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Monitoring large marine mammals is challenging due to their low abundances in general, an ability to move over large distances and wide geographical range sizes. The distribution of the pygmy (Kogia breviceps) and dwarf (Kogia sima) sperm whales is informed by relatively rare sightings, which does not permit accurate estimates of their distribution ranges. Hence, their conservation status has long remained Data Deficient (DD) in the Red list of the International Union for Conservation of Nature (IUCN), which prevent appropriate conservation measures. Environmental DNA (eDNA) metabarcoding uses DNA traces left by organisms in their environments to detect the presence of targeted taxon, and is here proved to be useful to increase our knowledge on the distribution of rare but emblematic megafauna. Retrieving eDNA from filtered surface water provides the first detection of the Dwarf sperm whale (Kogia sima) around the remote Malpelo island (Colombia). Environmental DNA collected during oceanic missions can generate better knowledge on rare but emblematic animals even in regions that are generally well sampled for other taxa.

How far do marine larvae disperse in the ocean? Decades of population genetic studies have revealed generally low levels of genetic structure at large spatial scales (hundreds of kilometres). Yet this result, typically based on discrete sampling designs, does not necessarily imply extensive dispersal. Here, we adopt a continuous sampling strategy along 950 km of coast in the northwestern Mediterranean Sea to address this question in four species. In line with expectations, we observe weak genetic structure at a large spatial scale. Nevertheless, our continuous sampling strategy uncovers a pattern of isolation by distance at small spatial scales (few tens of kilometres) in two species. Individual-based simulations indicate that this signal is an expected signature of restricted dispersal. At the other extreme of the connectivity spectrum, two pairs of individuals that are closely related genetically were found more than 290 km apart, indicating long-distance dispersal. Such a combination of restricted dispersal with rare long-distance dispersal events is supported by a high-resolution biophysical model of larval dispersal in the study area, and we posit that it may be common in marine species. Our results bridge population genetic studies with direct dispersal studies and have implications for the design of marine reserve networks.

Marine protected areas (MPAs) are globally important environmental management tools that provide protection from the effects of human exploitation and activities, supporting the conservation of marine biological diversity, habitats, ecosystems and the processes they host, as well as resources in a broad sense. Consequently, they are also expected to manage and enhance marine ecosystem services and material, non-material, consumptive and non-consumptive goods, and benefits for humans. There is however certain confusion on what constitutes an ecosystem service, and it is not always easy to distinguish between them and societal benefits. The main nuance is that an ecosystem service is the aptitude an ecosystem has or develops naturally or as consequence of a management action, and that manifests through its own properties (productivity, diversity, stability, quality of its key parameters, etc.), while a societal benefit is the economic or other profitability (emotional, educational, scientific, etc.) that humans obtain from said service or quality. In this work, 268 publications, together with our own experiences in the different investigations carried out in the MPAs that are part of the BiodivERsA3-2015-21 RESERVEBENEFIT European project, have been selected, reviewed and discussed to analyze the knowledge status of the expected ecosystem services of MPAs and the societal benefits derived from them, sometimes providing information on their evidence, when they exist. We define and classify the effects of protection, ecosystem services and societal benefits and elaborate a conceptual model of the cause-effect relationships between them.

Climate change is rapidly becoming one of the biggest threats to marine life, and its impacts have the potential to strongly affect fisheries upon which millions of people rely. This is particularly crucial for the Mediterranean Sea, which is one of the world’s biodiversity hotspots, one of the world’s most overfished regions, and where temperatures are rising 25% faster than in the rest of the ocean on average. In this study, we calculated a vulnerability index for 100 species that compose 95% of the Mediterranean catches, through a trait-based approach. The Climate Risk Assessment (CRA) methodology was subsequently used to assess the risks due to climate change of Mediterranean fisheries. We found that the northern Mediterranean fisheries target more vulnerable species than their southern counterparts. However, when combining this catch-based vulnerability with a suite of socio-economic parameters, north African countries stand out as the most vulnerable to climate change impacts. Indeed, considering countries’ exposure of the fisheries sector and their vulnerability to climate change, a sharp contrast between northern and southern Mediterranean appears, with Egypt and Tunisia scoring the highest risk. By integrating a trait-based approach on targeted marine species with socio-economic features, our analysis helps to better understand the ramifications of climate change consequences on Mediterranean fisheries and highlights the regions that could potentially be particularly affected.

