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

Cite this dataset

Yates, Matthew et al. (2020). Data from: Allometric scaling of eDNA production in stream-dwelling brook trout (Salvelinus fontinalis) inferred from population size structure [Dataset]. Dryad. https://doi.org/10.5061/dryad.bvq83bk6v

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.

Usage notes

Data originally from Wilcox et al. 2016, and was re-analyzed using methods developed in Yates et al. 2020. Summary file contains brook trout abundance, eDNA, and habitat data. 'Raw-file-multipass' contains data on population/site size structure variation.

In summary file, variable names refere to:

'site' = population study site

'lat' = latitude

'long' = longitude

'bkt.pass1', 'bkt.pass.2', 'bkt.pass.3' = number of fish captured during first, second, or third pass (respectively) to catch fish using Zippin method

'bkt.cap'  = total number of brook trout captured in all passes

'unstandardized.bkt.estimate' = brook trout census estimate not standardized for stream reach length

'standardized.bkt.estimate' = brook trout census estimate standardized for stream reach length

'bkt.ds.copies.L' = eDNA copies per L detected at downstream point of stream reach

'site.length' = length of stream reach

'site.width' = width of stream reach

'discharge.L.sec' = stream discharge in L/sec

'perc.slope' = gradient of slope for stream reach

'SumMassCapturedFish' = total biomass of captured fish

'MeanMass' = mean mass of fish captured in stream reach

'MeanLength' = mean length of fish captured in stream reach

 

Funding

Natural Sciences and Engineering Research Council

Fonds de Recherche du Québec – Nature et Technologies