Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
  • BCO-DMO Processing Description
• Data Files
• Related Publications
• Related Datasets
• Parameters
• Instruments
• Project Information
• Program Information
• Funding

The methods reported below are summarized from Rynearson et al. (2020) and Fontaine and Rynearson (2023), two publications that used this dataset.

Filtered biomass sample collection, processing, and sequencing
As part of the Narragansett Bay Plankton Time Series (NBPTS), weekly surface water samples (9 meters depth) were collected between December 2008 and December 2014 from the west passage of Narragansett Bay (41°34.2'N, 71°23.4'W), a partially mixed estuary in the northwest Atlantic. Sampling occurred at a fixed location (historically this station has been called 'Station II') with a small boat operated by the University of Rhode Island (Cap'n Bert).

Water samples were filtered in triplicate onto 0.22-micrometer (μm) pore size, 25-millimeter (mm) diameter ExpressPlus filters (MilliporeSigma, Burlington, Massachussetts, USA) and stored at -80° Celsius (C) for later DNA extraction. Filter volume was dependent on the in situ Secchi depth; 100 milliliters (mL) of water were filtered per 1 meter (m) of Secchi depth which ranged from 1- 6 m. Previously extracted DNA from 68 monthly surface water samples collected between December 2008 and December 2014 was used here (Canesi and Rynearson, 2020) in addition to extracted DNA from 12 monthly samples collected between January and December 2014 (Rynearson et al. 2020).

To identify the diatoms present in each sample, a 420 base pair (bp) fragment within the variable V4 region of the 18S rDNA gene was amplified using primers D512 and D978rev (Zimmermann et al. 2011). Primers were modified by the addition of Illumina-specific adaptors: D512_illumina: 5' TCGTCGGCAGCGTCAGATGTGTATAAGAGACAGATT CCAGCTCCAATAGCG 3' and D978_illumina: 5' GTCTCGTGGGCTCGGAGATGTGTATAA GAGACAGGACTACGATGGTATCTAATC 3'. Ten microliter PCR reactions contained the following reagents: 1x Bio-x-Act Short Mix (Bioline USA Inc., Taunton, Massachusetts, USA), 0.5 micromolar (µM) each forward and reverse primer and approximately 0.3-2.7 nanograms (ng) DNA template. Reactions were amplified with a multi-step thermocycler protocol, consisting of a two-minute denaturing step at 94°C, followed by 20 cycles of 30 seconds each at 94°C, 49°C and 72°C, followed by 15 cycles of 30 seconds each at 94°C, 67°C and 72°C, followed by 10 minutes at 72°C. PCR amplicons were cleaned with Ampure XP beads (Beckman Coulter, Inc., Brea, California, USA), quantified with the Qubit High Sensitivity DNA Assay Kit (Thermo Fisher Scientific, Inc., Waltham, Massachusetts, USA), amplified for an additional five cycles to add Nextera indices and adaptors (Illumina, Inc., San Diego, California, USA) and cleaned again with Ampure XP beads. PCR products were pooled with the KAPA qPCR kit (Kapa Biosystems, Wilmington, Massachusetts, USA) and sequenced on the Illumina MiSeq platform with V2 chemistry (2x250bp reads; Illumina, Inc., San Diego, California, USA) at the University of Rhode Island Genomics and Sequencing Center.

Raw sequence data can be found on NCBI under BioProject number PRJNA327394 (https://www.ncbi.nlm.nih.gov/bioproject/327394).

Sampling Gaps:
Samples were not collected In February, March, April, and December 2012.

