A framework for inferring biological communities from environmental DNA

Abstract

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 for illuminating the gaps in our current knowledge. 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 provide a map that illustrates potential methods for bridging these gaps. Additionally, we use an original data set 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 also applies to single-taxon applications (including applications using qPCR), studies of diversity, and studies focused on occurrence. By grounding inferences about eDNA community composition in a rigorous statistical framework, and by making these inferences explicit, we hope to improve the inferential potential for the emerging field of community-level eDNA analysis.

Under the canopy: Community-wide effects of invasive algae in Marine Protected Areas revealed by metabarcoding

“…Nevertheless, most studies analysing this relationship report a gross correlation, in the sense that more abundant species also tend to be represented by a higher relative or absolute number of reads (reviewed in Lejzerowicz et al, 2015;Barnes and Turner, 2016;Valentini et al, 2016;Bucklin et al, 2016). It can be added here that abundance estimation using traditional methods is not free of biases, either (Shelton et al, 2016). Several metabarcoding studies opted for considering exclusively qualitative information.…”

Genetic and Manual Survey Methods Yield Different and Complementary Views of an Ecosystem

“…The primer sets amplified two mitochondrial loci [16S, ca. 116 bp, O'Donnell et al, 2016;Shelton et al, 2016), targeting metazoans exclusively; COI, ca. 315 bp, (Leray et al, 2013), targeting eukaryotes], and one nuclear ribosomal gene [18S, ca.…”

“…We note that this occupancy modeling is a special case of the more general framework elaborated in Shelton et al (2016), which uses a Bayesian hierarchical model to estimate community structure from eDNA reads. However, for ease of computation our simulation below uses a version of binomial occupancy modeling.…”

DNA Sequencing as a Tool to Monitor Marine Ecological Status

“…For the purposes here, the focus is on high throughput, short-read sequencing of amplicons from macroeukaryotic assemblages (metabarcoding) or individuals (barcoding); amplicons from assemblages of maroeukaryotes obtained indirectly from the environment rather than from whole organisms or tissues (eDNA); amplicons from prokaryotic/microeukaryotic assemblages (metagenetics); and shotgun sequencing of prokaryotic/microeukaryotic assemblages (metagenomics). A variety of references regarding extraction (Cox and Goodwin, 2013;Hazen et al, 2013), amplification, and sequencing strategies for water, sediments, and tissues are available herein, and eDNA is also reviewed extensively elsewhere (Bohmann et al, 2014;Rees et al, 2014;Pedersen et al, 2015;Thomsen and Willerslev, 2015;Shelton et al, 2016); therefore, only a brief technical overview is provided here.…”

“…The eDNA approach promises information about bioindicators and commercially important or protected species without the need to collect tissue or trawl through sensitive habitats (Foote et al, 2012;Bohmann et al, 2014;Thomsen and Willerslev, 2015;Evans et al, 2016;Lacoursière-Roussel et al, 2016;Shelton et al, 2016). Some studies show promising results with regard to abundance estimates (Hänfling et al, 2016;Port et al, 2016), but others show significant differences between eDNA results and traditional tows for epibenthic macroinvertebrates (Kelly et al, 2017) and zooplankton (Hirai et al, 2015b), suggesting that these methods require further research.…”