Biology subjects

Manel, S.

Publications and source records attributed to Manel, S..

10 recordsLinked to original sources

bioRxiv2026

Navigating between global robustness and fine-scale resolution: the potential of demographic inference based on identical-by-descent segments.

Understanding the demographic processes shaping population connectivity is essential for conservation. Yet disentangling the effects of dispersal and local effective density remains challenging because traditional genetic approaches integrate signals over evolutionary timescales. Identity-by-descent (IBD) segments provide opportunities to reconstruct recent demographic connectivity over timescales relevant to contemporary conservation challenges, but their reliability under realistic ecological conditions remains poorly evaluated. Here, we assess the ability of two promising spatiall IBD-based methods, IBD-Analysis and MAPS, to estimate effective density and dispersal variance. Using a simulation-inference framework combining spatially explicit simulations, IBD segment extraction, and demographic inference, we evaluated both methods across a wide range of demographic, ecological and methodological scenarios. Both approaches reliably recovered demographic parameters under homogeneous landscapes, with IBD-Analysis providing accurate estimates of global effective density and dispersal across a broad range of conditions. Spatial heterogeneity emerged as the main driver of inference performance. When demographic parameters varied across space, IBD-Analysis integrated local variation into biased global estimates, whereas MAPS captured spatial patterns but showed substantial variability and generated spurious spatial structure in homogeneous landscapes. Methodological factors had comparatively weaker effects than ecological complexity, highlighting the importance of accounting for landscape structure when applying IBD-based demographic inference. These results highlight the potential of IBD-based approaches to move beyond descriptive patterns of genetic connectivity toward mechanistic inference of demographic processes. By distinguishing the contributions of dispersal and density, these methods can improve conservation decisions by linking genomic patterns to key demographic parameters relevant for conservation.

evolutionary biology↗

bioRxiv2025

NeMO: a flexible R package for nested multi-species occupancy modelling and eDNA study optimization

Biodiversity monitoring using environmental DNA (eDNA) metabarcoding has expanded rapidly, providing a non-invasive tool widely adopted by ecologists and stakeholders. However, eDNA surveys are prone to imperfect detection, and non-detections are often misinterpreted as true absences - a critical issue when monitoring rare or elusive species. Despite its implications for biodiversity assessments, detection uncertainty is rarely quantified in eDNA-based studies. Occupancy modeling offers a powerful solution to this limitation but remains underused, partly due to a lack of accessible and flexible tools. We developed NeMO (Nested eDNA Metabarcoding Occupancy), a user-friendly R package for fitting multi-species occupancy models in a Bayesian framework. NeMO explicitly accounts for the nested structure of eDNA metabarcoding workflows - typically involving multiple replication steps such as field samples and PCR replicates - while accommodating presence/absence or read-count data. The framework estimates species occupancy, eDNA collection probability, amplification probability, and expected read counts, and allows users to assess the influence of environmental or methodological covariates on each process. Crucially, NeMO helps rigorously assess detectability and optimize resource allocation in eDNA surveys. It estimates the minimum number of eDNA samples, PCR replicates, and sequencing depth required to reliably detect species when present, thereby guiding study design. We illustrate its utility using a fish biodiversity dataset from the Rhone River (France). NeMO integrates key modelling features into a single streamlined framework, providing researchers and practitioners with an accessible and effective tool to assess detectability and optimize resource allocation in eDNA metabarcoding surveys. Our results highlight the importance of quantifying detection uncertainty, which has major implications for conservation monitoring and for designing cost-effective and reliable eDNA strategies. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=113 SRC="FIGDIR/small/655794v3_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@3a8f2borg.highwire.dtl.DTLVardef@8d8375org.highwire.dtl.DTLVardef@b1976forg.highwire.dtl.DTLVardef@14cfde5_HPS_FORMAT_FIGEXP M_FIG NeMO provides a flexible framework for modeling multi-species site occupancy from eDNA data, estimating species presence and detectability despite imperfect detection. It supports diverse experimental designs, enables model comparison, and guides study design optimization by calculating minimal sampling effort to detect species, helping ecologists balance detection accuracy and resource allocation. C_FIG

ecology↗

bioRxiv2024

Improving the monitoring of the invasive Blue Crab (Callinectes sapidus): combining environmental DNA and citizen observations

O_LIEarly detection is a crucial tool for identifying the spread of invasive species. C_LIO_LIIn this study, we validated a probe-based quantitative polymerase chain reaction (qPCR) assay for the detection of the invasive Blue Crab, Callinectes sapidus, in the Mediterranean Sea, using 22 initial eDNA environmental samples (eDNA) collected from three coastal lagoons. C_LIO_LIA subsequent large-scale eDNA sampling campaign (61 samples in 31 sites), conducted in collaboration with local stakeholders, was carried out to map the distribution of Callinectes sapidus along the Occitanie coastline (Western Mediterranean, France). C_LIO_LIUsing eDNA probe-based qPCR, Callinectes sapidus was detected in 32 out the 61 samples (52%), confirming its presence in 24 out of 31 sites surveyed, including the 13 lagoons where its occurrence had already been reported, as well as two additional lagoons and at sea where no prior records existed. C_LIO_LIOur results demonstrate the utility of eDNA probe-based qPCR for effective monitoring the invasive Blue Crab. The integration of eDNA analysis with citizen science observations enhances the monitoring framework, facilitating early detection and contributing to improved management strategies at the very beginning of species colonization when practical actions could be implemented. C_LI

