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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.