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Albouy, C.

Publications and source records attributed to Albouy, C..

7 recordsLinked to original sources

Large river eDNA sampling designs with remote-sensing-based clustering stratification

Environmental DNA (eDNA) provides a powerful tool for biodiversity monitoring in large river ecosystems. However, current studies often rely on subjective site selection and lack systematic sampling designs. This can limit the ability to capture the full spectrum of environmental conditions that species depend on, thereby compromising sampling efficiency. To address this challenge, we propose utilizing remote sensing-based clustering for environmental stratification of sampling designs, thereby enhancing detection capabilities and increasing the objectivity of eDNA sampling. Using GBIF-based fish species distribution models and simulated distributions along the Danube, we demonstrate that this approach enhances detection efficiency compared to conventional random and regular sampling methods. To facilitate practical implementation, we developed a tool to help fieldwork planners of river sampling campaigns automatically apply this method and select stratified sampling sites without the need for extensive data processing. Finally, we demonstrate that eDNA detection occurred most frequently within the range of 0-20km downstream of the expected modeled distribution of species, suggesting that the diffusion of the signal should be further considered in the sampling design process. Our findings highlight the potential of remote sensing-based stratification to create more efficient and objective sampling designs but suggest that sampling design should be further combined with hydrological information to optimize cost-efficient sampling. The development of standard and robust sampling protocols will help advance more cost-effective eDNA-based biodiversity monitoring in riverine ecosystems.

ecology↗

How many replicates to accurately estimate fish biodiversity using environmental DNA on coral reefs?

Quantifying the diversity of species in rich tropical marine environments remains challenging. Environmental DNA (eDNA) metabarcoding is a promising tool to face this challenge through the filtering, amplification, and sequencing of DNA traces from water samples. However, the reliability of biodiversity detection from eDNA samples can be low in marine environments because eDNA density is low and certainly patchy in this vast, heterogenous and dynamic environment. So, the number of sampling replicates and filtered volume necessary to obtain accurate estimates of biodiversity in rich tropical marine environments using eDNA metabarcoding is still unknown. Here, we used a paired sampling design of 30L per replicate on 68 reef transects from 8 sites in three tropical regions and identified fish Molecular Taxonomic Units (MOTUs) using a 12S marker. We quantified local biodiversity variation as MOTU richness, compositional turnover and compositional nestedness between replicated pairs of seawater samples. We report strong turnover of MOTUs between replicated pairs of samples undertaken in the same location, time, and conditions. Paired samples contained non-overlapping assemblages rather than subsets of one-another. As a result, localised diversity accumulation curves showed that even 6 replicates (180L) in the same location underestimated local diversity (for an area <1km). However, sampling of regional diversity using [~]25 replicates in variable locations (often covering 10s of km) achieved saturation of biodiversity accumulation curves. Our results demonstrate high variability of diversity estimates perhaps arising from heterogeneous and local distribution of eDNA distribution in seawater or highly skewed frequencies of eDNA traces. This high compositional variability has consequences for using eDNA to monitor temporal and spatial biodiversity changes of local assemblages. Future biomonitoring efforts could be strongly undermined by a high level of false-negative detections under low replication protocols. We reveal the need to increase replicates or increase sampled water volume to better inform management of marine biodiversity using eDNA.

ecology↗

A quantitative review of abundance-based species distribution models

The contributions of species to ecosystem functions or services depend not only on their presence in a given community, 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 high heterogeneity in 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 extrapolated predictions of abundance, e.g. under climate change, have a much greater uncertainty. Our synthesis provides a roadmap for modelling abundance patterns, a key property of species distributions that underpins theoretical and applied questions in ecology and conservation.

ecology↗

Fast processing of environmental DNA metabarcoding sequence data using convolutional neural networks

1The intensification of anthropogenic pressures have increased consequences on biodiversity and ultimately on the functioning of ecosystems. To monitor and better understand biodiversity responses to environmental changes using standardized and reproducible methods, novel high-throughput DNA sequencing is becoming a major tool. Indeed, organisms shed DNA traces in their environment and this "environmental DNA" (eDNA) can be collected and sequenced using eDNA metabarcoding. The processing of large volumes of eDNA metabarcoding data remains challenging, especially its transformation to relevant taxonomic lists that can be interpreted by experts. Speed and accuracy are two major bottlenecks in this critical step. Here, we investigate whether convolutional neural networks (CNN) can optimize the processing of short eDNA sequences. We tested whether the speed and accuracy of a CNN are comparable to that of the frequently used OBITools bioinformatic pipeline. We applied the methodology on a massive eDNA dataset collected in Tropical South America (French Guiana), where freshwater fishes were targeted using a small region (60pb) of the 12S ribosomal RNA mitochondrial gene. We found that the taxonomic assignments from the CNN were comparable to those of OBITools, with high correlation levels and a similar match to the regional fish fauna. The CNN allowed the processing of raw fastq files at a rate of approximately 1 million sequences per minute which was 150 times faster than with OBITools. Once trained, the application of CNN to new eDNA metabarcoding data can be automated, which promises fast and easy deployment on the cloud for future eDNA analyses.

