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Biodiversity loss in river ecosystems is much faster and more severe than in terrestrial systems, and spatial conservation and restoration plans are needed to halt this erosion. Reliable and highly resolved data on the state of and change in biodiversity and species distributions are critical for effective measures. However, high‐resolution maps of fish distribution remain limited for large riverine systems. Coupling data from global satellite sensors with broad‐scale environmental DNA (eDNA) and machine learning could enable rapid and precise mapping of the distribution of river organisms. Here, we investigated the potential for combining these methods using a fish eDNA dataset from 110 sites sampled along the full length of the Rhone River in Switzerland and France. Using Sentinel 2 and Landsat 8 images, we generated a set of ecological variables describing both the aquatic and the terrestrial habitats surrounding the river corridor. We combined these variables with eDNA‐based presence and absence data on 29 fish species and used three machine‐learning models to assess environmental suitability for these species. Most models showed good performance, indicating that ecological variables derived from remote sensing can approximate the ecological determinants of fish species distributions, but water‐derived variables had stronger associations than the terrestrial variables surrounding the river. The species range mapping indicated a significant transition in the species occupancy along the Rhone, from its source in the Swiss Alps to outlet into the Mediterranean Sea in southern France. Our study demonstrates the feasibility of combining remote sensing and eDNA to map species distributions in a large river. This method can be expanded to any large river to support conservation schemes.

Mesophotic marine ecosystems are characterized by lower light penetration supporting specialized fish fauna. Due to their depths (−30–−150 m), accessibility is challenging, and the structure of mesophotic fish assemblages is generally less known than either shallow reefs or deep zones with soft bottoms which are generally trawled. Environmental DNA metabarcoding from seawater filtered in situ could improve our ability to monitor the diversity of mesophotic ecosystems. Here, we developed and tested a submersible standalone pumping device allowing targeted marine water filtering to explore the biodiversity of two mesophotic ecosystems, one temperate along the Provence coast in the North-Western Mediterranean Sea and one tropical at the seamount La Pérouse in the Western Indian Ocean. We filtered water samples from depths ranging between 0 and 200 m in the Mediterranean Sea and between 60 and 140 m in the Indian Ocean and applied a metabarcoding protocol using the teleo primer pair targeting the 12S mitochondrial rDNA (Actinopterygii and Chondrichthyes). For both study regions, our eDNA surveys were able to recover highly diverse fish assemblages, and the compositional analysis of eDNA samples showed both a marked signal of fish compositional turnover and overlapping taxa between depth zones. Further, we observed that a substantial number of species were found in samples collected in depths beyond their reported depth range suggesting an underestimation of species' depth tolerances. eDNA metabarcoding should thus complement existing knowledge of species' geographic distributions across space and depth. Overall, our results demonstrate the potential of eDNA metabarcoding for future mesophotic surveys as it allows fast and broad biodiversity assessment.

The global biodiversity crisis due to anthropogenic pressures jeopardizes marine ecosystems functioning and services. Community responses to these environmental changes can be assessed through functional diversity, a biodiversity component related to organism-environment interactions, estimated through biological traits related to organism functions (locomotion, feeding mode, reproduction). Fishes play a key role in marine systems functioning and supply proteins for billions of humans worldwide, yet most of the knowledge is limited to several commercial species and little is known about the intraspecific variability of their functional traits. The data provided here consists of 867 records of individuals from 85 species of ray-finned (Actinopterygii) and cartilaginous (Chondrichthyes) fishes sampled in the Bay of Biscay (Atlantic, France) between autumn 2017 and 2019. We provided for each individual the taxonomic classification, 16 ecomorphological measures (5 directly made on fresh individuals and 11 realized using individual pictures), that were converted into 9 ecomorphological traits classically documented in the literature (biomass, protrusion, oral gape shape, surface and position, eye size and position, body transversal shape and surface, pectoral fin position and caudal peduncle throttling) and 8 life history traits obtained from Fishbase (maximum length, average depth, depth range, trophic level, reproduction mode, fertilization mode, parental care, vertical position in the water column). These traits document several functions such as dispersion, feeding mode, habitat use, position in the food web, and reproduction. To improve the development of new traits, we provided a picture of each individual with an ROI file containing the different morpho-anatomical measures made using “ImageJ” software and an R function to extract them. In addition, we provided the metadata from each sampling site (years, dates, stations, sampling hours, strata, gears, latitudes, l

