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An analytical framework for estimating aquatic species density from environmental DNA.

ABSTRACT: Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. The modeling combines eDNA and animal count data from a subset of sites to estimate species density (and associated uncertainties) at other sites where only eDNA data are available. As a proof of concept, we first perform a cross-validation study using experimental data on carp in mesocosms. In these data, fish densities are known without error, which allows us to test the performance of the method with known data. We then evaluate the model using field data from a study on a stream salamander species to assess the potential of this method to work in natural settings, where density can never be known with absolute certainty. Two alternative distributions (Normal and Negative Binomial) to model variability in eDNA concentration data are assessed. Assessment based on the proof of concept data (carp) revealed that the Negative Binomial model provided much more accurate estimates than the model based on a Normal distribution, likely because eDNA data tend to be overdispersed. Greater imprecision was found when we applied the method to the field data, but the Negative Binomial model still provided useful density estimates. We call for further model development in this direction, as well as further research targeted at sampling design optimization. It will be important to assess these approaches on a broad range of study systems.

SUBMITTER: Chambert T

PROVIDER: S-EPMC5869225 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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An analytical framework for estimating aquatic species density from environmental DNA.

Chambert Thierry T Pilliod David S DS Goldberg Caren S CS Doi Hideyuki H Takahara Teruhiko T

Ecology and evolution 20180225 6

Environmental DNA (eDNA) analysis of water samples is on the brink of becoming a standard monitoring method for aquatic species. This method has improved detection rates over conventional survey methods and thus has demonstrated effectiveness for estimation of site occupancy and species distribution. The frontier of eDNA applications, however, is to infer species density. Building upon previous studies, we present and assess a modeling approach that aims at inferring animal density from eDNA. Th ...[more]

PMID: 29607039

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Project description:Estimating the species richness of microorganisms is of great importance in predicting, maintaining and managing microbial communities. Although the roles of environmental heterogeneity and geographical distance in structuring soil microbial communities have been studied intensively, the effects of environmental and spatial variation on the species richness estimation have not been examined. To this end, we have explored their effects on estimating the belowground soil bacterial species richness within a 50 ha forest dynamic plot (FDP) using a published massive sequencing dataset with intensive sampling scheme. Our resampling analyses showed that, for a given sequencing depth, increasing the sample size could significantly enhance the detection of rare species by capturing more of the environmental and spatial variation, thus obtaining higher observed and estimated species richness. Additionally, the estimates of bacterial species richness were significantly and positively correlated with environmental variation among samples, indicating that environmental filtering was the main mechanism driving the processes of community assembly for belowground soil bacterial communities in the plot. Moreover, this effect of environmental variation could be markedly alleviated when the sample size was higher than 450, and thus we predicted that there were at least 42,866 soil bacterial species based on 8,296,878 sequences from 550 samples in the whole 50 ha FDP. Furthermore, we built a power law environmental heterogeneity equation (EHE) as a decision-tool to determine an approximate sample size for comprehensively capturing the environmental gradient within a given habitat. Collectively, this work further links the inherent environmental and spatial variation to the estimation of soil bacterial species richness within a given region, and provides a useful tool of sampling design for a better understanding of microbial biogeographic patterns and estimation of microbial biodiversity.

Dataset Information

An analytical framework for estimating aquatic species density from environmental DNA.

Publications

An analytical framework for estimating aquatic species density from environmental DNA.

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