We investigated the presence and diversity of cetaceans in the Mediterranean Sea, analysing the data collected by 32 different research units, over a period of 15 years (2004–2018), and shared on the common web-GIS platform named Intercet. We used the encounter rate, the species prevalence, and the Shannon diversity index as parameters for data analysis. The results show that cetacean diversity, in the context of the Mediterranean basin, is generally quite low when compared with the eastern Atlantic, as few species, namely the striped dolphin, the bottlenose dolphin, the fin whale, and the sperm whale, dominate over all the others. However, some areas, such as the Alboran Sea or the north-western Mediterranean Sea, which includes the Pelagos Sanctuary (the Specially Protected Area of Mediterranean Interest located in the northern portion of the western basin), show higher levels of diversity and should be considered hotspots to be preserved. Primary production and seabed profile seem to be the two main drivers influencing the presence and distribution of cetaceans, with the highest levels of diversity observed in areas characterized by high levels of primary production and high bathymetric variability and gradient. This collective work underlines the importance of data sharing to deepen our knowledge on marine fauna at the scale of the whole Mediterranean Sea and encourages greater efforts in the networking process, also to accomplish the requirements of the Marine Strategy Framework Directive, with particular reference to Descriptor 1: biological diversity is maintained.

The automatic classification of fish species appearing in images and videos from underwater cameras is a challenging task, albeit one with a large potential impact in environment conservation, marine fauna health assessment, and fishing policy. Deep neural network models, such as convolutional neural networks, are a popular solution to image recognition problems. However, such models typically require very large datasets to train millions of model parameters. Because underwater fish image and video datasets are scarce, non-uniform, and often extremely unbalanced, deep neural networks may be inadequately trained, and undergo a much larger risk of overfitting. In this paper, we propose small convolutional neural networks as a practical engineering solution that helps tackle fish image classification. The concept of “small” refers to the number of parameters of the resulting models: smaller models are lighter to run on low-power devices, and drain fewer resources per execution. This is especially relevant for fish recognition systems that run unattended on offshore platforms, often on embedded hardware. Here, established deep neural network models would require too many computational resources. We show that even networks with little more than 12,000 parameters provide an acceptable working degree of accuracy in the classification task (almost 42% for six fish species), even when trained on small and unbalanced datasets. If the fish images come from videos, we augment the data via a low-complexity object tracking algorithm, increasing the accuracy to almost 49% for six fish species. We tested the networks with images obtained from the deployments of an experimental system in the Mediterranean sea, showing a good level of accuracy given the low quality of the dataset.

Common bottlenose dolphin (CBD) and bottom trawlers exploit the same ecological niche. The estimated CBD population along the Israeli coastline consumes roughly 1280 t of prey annually, similar to the mean annual trawl-fishery yield of 1300 t. In the ultra-oligotrophic Levantine Basin, the potential for competition for limited resources therefore exists. We aimed to examine whether the two consumers indeed harvest the same trophic level of the food web and the same members of that level. These questions were addressed by stomach content and stable isotope (δ¹⁵N and δ¹³C) analyses. The database included 26 prey-containing stomachs collected between 1996 and 2008 and muscle tissue samples of 23 dolphins and of 27 species of commercial fish and invertebrates for stable isotopes analysis. The 59.3 kg combined stomach content included at least 754 prey items, 97.3% of which were fish, belonging to 22 identified species. About half (46.4%) of the prey mass had medium-to-high commercial value. The overall similarity of the composition of the pooled biomass and that of the average commercial catch was expressed by a Pianka index of 0.49. Sparidae (sea bream) was the only family important for both consumers. The mean δ¹⁵N value of CBD muscle was found to be relatively low compared to other geographical areas and the estimated mean δ¹⁵N of its diet fell below that of most commercial species tested. Our findings suggest that CBD and the fisheries only partly share resources, with CBD having an overall minor effect on the bottom trawl fishery, mainly on the Sparidae catch.

In contrast to numerous documented pathogens and infectious diseases of aquaculture, there is a lack of baseline data and information regarding pathogenic agents’ prevalence in wild marine fish populations. This study focused on two common fish pathogenic microorganisms, namely Mycobacterium species and Vibrio species, both of which are known to be major causes of fish loss, occasionally to the extent of being a limiting factor in fish production. Both microorganisms are known as zoonotic agents. In total, 210 wild marine indigenous and Lessepsian fish from four different species from the eastern Mediterranean Sea were sampled and tested for Vibrio species and Mycobacterium species during a two-year period (2016–2017). Using PCR with 16S rRNA primers, we detected different strain variations of Mycobacterium species and Vibrio species and, based on the sequencing results, the overall prevalence for Vibrio species in wild fish in 2016 was significantly higher compared to 2017. No significant difference was detected for Mycobacterium species prevalence in wild fish between 2016 and 2017. In addition, 72 gilthead seabream (Sparus aurata) from an Israeli offshore marine farm were also examined during the two-year period (2017–2018). The results suggest that Mycobacterium species prevalence was significantly higher in 2018, while in 2017 there was no positive results for Mycobacterium species. In addition, there was no significant difference between both years in regard to the prevalence of Vibrio species for maricultured fish. These results highlight the necessity of continuous molecular monitoring in order to evaluate the prevalence of pathogenic microorganisms in both wild and cultured fish populations.

Streptococcus agalactiae is one of the most important fish pathogenic bacteria as it is responsible for epizootic mortalities in both wild and farmed species. S. agalactiae is also known as a zoonotic agent. In July 2018, a stranded wild sandbar shark (Carcharhinus plumbeus), one of the most common shark species in the Mediterranean Sea, was found moribund on the seashore next to Netanya, Israel, and died a few hours later. A post-mortem examination, histopathology, classical bacteriology and advanced molecular techniques revealed a bacterial infection caused by S. agalactiae, type Ia-ST7. Available sequences publicly accessible databases and phylogenetic analysis suggest that the S. agalactiae isolated in this case is closely related to fish and human isolates. To the best of our knowledge, this is the first description of a fatal streptococcosis in sandbar sharks.

In recent years, much attention has been focused on the impact of climate change, particularly via ocean acidification (OA), on marine organisms. Studying the impact of OA on long-living organisms, such as sharks, is especially challenging. When the ocean waters absorb anthropogenic carbon dioxide (CO₂), slow-growing shark species with long generation times may be subjected to stress, leading to a decrease in functionality. Our goal was to examine the behavioral and physiological responses of sharks to OA and the possible impacts on their fitness and resilience. We conducted a systematic review in line with PRISMA-Analyses, of previously reported scientific experiments. We found that most studies used CO₂ partial pressures (pCO₂) that reflect representative concentration pathways for the year 2100 (e.g., pH ~7.8, pCO₂ ~1000 μatm). Since there is a considerable knowledge gap on the effect of OA on sharks, we utilized existing data on bony fish to synthesize the available knowledge. Given the similarities between the behaviors and physiology of these two superclasses’ to changes in CO₂ and pH levels, there is merit in including the available information on bony fish as well. Several studies indicated a decrease in shark fitness in relation to increased OA and CO₂ levels. However, the decrease was species-specific and influenced by the intensity of the change in atmospheric CO₂ concentration and other anthropogenic and environmental factors (e.g., fishing, temperature). Most studies involved only limited exposure to future environmental conditions and were conducted on benthic shark species studied in the laboratory rather than on apex predator species. While knowledge gaps exist, and more research is required, we conclude that anthropogenic factors are likely contributing to shark species’ vulnerability worldwide. However, the impact of OA on the long-term stability of shark populations is not unequivocal.