The relationship between eDNA particle concentration and organism abundance in nature is strengthened by allometric scaling

Abstract

17Organism abundance is a critical parameter in ecology, but its estimation is often challenging. 18Approaches utilizing eDNA to indirectly estimate abundance have recently generated substantial 19 interest. However, preliminary correlations observed between eDNA concentration and 20 abundance in nature are typically moderate in strength with significant unexplained variation. 21Here we apply a novel approach to integrate allometric scaling coefficients into models of eDNA 22 concentration and organism abundance. We hypothesize that eDNA particle production scales 23 non-linearly with mass, with scaling coefficients < 1. Wild populations often exhibit substantial 24 variation in individual body size distributions; we therefore predict that the distribution of mass 25 across individuals within a population will influence population-level eDNA production rates. To 26 test our hypothesis, we collected standardized body size distribution and mark-recapture 27 abundance data using whole-lake experiments involving nine populations of brook trout. We 28 correlated eDNA concentration with three metrics of abundance: density (individuals/ha), 29 biomass (kg/ha), and allometrically scaled mass (ASM) (∑(individual mass 0.73 )/ha). Density and 30 biomass were both significantly positively correlated with eDNA concentration (adj. R 2 = 0.59 31 and 0.63, respectively), but ASM exhibited improved model fit (adj. R 2 = 0.78). We also 32 demonstrate how estimates of ASM derived from eDNA samples in 'unknown' systems can be 33 converted to biomass or density estimates with additional size structure data. Future experiments 34 should empirically validate allometric scaling coefficients for eDNA production, particularly 35 where substantial intraspecific size distribution variation exists. Incorporating allometric scaling 36 may improve predictive models to the extent that eDNA concentration may become a reliable 37 indicator of abundance in nature. 38 39 3

Allometric scaling of RNA abundance from genes to communities

“…This study also highlights the possible use of allometric scaling via a power function as a framework for modeling mRNA transcript and ribosome abundance. We have demonstrated that using allometric scaling coefficients as the power of individual body mass substantially improves the relationship between RNA abundance and species biomass (3). This study provides a robust empirical framework explaining the relationship between RNA abundance through metatranscriptomic reads and the size distribution of species in community samples.…”

“…To see if transcript scaling can improve predictive models for the relationship between RNA transcripts and biomass, we ran several sets of correlation analyses among commonly used S4) for body size scaling (3). .…”

Exploring video and eDNA metabarcoding methods to assess oyster aquaculture cages as fish habitat

“…We used published literature on fish habitat preferences (Leim & Scott 1966, Whitehead 1985, Makushok 1986, Robins & Ray 1986, Whitehead et al 1988, Dooley 1990, Collette & Klein-MacPhee 2002 as referenced in Fishbase [https:// www.fishbase.se]) to select the subset of 5 abundant finfish species known to be dependent on structured habitat for further examination. Given the current uncertainty around correlations between eDNA read number and fish abundance or biomass (Yates et al 2021) and the spatiotemporal limitations of our data, we have chosen to report and visualize eDNA read number here and make qualitative comparisons with fish assemblages observed by video, but not to perform a quantitative statistical analysis of these data.…”

“…Di Muri et al 2020), and others have observed significant correlation between read number and biomass (Stoeckle et al 2021). It could be anticipated that read number would more closely correlate with biomass, since eDNA production (by shedding and/or meta bolic pro cesses) by many small fish could be similar in quantity to a much smaller number of larger fish (Yates et al 2021). The 2-dimensional nature of video makes estimates of fish size unreliable, thus we were unable to calculate biomass of ob served fish, which would potentially have been a better metric for comparison to read number.…”

Testing allometric scaling relationships in plant roots

“…However, the universal application of Kleiber's law is contested (Brown et al 2005;da Silva and Barbosa 2009;Glazier 2010;Hamilton et al 2011;Glazier 2014;Yates et al 2020). For example, Kozłowski and Konarzewski (2004) argue that Kleiber's law cannot be explained using any limiting factor because metabolic rates vary by factors of 4-5 between rest and activity.…”