|Document Type:||Journal Article|
|Title:||A framework for inferring biological communities from environmental DNA|
|Author:||Andrew Olaf Shelton, James Lawrence O'Donnell, J. F. Samhouri, Natalie Lowell, G. D. Williams, Ryan Kelly|
|Keywords:||environmental DNA,community ecology,Bayesian statistics,ecosystem assessment,multinomial-Poisson|
Environmental DNA (eDNA)—genetic material recovered from an environmental medium such as soil, water, or feces—reflects the membership of the ecological community present in the sampled environment. As such, eDNA is a potentially rich source of data for basic ecology, conservation, and management, because it offers the prospect of quantitatively reconstructing whole ecological communities from easily-obtained samples. However, like all sampling methods, eDNA sequencing is subject to methodological limitations that can generate biased descriptions of ecological communities. Here, we demonstrate parallels between eDNA sampling and traditional sampling techniques, and use these parallels to offer a statistical structure for framing the challenges faced by eDNA and illuminating the gaps in our current knowledge that are needed to glean the greatest insights from eDNA data. Although the current state of knowledge on some of these steps precludes a full estimate of biomass for each taxon in a sampled eDNA community, we use an original dataset to estimate the relative abundances of taxon-specific template DNA prior to PCR, given the abundance of DNA sequences recovered post-PCR-and-sequencing, a critical step in the chain of eDNA inference. While we focus on the use of eDNA samples to determine the relative abundance of taxa within a community, our approach applies directly to single-taxon applications, as well as those that focus on estimating occurrence rather than abundance. By grounding inferences about eDNA community composition in a rigorous statistical framework, and by making these inferences explicit, we hope to improve the quantitative potential for the emerging field of community-level eDNA analysis.
|Theme:||Recovery and rebuilding of marine and coastal species|
Develop methods to use physiological, biological and behavioral information to predict population-level processes.
Characterize the population biology of species, and develop and improve methods for predicting the status of populations.