A general framework to unify the estimation of numerical abundance and biomass from quantitative eDNA data

Does environmental DNA (eDNA) correlate more closely with numerical abundance (N) or biomass in aquatic organisms? We hypothesize that the answer is neither: eDNA production likely scales allometrically, reflecting key physiological rates and surface area-to-body mass relationships. Building on individual-level frameworks developed from the Metabolic Theory of Ecology, we derive a framework through which quantitative eDNA data can be transformed to simultaneously reflect both population-level N and biomass. We then validated our framework using data from two previously published studies: (i) a marine eDNA metabarcoding dataset; and (ii) a freshwater single-species qPCR dataset. Using a Bayesian modeling approach, we estimated the value of the allometric scaling coefficient that jointly optimized the relationship between N, biomass, and corrected eDNA data to be 0.82 and 0.77 in Case Studies (i) and (ii), respectively. These estimates closely match expected scaling coefficients estimated in previous work on Teleost fish metabolic rates. We also demonstrate that correcting quantitative eDNA can significantly improve correspondence between eDNA- and traditionally-derived quantitative community biodiversity metrics (e.g., Shannon index and Bray-Curtis dissimilarity) under some circumstances. Collectively, we show that quantitative eDNA data is unlikely to correspond exactly to either N or biomass, but can be corrected to reflect both through our unifying joint modelling framework. This framework can also be further expanded to include other variables that might impact eDNA pseudo-steady-state concentrations in natural ecosystems (e.g., temperature, pH, and phenology), and is flexible enough to model these relationships across trophic levels. Significance StatementAquatic animals release DNA (from shed cells, mucous, faeces, etc.) into water, which can be detected via environmental DNA (eDNA) sampling. What is less clear is whether we can estimate numerical abundance (N) or biomass from eDNA concentrations. We hypothesize that eDNA production scales allometrically; that is, large animals release less DNA per unit mass than smaller animals. Building from the Metabolic Theory of Ecology, we derived a framework through which eDNA data can be transformed to simultaneously reflect both N and biomass. We then validated the framework using two case studies in marine and freshwater systems. This framework unifies discrepancies between eDNA, N, and biomass data, unlocking the potential of eDNA to monitor population abundance/biomass and quantify biodiversity.