Sequence analysis and taxonomic assignment
To ultimately assign taxon identity to each read, paired-end sequencing reads were first processed using Cutadapt (Martin, 2011; version 2.10) to remove primers and Illumina adaptors. Reads were then processed and taxonomically assigned using the Divisive Amplicon Denoising Algorithm (DADA2) R package (Callahan et al. 2016; version 1.16). Forward (F) and reverse (R) reads were trimmed (F: 220 nucleotides (nt) and R: 210 nt), filtered (maxEE = F/ R: 2, truncQ = F/R: 2), denoised, and merged. Chimeras were removed using the consensus method in DADA2 (Callahan et al. 2016). Taxonomy was assigned to amplicon sequence variants (ASVs) using a naïve Bayesian classifier algorithm (Wang et al. 2007) with a minimum bootstrap confidence of 80% using the Protist Ribosomal Reference database (Guillou et al. 2013). ASVs that were identified to the same species were retained as separate ASVs here because the primers we used amplify a region of the 18S rRNA gene that has been shown to predominantly recover differences among species and not strains (Zimmermann et al. 2011). For ASVs where no species level information could be obtained, the species was reported as "Genus sp#" (e.g., "Chaetoceros sp1").

An additional taxonomic assignment step was performed using the assignSpecies function (Callahan et al. 2016) to allow for a single ASV to be assigned multiple species which resulted in some ASVs being classified as species groups because their sequences were not unique at the V4 region of the 18S rRNA gene. For Skeletonema and Thalassiosira ASVs, assignment of these sequences was performed upon manual examination of ASV sequences in Geneious (Kearse et al. 2012). The sequences were compared to a custom reference database for Skeletonema and Thalassiosira and taxonomies were assigned with 100% identity (Canesi and Rynearson 2016; Rynearson et al. 2020; accessible under DOI 10.5281/zenodo.10067598). The final dataset contained only ASVs that made up more than 0.075% of total sequence reads per sample, a threshold based on mock community analysis to determine spurious ASVs (Reitmeier et al. 2021).

- Imported original file "Diatom_ASV_Table_V2.csv" into the BCO-DMO system.
- Flagged 'NA' as a missing data value. Missing data are blank/empty in the final CSV file.
- Created columns for Longitude and Latitude and filled in with the coordinates of the sampling locations provided in the metadata.
- Renamed the "Sample" column to "Sample_Date".
- Saved the final file as "911102_v1_diatom_asvs_narragansett.csv".

NSF Award Abstract:
Photosynthetic marine microbes, phytoplankton, contribute half of global primary production, form the base of most aquatic food webs and are major players in global biogeochemical cycles. Understanding their community composition is important because it affects higher trophic levels, the cycling of energy and elements and is sensitive to global environmental change. This project will investigate how phytoplankton communities respond to two major global change stressors in aquatic systems: warming and changes in nutrient availability. The researchers will work in two marine systems with a long history of environmental monitoring, the temperate Narragansett Bay estuary in Rhode Island and a subtropical North Atlantic site near Bermuda. They will use field sampling and laboratory experiments with multiple species and varieties of phytoplankton to assess the diversity in their responses to different temperatures under high and low nutrient concentrations. If the diversity of responses is high within species, then that species may have a better chance to adapt to rising temperatures and persist in the future. Some species may already be able to grow at high temperatures; consequently, they may become more abundant as the ocean warms. The researchers will incorporate this response information in mathematical models to predict how phytoplankton assemblages would reorganize under future climate scenarios. Graduate students and postdoctoral associates will be trained in diverse scientific approaches and techniques such as shipboard sampling, laboratory experiments, genomic analyses and mathematical modeling. The results of the project will be incorporated into K-12 teaching, including an advanced placement environmental science class for underrepresented minorities in Los Angeles, data exercises for rural schools in Michigan and disseminated to the public through an environmental journalism institute based in Rhode Island.

