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Biology subjects

Dubut, V.

Publications and source records attributed to Dubut, V..

4 recordsLinked to original sources

Separating faces in ARMS metabarcoding improves marine biodiversity monitoring: a comparison across protocols, experimental designs, and photographic surveys

Monitoring marine biodiversity requires approaches that capture its full complexity through space and time. DNA metabarcoding coupled with Autonomous Reef Monitoring Structures (ARMS) is increasingly used for this purpose, yet most applications still pool all sessile fractions and rarely benchmark molecular ouputs against photographic observations. Here, we combined photographic analysis with cytochrome c oxidase I (COI) metabarcoding across ten north-western Mediterranean sites to test, compare, and refine ARMS-based monitoring protocols. We first optimized laboratory procedures (DNA extraction and polymerase choice) and applied the control-driven, replicate-aware VTAM pipeline to minimize false positives and ensure full traceability. We then conducted the first face-by-face comparison of - and {beta}-diversity between imaging and eDNA in which each individual ARMS face was metabarcoded separately rather than pooled. Metabarcoding detected [~]15x higher site-level richness and revealed stronger correlations with geographic distance and environmental gradients, whereas photography provided complementary information on macro-taxa and surface cover. For metabarcoding, processing each face separately yielded much higher richness and markedly stronger {beta}-diversity-distance correlations than with the NOAA pooling protocol, demonstrating that pooling inflates sampling variance resulting in a loss of the ecological signal. Grouping faces into five structural categories offered a more operational alternative while further increasing -diversity and strengthening {beta}-diversity correlations. Overall, our results show that retaining ARMS microhabitat structure is critical for maximizing metabarcoding performance. Using five structural sessile fractions per ARMS combined with a control-driven bioinformatic workflow provides a reproducible, scalable framework for long-term eDNA monitoring and early detection of biodiversity change.

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DNA metabarcoding reveals adaptive seasonal variation of individual trophic traits in a critically endangered fish

Dietary studies are critical for understanding foraging strategies and have important applications in conservation and habitat management. We applied a robust metabarcoding protocol to characterize the diet of the critically endangered freshwater fish Zingel asper and conducted modelling and simulation analyses to characterize and identify some of the drivers of individual trophic trait variation in this species. We found that intra-specific competition and ontogeny had minor effects on the trophic niche of Z. asper. Instead, our results suggest that the majority of trophic niche variation was driven by seasonal variation in ecological opportunity (in our case, the seasonal variation in the availability of preferred prey types). Overall, our results are in line with the optimal foraging theory and suggest that Z. asper is specialized on a few ephemeropteran prey species (Baetis fuscatus and Ecdyonurus) but adapts its foraging by becoming more opportunistic as its favoured prey seasonally decline. Despite the now widespread usage of metabarcoding, very few studies have attempted to study inter- and intra-populational individual trophic traits variation with metabarcoding data. This study illustrates how metabarcoding data obtained from feces can be combined with modelling and simulation approaches to test hypotheses in the conventional analytic framework of trophic analysis.

ecology↗

VTAM: A robust pipeline for validating metabarcoding data using internal controls

O_LIMetabarcoding studies should be carefully designed to minimize false positives and false negative occurrences. The use of internal controls, replicates, and several overlapping markers is expected to improve the bioinformatics data analysis. C_LIO_LIVTAM is a tool to perform all steps of data curation from raw fastq data to taxonomically assigned ASV (Amplicon Sequence Variant or simply variant) table. It addresses all known technical error types and includes other features rarely present in existing pipelines for validating metabarcoding data: Filtering parameters are obtained from internal control samples; cross-sample contamination and tag-jump are controlled; technical replicates are used to ensure repeatability; it handles data obtained from several overlapping markers. C_LIO_LITwo datasets were analysed by VTAM and the results were compared to those obtained with a pipeline based on DADA2. The false positive occurrences in samples were considerably higher when curated by DADA2, which is likely due to the lack of control for tag-jump and cross-sample contamination. C_LIO_LIVTAM is a robust tool to validate metabarcoding data and improve traceability, reproducibility, and comparability between runs and datasets. C_LI

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Quantifying The Individual Impact Of Artificial Barriers In Freshwaters: A Standardized And Absolute Index Of Genetic Connectivity

Fragmentation by artificial barriers is an important threat to freshwater biodiversity. Mitigating the negative aftermaths of fragmentation is of crucial importance, and it is now essential for environmental managers to benefit from a precise estimate of the individual impact of weirs and dams on river connectivity. Although the indirect monitoring of fragmentation using molecular data constitutes a promising approach, it is plagued with several constraints preventing a standardized and individual quantification of barrier effects. Indeed, observed levels of genetic differentiation depend on both the age of the obstacle and the effective size of the populations it separates, making difficult comparisons of the actual barrier effect of different obstacles. Here, we developed a standardized genetic index of fragmentation (FINDEX), allowing an absolute and independent assessment of the individual effects of obstacles on connectivity. The FINDEX is the standardized ratio (expressed as a percentage) between the observed genetic differentiation between pairs of populations located on either side of an obstacle and the genetic differentiation expected if this obstacle completely prevented gene flow. The expected genetic differentiation is calculated from simulations taking into account two nuisance parameters: the number of generations since barrier creation (the age of the obstacle) and the expected heterozygosity of the targeted populations, a proxy for effective population sizes. Using both simulated and published empirical datasets, we explored and discussed the validity and the limits of the FINDEX. We demonstrated that it allows quantifying genetic effects of fragmentation only from a few generations after barrier creation and provides valid comparisons among populations (or species) of different effective populations sizes and obstacles of different ages. The computation of the FINDEX requires a minimum amount of fieldwork and genotypic data, and solves some of the difficulties inherent to the study of artificial fragmentation in rivers and potentially in other ecosystems. This makes the FINDEX a promising and objective tool for managers aiming at at planning restoration programs and at evaluating the efficiency of these programs.

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