Coral reef ecosystems hold important biological, ecological and economic value, but are in decline due to a combination of global and local stressors resulting in loss of reef structural complexity and biodiversity. Given the foundational role reef structure plays in marine ecosystem health and diversity, there is a need for tools capable of quantifying this complexity over larger scales and higher resolutions. In this study, we present an approach that integrates drones, various color space information, and deep learning neural networks to predict three-dimensional complexity metrics—height range, rugosity and fractal dimension—across large (thousands of m2) spatial scales. The validation of our model resulted in R2 values of 0.71, 0.65, and 0.56 for each metric, respectively, indicating a robust predictive capability. Because these three complexity metrics can be depicted through a plane equation, we could calculate the metric with the lowest color space predictive accuracy from the other two, thereby enhancing overall predictive accuracy. Our deep learning approach offers a scalable solution to measure structural complexity of shallow coral reefs, providing a balance of spatial resolution and extent that is more ecologically relevant than other large-scale, airborne approaches. The application of this method to four distinct patch reef habitats revealed unique structural signatures among seemingly similar reefs, highlighting the importance of site-specific considerations in assessing reef complexity. A scalable, high-resolution method such as we present will provide a more cost-effective and nuanced understanding of reef habitats, ultimately aiding in their conservation and management amid ongoing environmental challenges.

Marine protected areas (MPAs) have been identified as one of the most effective tools to halt marine biodiversity loss. However, conflicting evidence from disparate, small-scale studies obfuscate a cohesive global picture of the role that MPAs can play in enhancing local fisheries through spillover benefits. We conducted a global analysis of trophy-size fish catches as a proxy for spillover occurring outside of fully protected MPAs, focusing on time series of recreational angling catch records. We show that the accumulation of recreational fishing records accelerates close to MPAs (compared to reference areas) and that this effect grows stronger over time. Our results provide a standardized global assessment of one of the benefits MPAs provide to recreational anglers.

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The progressive increase of marine macro-litter on the bottom of the Mediterranean Sea is an urgent problem that needs accurate information and guidance to identify those areas most at risk of accumulation. In the absence of dedicated monitoring programs, an important source of opportunistic data is fishery-independent monitoring campaigns of demersal resources. These data have long been used but not yet extensively. In this paper, MEDiterranean International Trawl Survey (MEDITS) data was supplemented with 18 layers of information related to major environmental (e.g. depth, sea water and wind velocity, sea waves) and anthropogenic (e.g. river inputs, shipping lanes, urban areas and ports, fishing effort) forcings that influence seafloor macro-litter distribution. The Random Forest (RF), a machine learning approach, was applied to: i) model the distribution of several litter categories at a high spatial resolution (i.e. 1 km2); ii) identify major accumulation hot spots and their temporal trends. Results indicate that RF is a very effective approach to model the distribution of marine macro-litter and provides a consistent picture of the heterogeneous distribution of different macro-litter categories. The most critical situation in the study area was observed in the north-eastern part of the western basin. In addition, the combined analysis of weight and density data identified a tendency for lighter items to accumulate in areas (such as the northern part of the Tyrrhenian Sea) with more stagnant currents. This approach, based on georeferenced information widely available in public databases, seems a natural candidate to be applied in other basins as a support and complement tool to field monitoring activities and strategies for protection and remediation of the most impacted areas.

