Data from: A framework to unify the relationship between numerical abundance, biomass, and environmental DNA

Does environmental DNA (eDNA) concentration correlate with numerical
abundance (N) or biomass in aquatic organisms? We hypothesize that eDNA
can be adjusted to simultaneously reflect both. Building on frameworks
developed from the Metabolic Theory of Ecology, we derive two equations to
adjust eDNA data to simultaneously reflect both N and biomass using
population size structure data and allometric scaling coefficients. We
also demonstrate that these equations share model parameters,
necessitating the joint estimation of regressions between adjusted eDNA,
N, and biomass. Furthermore, our framework can be extended to model how
other variables (temperature, taxa, diet, trophic level, etc.) might
impact relationships between eDNA, N, and biomass in natural ecosystems.
We applied our framework to data from two previously published studies
correlating eDNA to Brook Trout (Salvelinus fontinalis) N and biomass. In
both case studies, point estimates of the scaling coefficient (b)
reflected allometric processes (b = 0.51 and 0.37 for Case Study 1 and 2,
respectively), with credible intervals indicating that b likely differed
from zero (i.e., eDNA scales with N) and one (i.e., eDNA scales with
biomass). Directly estimating the value of b improved estimates of N and
biomass relative to assuming b equals 0, which particularly affected the
capacity to estimate biomass. However, models assuming eDNA production
scaled with biomass (i.e., b = 1) were largely similar to estimating b,
implying that assuming eDNA scales linearly with biomass might be a
sufficient approximation for some systems. Nevertheless, the framework
demonstrates that correlating eDNA directly with either N or biomass (as
is commonly done in many studies) inherently necessitates an adjustment to
infer the other metric if populations exhibit size structure variation.
Collectively, we demonstrate that quantitative eDNA data is unlikely to
correspond exactly to either population N or biomass but can be adjusted
to simultaneously reflect both.