Cross-ocean patterns and processes in fish biodiversity on coral reefs through the lens of eDNA metabarcoding

Environmental DNA recovers fish composition turnover of the coral reefs of West Indian Ocean islands

Islands have been used as model systems to study ecological and evolutionary processes, and they provide an ideal set-up for validating new biodiversity monitoring methods. The application of environmental DNA metabarcoding for monitoring marine biodiversity requires an understanding of the spatial scale of the eDNA signal, which is best tested in island systems. Here, we investigated the variation in Actinopterygii and Elasmobranchii species composition recovered from eDNA metabarcoding along a gradient of distance-to-reef in four of the five French Scattered Islands in the Western Indian Ocean. We collected surface water samples at an increasing distance from reefs (0 m, 250 m, 500 m, 750 m). We used a metabarcoding protocol based on the 'teleo' primers to target marine reef fishes and classified taxa according to their habitat types (benthic or pelagic). We investigated the effect of distance-to-reef on β diversity variation using generalised linear mixed models and estimated species-specific distance-to-reef effects using a model-based approach for community data. Environmental DNA metabarcoding analyses recovered distinct fish species compositions across the four inventoried islands and variations along the distance-to-reef gradient. The analysis of β-diversity variation showed significant taxa turnover between the eDNA samples on and away from the reefs. In agreement with a spatially localised signal from eDNA, benthic species were distributed closer to the reef than pelagic ones. Our findings demonstrate that the combination of eDNA inventories and spatial modelling can provide insights into species habitat preferences related to distance-to-reef gradients at a small scale. As such, eDNA can not only recover large compositional differences among islands but also help understand habitat selection and distribution of marine species at a finer spatial scale.

Combining environmental DNA and visual surveys can inform conservation planning for coral reefs

Environmental DNA (eDNA) metabarcoding has the potential to revolutionize conservation planning by providing spatially and taxonomically comprehensive data on biodiversity and ecosystem conditions, but its utility to inform the design of protected areas remains untested. Here, we quantify whether and how identifying conservation priority areas within coral reef ecosystems differs when biodiversity information is collected via eDNA analyses or traditional visual census records. We focus on 147 coral reefs in Indonesia's hyper-diverse Wallacea region and show large discrepancies in the allocation and spatial design of conservation priority areas when coral reef species were surveyed with underwater visual techniques (fishes, corals, and algae) or eDNA metabarcoding (eukaryotes and metazoans). Specifically, incidental protection occurred for 55% of eDNA species when targets were set for species detected by visual surveys and 71% vice versa. This finding is supported by generally low overlap in detection between visual census and eDNA methods at species level, with more overlap at higher taxonomic ranks. Incomplete taxonomic reference databases for the highly diverse Wallacea reefs, and the complementary detection of species by the two methods, underscore the current need to combine different biodiversity data sources to maximize species representation in conservation planning.

Rays in the Shadows: Batoid Diversity, Occurrence, and Conservation Status in Fiji

Over recent decades, elasmobranchs (sharks, rays, and skates) have been increasingly recognized among the world's most threatened marine wildlife, leading to heightened scientific attention. However, batoids (rays and skates) are relatively understudied, especially in Large Ocean States of the Pacific. This synthesis compiles insights on batoid diversity and occurrence in Fiji's waters by integrating a literature review, participatory science programs such as the Great Fiji Shark Count (GFSC) Initiative, Projects Abroad Fiji (PA), Manta Project Fiji (MPF), and iNaturalist, along with environmental DNA. Nineteen batoid species from seven families were identified: 19 species from the literature, 12 from participatory science programs, and six from eDNA analysis. Notably, this study provides the first photographic evidence for the bentfin devil ray (Mobula thurstoni, Lloyd, 1908) in Fiji. GFSC data indicated the highest species diversity in the Western Division, with spotted eagle rays (Aetobatus ocellatus, Kuhl, 1823) and maskrays (Neotrygon sp.) being observed most. In-person interviews conducted by PA provided information on the occurrence of wedgefishes and potentially sawfishes. MPF records and iNaturalist uploads were dominated by reef manta rays (M. alfredi, Krefft, 1868), while the pink whipray (Pateobatis fai, Jordan and Seale, 1906) yielded the most DNA sequences. Overall, 68.4% of the species face an elevated extinction risk based on the International Union for the Conservation of Nature Red List criteria. Although caution is warranted with older literature-based records for the giant guitarfish (Glaucostegus typus, Anonymous [Bennett], 1830), giant stingaree (Plesiobatis daviesi, Wallace, 1967), and the lack of sawfish verification, this synthesis highlights the effectiveness of a combined methodological approach in establishing a reference point for the diversity and occurrence of this understudied taxon in Fiji.