The bathymetric and geographical distribution of marine species represent a key information in biodiversity conservation. Yet, deep-sea ecosystems are among the least explored on Earth and are increasingly impacted by human activities. Environmental DNA (eDNA) metabarcoding has emerged as a promising method to study fish biodiversity but applications to the deep-sea are still scarce. A major limitation in the application of eDNA metabarcoding is the incompleteness of species sequences available in public genetic databases which reduces the extent of detected species. This incompleteness by depth is still unknown. Here, we built the global bathymetric and geographical distribution of 10,826 actinopterygian and 960 chondrichthyan fish species. We assessed their genetic coverage by depth and by ocean for three main metabarcoding markers used in the literature: teleo and MiFish-U/E. We also estimated the number of primer mismatches per species amplified by in silico polymerase chain reaction which influence the probability of species detection. Actinopterygians show a stronger decrease in species richness with depth than Chondrichthyans. These richness gradients are accompanied by a continuous species turnover between depths. Fish species coverage with the MiFish-U/E markers is higher than with teleo while threatened species are more sequenced than the others. “Deep-endemic” species, those not ascending to the shallow depth layer, are less sequenced than not threatened species. The number of primer mismatches is not higher for deep-sea species than for shallower ones. eDNA metabarcoding is promising for species detection in the deep-sea to better account for the 3-dimensional structure of the ocean in marine biodiversity monitoring and conservation. However, we argue that sequencing efforts on “deep-endemic” species are needed.

Environmental DNA (eDNA) metabarcoding is a method to detect taxa from environmental samples. It is increasingly used for marine biodiversity surveys. As it only requires water collection, eDNA metabarcoding is less invasive than scientific trawling and might be more cost effective. Here, we analysed data from both sampling methods applied in the same scientific survey targeting Northeast Atlantic fish in the Bay of Biscay. We compared the methods regarding the distribution of taxonomic, phylogenetic, and functional diversity. We found that eDNA captured more taxonomic and phylogenetic richness than bottom trawling and more functional richness at the local scale. eDNA was less selective than trawling and detected species in local communities spanning larger phylogenetic and functional breadths, especially as it detected large pelagic species that escaped the trawl, even though trawling detected more flat fish. eDNA indicated differences in fish community composition that were comparable to those based on trawling. However, consistency between abundance estimates provided by eDNA metabarcoding and trawl catches was low, even after accounting for allometric scaling in eDNA production. We conclude that eDNA metabarcoding is a promising method that can complement scientific trawling for multi-component biodiversity monitoring based on presence/absence, but not yet for abundance.

Reliable and comparable estimates of biodiversity are the foundation for understanding ecological systems and informing policy and decision-making, especially in an era of massive anthropogenic impacts on biodiversity. Environmental DNA (eDNA) metabarcoding is at the forefront of technological advances in biodiversity monitoring, and the last few years have seen major progress and solutions to technical challenges from the laboratory to bioinformatics. Water eDNA has been shown to allow the fast and efficient recovery of biodiversity signals, but the rapid pace of technological development has meant that some important principles regarding sampling design, which are well established in traditional biodiversity inventories, have been neglected. Using a spatially explicit river flow model, we illustrate how sampling must be adjusted to the size of the watercourse to increase the quality of the biodiversity signal recovered. We additionally investigate the effect of sampling parameters (volume, number of sites, sequencing depth) on detection probability in an empirical data set. Based on traditional sampling principles, we propose that aquatic eDNA sampling replication and volume must be scaled to match the organisms' and ecosystems' properties to provide reliable biodiversity estimates. We present a generalizable conceptual equation describing sampling features as a function of the size of the ecosystem monitored, the abundance of target organisms, and the properties of the sequencing procedure. The aim of this formalization is to enhance the standardization of critical steps in the design of biodiversity inventory studies using eDNA. More robust sampling standards will generate more comparable biodiversity data from eDNA, which is necessary for the method's long-term plausibility and comparability.

Reliable and comparable estimates of biodiversity are the foundation for understanding ecological systems and informing policy and decision‐making, especially in an era of massive anthropogenic impacts on biodiversity. Environmental DNA (eDNA) metabarcoding is at the forefront of technological advances in biodiversity monitoring, and the last few years have seen major progress and solutions to technical challenges from the laboratory to bioinformatics. Water eDNA has been shown to allow the fast and efficient recovery of biodiversity signals, but the rapid pace of technological development has meant that some important principles regarding sampling design, which are well established in traditional biodiversity inventories, have been neglected. Using a spatially explicit river flow model, we illustrate how sampling must be adjusted to the size of the watercourse to increase the quality of the biodiversity signal recovered. We additionally investigate the effect of sampling parameters (volume, number of sites, sequencing depth) on detection probability in an empirical data set. Based on traditional sampling principles, we propose that aquatic eDNA sampling replication and volume must be scaled to match the organisms' and ecosystems' properties to provide reliable biodiversity estimates. We present a generalizable conceptual equation describing sampling features as a function of the size of the ecosystem monitored, the abundance of target organisms, and the properties of the sequencing procedure. The aim of this formalization is to enhance the standardization of critical steps in the design of biodiversity inventory studies using eDNA. More robust sampling standards will generate more comparable biodiversity data from eDNA, which is necessary for the method's long‐term plausibility and comparability.