Predicting how ecological communities will respond to a changing environment requires knowledge of genetic, phylogenetic and functional diversity within and across species. This project will investigate how the interaction of phylogenetic, genetic and functional diversity in thermal traits within and across a broad range of species determines the responses of marine phytoplankton communities to rising temperature and changing nutrient regimes. High genetic and functional diversity within a species may allow evolutionary adaptation of that species to warming. If the phylogenetic and functional diversity is higher across species, species sorting and ecological community reorganization is likely. Different marine sites may have a different balance of genetic and functional diversity within and across species and, thus, different contribution of evolutionary and ecological responses to changing climate. The research will be conducted at two long-term time series sites in the Atlantic Ocean, the Narragansett Bay Long-Term Plankton Time Series and the Bermuda Atlantic Time Series (BATS) station. The goal is to assess intra- and inter-specific genetic and functional diversity in thermal responses at contrasting nutrient concentrations for a representative range of species in communities at the two sites in different seasons, and use this information to parameterize eco-evolutionary models embedded into biogeochemical ocean models to predict responses of phytoplankton communities to projected rising temperatures under realistic nutrient conditions. Model predictions will be informed by and tested with field data, including the long-term data series available for both sites and in community temperature manipulation experiments. This project will provide novel information on existing intraspecific genetic and functional thermal diversity for many ecologically and biogeochemically important phytoplankton species, estimate generation of new genetic and functional diversity in evolution experiments, and develop and parameterize novel eco-evolutionary models interfaced with ocean biogeochemical models to predict future phytoplankton community structure. The project will also characterize the interaction of two major global change stressors, warming and changing nutrient concentrations, as they affect phytoplankton diversity at functional, genetic, and phylogenetic levels. In addition, the project will develop novel modeling methodology that will be broadly applicable to understanding how other types of complex ecological communities may adapt to a rapidly warming world.

Continuing Award OCE-2322676
Sep 2023 to Aug 2028 (estimated)
LTER: Scales of Variability in Ecosystem Dynamics and Production on the Changing Northeast U.S. Shelf (NES II)
NSF Award Abstract:

The Northeast U.S. Shelf (NES) is the region of the Northwest Atlantic Ocean that overlies the continental shelf from North Carolina to Maine. The NES has a long history of intense human utilization and provides an array of ecosystem services including shipping, recreation, conservation, and energy development. The NES also comprises a seasonally dynamic and productive ecosystem, supporting renowned fisheries, whose integrity is critical to the health of the Northeast U.S. economy. The NES ecosystem's productivity is fueled by planktonic organisms that interact with each other in complex food webs whose structure depends on environmental conditions (e.g., temperature, light, and nutrient levels). These conditions are rapidly changing because of climate-change-related warming and human utilization. For example, the NES is seeing the largest development of coastal wind farms in the U.S. to date. Phase II of the Northeast U.S. Shelf Long-Term Ecological Research program (NES-LTER II) advances our ability to predict how anthropogenic impacts will affect the dynamics of the shelf's planktonic food webs and their ability to support the productivity of higher trophic levels, from fish to whales and humans. Because the NES is subject to long-term challenges that will impact many people, the project emphasizes an active education component for helping to train the next generation of marine scientists and outreach activities to increase public understanding of marine science and technology. The project team conducts education and outreach via three main components: (1) training and mentoring for early career researchers from undergraduates to postdoctoral researchers in LTER research; (2) an LTER Schoolyard program that engages middle and high school teachers and students; and (3) public outreach through targeted events, the project website, and social media channels.

Patterns of ecosystem change over seasons to decades have been documented in the NES, but the key mechanisms linking changes in the physical environment, planktonic food webs, and higher trophic levels remain poorly understood. As a result, predictive capability is limited and management strategies are largely reactive. To address these needs, NES II is targeting a mechanistic understanding of how food web structure and function responds to environmental conditions, natural variability and human induced changes. NES II combines observations that provide regional-scale context, process cruises along a high gradient cross-shelf transect, high-frequency time series at an inner-shelf location, coupled biological-physical food web models, and targeted population models. In addition, the research team is investigating how community structure and trophic transfer are impacted by disturbances including (i) the increasing prevalence of heat waves, (ii) intrusions of offshore water associated with increasing instability in the Gulf Stream, and (iii) offshore wind farms now under construction on the NES. The long-term research plan is guided by the overarching science question: "How is climate change impacting the pelagic NES ecosystem and, in particular, affecting the relationship between compositional (e.g., species diversity and size structure) and aggregate (e.g., rates of primary production, and transfer of energy to higher trophic levels) variability?" The investigators are assessing the extent to which the NES ecosystem possesses a biodiversity reservoir that is resilient to dramatic changes in the environment and that will allow the ecosystem to maintain overall productivity.
 

