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Data from: Allometric scaling of eDNA production in stream-dwelling brook trout (Salvelinus fontinalis) inferred from population size structure

Yates, Matthew1; Wilcox, Taylor2; McKelvey, Kevin2; Young, Michael2; Schwartz, Michael2; Derry, Alison1

Published Oct 05, 2020 on Dryad. https://doi.org/10.5061/dryad.bvq83bk6v

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Oct 05, 2020 version files 37.91 KB

Abstract

Environmental DNA (eDNA) concentration exhibits a positive correlation with organism abundance in nature, but modelling this relationship could be substantially improved by incorporating the biology of eDNA production. A recent model (Yates et al. 2020) extended models of physiological allometric scaling to eDNA production, hypothesizing that brook trout eDNA production scales non-linearly with mass as a power-function with scaling coefficients < 1 in lakes. To validate this hypothesis, we re-analysed data from Wilcox et al. (2016) that examined the correlation between eDNA concentration and brook trout abundance in streams. We found that allometrically scaled mass (ASM) (e.g. ∑(individual mass0.36) best described patterns of eDNA concentration across streams (r2 = 0.43). ASM exhibited substantially improved model fit relative to biomass (r2 = 0.31, ∆AIC = 5.19), indicating that eDNA production did not scale linearly with biomass. However, the explanatory power of ASM was comparable to density (r2 = 0.40, ∆AIC = 1.25). Additionally, the optimal scaling coefficient estimated from the data (0.36) was substantially lower than that found in Yates et al. (2020) (0.72). Discrepancies between datasets could be attributable to ecological differences between study habitats (streams vs lakes) or due to the exclusion of juveniles (i.e. individuals < 75 mm) that can be abundant in stream environments. Nevertheless, this study adds to the growing body of literature demonstrating that individual eDNA production does not scale linearly with biomass.