Elasmobranchs (sharks, rays and skates) are among the most threatened marine vertebrates, yet their global functional diversity remains largely unknown. Here, we use a trait dataset of >1000 species to assess elasmobranch functional diversity and compare it against other previously studied biodiversity facets (taxonomic and phylogenetic), to identify species- and spatial- conservation priorities. We show that threatened species encompass the full extent of functional space and disproportionately include functionally distinct species. Applying the conservation metric FUSE (Functionally Unique, Specialised, and Endangered) reveals that most top-ranking species differ from the top Evolutionarily Distinct and Globally Endangered (EDGE) list. Spatial analyses further show that elasmobranch functional richness is concentrated along continental shelves and around oceanic islands, with 18 distinguishable hotspots. These hotspots only marginally overlap with those of other biodiversity facets, reflecting a distinct spatial fingerprint of functional diversity. Elasmobranch biodiversity facets converge with fishing pressure along the coast of China, which emerges as a critical frontier in conservation. Meanwhile, several components of elasmobranch functional diversity fall in high seas and/or outside the global network of marine protected areas. Overall, our results highlight acute vulnerability of the world’s elasmobranchs’ functional diversity and reveal global priorities for elasmobranch functional biodiversity previously overlooked.

The documentation of biodiversity distribution through species range identification is crucial for macroecology, biogeography, conservation, and restoration. However, for plants, species range maps remain scarce and often inaccurate. We present a novel approach to map species ranges at a global scale, integrating polygon mapping and species distribution modelling (SDM). We develop a polygon mapping algorithm by considering distances and nestedness of occurrences. We further apply an SDM approach considering multiple modelling algorithms, complexity levels, and pseudo-absence selections to map the species at a high spatial resolution and intersect it with the generated polygons. We use this approach to construct range maps for all 1957 species of Fagales and Pinales with data compilated from multiple sources. We construct high-resolution global species richness maps of these important plant clades, and document diversity hotspots for both clades in southern and south-western China, Central America, and Borneo. We validate the approach with two representative genera, Quercus and Pinus, using previously published coarser range maps, and find good agreement. By efficiently producing high-resolution range maps, our mapping approach offers a new tool in the field of macroecology for studying global species distribution patterns and supporting ongoing conservation efforts.

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.

Understanding the ecological rules structuring the organization of species interactions is a prerequisite to predicting how ecosystems respond to environmental changes. While the ecological determinants of single networks have been documented, it remains unclear whether network ecological rules are conserved along spatial and environmental gradients. To address this gap, we reconstructed 48 plant–herbivore interaction networks along six elevation gradients in the Central European Alps in Switzerland, using DNA metabarcoding on orthoptera feces. We developed hypotheses on the ecological mechanisms expected to structure interaction networks, based on plant phylogeny, plant abundance, leaf toughness, leaf nitrogen content and plant metabolomics. We show that plant phylogenetic relationships and species abundance have the greatest explanatory power regarding the structure of the ecological networks. Moreover, we found that leaf nitrogen content is a key determinant of interactions in warmer environments, while phenolic compounds and terpenoids are more important in colder environments, suggesting that determinants of species interactions can shift along environmental gradients. With this work, we propose an approach to study the mechanisms that structure the way species interact with each other between bioregions and ecosystems.

Human activities can degrade the quality of coral reefs and cause a decline in fish species richness and functional diversity and an erosion of the ecosystem services provided. Environmental DNA metabarcoding (eDNA) has been proposed as an alternative to Underwater Visual Census (UVC) to offer more rapid assessment of marine biodiversity to meet management demands for ecosystem health indices. Taxonomic information derived from sequenced eDNA can be combined with functional traits and phylogenetic positions to generate a variety of ecological indices describing ecosystem functioning. Here, we inventoried reef fish assemblages of two contrasting coastal areas of Curaçao, (i) near the island's capital city and (ii) in a remote area under more limited anthropogenic pressure. We sampled eDNA by filtering large volumes of seawater (2 × 30 L) along 2 km boat transects, which we coupled with species ecological properties related to habitat use, trophic level, and body size to investigate the difference in fish taxonomic composition, functional and phylogenetic indices recovered from eDNA metabarcoding between these two distinct coastal areas. Despite no marked difference in species richness, we found a higher phylogenetic diversity in proximity to the city, but a higher functional diversity on the more isolated reef. Composition differences between coastal areas were associated with different frequencies of reef fish families. Because of a partial reference database, eDNA only partly matched those detected with UVC, but eDNA surveys nevertheless provided rapid and robust species occurrence responses to contrasting environments. eDNA metabarcoding coupled with functional and phylogenetic diversity assessment can serve the management of coastal habitats under increasing threat from global changes.

