Nestedness and turnover of riverine species and functional diversity using eDNA and traditional approaches

Mathew Seymour, François Edwards, Pete Scarlet, Iliana Bista, Francesca Brailsford, Helen Glanville, Mark de Bruyn, Gary Carvahlo, Simon Creer

Research output: Contribution to specialist publicationArticle

Abstract

Accurately assessing community diversity in time and space, and linking these patterns to ecological theory, is essential for effective environmental monitoring. Freshwater macroinvertebrates are an important group of taxa routinely used for riverine environmental assessments due to their wide biological, functional and phylogenetic diversity and their responses to environmental factors. Recently, eDNA metabarcoding based sampling and identification has been shown to increase the accuracy of biodiversity assessments, while reducing cost and time, compared to traditional methods. Here, we present results from a field comparison of eDNA versus traditional riverine biodiversity techniques to assess freshwater macroinvertebrates. In addition, we investigated the effects of landuse and seasonality on community and functional diversity, to infer the underlying regional ecological temporal and spatial dynamics. Comparison of biodiversity dynamics based on traditional and eDNA survey methods showed significant differences in taxonomic groups identified between methods, landuse type, and method x season interactions. Our findings are the first example of eDNA derived functional spatio-temporal and dynamics, indicating that the regional shifts in diversity and function are linked to regional seasonal fluctuations in fine particle matter versus localized landuse type. Beta diversity components (nestedness and turnover) differed significantly along the environmental gradient, but in different directions, for each methodology. Overall, our findings show that eDNA based ecological assessment is effective in assessing temporal and spatial diversity and functional dynamics of macroinvertebrates, while demonstrating that these data can be used to infer effective biodiversity assessment and management strategies.
Original languageEnglish
Specialist publicationResearch Square Preprint Platform
DOIs
Publication statusUnpublished - 1 Oct 2020

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