Skip to main content
Dryad logo

Data from: eDNA concentration, population size structure, and mark-recapture data

Citation

Yates, Matthew et al. (2020), Data from: eDNA concentration, population size structure, and mark-recapture data, Dryad, Dataset, https://doi.org/10.5061/dryad.8kprr4xkf

Abstract

Organism abundance is a critical parameter in ecology, but its estimation is often challenging. Approaches utilizing eDNA to indirectly estimate abundance have recently generated substantial interest. However, preliminary correlations observed between eDNA concentration and abundance in nature are typically moderate in strength with significant unexplained variation. Here we apply a novel approach to integrate allometric scaling coefficients into models of eDNA concentration and organism abundance. We hypothesize that eDNA particle production scales non-linearly with mass, with scaling coefficients < 1. Wild populations often exhibit substantial variation in individual body size distributions; we therefore predict that the distribution of mass across individuals within a population will influence population-level eDNA production rates. To test our hypothesis, we collected standardized body size distribution and mark-recapture abundance data using whole-lake experiments involving nine populations of brook trout. We correlated eDNA concentration with three metrics of abundance: density (individuals/ha), biomass (kg/ha), and allometrically scaled mass (ASM) (∑(individual mass0.73)/ha). Density and biomass were both significantly positively correlated with eDNA concentration (adj. r2 = 0.59 and 0.63, respectively), but ASM exhibited improved model fit (adj. r2 = 0.78). We also demonstrate how estimates of ASM derived from eDNA samples in ‘unknown’ systems can be converted to biomass or density estimates with additional size structure data. Future experiments should empirically validate allometric scaling coefficients for eDNA production, particularly where substantial intraspecific size distribution variation exists. Incorporating allometric scaling may improve predictive models to the extent that eDNA concentration may become a reliable indicator of abundance in nature.

Usage Notes

Schnabel_input file is formatted to use the mrClosed() function from the Fisheries Stock Assessment package FSA in R.

For other methods, refer to details in manuscript.

Funding

Natural Sciences and Engineering Research Council of Canada

Fonds de recherche du Québec – Nature et technologies