bioinformatics↗

Species ecology explains the various spatial components of genetic diversity in tropical reef fishes

Intraspecific genetic diversity should be dependent on species ecology, but the influence of ecological traits on interspecific differences in genetic variation is yet to be explored. Generating sequenced data for 20 tropical reef fish species of the Western Indian Ocean, we investigate how species ecology influences genetic diversity patterns from local to regional scales. We distinguish between the , {beta} and{gamma} components of genetic diversity, which we subsequently link to six ecological traits. In contrast to what is expected by the neutral theory of molecular evolution, we find that the and{gamma} components of genetic diversity are negatively associated with species abundance, which can be explained by larger variance in reproductive success in large populations and/or higher introgression in less frequent species. Pelagic larval duration, an important dispersal trait in marine fishes, is found to be negatively related to genetic {beta} diversity, as expected by theory. We conclude that the neutral theory of molecular evolution may not be sufficient to explain genetic diversity in tropical reef fishes and that additional processes influence those relationships.

genetics↗

Functionally unique, specialised, and endangered (FUSE) species: towards integrated metrics for the conservation prioritisation toolbox

Identifying species with disproportionate contributions to biodiversity can lead to effective conservation prioritisation. Despite well-established methods for identifying endangered species adding inordinately to evolutionary diversity, in this context functional diversity has been overlooked. Here, we compare different metrics designed to identify threatened species that contribute strongly to functional diversity. We use the diverse and threatened global marine megafauna as a case study. We found that functional contributions of species are not fully captured in a single metric. Although we found a very strong correlation between functional specialisation and distinctiveness, functional uniqueness was only moderately correlated with the other two metrics and identified a different set of top-10 species. These functional contributions were then integrated and combined with extinction risk to identify species that are both important contributors to functional diversity and endangered. For instance, the top-10 Functionally Unique Specialized and Endangered (FUSE) species contains three critically endangered, five endangered and two vulnerable species which - despite comprising only 3% of species - are among the top 10% most functionally unique and hold 15% of the global functional richness. The FUSE index was remarkably robust to different mathematical formulations. Combining one or more facets of a species contribution to functional diversity with endangerment, such as with the FUSE index, adds to the toolbox for conservation prioritisation. Nevertheless, we discuss how these new tools must be handled with care alongside other metrics and information.

ecology↗

Are Global Hotspots Of Endemic Richness Shaped By Plate Tectonics?

Singular regions of the globe harbour a disproportionally large fraction of extant biodiversity. Spatial biodiversity gradients are frequently associated to extant ecological conditions using statistical models, but more rarely to paleo-environmental conditions, especially beyond the Quaternary. On one hand the role of plate tectonics in shaping the extant diversity of lineages is supported by numerous phylogenetic and fossil evidences, and on the other hand the spatial variation of biodiversity across the globe is rarely associated to geodynamic variables. In this study, we propose that plate tectonics explain the current location of hotspots of endemic richness across the globe. As an illustration, we used paleogeographies in a model, which quantifies through time and for each cell the potential dispersal across disconnected habitat patches. Rare events of dispersal across dynamic straits of unsuitable habitats allows species colonisation and that a subsequent absence of gene flow could lead to in-situ speciation. We evaluated whether this process could pinpoint the locations of hotspots of endemic richness computed from the ranges of 181,603 species across 14 taxonomic groups. The significant congruence between the regions highlighted by the model and the endemic richness provides evidences of the contribution of plate tectonics in shaping global biodiversity gradients. Places with high tectonic complexity, predominantly located at the confluence of major lithospheric plates such as the Mediterranean basin, Central America, Madagascar and South East Asia likely provided favourable circumstances for allopatric speciation and the emergence of new species across straits. While our illustration supports the role of plate tectonics, accounting for deep time geological events in spatial models of extant biodiversity is not straightforward. Future research should develop quantitative spatial models of biodiversity including the dynamic of ancient habitats.

evolutionary biology↗