ecology↗

bioRxiv2022

Global connectivity and networks of marine reserves

Cooperation between countries in managing and protecting shared marine resources is beneficial both ecologically and economically, but how best to establish the cooperation needed at a global scale is largely unknown. Here, we used hydrodynamic modelling to identify ecologically connected networks of marine reserves (MRs) and evaluated these networks with socio-economic indicators. Most of the networks are homogenous with similar levels of development, shared languages, and other cultural values. However, we found that 17% (11/66) of the largest networks (>20 MRs) span multiple countries. These heterogenous networks are composed of countries with different economic, political, and cultural views. Countries that control more, larger marine reserves also have a more even ratio of source reserves to sinks. We discuss that, while such economic and cultural homogeneity might lead to more efficient ecological management in the short term, heterogeneous networks may prove to be more resilient in the longer term, when climate change will modify marine connectivity.

systems biology↗

bioRxiv2021

Identifying barriers to gene flow and hierarchical conservation units from seascape genomics: a modelling framework applied to a marine predator

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 4,491 nuclear single-nucleotide polymorphisms, to explore which parameters drive their population genetic differentiation. 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.

ecology↗

bioRxiv2021

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↗

bioRxiv2021

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↗

bioRxiv2021

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↗

bioRxiv2018

Effect of riverscape and exotic introgression on the genetic structure and local adaptation of the endangered Mexican golden trout (Oncorhynchus chrysogaster)

How environmental and anthropogenic factors influence genetic variation and local adaptation is a central issue in evolutionary biology. The Mexican golden trout (Oncorhynchus chrysogaster), one of the southernmost native salmonid species in the world, is susceptible to climate change, habitat perturbations and the competition and hybridization with exotic rainbow trout (O. mykiss). The present study aimed for the first time to use genotyping-by-sequencing to explore the effect of genetic hybridization with O. mykiss and of riverscape and climatic variables on the genetic variation among O. chrysogaster populations. Genotyping-by-sequencing (GBS) was applied to generate 9767 single nucleotide polymorphisms (SNPs), genotyping 272 O. chrysogaster and O. mykiss. Population genomics analyses were combined with landscape ecology approaches into a riverine context (riverscape genetics). The clustering analyses detected seven different genetic groups (six for O. chrysogater and one for aquaculture O. mykiss) and a small amount of admixture between aquaculture and native trout with only two native genetic clusters showing exotic introgression. Latitude and precipitation of the driest month had a significant negative effect on genetic diversity and evidence of isolation by river resistance was detected, suggesting that the landscape heterogeneity was preventing trout dispersal, both for native and exotic individuals. Moreover, several outlier SNPs were identified as potentially implicated in local adaptation to local hydroclimatic variables. Overall, this study suggests that O. chrysogater may require conservation planning given i) exotic introgression from O. mykiss locally threatening O. chrysogater genetic integrity, and ii) putative local adaptation but low genetic diversity and hence probably reduced evolutionary potential especially in a climate change context.

evolutionary biology↗

bioRxiv2018

Pleistocene climate changes explain large-scale genetic variation in a dominant grassland species, Lolium perenne L.

AimGrasslands have been pivotal in the development of herbivore breeding since the Neolithic and are still nowadays the most widespread agricultural land-use across Europe. However, it remains unclear whether the current large-scale genetic variation of plant species found in natural grasslands of Europe is the result of human activities or natural processes.\n\nLocationEurope.\n\nTaxonLolium perenne L (perennial ryegrass).\n\nMethodsWe reconstructed the phylogeographic history of L. perenne, a dominant grassland species, using 481 natural populations including 11 populations from closely related taxa. We combined the Genotyping-by-Sequencing (GBS) and Pool-sequencing (Pool-seq) methods to obtain high-quality allele frequency calls of ~ 500 k SNP loci. We performed genetic structure analyses and demographic reconstructions based on the site frequency spectrum (SFS). We additionally used the same genotyping protocol to assess the genomic diversity of a set of 32 cultivars representative of the L. perenne cultivars widely used for forage purposes.\n\nResultsExpansion across Europe took place during the Wurm glaciation (12-110 kya), a cooling period that decreased the dominance of trees in favour of grasses. Splits and admixtures in L. perenne fit historical sea level changes in the Mediterranean basin. The development of agriculture in Europe (7-3.5 kya), that caused an increase in the abundance of grasslands, did not have an effect on the demographic patterns of L. perenne. We found little differentiation between modern cultivars and certain natural variants. However, modern cultivars do not represent the wide genetic variation found in natural populations.\n\nMain conclusionsDemographic events in L. perenne can be explained by the changing climatic conditions during the Pleistocene. Natural populations maintain a wide genomic variability at continental scale that has been underused by recent breeding activities. This variability constitutes valuable standing genetic variation for future adaptation of grasslands to climate change, safeguarding the agricultural services they provide.

evolutionary biology↗