The spring phytoplankton bloom is the main event influencing ecosystem richness in the pelagic realm of the Northwestern Mediterranean Sea (NW Med Sea). The Marine Strategy Framework Directive requires the achievement of a good ecological status for the pelagic habitat, and phytoplankton bloom phenology has been used as an indicator of the status of offshore waters. In this work we investigate interannual changes in the timing and magnitude of the phytoplankton bloom in the NW Med Sea, using phenological metrics. Daily maps of Chl-a concentration from 1998 to 2022 obtained by CMEMS were used to analyse bloom phenological metrics in 5 representative sites in the area. Chlorophyll-a data from 1998 to 2007 were used for determining the climatological behaviour, while 2008-2022 was identified as the study period. For this latter period, yearly spring bloom were identified and interannual variability and overall trends were analysed for each of the phenological metrics considered. Winter oceanographic and meteorological data were analysed to investigate possible correlations with the subsequent spring bloom. The frequency of anomalous years is increasing, both for bloom intensity and sea temperature. Bloom analysis revealed a negative trend only in some areas, but a steep decrease in the last 7 years was noticeable for all sites considered. Correlations of the Chl-a concentration during bloom with oceanographic variables revealed the importance of temperature, both marine and atmospheric, while Mixed Layer Depth played a lesser role. This work contributes to a better understanding of the dynamics of an area already under severe threat from human activities.

Understanding the habitat of highly migratory species is aided by using species distribution models to identify species‐habitat relationships and to inform conservation and management plans. While Generalized Additive Models (GAMs) are commonly used in ecology, and particularly the habitat modeling of marine mammals, there remains a debate between modeling habitat (presence/absence) versus density (# individuals). Our study assesses the performance and predictive capabilities of GAMs compared to boosted regression trees (BRTs) for modeling both fin whale density and habitat suitability alongside Hurdle Models treating presence/absence and density as a two‐stage process to address the challenge of zero‐inflated data. Fin whale data were collected from 2008 to 2022 along fixed transects crossing the NW Mediterranean Sea during the summer period. Data were analyzed using traditional line transect methodology, obtaining the Effective Area monitored. Based on existing literature, we select various covariates, either static in nature, such as bathymetry and slope, or variable in time, for example, SST, MLD, Chl concentration, EKE, and FSLE. We compared both the explanatory power and predictive skill of the different modeling techniques. Our results show that all models performed well in distinguishing presences and absences but, while density and presence patterns for the fin whale were similar, their dependencies on environmental factors can vary depending on the chosen model. Bathymetry was the most important variable in all models, followed by SST and the chlorophyll recorded 2 months before the sighting. This study underscores the role SDMs can play in marine mammal conservation efforts and emphasizes the importance of selecting appropriate modeling techniques. It also quantifies the relationship between environmental variables and fin whale distribution in an understudied area, providing a solid foundation for informed decision making and spatial management.

The Pelagos Sanctuary hosts eight resident cetacean species. Genetically different from Atlantic populations, their conservation is essential to preserve the whole biodiversity of the Ligurian Sea. The NATURA 2000 network is currently identified as one of the most efficient conservation tools due to its legally binding nature; however, its effectiveness for cetacean preservation is still unclear. The study used data systematically collected within the Pelagos Sanctuary from 2008 to 2021 by the FLT Med Net and the LIFE Conceptu Maris projects to investigate cetaceans distribution, Richness and diversity related to the existing protected areas. Of the 423 hexagons considered, only 21.28% of the study area was covered by French NATURA 2000 sites and 9.22% by Italian sites. French NATURA 2000 sites had the highest coverage of weighted Encounter Rate (ER_w) and biodiversity values. Only three species showed statistically significant differences between the French and Italian protected and non-protected hexagons, and biodiversity showed no significant difference. Only T. truncatus had higher median over Italian protected hexagons. The Pelagos Sanctuary still lacks offshore NATURA 2000 sites, especially in Italian waters. For this reason, areas to amplify the Network aimed at increasing cetacean and biodiversity conservation were highlighted in the results of this study.

Information on winter distribution and habitat preferences of cetaceans in the Northwestern Mediterranean Sea (NWMS) is still limited. Using observational data collected from 2008 to 2020 using platforms of opportunity during winter (November–March), this work investigates species presence and habitat use across the NWMS at different spatial scales. In total, 51,030 km on-effort and 852 sightings were analysed. All the eight regular cetacean species were identified. Fin whales, sperm whales, striped dolphins and bottlenose dolphins showed a preference for the routes in Liguro-Provencal basin and the Tyrrhenian Sea. Habitat models confirmed that the distribution of cetacean species at basin-scale is shaped primarily by bathymetric features, and dynamic variables such as sea surface temperature, eddy kinetic energy and sea surface chlorophyll concentration have a role in determining species-specific habitat preferences. At subregional scale, the differences highlighted in the habitat use suggested that some areas, like the Liguro-Provencal basin are mainly used to perform feeding activities, while others more probably work as warm resting areas and/or travelling corridors. Results highlight the importance of NWMS as a key area for cetaceans during winter, therefore habitat preferences throughout the year should be considered to properly manage the overlap between marine resources and human activities.

Modeling species distributions in dynamic pelagic environments remains challenging, particularly for wide‐ranging and highly mobile species when there is limited guidance on model performance. This limitation constrains the effective use of species distribution models (SDMs) in marine conservation, where robust and transferable predictions are essential for conservation planning. Using the loggerhead turtle ( Caretta caretta ) as a case study, we developed a benchmarking workflow to compare modeling strategies across spatial resolutions, environmental predictor variables, and algorithms. We evaluated five common modeling approaches—generalized linear models, generalized additive models, random forest, boosted regression trees, and MaxEnt—and used a 15‐year dataset of visual surveys collected along standardized ferry‐based transects across the Mediterranean Sea, with environmental predictor variables averaged across years to capture recurrent summer conditions. Model outputs were assessed for their ability to predict habitat suitability and space‐use patterns in dynamic pelagic environments. At the same time, robustness and spatial transferability were evaluated using an independent, basin‐scale aerial survey dataset. Our results revealed consistent patterns informing SDM selection for wide‐ranging pelagic species. In offshore Mediterranean pelagic systems, increased spatial resolution improved the ecological interpretability of predicted habitat patterns, whereas an extended set of dynamic oceanographic predictors enhanced the characterization of habitat associations. Independent validation was critical for selecting robust and transferable modeling algorithms, with MaxEnt and generalized additive models providing the most reliable performance for suitability and encounter rate (ER) modeling, respectively. Combining presence‐only and encounter rate models helped distinguish habitat suitability from observation intensity. Overall, this study developed an empirically tested workflow to support robust, consistent, and policy‐relevant SDM applications for mobile marine species in offshore, data‐limited systems. By clarifying trade‐offs among modeling approaches, this framework enhanced the application of SDMs to inform spatial planning, conservation prioritization, and species distribution and habitat‐use assessments within regional and international conservation frameworks.