The increase in the construction of mega dams in tropical basins is considered a threat to freshwater fish diversity. Although difficult to detect in conventional monitoring programs, rheophilic species and those reliant on shallow habitats comprise a large proportion of fish diversity in tropical basins and are among the most sensitive species to hydropower impacts. We used Baited Remote Underwater Video (BRUV), an innovative, non-invasive sampling technique, to record the impacts caused by Belo Monte, the third largest hydropower project in the world, on fishes inhabiting fast waters in the Xingu River. BRUV were set in a river stretch of ~ 240 km for 7 years, 2 before and 5 after the Belo Monte operation. We explored the spatial and temporal variation in fish diversity (α, β, and γ) and abundance (MaxN) using generalized additive models. We also investigated the variation of environmental variables and tested how much information we gained by including them in the diversity and abundance models. Belo Monte altered the flow regime, water characteristics, and fishery yield in the Xingu, resulting in changes in the fish community structure. Temporally, we observed sharp declines in α diversity and abundance, far exceeding those from a previous study conducted with more conventional sampling methods (i.e., catch-based) in the region. γ-diversity was also significantly reduced, but we observed a non-expected increase in β diversity over time. The latter may be associated with a reduction in river connectivity and an increase in environmental heterogeneity among river sectors. Unexpected signs of recovery in diversity metrics were observed in the last years of monitoring, which may be associated with the maintenance of flow levels higher than those previously planned. These results showed that BRUV can be a useful and sensitive tool to monitor the impacts of dams and other enterprises on fish fauna from clear-water rivers. Moreover, this study enhances our comprehension of the temporal variations in freshwater fish diversity metrics and discusses the prevalent assumption that a linear continuum in fish-structure damage associated with dam impoundments may exhibit temporal non-linearity.

Pollution by plastics is a worldwide problem on par with climatic change and biological invasions. In coastal sediments, plastic particles tend to accumulate and persist over the long term. We assessed the plastic pollution using a standardized surface sediment sampling protocol on 22 sandy beaches along >4600 km of the Brazilian coast. The abundance, size, color, type, and polymeric composition of all meso-and microplastic items found in the surveys were processed to disclose spatial patterns of distribution and pollution associated drivers. A General Linear Model (GLM) was run to investigate how the predictor variables influenced overall beach plastic amounts and by plastic type and size class. Overall, 3114 plastic items were found, with microplastics comprising just over half of all items (54 %). Most items were either white (60 %) or blue (13 %), while polystyrene foam (45 %) and fragments (39 %) comprised the most abundant plastic types. The principal polymers were Polyethylene (40 %) and Polypropylene (32 %). The analyses indicated that the distribution of plastic litter along beaches is deter-mined by three predictive variables: the distance to the nearest estuary (-), tourism (+), and the number of inhabitants in the nearest urban center (+). Tourist (highly-visited) beaches and those near estuarine runoffs or urban centers presented the highest plastic pollution rates. The unveiling of plastic pollution patterns through a large-scale systematic survey is essential for future management guidance and science-based decisions for mitigating and solving the plastic pollution crisis.

Reef halos are rings of bare sand that surround coral reef patches. Halo formation is likely to be the indirectly result of interactions between relatively healthy predator and herbivore populations. To reduce the risk of predation, herbivores preferentially graze close to the safety of the reef, potentially affecting the presence and size of the halo. Reef halos are readily visible in remotely sensed imagery, and monitoring their presence and changes in size may therefore offer clues as to how predator and herbivore populations are faring. However, manually identifying and measuring halos is slow and limits the spatial and temporal scope of studies. There are currently no existing tools to automatically identify single reef halos and measure their size to speed up their identification and improve our ability to quantify their variability over space and time. Here we present a set of convolutional neural networks aimed at identifying and measuring reef halos from very high-resolution satellite imagery (i.e., similar to 0.6 m spatial resolution). We show that deep learning algorithms can successfully detect and measure reef halos with a high degree of accuracy (F1 = 0.824), thereby enabling faster, more accurate spatio-temporal monitoring of halo size. This tool will aid in the global study of reef halos, and potentially coral reef ecosystem monitoring, by facilitating our discovery of the ecological dynamics underlying reef halo presence and variability.