Assessing the impact of global changes and protection effectiveness is a key step in monitoring marine fishes. Most traditional census methods are demanding or destructive. Nondisturbing and nonlethal approaches based on video and environmental DNA are alternatives to underwater visual census or fishing. However, their ability to detect multiple biodiversity factors beyond traditional taxonomic diversity is still unknown. For bony fishes and elasmobranchs, we compared the performance of eDNA metabarcoding and long-term remote video to assess species’ phylogenetic and functional diversity. We used 10 eDNA samples from 30 L of water each and 25 hours of underwater videos over 4 days on Malpelo Island (pacific coast of Colombia), a remote marine protected area. Metabarcoding of eDNA detected 66% more molecular operational taxonomic units (MOTUs) than video. We found 66 and 43 functional entities with a single eDNA marker and videos, respectively, and higher functional richness for eDNA than videos. Despite gaps in genetic reference databases, eDNA also detected a higher fish phylogenetic diversity than videos; accumulation curves showed how 1 eDNA transect detected as much phylogenetic diversity as 25 hours of video. Environmental DNA metabarcoding can be used to affordably, efficiently, and accurately census biodiversity factors in marine systems. Although taxonomic assignments are still limited by species coverage in genetic reference databases, use of MOTUs highlights the potential of eDNA metabarcoding once reference databases have expanded.

Underwater cameras are widely used to monitor marine biodiversity, and the trend is increasing due to the availability of cheap action cameras. The main bottleneck of video methods now resides in the manual processing of images, a time-consuming task requiring trained experts. Recently, several solutions based on Deep Learning (DL) have been proposed to automatically process underwater videos. The main limitation of such algorithms is that they require thousands of annotated images in order to learn to discriminate classes (here species). This limitation implies two issues: 1) the annotation of hundreds of common species requires a lot of efforts 2) many species are too rare to gather enough data to train a classic DL algorithm. Here, we propose to explore how few-shot learning (FSL), an emerging research field, could overcome DL limitations. Few-shot learning is based on the principle of training a Deep Learning algorithm on “how to learn a new classification problem with only few images”. In our case-study, we assess the robustness of FSL to discriminate 20 coral reef fish species with a range of training databases from 1 image per class to 30 images per class, and compare FSL to a classic DL approach with thousands of images per class. We found that FSL outperform classic DL approach in situations where annotated images are limited, yet still providing good classification accuracy.

As climate change accelerates, species are shifting poleward and subtropical and tropical species are colonizing temperate environments. A popular approach for characterizing such responses is the community temperature index (CTI), which tracks the mean thermal affinity of a community. Studies in marine, freshwater, and terrestrial ecosystems have documented increasing CTI under global warming. However, most studies have only linked increasing CTI to increases in warm-affinity species. Here, using long-term monitoring of marine fishes across the Northern Hemisphere, we decomposed CTI changes into four underlying processes—tropicalization (increasing warm-affinity), deborealization (decreasing cold-affinity), borealization (increasing cold-affinity), and detropicalization (decreasing warm-affinity)—for which we examined spatial variability and drivers. CTI closely tracked changes in sea surface temperature, increasing in 72% of locations. However, 31% of these increases were primarily due to decreases in cold-affinity species, i.e., deborealization. Thus, increases in warm-affinity species were prevalent, but not ubiquitous. Tropicalization was stronger in areas that were initially warmer, experienced greater warming, or were deeper, while deborealization was stronger in areas that were closer to human population centers or that had higher community thermal diversity. When CTI (and temperature) increased, species that decreased were more likely to be living closer to their upper thermal limits or to be commercially fished. Additionally, warm-affinity species that increased had smaller body sizes than those that decreased. Our results show that CTI changes arise from a variety of underlying community responses that are linked to environmental conditions, human impacts, community structure, and species characteristics.

