: mathematically efficient solutions provide less flexibility, and the flexible solutions provided by heuristics are sub-optimal. To avoid this trade-off between flexibility and efficiency in SCP, we propose a reserve-selection framework, based on exact optimization combined with a post-selection of SDM outputs. This reserve-selection framework provides flexibility and addresses the efficiency and representativeness of conservation solutions. To exemplify the approach, we analyzed an experimental design, crossing pre- and post-selection of SDM outputs versus heuristics and exact mathematical optimizations. We used the Mediterranean Sea as a biogeographical template for our analyses, integrating the outputs of eight SDM techniques for 438 fish species.

Environmentally driven changes in small pelagic fish condition and size have been observed in the Gulf of Lions (GOL) since 2008, leading to a significant fishery crisis. However, the effect of changes in environment and/or in the small pelagic community on the demersal community remain unknown. For the first time, this study examines the body condition (bc) and population density of 22 demersal species since 1994, using dynamic factor analysis (DFA). Most (but not all) of demersal species have shown a common shift between 2006 and 2009, which is synchronous with that observed in small pelagic species and the environmental conditions in the GOL. It had been concluded that the environmentally driven changes detected in the pelagic fish community also affected the demersal fish community, but with less drastic and lasting consequences. As the DFA revealed that the bc displayed important variations for several species, notably hake (Merlucius merluccius), the interaction between the bc and population density was investigated using the Multivariate Autoregressive (MAR) model on hake population at three life stages (recruits, juveniles, and adults). Results showed that adult bc, while negatively affected by density, had a positive effect on recruitment. So hake bc could have affected population dynamics by promoting higher recruitment at low densities. Further work is needed to ascertain whether such effects exist in other demersal species.

In face of global changes, projecting and mapping biodiversity changes are of critical importance to support management and conservation measures of marine ecosystems. Despite the development of a wide variety of ecosystem models capable of integrating an increasing number of ecological processes, most projections of climate-induced changes in marine biodiversity are based on species distribution models (SDMs). These correlative models present a significant advantage when the lack of knowledge on the species physiology is counterbalanced by the availability of relevant environmental variables over the species geographical range. However, correlative SDMs neglect intra- and inter-specific interactions and thereby can lead to biased projections of changes in biodiversity distribution. To evaluate the influence of trophic interactions on projections of species richness and assemblage composition under climate change scenarios, we compared biodiversity projections derived from an ensemble of different SDMs to projections derived from a hybrid model coupling SDMs and a multispecies trophic model in the Mediterranean Sea. Our results show that accounting for trophic interactions modifies projections of future biodiversity in the Mediterranean Sea. Under the RCP8.5 scenario, SDMs tended to overestimate the gains and underestimate the losses of species richness by the end of the 21st century, with marked local differences in projections, both in terms of magnitude and trend, in some biodiversity hotspots. In both SDMs and hybrid approaches, nestedness with gains in species richness was the main pattern driving dissimilarity between present and future fish and macro-invertebrate species assemblages at the Mediterranean basin scale. However, at local scale, we highlighted some differences in the relative contribution of nestedness vs replacement in driving dissimilarity. Our results call for the development of integrated modelling tools that can mechanistically consider multiple biotic and abiotic drivers to improve projections of future marine biodiversity.

Abstract This research represents the first approach to the study of the shelf zooplankton community at a Mediterranean scale, using acoustic standardized data collected in June-July in 10 different geographical sub-areas (GSAs) established by the General Fisheries Commission for the Mediterranean (GFCM) within the framework of the MEDiterranean International Acoustic Survey (MEDIAS). The analysis of the zooplankton layers based on their acoustic characteristics has revealed the potential of these surveys for the study of zooplankton at a Mediterranean basin scale and, also, the need to collect biological samples to interpret the acoustic records in terms of species. The fish population’s direct assessment is established in the MEDIAS framework, but the integration of zooplankton community data would constitute a qualitative step for the understanding of the fluctuations of fish populations and therefore to achieve the objective of an ecosystem-based management. Results have revealed the ubiquity of the zooplankton layers and its ability to form layers detectable by scientific echosounders throughout the Mediterranean at the common fish assessment frequency (38 kHz). In addition, the use of two frequencies (38 and 120 kHz) has allowed to apply the dB difference method, observing changes in the difference of the Mean Volume Backscattering Strength (∆MVBS) at 38 and 120 kHz frequencies, which would be related to changes in the composition of the zooplankton community.

Marine biota are redistributing at a rapid pace in response to climate change and shifting seascapes. While changes in fish populations and community structure threaten the sustainability of fisheries, our capacity to adapt by tracking and projecting marine species remains a challenge due to data discontinuities in biological observations, lack of data availability, and mismatch between data and real species distributions. To assess the extent of this challenge, we review the global status and accessibility of ongoing scientific bottom trawl surveys. In total, we gathered metadata for 283,925 samples from 95 surveys conducted regularly from 2001 to 2019. We identified that 59% of the metadata collected are not publicly available, highlighting that the availability of data is the most important challenge to assess species redistributions under global climate change. Given that the primary purpose of surveys is to provide independent data to inform stock assessment of commercially important populations, we further highlight that single surveys do not cover the full range of the main commercial demersal fish species. An average of 18 surveys is needed to cover at least 50% of species ranges, demonstrating the importance of combining multiple surveys to evaluate species range shifts. We assess the potential for combining surveys to track transboundary species redistributions and show that differences in sampling schemes and inconsistency in sampling can be overcome with spatio‐temporal modeling to follow species density redistributions. In light of our global assessment, we establish a framework for improving the management and conservation of transboundary and migrating marine demersal species. We provide directions to improve data availability and encourage countries to share survey data, to assess species vulnerabilities, and to support management adaptation in a time of climate‐driven ocean changes.

Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called 'sPlot', compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01-40,000 m(2). Time period and grain 1888-2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot-level records. Software format Three main matrices (.csv), relationally linked.