A comprehensive understanding of the concentration of microplastics (MPs) in seawaters is essential to implement monitoring programs and understand the impacts on ecosystems, as required by the European legislation to protect the marine environment. In this context, the purpose of this study is to investigate the composition, quantity, and spatial distribution of microplastics from coastal to offshore areas in three Italian seawaters. In addition, the distribution of microplastics between surface and subsurface water layers was analyzed in order to better understand the dynamics of MPs in the upper layers of the water column. A total number of 6069 MPs (mean total concentration of 0.029 microplastics · m −2 ) were found to be heterogeneous in type, shape, and color. In general, MPs concentrations decrease with coastal distance, except when environmental forcings are predominant (such as sea currents). Moreover, the amount of surface MPs was almost four times that of subsurface microplastics, which consisted mostly of fibers. In light of these results, it becomes clear how critical it is to plan remediation actions and programs to minimize microplastic accumulations in the sea.

The presence of plastic waste in the marine environment has driven the scientific community to make significant efforts to study and mitigate its possible effects. One of the critical aspects is to determine if and how an increase in ingestion events may occur as a result of the accumulation of plastic waste on the seabed. In this study, G. melastomus is examined for its ability to indirectly provide information on the amount of macroplastics accumulating on the seafloor. Plastic ingestion is explored by describing the feeding habits of the species, which have the potential to provide very useful information regarding biological or ecological issues. The diet of G. melastomus mainly consisted of cephalopods, bathypelagic fishes, and decapod crustaceans, increasing in diversity during growth. The generalist-opportunistic feeding behaviour of this species leads to the incidental ingestion of plastic particles ( N = 47, with a mean (± SD) of 1.47 ± 0.28 per specimen) which can be indirectly associated to the presence of macroplastics on the seafloor. Indeed, our results indicate a significant relationship between the amount of macroplastics present on the seabed and the frequency of ingestion of plastic particles by blackmouth catshark. We propose G. melastomus as an excellent candidate for developing a valid monitoring strategy for the presence of plastics on the seabed, as requested by the EU Marine Strategy Framework Directive.

Plastics are one of the most used materials in the world. Their indiscriminate use and inappropriate disposal have led to inevitable impacts, for instance ingestion, on the environment arousing the attention of the global community. In addition, plastic ingestion studies are often written in scientific jargon or hidden behind paywalls, which makes these studies inaccessible. GLOVE is an online and open-access dashboard database available at gloveinitiative.shinyapps.io/Glove/ to support scientists, decision-makers, and society with information collected from plastic ingestion studies. The platform was created in the R environment, with a web interface developed through Shiny. It already comprises 530 studies, including all biological groups, with 245,366 individual records of 1458 species found in marine, freshwater, and terrestrial environments. The main goal of the GLOVE dashboard database is to improve data accessibility by being a scientifically useful grounded tool for designing effective and innovative actions in the current scenario of upcoming global and local agreements and actions on plastic pollution.

This paper presents an analysis of the effect of SARS-CoV-2 coronavirus pandemic and related restrictive measures on the activity of the Italian fleet of trawlers, which represents one of the most important fisheries in the Mediterranean Sea. We integrated multiple sources of information including: (1) Fleet activity data from Vessel Monitoring System, the most important satellite-based tracking device; (2) vessel-specific landing data disaggregated by species; (3) market and economic drivers affecting the effort variation during the lockdown and in the related fishing strategies; (4) monthly landings of demersal species in the main Italian harbors. These data sources are combined to: (1) Assess the absolute and relative changes of trawling effort in the geographical sub-areas surrounding the Italian coasts; (2) integrate and compare these changes with the market and economic drivers in order to explain the observed changes in fishing effort and strategy; (3) analyze the changes of the fishing effort on the Landing-per-unit-effort (LPUE) in order to further understand the strategy adopted by fishers during this crisis and to infer the potential consequence for the different stocks. The results provide an overview of the effects of the “COVID-19 shock,” in terms of fishing activity and socio-economic drivers, demonstrating that the consequences of the pandemic have been very varied. Although the COVID-19 shock has caused a marked overall reduction in activity in the first semester of 2020, in some cases the strategies adopted by fishermen and the commercial network linked to their activity have significantly reduced the impact of the emergency and taken back catch and effort to levels similar to those of previous years. These results could provide insights for management measures based on temporal stops of fishing activities. In particular, if no limits to the fishing effort after the restart of fishing activities are adopted, the benefits of fishing pressure reduction on fishery resources could be nullified. On the other hands, when fishing activities restart, and in the absence of catch control, effort tends to increase on coastal bottoms characterized by greater abundance of resources and longer effective fishing time.