Bioinformatic analysis of eDNA metabarcoding data is crucial toward rigorously assessing biodiversity. Many programs are now available for each step of the required analyses, but their relative abilities at providing fast and accurate species lists have seldom been evaluated. We used simulated mock communities and real fish eDNA metabarcoding data to evaluate the performance of 13 bioinformatic programs and pipelines to retrieve fish occurrence and read abundance using the 12S mt rRNA gene marker. We used four indices to compare the outputs of each program with the simulated samples: sensitivity, F-measure, root-mean-square error (RMSE) on read relative abundances, and execution time. We found marked differences among programs only for the taxonomic assignment step, both in terms of sensitivity, F-measure and RMSE. Running time was highly different between programs for each step. The fastest programs with best indices for each step were assembled into a pipeline. We compare this pipeline to pipelines constructed from existing toolboxes (OBITools, Barque, and QIIME 2). Our pipeline and Barque obtained the best performance for all indices and appear to be better alternatives to highly used pipelines for analyzing fish eDNA metabarcoding data with a complete reference database. Real eDNA metabarcoding data also indicated differences for taxonomic assignment and execution time only. This study reveals major differences between programs during the taxonomic assignment step. The choice of algorithm for the taxonomic assignment can have a significant impact on diversity estimates and should be made according to the objectives of the study.

Estuaries are characterized by a tidal regime and are strongly influenced by hydrodynamics and host diverse and highly dynamic habitats, from fresh, brackish, or saltwater to terrestrial, whose biodiversity is especially difficult to monitor. Here, we investigated the potential of environmental DNA (eDNA) metabarcoding, with three primer sets targeting different regions of the mitochondrial DNA 12S ribosomal RNA gene, to detect vertebrate diversity in the estuary of the Don Diego River in Colombia. With eDNA, we detected not only aquatic organisms, including fishes, amphibians, and reptiles, but also a large diversity of terrestrial, arboreal, and flying vertebrates, including mammals and birds, living in the estuary surroundings. Further, the eDNA signal remained relatively localized along the watercourse. A transect from the deep outer section of the estuary, across the river mouth toward the inner section of the river, showed marked taxonomic turnover from typical marine to freshwater fishes, while eDNA of terrestrial and arboreal species was mainly found in the inner section of the estuary. Our results indicate that eDNA enables the detection of a large diversity of vertebrates and could become an important tool for biodiversity monitoring in estuaries, where water integrates information across the ecosystem.

Trait- based ecology aims to understand the processes that generate the overarching diversity of organismal traits and their influence on ecosystem functioning. Achieving this goal requires simplifying this complexity in synthetic axes defining a trait space and to cluster species based on their traits while identifying those with unique combinations of traits. However, so far, we know little about the dimensionality, the robustness to trait omission and the structure of these trait spaces. Here, we propose a unified framework and a synthesis across 30 trait datasets representing a broad variety of taxa, ecosystems and spatial scales to show that a common trade- off between trait space quality and operationality appears between three and six dimensions. The robustness to trait omission is generally low but highly variable among datasets. We also highlight invariant scaling relationships, whatever organismal complexity, between the number of clusters, the number of species in the dominant cluster and the number of unique species with total species richness. When species richness increases, the number of unique species saturates, whereas species tend to disproportionately pack in the richest cluster. Based on these results, we propose some rules of thumb to build species trait spaces and estimate subsequent functional diversity indices.

Long-distance (>40-km) dispersal from marine reserves is poorly documented; yet, it can provide essential benefits such as seeding fished areas or connecting marine reserves into networks. From a meta-analysis, we suggest that the spatial scale of marine connectivity is underestimated due to the limited geographic extent of sampling designs. We also found that the largest marine reserves (>1000 km2) are the most isolated. These findings have important implications for the assessment of evolutionary, ecological, and socio-economic long-distance benefits of marine reserves. We conclude that existing methods to infer dispersal should consider the up-to-date genomic advances and also expand the spatial scale of sampling designs. Incorporating longdistance connectivity in conservation planning will contribute to increase the benefits of marine reserve networks.

