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-km2 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.
Highlights
The alarming declines of freshwater biodiversity call for efficient biomonitoring at fine spatiotemporal scales, such that conservation measures be grounded upon accurate biodiversity data
We develop an integrated hydrology-based modeling framework, built on the approach of refs. 30,31, to analyze metabarcoding environmental DNA (eDNA) data collected at 61 locations in a 740-km[2] river basin and derive the spatial patterns of all aquatic insect taxa belonging to the orders of may, stone, and caddisflies (Ephemeroptera, Plecoptera, and Trichoptera, abbreviated as EPT)
As widely recognized[11,16,23], the use of eDNA in rivers leads to a faster and less invasive biodiversity monitoring as compared to kicknet sampling, but its results consist in a number of pointwise estimates that could hardly be projected into biodiversity maps at high spatial resolution
Summary
The alarming declines of freshwater biodiversity call for efficient biomonitoring at fine spatiotemporal scales, such that conservation measures be grounded upon accurate biodiversity data. 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. 1234567890():,; Global biodiversity[1,2], and freshwater biodiversity in particular[3,4,5,6], are declining at large, unprecedented rates with potentially devastating effects on ecosystems’ state and function[2,7], and, subsequently, deleterious consequences for human well-being To mitigate these threats, effective management and policy making are pivotal, thereby calling for accurate biodiversity data at high spatiotemporal resolution[8,9,10,11]. The ensemble results enable us to identify the portions and locations of the catchment with highest EPT taxa richness
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