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.

The global biodiversity crisis from anthropogenic activities significantly weakens the functioning of marine ecosystems and jeopardizes their ecosystem services. Increasing monitoring of marine ecosystems is crucial to understand the breadth of the changes in biodiversity, ecosystem functioning and propose more effective conservation strategies. Such strategies should not only focus on maximizing the number of species (i.e., taxonomic diversity) but also the diversity of phylogenetic histories and ecological functions within communities. To support future conservation decisions, multicomponent biodiversity monitoring can be combined with high-throughput species assemblage detection methods such as environmental DNA (eDNA) metabarcoding. Here, we used eDNA to assess fish biodiversity along the coast of southern Brittany (France, Iroise Sea). We filtered surface marine water from 17 sampling stations and applied an eDNA metabarcoding approach targeting Actinopterygii and Elasmobranchii taxa. We documented three complementary biodiversity components—taxonomic, phylogenetic, and functional diversity—and three diversity facets—richness, divergence and regularity. We identified a north/south contrast with higher diversity for the three facets of the biodiversity components in the northern part of the study area. The northern communities showed higher species richness, stronger phylogenetic overdispersion and lower functional clustering compared to the ones in the southern part, due to the higher diversity of habitats (reefs, rocky shores) and restricted access for fishing. Moreover, we also detected a higher level of taxonomic, phylogenetic, and functional uniqueness in many offshore stations compared to more coastal ones, with the presence of species typically living at greater depths (> 300 m), which suggests an influence of hydrodynamic structures and currents on eDNA dispersion and hence sample composition. eDNA metabarcoding can, therefore, be used as an efficient sa

Cetaceans play key roles in the world's ecosystems and provide important economic and social benefits. New Zealand's Exclusive Economic Zone is a global biodiversity hotspot for cetaceans and benefits from a system of marine protected areas (MPAs). However, spatial patterns of cetacean biodiversity and their overlap with MPAs have never been assessed.We quantify this overlap by using a comprehensive cetacean at-sea sightings database, high-resolution environmental data layers, and information on ecological and evolutionary characteristics of each species to model spatial patterns of taxonomic, functional, and phylogenetic diversity of cetaceans. We examine areas of congruence among hotspots of richness and uniqueness components of biodiversity and measure the contribution of species to biodiversity.We find that cetacean taxonomic and phylogenetic diversity are spatially mismatched with MPAs, but this is less true for functional diversity. Hotspots of congruence among richness indices are located on the continental shelf break, whereas hotspots of uniqueness indices are located closer to shore on the continental shelf. Seven species have high contributions to biodiversity, with blue whale being the only species being evolutionarily distinct, functionally unique, specialised and globally endangered.Our results underline the potential of multicomponent biodiversity indices, their spatial congruence, and the contribution of species to biodiversity to be used as guides for a strategic placement and expansion of MPAs to protect biodiversity.

The Eastern Corsican Coast (ECC) is distinguished by its shallow sandy shelf, extensive Posidonia seagrass meadows, and the relatively limited exploitation of fish in this region. To understand ECC trophic functioning and the effects of fishing in this region of the Mediterranean Sea, we applied the Ecopath and EcoTroph approaches. Our model encompassed 5 groups of primary producers and detritus, 14 invertebrate groups, two groups of Chondrichthyes, 16 teleost groups, one seabird group, and one group of cetaceans. The ECC ecosystem was structured into five trophic levels, regulated top–down by Sphyraenidae, Epinephelus marginatus, and Dentex dentex. The ecosystem displayed a high degree of benthic–pelagic coupling, confirmed by keystone groups/species located at intermediate trophic levels (Seriola dumerilii, planktivorous teleosts, benthic cephalopods, shrimps, zooplankton). The ECC demonstrated the lowest exploitation rate (F/Z) of all exploited Mediterranean ecosystems, with trawling representing 55% of catches, followed by the lobster net (27%) and fish net (18%) fisheries. Catches often included untargeted groups—often discarded dead—in particular sharks and rays, and several protected species. Moreover, Palinurus elephas, Scorpaena scrofa, and Dentex dentex had elevated F/Z values, highlighting their vulnerabilities to fishing. Although the fishing simulations suggested that the ECC could support a greater exploitation, they also revealed that these fisheries have a marked impact on upper trophic levels. Our study draws attention to the critical habitat the ECC provides for Chondrichthyes, evidenced by the significant biomass for these taxa and the low fishing pressure relative to other exploited Mediterranean systems. This first modelling of the ECC is an initial step towards modelling all Corsican marine ecosystems to serve as a guide for preserving these ecosystems through appropriate management measures.