Beach litter represents a worldwide problem impacting both terrestrial and aquatic environments. In the present study, we assessed beach litter pollution in a prominent touristic site in Brazil, the Jericoacoara National Park. In particular, we applied a delta-generalized additive modeling (GAM) approach in order to investigate pollution hotspots and to provide better guidelines for coastal environmental managers. A total of 7549 litter items were collected, resulting hard and flexible plastics the most abundant type. Our GAM analysis revealed that the distribution of each type of litter was affected by distinct drivers in the protected area, with the extension of the beach, tourist attractions, wind angle, and the distance to water bodies and villages as the most significant explanatory variables. Our model is suitable in predicting litter pollution hotspots on beaches, which is a valuable tool for future guidelines and effective management strategies to prevent beach pollution worldwide.

The global need to monitor the status of marine resources is a priority task in marine management, but most ocean surveys still rely on costly and time-consuming capture-based techniques. Here we test a novel, easy-to use device to collect eDNA on board of bottom trawl fishing vessels, during normal fishing operations, quickly and easily: custom-made rolls of gauze tied to a hollow perforated spherical probe (the 'metaprobe') that placed inside the fishing net aims to gather traces of genetic material from the surrounding environment. We collected six samples from three central Tyrrhenian sites. Using an established fish-specific metabarcoding marker, we recovered over 70% of the caught species and accurately reconstructed fish assemblages typical of the different bathymetric layers considered. eDNA metabarcoding data also returned a biodiversity 'bonus' of mostly mesopelagic species, not catchable by bottom trawls. Further investigation is needed to upscale this promising approach as a powerful tool to monitor catch composition, assess the distribution of stocks, and generally record changes in fish communities across the oceans.

Marine litter is an ever-increasing problem that demands immediate reduction plans and mitigation actions that should act synergically to efficiently meet ambitious goals. Since the seafloor has been recognized as the major sink for marine debris, the study of litter accumulation dynamics represents a fundamental tool to evaluate future removal actions. We analysed a 7 years (2013-2019) standardized data series collected along Sardinian fishing grounds through MEDiterranean International Trawl Survey, for which estimates of density and weight of seafloor macro-litter were calculated over 707 hauls. Results show the absence of any temporal trend in seafloor macro-litter density and weight, but rather indicate a spatial and bathymetric segregation of different litter categories. Our data showed how different sources and physical features of macro-litter items (i.e., plastic and fishing gears, rubber, glass, metal and textile) led to spatially segregated accumulation hotspots. These hotspots often occurred at shallower depths and closer to coastlines, representing spots where future litter removal action could be prioritized. We also point out here how the identification of seafloor macro-litter hotspots using aggregated data that include plastic items could indeed hide the identification of hotspots of other less abundant but yet detrimental macro-litter categories accumulated in the marine environment.

Monitoring marine resource exploitation is a key activity in fisheries science and biodiversity conservation. Since research surveys are time consuming and costly, fishery-dependent data (i.e., derived directly from fishing vessels) are increasingly credited with a key role in expanding the reach of ocean monitoring. Fishing vessels may be seen as widely ranging data-collecting platforms, which could act as a fleet of sentinels for monitoring marine life, in particular exploited stocks. Here, we investigate the possibility of assessing catch composition of single hauls carried out by trawlers by applying DNA metabarcoding to the dense water draining from fishing nets just after the end of hauling operations (hereafter "slush"). We assess the performance of this approach in portraying β-diversity and examining the quantitative relationship between species abundances in the catch and DNA amount in the slush (read counts generated by amplicon sequencing). We demonstrate that the assemblages identified using DNA in the slush satisfactorily mirror those returned by visual inspection of net content (about 71% of species and 86% of families of fish) and detect a strong relationship between read counts and species abundances in the catch. We therefore argue that this approach could be upscaled to serve as a powerful source of information on the structure of demersal assemblages and the impact of fisheries.