Howfar domarine larvae disperse in the ocean? Decades of population genetic studies have revealed generally low levels of genetic structure at large spatial scales (hundreds of kilometres). Yet this result, typically based on discrete sampling designs, does not necessarily imply extensive dispersal. Here, we adopt a continuous sampling strategy along 950 km of coast in the northwestern Mediterranean Sea to address this question in four species. In line with expectations, we observe weak genetic structure at a large spatial scale. Nevertheless, our continuous sampling strategy uncovers a pattern of isolation by distance at small spatial scales (few tens of kilometres) in two species. Individual- based simulations indicate that this signal is an expected signature of restricted dispersal. At the other extreme of the connectivity spectrum, two pairs of individuals that are closely related genetically were found more than 290 km apart, indicating long-distance dispersal. Such a combination of restricted dispersal with rare long-distance dispersal events is supported by a high-resolution biophysical model of larval dispersal in the study area, and we posit that it may be common in marine species. Our results bridge population genetic studies with direct dispersal studies and have implications for the design of marine reserve networks

Identifying species that are both geographically restricted and functionally distinct, i.e. supporting rare traits and functions, is of prime importance given their risk of extinction and their potential contribution to ecosystem functioning. We use global species distributions and functional traits for birds and mammals to identify the ecologically rare species, understand their characteristics, and identify hotspots. We find that ecologically rare species are disproportionately represented in IUCN threatened categories, insufficiently covered by protected areas, and for some of them sensitive to current and future threats. While they are more abundant overall in countries with a low human development index, some countries with high human development index are also hotspots of ecological rarity, suggesting transboundary responsibility for their conservation. Altogether, these results state that more conservation emphasis should be given to ecological rarity given future environmental conditions and the need to sustain multiple ecosystem processes in the long-term. There are many available ways to rank species for conservation prioritization. Here the authors identify species of mammals and birds that are both spatially restricted and functionally distinct, finding that such species are currently insufficiently protected and disproportionately sensitive to current and future threats.

Many islands are biodiversity hotspots but also extinction epicenters. In addition to strong cultural connections to nature, islanders derive a significant part of their economy and broader wellbeing from this biodiversity. Islands are thus considered as the socio-ecosystems most vulnerable to species and habitat loss. Yet, the extent and key correlates of protected area coverage on islands is still unknown. Here we assess the relative influence of climate, geography, habitat diversity, culture, resource capacity, and human footprint on terrestrial and marine protected area coverage across 2323 inhabited islands globally. We show that, on average, 22% of terrestrial and 13% of marine island areas are under protection status, but that half of all islands have no protected areas. Climate, diversity of languages, human population density and development are strongly associated with differences observed in protected area coverage among islands. Our study suggests that economic development and population growth may critically limit the amount of protection on islands

Processing data from surveys using photos or videos remains a major bottleneck in ecology. Deep Learning Algorithms (DLAs) have been increasingly used to automatically identify organisms on images. However, despite recent advances, it remains difficult to control the error rate of such methods. Here, we proposed a new framework to control the error rate of DLAs. More precisely, for each species, a confidence threshold was automatically computed using a training dataset independent from the one used to train the DLAs. These species-specific thresholds were then used to post-process the outputs of the DLAs, assigning classification scores to each class for a given image including a new class called “unsure”. We applied this framework to a study case identifying 20 fish species from 13,232 underwater images on coral reefs. The overall rate of species misclassification decreased from 22% with the raw DLAs to 2.98% after post-processing using the thresholds defined to minimize the risk of misclassification. This new framework has the potential to unclog the bottleneck of information extraction from massive digital data while ensuring a high level of accuracy in biodiversity assessment.

Current approaches that compare spatial genetic structure of a given species and the dispersal of its mobile phase can detect a mismatch between both patterns mainly due to processes acting at different temporal scales. Genetic structure result from gene flow and other evolutionary and demographic processes over many generations, while dispersal predicted from the mobile phase often represents solely one generation on a single time‐step. In this study, we present a spatial graph approach to landscape genetics that extends connectivity networks with a stepping‐stone model to represent dispersal between suitable habitat patches over multiple generations. We illustrate the approach with the case of the striped red mullet Mullus surmuletus in the Mediterranean Sea. The genetic connectivity of M. surmuletus was not correlate with the estimated dispersal probability over one generation, but with the stepping‐stone estimate of larval dispersal, revealing the temporal scale of connectivity across the Mediterranean Sea. Our results highlight the importance of considering multiple generations and different time scales when relating demographic and genetic connectivity. The spatial graph of genetic distances further untangles intra‐population genetic structure revealing the Siculo‐Tunisian Strait as an important corridor rather than a barrier for gene flow between the Western‐ and Eastern Mediterranean basins, and identifying Mediterranean islands as important stepping‐stones for gene flow between continental populations. Our approach can be easily extended to other systems and environments.

