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Tropical reefs provide livelihood and food security to millions of people. However, tropical reefs are entering new configurations requiring management strategies to incorporate process-oriented measures such as biomass production to determine their dynamics and resilience. We proposed a new framework, comprising three management strategies based on fish standing biomass and productivity which were calculated on 2,027 reef sites over 39 countries. We found that 3.5% of the sites have low fish biomass and productivity, where alternative fisheries like seaweed and bivalve aquaculture are recommended. We identified 24% of high productivity sites where we suggest adaptive management: establishment of partially protected areas sustaining local fisheries when needed, or full protection when possible given their capacity for recovery. For the 5% high biomass sites, we urgently need full protection to maintain high reproductive capacity through large individuals. Our framework can thus guide management strategies by incorporating both static and process-oriented measures, tailoring each strategy to local priorities based on biodiversity and socio-economic objectives.

Increasing speed and magnitude of global change threaten the world's biodiversity and particularly coral reef fishes. A better understanding of large-scale patterns and processes on coral reefs is essential to prevent fish biodiversity decline but it requires new monitoring approaches. Here, we use environmental DNA metabarcoding to reconstruct well-known patterns of fish biodiversity on coral reefs and uncover hidden patterns on these highly diverse and threatened ecosystems. We analysed 226 environmental DNA (eDNA) seawater samples from 100 stations in five tropical regions (Caribbean, Central and Southwest Pacific, Coral Triangle and Western Indian Ocean) and compared those to 2047 underwater visual censuses from the Reef Life Survey in 1224 stations. Environmental DNA reveals a higher (16%) fish biodiversity, with 2650 taxa, and 25% more families than underwater visual surveys. By identifying more pelagic, reef-associated and crypto-benthic species, eDNA offers a fresh view on assembly rules across spatial scales. Nevertheless, the reef life survey identified more species than eDNA in 47 shared families, which can be due to incomplete sequence assignment, possibly combined with incomplete detection in the environment, for some species. Combining eDNA metabarcoding and extensive visual census offers novel insights on the spatial organization of the richest marine ecosystems.

Effective solutions to the ongoing “coral reef crisis” will remain limited until the underlying drivers of coral reef degradation are better understood. Here, we conduct a global-scale study of how four key metrics of ecosystem states and processes on coral reefs (top predator presence, reef fish biomass, trait diversity, and parrotfish scraping potential) are explained by 11 indicators based on key human-environment theories from the social sciences. Our global analysis of >1,500 reefs reveals three key findings. First, the proximity of the nearest market has the strongest and most consistent relationships with these ecosystem metrics. This finding is in keeping with a body of terrestrial research on how market accessibility shapes agricultural practices, but the integration of these concepts in marine systems is nascent. Second, our global study shows that resource conditions tend to display a n-shaped relationship with socioeconomic development. Specifically, the probabilities of encountering a top predator, fish biomass, and fish trait diversity were highest where human development was moderate but lower where development was either high or low. This finding contrasts with previous regional-scale research demonstrating an environmental Kuznets curve hypothesis (which predicts a U-shaped relationship between socioeconomic development and resource conditions). Third, together, our ecosystem metrics are best explained by the integration of different human-environment theories. Our best model includes the interactions between indicators from different theoretical perspectives, revealing how marine reserves can have different outcomes depending on how far they are from markets and human settlements, as well as the size of the surrounding human population.

Reef fishes are closely connected to many human populations, yet their contributions to society are mostly considered through their economic and ecological values. Cultural and intrinsic values of reef fishes to the public can be critical drivers of conservation investment and success, but remain challenging to quantify. Aesthetic value represents one of the most immediate and direct means by which human societies engage with biodiversity, and can be evaluated from species to ecosystems. Here, we provide the aesthetic value of 2,417 ray-finned reef fish species by combining intensive evaluation of photographs of fishes by humans with predicted values from machine learning. We identified important biases in species’ aesthetic value relating to evolutionary history, ecological traits, and International Union for Conservation of Nature (IUCN) threat status. The most beautiful fishes are tightly packed into small parts of both the phylogenetic tree and the ecological trait space. In contrast, the less attractive fishes are the most ecologically and evolutionary distinct species and those recognized as threatened. Our study highlights likely important mismatches between potential public support for conservation and the species most in need of this support. It also provides a pathway for scaling-up our understanding of what are both an important nonmaterial facet of biodiversity and a key component of nature’s contribution to people, which could help better anticipate consequences of species loss and assist in developing appropriate communication strategies.