Plastic waste dumped in the marine environment has severe ecological, social and economic impacts. In recent years, a series of scientific studies documented the contamination by macroplastic and its impact on marine organisms through the accidental ingestion of microplastics, which also originate from the degradation of macroplastic. However, the relationship between the spatial distribution of marine litter and the ingestion of plastics by organisms have never been related. In this work, we aimed to investigate, through a modeling approach, the relations between potential sources of microplastic particles (i.e., seafloor macroplastic accumulation hotspots detected by means of trawl surveys), and the ingestion by the benthic crustacean Norwegian lobster (Nephrops norvegicus). According to the literature, N. norvegicus is characterized by a sedentary behavior and therefore it has been highlighted as a proficient sentinel species for local microplastic contamination. Despite no significant relation has been found between microplastic ingestion and the local presence of seafloor macroplastic, it seems that proximity to hotspots of macroplastic accumulation is significantly related to microplastics ingestion. These results highlight important considerations on the fate of plastic in the marine environments with significant impacts on biota and the quality of the product caught at sea.

The amount of ingredients of marine origin used in salmonid feed industry is rapidly decreasing and fish meal and fish oil have been largely replaced by vegetable ingredients. New potential protein rich ingredients for aquafeed formulations should therefore be alternative to vegetable ones. The pattern of fillet pigmentation was thus assessed in rainbow trout (Oncorhynchus mykiss) fed for 15 weeks isoproteic (42%) and isolipidic (24%) diets deprived of fish meal where 10% of protein from a blend of vegetable ingredients was replaced by cyanobacteria and microalgae dried biomass (Arthrospira platensis, Tisochrysis lutea and Tetraselmis suecica) or Louisiana red swamp crayfish (Procambarus clarkii) meal. An automatic, repeatable, and objective image analysis tool for the integrated determination and direct visualization of fillet colour was applied to digital images. Colour of fillets was also measured with a chromameter, recording data as L*, a*, b* indexes and used to validate image analysis results. Fillet carotenoid and lipid contents were determined, and their pattern of variation was compared to that obtained by image analysis. Fillet colouring capacity of crayfish meal was also compared to that of commercial synthetic astaxanthin included in rainbow trout feed. To this last aim, test diets were administered for 12 additional weeks. The image analysis and colorimetric data consistently indicated that, even if characterized by a significantly higher carotenoid content respect to fish fed a vegetable diet, fillets of trout fed the cyanobacteria and microalgae including diets displayed an undesirable yellowish colour. P. clarkii meal instead resulted a promising functional ingredient to supplement plant protein-based diets for trout, in view of its lipid composition and astaxanthin content. In fact, despite a relatively low dietary carotenoid level due to low percentage of inclusion, a desirable pink pigmentation was clearly detectable in fillets of trout fed the crayfish meal-including diet, which resulted in colour differences which were less obvious relative to those of fish given the astaxanthin-supplemented feeds at the end of the additional 12 weeks.

Abstract An increasing number of ecologists and researchers have addressed microplastics pollution in marine waters to explain the source, the transport, and the fate of these pollutants. Further data on the concentration of microplastics in the water column are crucial for understanding the impacts on ecosystems and to implement monitoring programs.This study provides information on the concentration and composition of sea water surface microplastics in three Italian subregions of the MSFD. We examined the flow of MPs from coastal to offshore areas, comparing their densities. We tested the efficiency of two sampling methodologies to evaluate the abundance and typology of MPs between marine layers. The results of this study confirm the high values of this pollutant in the Mediterranean Sea (0.029 ± 0.033 items · m-2), a MPs gradient from coastal to offshore areas, and a difference between the surface and subsurface marine layers.