Wilderness areas offer unparalleled ecosystem conditions. However, growing human populations and consumption are among factors that drive encroachment on these areas. Here, we explore the threat of small‐scale fisheries to wilderness reefs by developing a framework and modeling fluctuations in fishery range with fuel costs and fish prices. We modeled biomass of four fishery groups across the New Caledonian archipelago, and used fish and fuel prices from 2005 to 2020 to estimate the extent of exploited reefs across three fishing scenarios. From 2012 to 2018, maximum profitable range increased from 15 to over 30 hr from the capital city, expanding to reefs previously uneconomic to fish, including a UNESCO heritage site. By 2020, over half of New Caledonian (∼17% global) wilderness reefs will become profitable to fish. Our results demonstrate that remoteness from humans should not be considered protection for wilderness coral reefs in the context of rising fish prices.

Genetic diversity is estimated to be declining faster than species diversity under escalating threats, but its spatial distribution remains poorly documented at the global scale. Theory predicts that similar processes should foster congruent spatial patterns of genetic and species diversity, but empirical studies are scarce. Using a mined database of 50,588 georeferenced mitochondrial DNA barcode sequences (COI) for 3,815 marine and 1,611 freshwater fish species respectively, we examined the correlation between genetic diversity and species diversity and their global distributions in relation to climate and geography. Genetic diversity showed a clear spatial organisation, but a weak association with species diversity for both marine and freshwater species. We found a predominantly positive relationship between genetic diversity and sea surface temperature for marine species. Genetic diversity of freshwater species varied primarily across the regional basins and was negatively correlated with average river slope. The detection of genetic diversity patterns suggests that conservation measures should consider mismatching spatial signals across multiple facets of biodiversity.

Although extinctions due to climate change are still uncommon, they might surpass those caused by habitat loss or overexploitation over the next few decades. Among marine megafauna, mammals fulfill key and irreplaceable ecological roles in the ocean, and the collapse of their populations may therefore have irreversible consequences for ecosystem functioning and services. Using a trait-based approach, we assessed the vulnerability of all marine mammals to global warming under high and low greenhouse gas emission scenarios for the middle and the end of the 21st century. We showed that the North Pacific Ocean, the Greenland Sea and the Barents Sea host the species that are most vulnerable to global warming. Future conservation plans should therefore focus on these regions, where there are long histories of overexploitation and there are high levels of current threats to marine mammals. Among the most vulnerable marine mammals were several threatened species, such as the North Pacific right whale (Eubalaena japonica) and the dugong (Dugong dugon), that displayed unique combinations of functional traits. Beyond species loss, we showed that the potential extinctions of the marine mammals that were most vulnerable to global warming might induce a disproportionate loss of functional diversity, which may have profound impacts on the future functioning of marine ecosystems worldwide.

The use of functional information in the form of species traits plays an important role in explaining biodiversity patterns and responses to environmental changes. Although relationships between species composition, their traits, and the environment have been extensively studied on a case-by-case basis, results are variable, and it remains unclear how generalizable these relationships are across ecosystems, taxa and spatial scales. To address this gap, we collated 80 datasets from trait-based studies into a global database for metaCommunity Ecology: Species, Traits, Environment and Space; “CESTES”. Each dataset includes four matrices: species community abundances or presences/absences across multiple sites, species trait information, environmental variables and spatial coordinates of the sampling sites. The CESTES database is a live database: it will be maintained and expanded in the future as new datasets become available. By its harmonized structure, and the diversity of ecosystem types, taxonomic groups, and spatial scales it covers, the CESTES database provides an important opportunity for synthetic trait-based research in community ecology.

Coelacanth fishes of the genus Latimeria are the only surviving representatives of a basal lineage of vertebrates that originated more than 400 million years ago. Yet, much remains to be unveiled about the diversity and evolutionary history of these ‘living fossils’ using new molecular data, including the possibility of ‘cryptic’ species or unknown lineages. Here, we report the discovery of a new specimen in eastern Indonesia allegedly belonging to the species L. menadoensis. Although this specimen was found about 750 km from the known geographical distribution of the species, we found that the molecular divergence between this specimen and others of L. menadoensis was great: 1.8% compared to 0.04% among individuals of L. chalumnae, the other living species of coelacanth. Molecular dating analyses suggested a divergence date of ca. 13 million years ago between the two populations of Indonesian coelacanths. We elaborate a biogeographical scenario to explain the observed genetic divergence of Indonesian coelacanth populations based on oceanic currents and the tectonic history of the region over Miocene to recent. We hypothesize that several populations of coelacanths are likely to live further east of the present capture location, with potentially a new species that remains to be described. Based on this, we call for an international effort to take appropriate measures to protect these fascinating but vulnerable vertebrates which represent among the longest branches on the Tree of Life.