Optimizing detectability of the endangered fan mussel using eDNA and ddPCR

Spatial and temporal monitoring of species threatened with extinction is of critical importance for conservation and ecosystem management. In the Mediterranean coast, the fan mussel (Pinna nobilis) is listed as critically endangered after suffering from a mass mortality event since 2016, leading to 100% mortality in most marine populations. Conventional monitoring for this macroinvertebrate is done using scuba, which is challenging in dense meadows or with low visibility. Here we developed an environmental DNA assay targeting the fan mussel and assessed the influence of several environmental parameters on the species detectability in situ. We developed and tested an eDNA molecular marker and collected 48 water samples in two sites at the Thau lagoon (France) with distinct fan mussel density, depths and during two seasons (summer and autumn). Our marker can amplify fan mussel DNA but lacks specificity since it also amplifies a conspecific species (Pinna rudis). We successfully amplified fan mussel DNA from in situ samples with 46 positive samples (out of 48) using ddPCR, although the DNA concentrations measured were low over almost all samples. Deeper sampling depth slightly increased DNA concentrations, but no seasonal effect was found. We highlight a putative spawning event on a single summer day with much higher DNA concentration compared to all other samples. We present an eDNA molecular assay able to detect the endangered fan mussel and provide guidelines to optimize the sampling protocol to maximize detectability. Effective and non-invasive monitoring tools for endangered species are promising to monitor remaining populations and have the potential of ecological restoration or habitat recolonization following a mass mortality event.

Comparing Seamounts and Coral Reefs with eDNA and BRUVS Reveals Oases and Refuges on Shallow Seamounts

Seamounts are the least known ocean biome. Considered biodiversity hotspots, biomass oases, and refuges for megafauna, large gaps exist in their real diversity relative to other ecosystems like coral reefs. Using environmental DNA metabarcoding (eDNA) and baited video (BRUVS), we compared fish assemblages across five environments of different depths: coral reefs (15 m), shallow seamounts (50 m), continental slopes (150 m), intermediate seamounts (250 m), and deep seamounts (500 m). We modeled assemblages using 12 environmental variables and found depth to be the main driver of fish diversity and biomass, although other variables like human accessibility were important. Boosted Regression Trees (BRT) revealed a strong negative effect of depth on species richness, segregating coral reefs from deep-sea environments. Surprisingly, BRT showed a hump-shaped effect of depth on fish biomass, with significantly lower biomass on coral reefs than in shallowest deep-sea environments. Biomass of large predators like sharks was three times higher on shallow seamounts (50 m) than on coral reefs. The five studied environments showed quite distinct assemblages. However, species shared between coral reefs and deeper-sea environments were dominated by highly mobile large predators. Our results suggest that seamounts are no diversity hotspots for fish. However, we show that shallower seamounts form biomass oases and refuges for threatened megafauna, suggesting that priority should be given to their protection.

New deep learning-based methods for visualizing ecosystem properties using environmental DNA metabarcoding data

Environmental DNA (eDNA) metabarcoding provides an efficient approach for documenting biodiversity patterns in marine and terrestrial ecosystems. The complexity of these data prevents current methods from extracting and analyzing all the relevant ecological information they contain, and new methods may provide better dimensionality reduction and clustering. Here we present two new deep learning-based methods that combine different types of neural networks (NNs) to ordinate eDNA samples and visualize ecosystem properties in a two-dimensional space: the first is based on variational autoencoders and the second on deep metric learning. The strength of our new methods lies in the combination of two inputs: the number of sequences found for each molecular operational taxonomic unit (MOTU) detected and their corresponding nucleotide sequence. Using three different datasets, we show that our methods accurately represent several biodiversity indicators in a two-dimensional latent space: MOTU richness per sample, sequence α-diversity per sample, Jaccard's and sequence β-diversity between samples. We show that our nonlinear methods are better at extracting features from eDNA datasets while avoiding the major biases associated with eDNA. Our methods outperform traditional dimension reduction methods such as Principal Component Analysis, t-distributed Stochastic Neighbour Embedding, Nonmetric Multidimensional Scaling and Uniform Manifold Approximation and Projection for dimension reduction. Our results suggest that NNs provide a more efficient way of extracting structure from eDNA metabarcoding data, thereby improving their ecological interpretation and thus biodiversity monitoring.

