Table of Contents

• Coverage
• Dataset Description
  • Methods & Sampling
  • Data Processing Description
• Data Files
• Supplemental Files
• Related Publications
• Related Datasets
• Parameters
• Project Information
• Program Information
• Funding

Phytoplankton thermal traits were estimated for diatoms (n=135), dinoflagellates (n=46), coccolithophores (n=30), and cyanobacteria (n=32). This dataset contains estimated traits and parameters presented in Thomas et al (2012) as well as those for 59 additional strains (Anderson et al, in review). Study selection followed the criteria outlined in Thomas et al (2012) and Anderson et al (in review).

Thermal reaction norms were used to describe phytoplankton thermal responses following the equation presented in Thomas et al. (2012). For strains compiled previously, parameters for thermal reaction norms were provided (Thomas et al 2012 & 2016). For added strains, parameters were estimated using the thermal growth rates found in the related dataset, https://www.bco-dmo.org/dataset/839696, and the maximum likelihood approach described in Thomas et al. (2012) and the bbmle package in R 3.6.1 (2019).

Traits were then estimated for each strain using their respective thermal reaction norms, as outlined previously (Thomas et al. 2012 & 2016; Anderson and Rynearson, 2020). This included the thermal optima (Topt), thermal maxima (Tmax) and thermal niche width. The thermal maxima were quality controlled according to Thomas et al. (2016) to ensure validity.

BCO-DMO Processing:
- replaced "NA" with "nd" as missing data value;
- renamed fields (replaced periods with underscores);
- removed commas from "study" and "source" columns;
- replaced commas with semi-colons in the "name", "strain", and "clone" columns;
- replaced comments with codes due to length and generated file "derived_traits_comment_codes.csv";
- replaced/removed un-renderable characters from the "source" column.

Definitions/descriptions for "comment_code" columns:
Note 1 = Latitude approximate. Based on information from Jacques (1983), Fiala & Oriol (1984), & Fiala & Oriol (1990), there are 5 possible isolation locations, all along the same longitude: 48S, 54S, 58S, 60S, and 65S. In the absence of further information from the authors, I have used the median location.

Note 2= Growth rates estimated from nonlinear fitting. One value presented was measured in previous study.

Note 3 = location approximate

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.

(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.