Species inventories are the building blocks of our assessment of biodiversity patterns and human impact. Yet, historical inventories based on visual observations are often incomplete, impairing subsequent analyses of ecological mechanisms, extinction risk and management success. Environmental DNA (eDNA) metabarcoding is an emerging tool that can provide wider biodiversity assessments than classical visual-based surveys. However, eDNA-based inventories remain limited by sampling effort and reference database incompleteness. In this study, we propose a new framework coupling eDNA surveys and sampling-theory methods to estimate species richness in under-sampled and hyper-diverse regions where some species remain absent from the checklist or undetected by visual surveys. We applied this framework to the coastal fish diversity in the heart of the coral triangle, the richest marine biodiversity hotspot worldwide. Combining data from 279 underwater visual censuses, 92 eDNA samples and an extensive custom genetic reference database, we show that eDNA metabarcoding recorded 196 putative species not detected by underwater visual census including 37 species absent from the regional checklist. We provide an updated checklist of marine fishes in the ‘Raja Ampat Bird's Head Peninsula' ecoregion with 2534 species including 1761 confirmed and 773 highly probable presences. The Chao lower-bound diversity estimator, based on the incidence of rare species, shows that the region potentially hosts an additional 123 fish species, including pelagic, cryptobenthic and vulnerable species. The extended and hidden biodiversity along with their asymptotic estimates highlight the ability of eDNA to expand regional inventories and species distributions to better guide conservation strategies.

Although how rare species persist in communities is a major ecological question, the critical phenotypic dimension of rarity is broadly overlooked. Recent work has shown that evaluating functional distinctiveness, the average trait distance of a species to other species in a community, offers essential insights into biodiversity dynamics, ecosystem functioning, and biological conservation. However, the ecological mechanisms underlying the persistence of functionally distinct species are poorly understood. Here we propose a heterogeneous fitness landscape framework, whereby functional dimensions encompass peaks representing trait combinations that yield positive intrinsic growth rates in a community. We identify four fundamental causes leading to the persistence of functionally distinct species in a community. First, environmental heterogeneity or alternative phenotypic designs can drive positive population growth of functionally distinct species. Second, sink populations with negative growth can deviate from local fitness peaks and be functionally distinct. Third, species found at the margin of the fitness landscape can persist but be functionally distinct. Fourth, biotic interactions (either positive or negative) can dynamically alter the fitness landscape. We offer examples of these four cases and some guidelines to distinguish among them. In addition to these deterministic processes, we also explore how stochastic dispersal limitation can yield functional distinctiveness.

Large land and ocean mammals, like elephants and whales, play essential roles in the environment but are severely threatened by human activities. Images taken from planes can be used to spot these animals from the air. However, these species are difficult to observe because they are rare and move a lot, so unfortunately there are not many images collected from planes that contain these species. Fortunately, however, people share many photos and videos of large animals on social networks because these animals are attractive. These images have been used by researchers to train a computer program to recognize an endangered ocean mammal: the dugong. The program found up to 79% of the dugongs present in images collected by a plane flying around the main island of New Caledonia, which is in the Pacific Ocean. The goal is to use this program to automatically count and map dugongs in New Caledonia.

Despite the importance of marine megafauna on ecosystem functioning, their contribution to the oceanic carbon cycle is still poorly known. Here, we explored the role of baleen whales in the biological carbon pump across the southern hemisphere based on the historical and forecasted abundance of five baleen whale species. We modelled whale-mediated carbon sequestration through the sinking of their carcasses after natural death. We provide the first temporal dynamics of this carbon pump from 1890 to 2100, considering both the effects of exploitation and climate change on whale populations. We reveal that at their pre-exploitation abundance, the five species of southern whales could sequester 4.0 × 10 5 tonnes of carbon per year (tC yr −1 ). This estimate dropped to 0.6 × 10 5 tC yr −1 by 1972 following commercial whaling. However, with the projected restoration of whale populations under a RCP8.5 climate scenario, the sequestration would reach 1.7 × 10 5 tC yr −1 by 2100, while without climate change, recovered whale populations could sequester nearly twice as much (3.2 × 10 5 tC yr −1 ) by 2100. This highlights the persistence of whaling damages on whale populations and associated services as well as the predicted harmful impacts of climate change on whale ecosystem services.