The worldwide decline of coral reefs necessitates targeting management solutions that can sustain reefs and the livelihoods of the people who depend on them. However, little is known about the context in which different reef management tools can help to achieve multiple social and ecological goals. Because of nonlinearities in the likelihood of achieving combined fisheries, ecological function, and biodiversity goals along a gradient of human pressure, relatively small changes in the context in which management is implemented could have substantial impacts on whether these goals are likely to be met. Critically, management can provide substantial conservation benefits to most reefs for fisheries and ecological function, but not biodiversity goals, given their degraded state and the levels of human pressure they face.

Rapid degradation of the world’s coral reefs jeopardizes their ecological functioning and ultimately imperils the wellbeing of the millions of people with reef-dependent livelihoods. Ecosystem accessibility is the main driver of their conditions, with the most accessible ecosystems being most at risk of resource depletion. People’s socioeconomic conditions can change as they get further from urban centers and can profoundly influence people’s relationship with the environment. However, the mechanisms through which increasing accessibility from human societies affects natural resources are still unclear. A plausible mechanism through which markets influence the environment is through the socioeconomic changes that tend to accompany accessibility. We used social and ecological data from 10 coastal communities and 31 reefs in northwest Madagascar to (i) unravel the respective influences of the local fish market and coastal communities on reef fish biomass and (ii) investigate how communities’ socioeconomic and resource use characteristics change with increasing proximity to markets. We used generalized additive models to reveal that reef fish biomass is strongly related to the accessibility of both markets and local communities. We also highlight that the ways coastal communities use marine resources changes predictably with market proximity. More precisely, market proximity affects fishing gear (technique effect), wealth, and selling strategies (scale effect) of coastal communities. Our findings emphasize the need to better quantify links between markets and fishing communities through household-level surveys to implement market-based actions that could help to regulate the effect of markets on both fish stocks and fishing communities.

Environmental DNA (eDNA) has the potential to provide more comprehensive biodiversity assessments, particularly for vertebrates in species-rich regions. However, this method requires the completeness of a reference database (i.e. a list of DNA sequences attached to each species), which is not currently achieved for many taxa and ecosystems. As an alternative, a range of operational taxonomic units (OTUs) can be extracted from eDNA metabarcoding. However, the extent to which the diversity of OTUs provided by a limited eDNA sampling effort can predict regional species diversity is unknown. Here, by modelling OTU accumulation curves of eDNA seawater samples across the Coral Triangle, we obtained an asymptote reaching 1531 fish OTUs, while 1611 fish species are recorded in the region. We also accurately predict (R² = 0.92) the distribution of species richness among fish families from OTU-based asymptotes. Thus, the multi-model framework of OTU accumulation curves extends the use of eDNA metabarcoding in ecology, biogeography and conservation.

Aquesta és una correcció a l'article 10.1038/s41597-019-0344-7

Limiting climate warming below 2°C requires both reducing anthropic greenhouse gas emissions and sequestering more atmospheric carbon. Natural Climate Solutions (NCS) rely on the ability of ecosystems to capture and store carbon. Despite the important role of marine megafauna on the ocean carbon cycle, its potential as a NCS has not yet been explored. Here, we quantify the amount of carbon potentially sequestered by five baleen whale species across the Southern Hemisphere between 1890 and 2100 through both the sinking of carcasses after natural death and the fertilisation of phytoplankton by nutrients in faeces. At their pre-exploitation abundances, the five whales could sequester 10.6 106 tonnes of carbon per year (tC.yr-1) but this natural carbon sink was reduced at 2 106 tC.yr-1 in 1965 due to commercial whaling. However, the restoration of whale populations could sequester 8.7 106 tC.yr-1 at the end of the 21st century suggesting an efficient but neglected NCS that remains to be estimated globally including all marine vertebrates.