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Nester, G.

Publications and source records attributed to Nester, G..

3 recordsLinked to original sources

Globally unified analysis of riverine eDNA reveals common associations of fish biodiversity with drainage characteristics

Freshwater biodiversity is declining at a pace that outstrips the capacity of existing monitoring approaches both in temporal and spatial dimensions, highlighting the urgent need for rapid and scalable assessment and attribution of biodiversity states and changes. Here, we present one of the first global assessments and unified analyses of riverine fish biodiversity using environmental DNA (eDNA) collected from 1818 sites across 113 river systems. We quantified species richness, functional redundancy, phylogenetic diversity, and genetic sequence diversity, and related them to drainage characteristics. Our results showed that eDNA effectively captured global patterns of multi-faceted riverine fish biodiversity and disentangled the roles of climate and human activities in shaping biodiversity-area relationships. Catchments in warmer climates consistently enhanced biodiversity accumulation with area, while higher human activity intensity weakened this scaling. Species richness, functional, and genetic sequence diversity exhibited stronger negative responses to human activities in larger catchments. In contrast, phylogenetic diversity showed the strongest negative effects in smaller catchments with these impacts diminishing as catchment area increased, highlighting the facet-dependent nature of biodiversity responses to environmental gradients. Our findings demonstrate the power of eDNA-based datasets for harmonized, multi-faceted biodiversity assessments, offering a scalable approach for detecting and attributing biodiversity change and informing conservation strategies under accelerating global change.

ecology↗

Integrated reanalysis of global riverine fish eDNA datasets shows robustness and congruence of biodiversity conclusions

The analysis of environmental DNA (eDNA) has revolutionized biodiversity assessments in aquatic ecosystems, enabling non-invasive monitoring of fish communities across diverse regions. However, the global comparability of these eDNA datasets remains ambiguous due heterogeneous sampling protocols and bioinformatic workflows across studies, particularly regarding the robustness of their conclusions on biodiversity assessments. Here, we conducted a meta-analysis of 58 riverine fish eDNA metabarcoding datasets, covering 1,818 sampling sites worldwide, to evaluate the robustness of eDNA-derived biodiversity patterns. We found that species richness estimates and metrics of community structure derived under a common bioinformatic workflow were overall consistent with those of original analyses, despite the relatively high variability in bioinformatic analyses in the respective original studies. Contrastingly, congruence of species identity varied more extensively across datasets, mostly reflecting different completeness and regional relevance of reference databases. Restricting taxonomic assignment to basin-specific species pools improved species identification accuracy, while datasets lacking publicly accessible or well-curated reference data were more prone to mismatches. Year of sampling had a positive effect on taxonomic congruence, such that more recent studies showed increased robustness, also reflecting improved reference database coverage and enhanced species-level identification over time and overall method congruence in more recent years. Overall, the suitability and potential of eDNA for global biodiversity monitoring is corroborating overall robust biodiversity estimates, irrespective of the bioinformatic approaches. Our study underlines the effectiveness and need of further harmonization of bioinformatic workflows and strengthened region-specific reference databases for improved taxonomic resolution and comparability across studies.

ecology↗

A comprehensive evaluation of taxonomic classifiers in marine vertebrate eDNA studies

Environmental DNA (eDNA) metabarcoding is a widely used tool for surveying marine vertebrate biodiversity. To this end, many computational tools have been released and a plethora of bioinformatic approaches are used for eDNA-based community composition analysis. Simulation studies and careful evaluation of taxonomic classifiers are essential to establish reliable benchmarks to improve accuracy and reproducibility of eDNA-based findings. Here we present a comprehensive evaluation of nine taxonomic classifiers exploring three widely used mitochondrial markers (12S rDNA, 16S rDNA, and COI) in Australian marine vertebrates. Curated reference databases and exclusion database tests were used to simulate diverse species compositions, including three positive control and two negative control datasets. Using these simulated datasets, we were able to identify between 19% to 85% of marine vertebrate species using mitochondrial markers. We show that MMSeqs2 and Metabuli generally outperform BLAST with 10% and 11% higher F1 scores for 12S and 16S rDNA markers, respectively, and that Naive Bayes Classifiers such as Mothur outperform sequence-based classifiers except MMSeqs2 for COI markers by 11%. Database exclusion tests reveal that MMSeqs2 and BLAST are less susceptible to false positives compared to Kraken2 with default parameters. Based on these findings, we recommend that MMSeqs2 is used for taxonomic classification of marine vertebrates given its ability to improve species-level assignments while reducing the number of false positives. Our work contributes to the establishment of best practices in eDNA-based biodiversity analysis to ultimately increase the reliability of this monitoring tool in the context of marine vertebrate conservation.

ecology↗