To mitigate the ongoing threats to coastal ecosystems, and the biodiversity erosion they are causing, Marine Protected Areas (MPAs) have emerged as powerful and widespread conservation tools. Strictly no-take MPAs, also called marine reserves, undeniably promote fish biomass and density, but it remains unclear how biodiversity responds to protection. Identifying which facets of biodiversity respond to protection is critical for the management of MPAs and the development of relevant conservation strategies towards the achievement of biodiversity targets. We collected 99 environmental DNA (eDNA) samples inside and outside nine marine reserves in the Mediterranean Sea to assess the effect of protection on 11 biodiversity indicators based on fish traits, phylogeny and vulnerability to fishing. We controlled for the effect of environmental heterogeneity (habitat, bathymetry, productivity, temperature, and accessibility) using a Principal Component Analysis, and for spatial autocorrelation due to potential unmeasured factors. We found a positive and significant effect of protection on only 3 out of 11 indicators: functional and phylogenic diversity but also the ratio between demerso-pelagic and benthic species richness. Rather, total fish richness responded significantly and negatively to protection. We did not detect any significant effect of protection on threatened and elasmobranch species richness, probably due to their large home range compared to the size of Mediterranean marine reserves. Synthesis and applications: Our findings highlight the importance of looking beyond the mere number of species to fully depict and understand the effect of marine reserves on biodiversity and evaluate the effectiveness of conservation measures. Rather, we propose a dashboard of three eDNA-based indicators that can provide an early signal of ecosystem deterioration or recovery. eDNA metabarcoding offers a powerful tool to supply site-specific and standardized taxonomic-, phylogeneti

1-Climate influences population genetic variation in marine species. Capturing these impacts remains challenging for marine fishes which disperse over large geographic scales spanning steep environmental gradients. It requires the extensive spatial sampling of individuals or populations, representative of seascape heterogeneity, combined with a set of highly informative molecular markers capable of revealing climatic-associated genetic variations. 2- We explored how space, dispersal and environment shape the genomic patterns of two sympatric fish species in the Mediterranean Sea, which ranks among the oceanic basins most affected by climate change and human pressure. We hypothesized that the population structure and climate-associated genomic signatures of selection would be stronger in the less mobile species, as restricted gene flow tends to facilitate the fixation of locally adapted alleles. 3- In order to test our hypothesis, we genotyped two species with contrasting dispersal abilities: the white seabream (Diplodus sargus) and the striped red mullet (Mullus surmuletus). We collected 823 individuals and used genotyping by sequencing (GBS) to detect 8,206 Single Nucleotides Polymorphisms (SNPs) for the seabream and 2,794 for the mullet. For each species, we identified highly differentiated genomic regions (i.e. outliers) and disentangled the relative contribution of space, dispersal and environmental variables (climate, marine primary productivity) on the outliers’ genetic structure to test the prevalence of gene flow and local adaptation. 4- We observed contrasting patterns of gene flow and adaptive genetic variation between the two species. The seabream showed a distinct Alboran sea population and panmixia across the Mediterranean Sea. The mullet revealed additional differentiation within the Mediterranean Sea that was significantly correlated to summer and winter temperatures, as well as marine primary productivity. Functional annotation of the climate-associa

unctional diversity (FD), the diversity of organism attributes that relates to their interactions with the abiotic and biotic environment, has been increasingly used for the last two decades in ecology, biogeography and conservation. Yet, FD has many facets and their estimations are not standardized nor embedded in a single tool. mFD (multifaceted functional diversity) is an R package that uses matrices of species assemblages and species trait values as building blocks to compute most FD indices. mFD is firstly based on two functions allowing the user to summarize trait and assemblage data. Then it calculates trait-based distances between species pairs, informs the user whether species have to be clustered into functional entities and finally computes multidimensional functional space. To let the user choose the most appropriate functional space for computing multidimensional functional diversity indices, two mFD functions allow assessing and illustrating the quality of each functional space. Next, mFD provides 6 core functions to calculate 16 existing FD indices based on trait-based distances, functional entities or species position in a functional space. The mFD package also provides graphical functions based on the ggplot library to illustrate FD values through customizable and high-resolution plots of species distribution among functional entities or in a multidimensional space. All functions include internal validation processes to check for errors in data formatting which return detailed error messages. To facilitate the use of mFD framework, we built an associated website hosting five tutorials illustrating the use of all the functions step by step.

