Dataset: Pseudo-nitzschia spp. presence-absence and environmental data in Narragansett Bay in Rhode Island, USA and the Northeast U.S. Shelf (NES-LTER transect) from 2018-2023

ValidatedFinal no updates expectedDOI: 10.26008/1912/bco-dmo.936856.1Version 1 (2024-10-14)Dataset Type:Cruise ResultsDataset Type:Other Field Results

Principal Investigator: Bethany D. Jenkins (University of Rhode Island)

Co-Principal Investigator: Matthew Bertin (University of Rhode Island)

Scientist: Riley Kirk (University of Rhode Island)

Scientist: Tatiana A. Rynearson (University of Rhode Island)

Scientist: Alexa Sterling (University of Rhode Island)

Student: Isabella Church (University of Rhode Island)

Student: Andrew Kim (University of Rhode Island)

Student, Contact: Katherine M. Roche (University of Rhode Island)

BCO-DMO Data Manager: Lynne M. Merchant (Woods Hole Oceanographic Institution)


Program: Long Term Ecological Research network (LTER)

Project: Northeast U.S. Shelf Long Term Ecological Research site (NES LTER)

Project: RII Track-1: Rhode Island Consortium for Coastal Ecology Assessment, Innovation, and Modeling (C-AIM)

Project: Narragansett Bay Long-Term Plankton Time Series (NBPTS)


Abstract

This dataset includes environmental measurements and presence-absence of Pseudo-nitzschia species, a harmful algal bloom diatom genus, associated with samples from various sites in Narragansett Bay, Rhode Island, including the Narragansett Bay Long Term Plankton Time Series site, and several stations along the Northeast U.S. Shelf Long Term Ecological Research program transect. These data correspond to an analysis of Pseudo-nitzschia species composition and domoic acid toxin production during wi...

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Acknowledgement:

We acknowledge the NSF RI C-AIM EPSCoR Cooperative Agreement (OIA-1004057) for research support. Sequencing was performed at the University of Rhode Island Molecular Informatics Core supported by the Institutional Development Award (IDeA) Network for Biomedical Research Excellence from the National Institute of General Medical Sciences of the National Institutes of Health (P20GM103430).


Related Datasets

IsRelatedTo

Dataset: Amplicon sequence variants (ASVs) and taxonomy of Pseudo-nitzschia spp.
Roche, K. M., Church, I., Sterling, A., Rynearson, T. A., Bertin, M., Kim, A., Kirk, R., Jenkins, B. D. (2024) Amplicon sequence variants (ASVs) and taxonomy of Pseudo-nitzschia spp. from Narragansett Bay in Rhode Island, USA and the Northeast U.S. Shelf (NES-LTER transect) from 2018-2023. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-10-11 doi:10.26008/1912/bco-dmo.936849.1

Related Publications

Results

Roche, K.M., Church, I.N., Sterling, A.R., Rynearson, T.A., Bertin, M.J., Kim, A.M., Kirk, R.D., Jenkins, B.D. (2024). Connectivity of toxigenic Pseudo-nitzschia species assemblages between the Northeast U.S. continental shelf and an adjacent estuary. Manuscript submitted for publication.
Methods

Roche, K. M., Sterling, A. R., Rynearson, T. A., Bertin, M. J., & Jenkins, B. D. (2022). A Decade of Time Series Sampling Reveals Thermal Variation and Shifts in Pseudo-nitzschia Species Composition That Contribute to Harmful Algal Blooms in an Eastern US Estuary. Frontiers in Marine Science, 9. https://doi.org/10.3389/fmars.2022.889840
Methods

Sterling, A. R., Kirk, R. D., Bertin, M. J., Rynearson, T. A., Borkman, D. G., Caponi, M. C., Carney, J., Hubbard, K. A., King, M. A., Maranda, L., McDermith, E. J., Santos, N. R., Strock, J. P., Tully, E. M., Vaverka, S. B., Wilson, P. D., & Jenkins, B. D. (2022). Emerging harmful algal blooms caused by distinct seasonal assemblages of a toxic diatom. Limnology and Oceanography, 67(11), 2341–2359. Portico. https://doi.org/10.1002/lno.12189
Methods

White, T. J., Bruns, T., Lee, S., & Taylor, J. (1990). AMPLIFICATION AND DIRECT SEQUENCING OF FUNGAL RIBOSOMAL RNA GENES FOR PHYLOGENETICS. PCR Protocols, 315–322. https://doi.org/10.1016/b978-0-12-372180-8.50042-1
Software

Andrews S. (2010). FastQC: a quality control tool for high throughput sequence data. Available online at: http://www.bioinformatics.babraham.ac.uk/projects/fastqc