Amplicon sequence variants from benthic and zooplankton samples generated using COI primers

Amplicon sequence variants from benthic and zooplankton samples generated using COI primers This research dataset has been reviewed in accordance with U.S. Environmental Protection Agency (U.S. EPA), Office of Research and Development, and approved for release. Mention of brand names or vendors does not constitute an endorsement of products or services by the U.S. EPA.”"

To evaluate the ability of precipitation-based environmental DNA (eDNA) sample collection and mitochondrial 12S metabarcoding sequencing to reconstruct well-studied fish communities in lakes and rivers. Specific objectives were to 1) determine correlations between eDNA species detections and known community composition based on traditional field sampling, 2) compare efficiency of eDNA to detect fish biodiversity among systems with variable morphologies and trophic states, and 3) determine if species habitat preferences predicts eDNA detection. Fish community composition was estimated for seven lakes and two MIssissippi River navigation pools using sequence data from the mitochonrial 12S gene amplified from 10 to 50 water samples per waterbody collected in 50-mL centrifuge tubes at a single time point. Environmental DNA (eDNA) was concentrated without filtration by centrifuging samples to reduce per-sample handling time. Taxonomic detections from eDNA were compared to established community monitoring databases containing up to 40 years of sampling and a detailed habitat/substrate preference matrix to identify patterns of bias. Mitochondrial 12S gene metabarcoding detectec 15-47% of the known species at each waterbody and 30-76% of known genera. Non-metric multidimensional scaling (NMDS) assessment of the community structure indicated that eDNA detected communities grouped in a similar pattern as known communities. Discriminant analysis of principal components indicated that there was a high degree of overlap in habitat/substrate preference of eDNA detected and eDNA undetected species suggesting limited habitat bias for eDNA sampling. Large numbers of small volume samples sequenced at the mitochondrial 12S gene can describe the course community structure of freshwater systems. However, additional traditional sampling and environmental DNA sampling may be necessary for a complete diversity census.

These data contain Genbank Accession numbers for DNA amplified and sequenced from a subset of Environmental Samplers that were positive for Ceratocystis lukuohia and Austropuccinia by quantitative PCR (qPCR)

This file has a listing of benthic macroinvertebrate taxa found in samples collected from coastal waters of Isle Royale and Chequamegon Bay (both in Lake Superior) in 2012 and 2013 respectively, This dataset is associated with the following publication: Meredith, C., A. Trebitz, and J. Hoffman. Post-processing of aquatic biodiversity data collected at multiple levels of resolution: Implications for estimates of taxa richness, abundance, and rarefaction curves. Freshwater Science. The Society for Freshwater Science, Springfield, IL, 98: 137-148, (2019).

This data set is an amalgamation of twenty-nine original data sets, which represent amphibian surveys in the seven national parks comprising the North Coast and Cascades Network (NCCN) of the National Park Service. The data were collected from 1984-2005, and include the localities of 19 species of amphibians at various life stages, 18 native to the Pacific Northwest and one invasive species.

Biological indicator taxa have long been used for integrative assessments of water quality, particularly benthic invertebrate groups such as arthropods. While standardized protocols have been developed to calculate 'biological index' scores based on the abundances of these taxa, such systems are challenging to implement at large scales due to the sampling effort required, taxonomic expertise needed, and the need for repeated sampling to reliably discriminate sites. Many of the same taxa detected by traditional surveys can also be detected by genetic analysis of environmental DNA (eDNA), potentially allowing for an alternative formulation of biological indexes that might be faster and more economical to produce. The current data were produced to evaluate eDNA-derived biological indexes at sites within the Potomac River watershed of the eastern United States, specifically within units of the National Park Service for which previous biological assessment data were available. This data release consists of five files: 1. sample.metadata.txt, which contains sampling metadata and identifiers linking to sample-derived sequence data that has been deposited in the Sequence Read Archive of the National Center for Biotechnology Information (NCBI). This database is authoritative and comprehensive for sharing high-throughput sequence data produced with public funds. All accessions listed in the file can be searched to retrieve sample and sequence information at www.ncbi.nlm.nih.gov. 2. cox1.references.fasta, which contains reference sequences of the cytochrome c oxidase 1gene of arthropods (typically abbreviated cox1 or COI), identified from regional checklists. The file is a text file in FASTA format. 3. mt16S.references.fasta, which contains reference sequences of the mitochondrial 16S ribosomal RNA (mt16S) gene of arthropods identified from regional checklists. The file is a text file in FASTA format. 4. first.stage.counts.txt, which is a tab-delimited table of counts of sequences that are attributed to each taxon from each sample for the first stage of the study. Whether the taxon attribution is from the mt16S or cox1 locus is also indicated. 5. second.stage.counts.txt, which is a tab-delimited table of counts of sequences that are attributed to each taxon from each sample for the second stage of the study. Whether the taxon attribution is from the mt16S or cox1 locus is also indicated.

This dataset contains information from surveys conducted 2004-2015 by USGS as part of a long-term amphibian monitoring effort in the Willamette Valley, Oregon. Data consist of site, survey, habitat, and species detection covariates.