The contributions of species to ecosystem functions or services depend not only on their presence but also on their local abundance. Progress in predictive spatial modelling has largely focused on species occurrence rather than abundance. As such, limited guidance exists on the most reliable methods to explain and predict spatial variation in abundance. We analysed the performance of 68 abundance-based species distribution models fitted to 800 000 standardised abundance records for more than 800 terrestrial bird and reef fish species. We found a large amount of variation in the performance of abundance-based models. While many models performed poorly, a subset of models consistently reconstructed range-wide abundance patterns. The best predictions were obtained using random forests for frequently encountered and abundant species and for predictions within the same environmental domain as model calibration. Extending predictions of species abundance outside of the environmental conditions used in model training generated poor predictions. Thus, interpolation of abundances between observations can help improve understanding of spatial abundance patterns, but our results indicate extrapolated predictions of abundance under changing climate have a much greater uncertainty. Our synthesis provides a road map for modelling abundance patterns, a key property of species distributions that underpins theoretical and applied questions in ecology and conservation.

Outside controlled experimental plots, the impact of community attributes on primary productivity has rarely been compared to that of individual species. Here, we identified plant species of high importance for productivity (key species) in >29,000 diverse grassland communities in the European Alps, and compared their effects with those of community-level measures of functional composition (weighted means, variances, skewness and kurtosis). After accounting for the environment, the five most important key species jointly explained more deviance of productivity than any measure of functional composition alone. Key species were generally tall with high specific leaf areas. By dividing the observations according to distinct habitats, the explanatory power of key species and functional composition increased and key-species plant types and functional composition-productivity relationships varied systematically, presumably because of changing interactions and trade-offs between traits. Our results advocate for a careful consideration of species’ individual effects on ecosystem functioning in complement to community-level measures.

Despite evidence of a positive effect of functional diversity on ecosystem productivity, the importance of functionally distinct species (i.e. species that display an original combination of traits) is poorly understood. To investigate how distinct species affect ecosystem productivity, we used a forest-gap model to simulate realistic temperate forest successions along an environmental gradient and measured ecosystem productivity at the end of the successional trajectories. We performed 10 560 simulations with different sets and numbers of species, bearing either distinct or indistinct functional traits, and compared them to random assemblages, to mimic the consequences of a regional loss of species. Long-term ecosystem productivity dropped when distinct species were lost first from the regional pool of species, under the harshest environmental conditions. On the contrary, productivity was more dependent on ordinary species in milder environments. Our findings show that species functional distinctiveness, integrating multiple trait dimensions, can capture species-specific effects on ecosystem productivity. In a context of an environmentally changing world, they highlight the need to investigate the role of distinct species in sustaining ecosystem processes, particularly in extreme environmental conditions.

The ongoing decline of large marine vertebrates must be urgently mitigated, particularly under increasing levels of climate change and other anthropogenic pressures. However, characterizing the connectivity among populations remains one of the greatest challenges for the effective conservation of an increasing number of endangered species. Achieving conservation targets requires an understanding of which seascape features influence dispersal and subsequent genetic structure. This is particularly challenging for adult-disperser species, and when distribution-wide sampling is difficult. Here, we developed a two-step modelling framework to investigate how seascape features drive the genetic connectivity of marine species without larval dispersal, to better guide the design of marine protected area networks and corridors. We applied this framework to the endangered grey reef shark, Carcharhinus amblyrhynchos, a reef-associated shark distributed across the tropical Indo-Pacific. In the first step, we developed a seascape genomic approach based on isolation-by-resistance models involving circuit theory applied to 515 shark samples, genotyped for 4991 nuclear single-nucleotide polymorphisms. We show that deep oceanic areas act as strong barriers to dispersal, while proximity to habitat facilitates dispersal. In the second step, we predicted the resulting genetic differentiation across the entire distribution range of the species, providing both local and global-scale conservation units for future management guidance. We found that grey reef shark populations are more fragmented than expected for such a mobile species, raising concerns about the resilience of isolated populations under high anthropogenic pressures. We recommend the use of this framework to identify barriers to gene flow and to help in the delineation of conservation units at different scales, together with its integration across multiple species when considering marine spatial planning.

