Data from: Estimating species richness using environmental DNA

Olds, Brett P., Notre Dame University, University of Notre Dame, Hawaii Pacific University

Jerde, Christopher L., University of Nevada Reno, Notre Dame University, University of Notre Dame

Renshaw, Mark A., Notre Dame University, University of Notre Dame

Li, Yiyuan, Notre Dame University, University of Notre Dame

Evans, Nathan T., Notre Dame University, University of Notre Dame

Turner, Cameron R., Notre Dame University, University of Notre Dame

Deiner, Kristy, Notre Dame University, University of Notre Dame

Mahon, Andrew R., Central Michigan University

Brueseke, Michael A., Notre Dame University, University of Notre Dame

Shirey, Patrick D., Notre Dame University, University of Notre Dame

Pfrender, Michael E., Notre Dame University, University of Notre Dame

Lodge, David M., Notre Dame University, University of Notre Dame

Lamberti, Gary A., Notre Dame University, University of Notre Dame

Published Apr 26, 2017 on Dryad. https://doi.org/10.5061/dryad.d63sc

Cite this dataset

Olds, Brett P. et al. (2017). Data from: Estimating species richness using environmental DNA [Dataset]. Dryad. https://doi.org/10.5061/dryad.d63sc

Abstract

The foundation for any ecological study and the for effective management of biodiversity in natural systems requires knowing what species are present in an ecosystem. We assessed fish communities in a stream using two methods, depletion-based electrofishing and environmental DNA metabarcoding (eDNA) from water samples, to test the hypothesis that eDNA provides an alternative means of determining species richness and species identities for a natural ecosystem. In a northern Indiana stream, electrofishing yielded a direct estimate of 12 species and a mean estimated richness (Chao II estimator) of 16.6 species with a 95% confidence interval from 12.8 to 42.2. eDNA sampling detected an additional four species, congruent with the mean Chao II estimate from electrofishing. This increased detection rate for fish species between methods suggests that eDNA sampling can enhance estimation of fish fauna in flowing waters while having minimal sampling impacts on fish and their habitat. Modern genetic approaches therefore have the potential to transform our ability to build a more complete list of species for ecological investigations and inform management of aquatic ecosystems.

Usage notes

Actino12s OTU Centroid Sequences

List of centroid sequences generated in OTU formation after HMMER filtering

Actino12s.OTU.ID.hmm.fasta

Actino16s OTU Centroid Sequences

List of centroid sequences generated in OTU formation after HMMER filtering

Actino16s.OTU.ID.hmm.fasta

Amphibia12s OTU Centroid Sequences

List of centroid sequences generated in OTU formation after HMMER filtering

Amphibia12s.OTU.ID.hmm.fasta

Cytb OTU Centroid Sequences

List of centroid sequences generated in OTU formation after HMMER filtering

Cytb.OTU.ID.hmm.fasta

Supplement Table 1

Electrofishing derived species counts in Juday Creek for each reach from September 2013. Samples are ordered from the most downstream reach (R1) to the most upstream reach (R4).

Supplement Table 2

Number of reads from each sample (i.e. library) run on the Illumina MiSeq platform for each step of the bioinformatic pipeline.

Supplement Table 3

Results for all species identified with OTU species assignment. Values of P1 – P7 represent the pathway taken to arrive at species assignment using SAP and USearch (Fig. S1).

Supplement Table 4

Raw read counts of each species identified, for each sample and all four markers.

Supplement Table 5

Putative false positive OTUs and the corresponding read number of each marker in each sample.

Supplement Table 6

List of species for which we had a reference sequence for each of the four markers used.

Supplement Table 7

This table shows read counts after filtering. The eDNA column shows the species detected in the actual Juday Creek samples with some reads counts in any of these control samples. The P/A columns shows Presence (1) or Absence (0) given our criteria of >1 read and reads in multiple markers or samples.