COS 62-7
Estimating species richness with environmental DNA

Wednesday, August 13, 2014: 10:10 AM
Regency Blrm D, Hyatt Regency Hotel
Christopher L. Jerde, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN
Brett P. Olds, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN
Mark A. Renshaw, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN
Cameron R. Turner, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN
Nathan Evens, University of Notre Dame
Arial Shogren, Biological Sciences, University of Notre Dame
Karen L. Uy, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN
Crysta A. Gantz, Biological Sciences, University of Notre Dame, Notre Dame, IN
Jennifer L. Tank, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN
Diogo Bolster, University of Notre Dame
Andrew R. Mahon, Institute for Great Lakes Research, Central Michigan University, MI
Michael E. Pfrender, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN
Gary A. Lamberti, Department of Biological Sciences, University of Notre Dame, Notre Dame, IN
David M. Lodge, Biological Sciences, University of Notre Dame, Notre Dame, IN
Background/Question/Methods

Using traditional capture methods, such as electrofishing and nets, to directly measure aquatic species richness is difficult when species are rare, so scientists use species richness estimators to account for undetected species. Environmental DNA (eDNA) is proving to be a robust indicator of rare, aquatic species presence. The metagenetics approach, that is the evaluation of taxon richness through homologous genes, potentially allows a water sample to reveal an aquatic system’s species richness without the effort of traditional capture methods. Two main obstacles exist for developing metagenetic approaches for estimating species richness with eDNA: quantifying errors in species detection, and defining the area over which an estimate of species richness relates.  Here we quantify detection errors using the metagenetic approach where presence of species is known from electrofishing and conduct eDNA release studies in flowing environments to measure the retention and residence time.

Results/Conclusions

The metagenetic approach is capable of detecting all 12 species found during electrofishing of four 60m reaches, but also identified species not observed in the study reaches. Two possible explanations for genetic detection of species not recovered using traditional gears is that DNA is sourced from fishes outside of the study area or species were not captured using electrofishing. From four independent trials of eDNA release, we show that eDNA is sticky and is retained in the environment much longer than conservative tracers. As a consequence, it is likely that if the DNA of an organism is found, then it is nearby. However, the residence time of our eDNA releases show that it is also plausible that DNA from outside the study reaches contribute to species richness estimates.  This study demonstrates how eDNA with a metagenetic approach can provide accurate estimates of aquatic species richness and identifies limits to the inferences that can be made.