Contributors | Affiliation | Role |
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Rynearson, Tatiana A. | University of Rhode Island (URI-GSO) | Principal Investigator |
Anderson, Stephanie I. | University of Rhode Island (URI-GSO) | Contact |
Rauch, Shannon | Woods Hole Oceanographic Institution (WHOI BCO-DMO) | BCO-DMO Data Manager |
Metrics for thermal capacity were calculated for phytoplankton strains of known origin (coccolithophores = 24, cyanobacteria = 31, diatoms = 115, dinoflagellates = 38). Trait values (derived_traits.csv) were used to compute the TSM (Topt – Thabitat) and the WT (Tmax-Thabitat). Additionally, we defined a new metric termed the distance to the growth equivalence (DGE), which describes the distance (ºC) to the temperature at which growth is equivalent to that at the organism’s mean habitat temperature (Tµequiv – Thabitat), but on the opposite side of the reaction norm.
To estimate past and future habitat temperatures for each phytoplankton strain, we utilized an ensemble mean of modeled sea surface temperature (SST) projections from the Coupled Model Intercomparison Project phase 5 (CMIP5), available at a 1.25° resolution, and presented in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (Collins et al., 2013). This data was extracted from the Royal Netherlands Meteorological Institute Climate Explorer portal (http://climexp.knmi.nl). Projections for sea surface temperature (SST) warming were calculated between a baseline (1950-1970) and future (2080-2100) time period under Representative Concentration Pathway RCP8.5.
All analyses were conducted in R 3.6.1 (2019).
Complete information on each isolate and their thermal traits can be found in related dataset, https://www.bco-dmo.org/dataset/839689.
BCO-DMO Processing:
- renamed fields (replaced periods with underscores).
File |
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thermal_capacity.csv (Comma Separated Values (.csv), 17.50 KB) MD5:247e3df1dfa1b70265243cbe699f3ab8 Primary data file for dataset ID 839713 |
Parameter | Description | Units |
isolate_code | Unique isolate ID adpated from Thomas et al. (2012). Full isolate information contained in related dataset https://www.bco-dmo.org/dataset/839689 | unitless |
isolation_longitude | longitude of isolation location | degrees East (0 to 360) |
isolation_latitude | latitude of isolation location | degrees North |
Thab_past | Modeled habitat temperature for strain's isolation location over the 1950-1970 time period | degrees Celsius |
Thab_fut | Modeled habitat temperature for strain's isolation location over the 2080-2100 time period | degrees Celsius |
safety_margin | Thermal Safety Margin (Difference between thermal optimum and habitat temperature) | degrees Celsius |
warming_tolerance | Warming tolerence (Difference between thermal maximum and habitat temperature) | degrees Celsius |
growth_eq | The temperature at which growth is equivalent to that at the organism's mean habitat temperature, but on the opposite side of the thermal reaction norm | degrees Celsius |
DGE | Distance to the Growth Equivalence (DGE). Describes the distance (degrees C) to growth equivalence (Tuequiv – Thabitat) | degrees Celsius |
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.
Funding Source | Award |
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NSF Division of Ocean Sciences (NSF OCE) |