Re-analyzing data from our study, Bruun & Ejrnaes (2022) show that key species to productivity are more abundant than species threatened by extinction. They therefore conclude that biodiversity loss hardly hampers ecosystem processes. Acknowledging the validity of the findings, we clarify why we believe their conclusions are drawn too far.

In a context of marine biodiversity erosion, the need to better understand the effects of overfishing stands out. New genetic techniques such as environmental DNA (eDNA) metabarcoding have emerged and allow the detection of a wider range of species compared to conventional methods, but still fall short of providing reliable abundance estimations and subsequent ecological indicators. In this paper, we propose a combination of metabarcoding and quantitative polymerase chain reaction to obtain the quantity of eDNA molecules per species. This method was used inside and outside six no-take Mediterranean marine reserves to measure the effect of the protection on fish species and build a new indicator. Even if the total quantity of fish eDNA molecules was not different between the inside and outside of the reserves, we detected that cryptobenthic fish eDNA was significantly associated to the outside of reserves. Based on this observation, we propose a novel ecological indicator, the Demerso-pelagic to Benthic fish eDNA Ratio (DeBRa), taking advantage of the eDNA capacity to detect cryptobenthic reef fishes which are often missed by classical surveys. The DeBRa was significantly higher inside reserves, reflecting a higher relative quantity of eDNA molecules belonging to pelagic and demersal fishes under protection against fishing, therefore it appears to be a reliable eDNA-based indicator of human pressure. Furthermore, the DeBRa was not sensitive to habitat or environmental variations and does not require a complete reference database of eDNA sequences since it can rely on sequences assigned at the genus or family scale if possible and necessary.

Deep learning has become a key tool for the automated monitoring of animal populations with video-surveys. However, obtaining large amounts of images to train such models is a major challenge for rare and elusive species since field video-surveys provide few sightings. We propose a methodological framework that takes advantage of videos accumulated on social media for training deep learning models to detect rare charismatic species in the field. We apply our framework to aerial video-surveys of dugongs (Dugong dugon) in New Caledonia (South-Western Pacific). Convolutional neural networks trained with 1,303 social media images yielded only 25% of false positives and 38% of false negatives when tested on independent field video surveys. Incorporating a small number of images from New Caledonia (equivalent to 12% of social media images) into the training dataset resulted in a drop by nearly half of false negatives. We highlight how and the extent to which images collected on social media can offer a solid basis to train deep learning models for rare species detection and that the incorporation of few images from the study site further boosts detection accuracy. Our method provides a new generation of deep learning models able to rapidly and accurately process field video-surveys for the monitoring of charismatic species.

Marine reserves are being established worldwide to conserve and manage marine resources, and are also often assumed to conserve the evolutionary potential of marine populations. However, comparisons of genomic patterns inside and outside marine reserves in multiple species are scarce. Here, we aim to fill this gap by 1) comparing genomic variation in protected versus unprotected areas in a network of eight reserves in the Mediterranean Sea, and 2) disentangling the effect of seascape, space and marine reserves on this genomic variation in 1297 individuals from four species genotyped at more than 10 000 SNPs each. We report homogeneous patterns of local genetic diversity within and outside reserves in three of the four species (the white seabream Diplodus sargus, the striped red mullet Mullus surmuletus and the European spiny lobster Palinurus elephas). Surprisingly, the comber Serranus cabrilla shows lower genetic diversity in protected areas, highlighting an apparent conservation paradox that may be due to increased predation by protected fishes in the reserves. Multivariate analyses reveal that seascape factors (salinity, temperature and chlorophyll) and space exert a significant influence on genomic variation in some cases, while protection status has no detectable effect. Nevertheless, four marine reserves (Cabo de Palos, Cerbère-Banyuls, Cap de Creus and Illes Columbretes) harbor singular genetic variation in one or two species. This pattern, observed in the four species, suggests that reserves contribute to preserve genetic variation locally. Our study illustrates that we can document key aspects of the genetic variation of marine species and their interaction with seascape factors, space and protection status in multiple species. It stresses the need for a multi-species approach to inform marine conservation planning, opening up new perspectives at the community level.