Prior Award
Sep 2017 to Feb 2024
LTER: Linking Pelagic Community Structure with Ecosystem Dynamics and Production Regimes on the Changing Northeast US Shelf
Summary information including abstract, PIs, and other award details are included in the Funding History PDF in the Files section below, or vist the NSF Award site to view the prior award: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1655686&HistoricalAwards=false

Additional Information:
The NES-LTER project includes collaboration with the National Marine Fisheries Service / Northeast Fisheries Science Center [NMFS/NEFSC] in particular for sharing data related to Project EcoMon Zooplankton https://www.bco-dmo.org/project/2106.

The Narragansett Bay Long-Term Plankton Time Series is one of the world’s longest-running plankton surveys. Beginning in 1957, weekly samples have been collected to assess the phytoplankton community and characterize the physical parameters of Narragansett Bay.

Samples are collected once per week -regardless of tidal stage- for temperature, salinity, turbidity, size-fractionated chlorophyll a and nutrients. Microplankton community composition (size range >10μm, both species identification and abundance) is determined using a light microscope to quantify live samples. The species list for the >10μm size fraction includes 246 different species or species complexes of protists. Samples are also collected for the determination of copepod and ctenophore concentrations.

Funding for the time series has come from the University of Rhode Island since 1999. Ship time is frequently provided by the U.S. Department of Fish and Wildlife.

This Time Series is related to the following projects at BCO-DMO:

• Connecting local, regional and global scales of gene flow in planktonic marine diatoms (https://www.bco-dmo.org/project/511708)
• Dimensions: Collaborative Research: Genetic, functional and phylogenetic diversity determines marine phytoplankton community responses to changing temperature and nutrients (https://www.bco-dmo.org/project/712787)
• LTER: Linking Pelagic Community Structure with Ecosystem Dynamics and Production Regimes on the Changing Northeast US Shelf (https://www.bco-dmo.org/project/747769)
• Quantifying Temperature Dependence In Growth & Grazing Rates of Planktonic Herbivores (https://www.bco-dmo.org/project/739232)
• RII Track-1: Rhode Island Consortium for Coastal Ecology Assessment, Innovation, and Modeling (https://www.bco-dmo.org/project/836631)

(adapted from the NSF Synopsis of Program)
Dimensions of Biodiversity is a program solicitation from the NSF Directorate for Biological Sciences. FY 2010 was year one of the program.  [MORE from NSF]

The NSF Dimensions of Biodiversity program seeks to characterize biodiversity on Earth by using integrative, innovative approaches to fill rapidly the most substantial gaps in our understanding. The program will take a broad view of biodiversity, and in its initial phase will focus on the integration of genetic, taxonomic, and functional dimensions of biodiversity. Project investigators are encouraged to integrate these three dimensions to understand the interactions and feedbacks among them. While this focus complements several core NSF programs, it differs by requiring that multiple dimensions of biodiversity be addressed simultaneously, to understand the roles of biodiversity in critical ecological and evolutionary processes.

adapted from http://www.lternet.edu/

The National Science Foundation established the LTER program in 1980 to support research on long-term ecological phenomena in the United States. The Long Term Ecological Research (LTER) Network is a collaborative effort involving more than 1800 scientists and students investigating ecological processes over long temporal and broad spatial scales. The LTER Network promotes synthesis and comparative research across sites and ecosystems and among other related national and international research programs. The LTER research sites represent diverse ecosystems with emphasis on different research themes, and cross-site communication, network publications, and research-planning activities are coordinated through the LTER Network Office.

2017 LTER research site map obtained from https://lternet.edu/site/lter-network/