Environmental DNA allows upscaling spatial patterns of biodiversity in freshwater ecosystems

Abstract

The alarming declines of freshwater biodiversity call for efficient biomonitoring at fine spatiotemporal scales, such that conservation measures be grounded upon accurate biodiversity data. Here, we show that combining environmental DNA (eDNA) extracted from stream water samples with models based on hydrological first principles allows upscaling biodiversity estimates for aquatic insects at very high spatial resolution. Our model decouples the diverse upstream contributions to the eDNA data, enabling the reconstruction of taxa distribution patterns. Across a 740-km 2 basin, we obtain a space-filling biodiversity prediction at a grain size resolution of 1-km long stream sections. The model’s accuracy in matching direct observations of aquatic insects’ local occurrence ranges between 57–100%. Our results demonstrate how eDNA can be used for high-resolution biodiversity assessments in rivers with minimal prior knowledge of the system. Our approach allows identification of biodiversity hotspots that could be otherwise overlooked, enabling implementation of focused conservation strategies.

Environmental DNA: What's behind the term? Clarifying the terminology and recommendations for its future use in biomonitoring

“…Currently, two definitions of eDNA are used in ecological studies in parallel. On the one hand, the definition of eDNA sensu lato is used in global biodiversity surveys that analyse microbial, meiofauna and macrofauna communities, focusing on their ecological interactions (Deiner et al, 2016;Djurhuus et al, 2020;Zhang et al, 2020) and temporal and spatial dynamics (Altermatt et al, 2020;Bálint et al, 2018;Carraro et al, 2020). Such a definition is also commonly used in environmental biomonitoring studies that target different groups of bioindicators to infer or predict biotic indices (Cordier et al, 2018(Cordier et al, , 2019Li et al, 2018;Pawlowski et al, 2018;Stoeck et al, 2018).…”

Human activities' fingerprint on multitrophic biodiversity and ecosystem functions across a major river catchment in China

“…eDNA technologies have rapidly advanced in their methodological development, with assessment of species' abundance or biomass being still more challenging than assessing species' presence/absence (Deiner et al., 2017). We take full advantage of the method to capture the complete biodiversity and to identify the spatial hierarchic structure of communities in rivers (Altermatt et al., 2020; Carraro et al., 2020; Deiner et al., 2016), so as to analyze the impact of human land use on multitrophic biodiversity and its dependencies with ecosystem functions (e.g., decomposition and enzyme activities). Our study hypothesizes that: (a) increased human land use reduces multitrophic and multifaceted biodiversity and ecosystem functions, yet the direction and intensity of their responses may be partially idiosyncratic at individual levels; (b) ecosystem functions are correlated with biodiversity, but their relationships may vary depending on the intensity of human land use.…”

How to design optimal eDNA sampling strategies for biomonitoring in river networks

“…Moreover, eDITH can be theoretically used with any taxonomic group, given that no specific assumption on the eDNA production rate p is made, its value being directly inferred from the eDNA concentration data. In particular, its application on motile taxa (e.g., fish or crustaceans) is guaranteed because the scale distance of mobility of most organisms is typically much shorter than that of hydrological transport in rivers (Carraro, Mächler, et al, 2020). Hence, the findings of the present study could potentially be generalized to the issue of determining the optimal sampling strategy within a river network in order to maximize information on the spatial distribution of biodiversity.…”