Gut content metabarcoding of specialized feeders is not a replacement for environmental DNA assays of seawater in reef environments

In tropical marine ecosystems, the coral-based diet of benthic-feeding reef fishes provides a window into the composition and health of coral reefs. In this study, for the first time, we compare multi-assay metabarcoding sequences of environmental DNA (eDNA) isolated from seawater and partially digested gut items from an obligate corallivore butterflyfish (Chaetodon lunulatus) resident to coral reef sites in the South China Sea. We specifically tested the proportional and statistical overlap of the different approaches (seawater vs gut content metabarcoding) in characterizing eukaryotic community composition on coral reefs. Based on 18S and ITS2 sequence data, which differed in their taxonomic sensitivity, we found that gut content detections were only partially representative of the eukaryotic communities detected in the seawater based on low levels of taxonomic overlap (3 to 21%) and significant differences between the sampling approaches. Overall, our results indicate that dietary metabarcoding of specialized feeders can be complimentary to, but is no replacement for, more comprehensive environmental DNA assays of reef environments that might include the processing of different substrates (seawater, sediment, plankton) or traditional observational surveys. These molecular assays, in tandem, might be best suited to highly productive but cryptic oceanic environments (kelp forests, seagrass meadows) that contain an abundance of organisms that are often small, epiphytic, symbiotic, or cryptic.

Black coral forests enhance taxonomic and functional distinctiveness of mesophotic fishes in an oceanic island: implications for biodiversity conservation

The degradation of shallow ecosystems has called for efforts to understand the biodiversity and functioning of Mesophotic Ecosystems. However, most empirical studies have been restricted to tropical regions and have majorly focused on taxonomic entities (i.e., species), neglecting important dimensions of biodiversity that influence community assembly and ecosystem functioning. Here, using a subtropical oceanic island in the eastern Atlantic Ocean (Lanzarote, Canary Islands), we investigated variation in (a) alpha and (b) beta functional (i.e., trait) diversity across a depth gradient (0-70 m), as a function of the presence of black coral forests (BCFs, order Antipatharian) in the mesophotic strata, a vulnerable but often overlooked 'ecosystem engineer' in regional biodiversity. Despite occupying a similar volume of the functional space (i.e., functional richness) than shallow (< 30 m) reefs, mesophotic fish assemblages inhabiting BCFs differed in their functional structure when accounting for species abundances, with lower evenness and divergence. Similarly, although mesophotic BCFs shared, on average, 90% of the functional entities with shallow reefs, the identity of common and dominant taxonomic and functional entities shifted. Our results suggest BCFs promoted the specialization of reef fishes, likely linked to convergence towards optimal traits to maximize the use of resources and space. Regional biodiversity planning should thus focus on developing specific management and conservation strategies for preserving the unique biodiversity and functionality of mesophotic BCFs.

The global depth range of marine fishes and their genetic coverage for environmental DNA metabarcoding

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.

Species diversity of coral reef fishes around the West Island of Sanya City, South China Sea, based on environmental DNA

Background

West Island is the second largest island in the Hainan Province, China and its surrounding sea area has a well-preserved coral reef ecosystem and high species diversity of coral reef fishes. Undoubtedly, coral reef fishes and coral reefs have complex symbiotic relationships and fish species diversity should reflect the healthy status of coral reef ecosystems. Environmental DNA (eDNA) is a useful and sensitive tool to detect fish species and causes less environmental damage than traditional fish survey methods. This paper investigated coral reef fish species of West Island, Hainan Province, China, based on eDNA and provided scientific data for understanding and protection of the coral reef ecosystem of the South China Sea.

New information

The sea area surrounding West Island is the most important component of the coral reef ecosystem in the northern part of the South China Sea, which is also an essential part of the largest National Coral Reef Reserve in China. However, complete data of fish species distributed in this region have been a long-term gap. This study provides information on 41 fish species belonging to 28 genera, 16 families and three orders in this sea area and is the first complete record of coral reef fishes surrounding the West Island. In addition, the information of Molecular Operational Taxonomic Units (MOTUs) for taxon identification were also provided and it could contribute to building specific eDNA taxonomy database of coral reef fishes of the South China Sea. The study includes three datasets, with aspects of fish taxon-occurrences, MOTUs sequences and information of environmental indicators surrounding West Island, Hainan Province, China. The "fish taxon occurrences" dataset presents records involving taxonomic, distribution, habitat condition, latitude and longitude of 41 coral reef fish species detected, based on eDNA, the "MOTUs sequences" dataset provides MOTUs sequences and their abundance of 31 species detected and the "information of environmental indicators" dataset presents records of transparency, temperature, water pressure, dissolved oxygen, electrical conductivity, hydrogen and redox potential measured from five sampling localities.