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  • 1
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    A phytoplankton model for the allocation of gross photosynthetic energy including the trade‐offs of diazotrophy (2018)
    John Wiley & Sons
    Details
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Biogeosciences 123 (2018): 1796-1816, doi:10.1029/2017JG004263.
    Description: Gross photosynthetic activity by phytoplankton is directed to linear and alternative electron pathways that generate ATP, reductant, and fix carbon. Ultimately less than half is directed to net growth. Here we present a phytoplankton cell allocation model that explicitly represents a number of cell metabolic processes and functional pools with the goal of evaluating ATP and reductant demands as a function of light, nitrate, iron, oxygen, and temperature for diazotrophic versus nondiazotrophic growth. We employ model analogues of Synechoccocus and Crocosphaera watsonii, to explore the trade‐offs of diazotrophy over a range of environmental conditions. Model analogues are identical in construction, except for an iron quota associated with nitrogenase, an additional respiratory demand to remove oxygen in order to protect nitrogenase and an additional ATP demand to split dinitrogen. We find that these changes explain observed differences in growth rate and iron limitation between diazotrophs and nondiazotrophs. Oxygen removal imparted a significantly larger metabolic cost to diazotrophs than ATP demand for fixing nitrogen. Results suggest that diazotrophs devote a much smaller fraction of gross photosynthetic energy to growth than nondiazotrophs. The phytoplankton cell allocation model model provides a predictive framework for how photosynthate allocation varies with environmental conditions in order to balance cellular demands for ATP and reductant across phytoplankton functional groups.
    Description: DOC | NOAA | Climate Program Office (CPO) Grant Number: NA100AR4310093; National Science Foundation (NSF) Grant Number: EF‐0424599; Center for Microbial Oceanography Research and Education (CMORE) Grant Number: NSF EF‐0424599; NOAA Global Carbon Program Grant Number: NA100AR4310093
    Description: 2018-11-01
    Keywords: Phytoplankton ; Diazotroph ; Photosynthesis ; Resource allocation ; Biogeochemistry
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 2
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    Skill metrics for confronting global upper ocean ecosystem-biogeochemistry models against field and remote sensing data (2009)
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    Publication Date: 2022-05-25
    Description: Author Posting. © Elsevier B.V., 2009. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Journal of Marine Systems 76 (2009): 95-112, doi:10.1016/j.jmarsys.2008.05.015.
    Description: We present a generalized framework for assessing the skill of global upper ocean ecosystem-biogeochemical models against in-situ field data and satellite observations. We illustrate the approach utilizing a multi-decade (1979-2004) hindcast experiment conducted with the Community Climate System Model (CCSM-3) ocean carbon model. The CCSM-3 ocean carbon model incorporates a multi-nutrient, multi-phytoplankton functional group ecosystem module coupled with a carbon, oxygen, nitrogen, phosphorus, silicon, and iron biogeochemistry module embedded in a global, threedimensional ocean general circulation model. The model is forced with physical climate forcing from atmospheric reanalysis and satellite data products and time-varying atmospheric dust deposition. Data-based skill metrics are used to evaluate the simulated time-mean spatial patterns, seasonal cycle amplitude and phase, and subannual to interannual variability. Evaluation data include: sea surface temperature and mixed layer depth; satellite derived surface ocean chlorophyll, primary productivity, phytoplankton growth rate and carbon biomass; large-scale climatologies of surface nutrients, pCO2, and air-sea CO2 and O2 flux; and time-series data from the Joint Global Ocean Flux Study (JGOFS). Where the data is sufficient, we construct quantitative skill metrics using: model-data residuals, time-space correlation, root mean square error, and Taylor diagrams.
    Description: This work was supported in part by grants from the NSF/ONR National Ocean Partnership Program (N000140210370), the NASA Ocean Biology and Biogeochemistry Program (NNX07AL80G), and the NSF Center for Microbial Oceanography Research and Education (C-MORE).
    Keywords: Marine ecology ; Biogeochemistry ; Modeling ; Evaluation ; Skill
    Repository Name: Woods Hole Open Access Server
    Type: Preprint
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  • 3
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    A decade of synthesis and modeling in the US Joint Global Ocean Flux Study (2006)
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    Publication Date: 2022-05-25
    Description: Author Posting. © The Authors, 2005. This is the author's version of the work. It is posted here by permission of Elsevier B.V. for personal use, not for redistribution. The definitive version was published in Deep Sea Research Part II: Topical Studies in Oceanography 53 (2006): 451-458, doi:10.1016/j.dsr2.2006.01.019.
    Description: A decade long Synthesis and Modeling Project (SMP) was conducted as the final element of the U.S. Joint Global Ocean Flux Study (JGOFS). The SMP goal was to synthesize knowledge gained from field studies into a set of models that reflect our current understanding of the oceanic carbon cycle. Specific, innovative aspects of the project included the close partnership among scientists conducting field, laboratory, remote sensing, and numerical research and the strong emphasis on data management and web-based, public release of models and data products. Several recurrent science themes arose across the SMP effort including: the development of a new generation of ocean ecosystem and biogeochemistry models that include iron limitation, flexible elemental composition, size structure, geochemical functional groups and particle composition; the application of inverse models and data assimilation techniques to marine food-web data; the creation of whole-ocean synthesis products from the JGOFS global CO2 survey and other studies; and the analysis and modeling of ecosystem and biogeochemical responses to climate and CO2 system perturbations on time-scales ranging from seasonal and interannual variability to anthropogenic climate warming and longer.
    Description: The U.S. JGOFS SMP management effort was supported by grants from the National Science Foundation (NSF/NCAR 97-142 and NSF OCE-0335589).
    Keywords: Marine ; Biogeochemistry ; Ecology ; Modeling
    Repository Name: Woods Hole Open Access Server
    Type: Preprint
    Format: 153847 bytes
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  • 4
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    Climate forcing for dynamics of dissolved inorganic nutrients at Palmer Station, Antarctica : an interdecadal (1993–2013) analysis (2016)
    John Wiley & Sons
    Details
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2016. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Biogeosciences 121 (2016): 2369–2389, doi:10.1002/2015JG003311.
    Description: We analyzed 20 years (1993–2013) of observations of dissolved inorganic macronutrients (nitrate, N; phosphate, P; and silicate, Si) and chlorophyll a (Chl) at Palmer Station, Antarctica (64.8°S, 64.1°W) to elucidate how large-scale climate and local physical forcing affect the interannual variability in the seasonal phytoplankton bloom and associated drawdown of nutrients. The leading modes of nutrients (N, P, and Si empirical orthogonal functions 1, EOF1) represent overall negative anomalies throughout growing seasons, showing a mixed signal of variability in the initial levels and drawdown thereafter (low-frequency dynamics). The second most common seasonal patterns of nitrate and phosphate (N and P EOF2) capture prolonged drawdown events during December–March, which are correlated to Chl EOF1. Si EOF2 captures a drawdown event during November–December, which is correlated to Chl EOF2. These different drawdown patterns are shaped by different sets of physical and climate forcing mechanisms. N and P drawdown events during December–March are influenced by the winter and spring Southern Annular Mode (SAM) phase, where nutrient utilization is enhanced in a stabilized upper water column as a consequence of SAM-driven winter sea ice and spring wind dynamics. Si drawdown during November–December is influenced by early sea ice retreat, where ice breakup may induce abrupt water column stratification and a subsequent diatom bloom or release of diatom cells from within the sea ice. Our findings underscore that seasonal nutrient dynamics in the coastal WAP are coupled to large-scale climate forcing and related physics, understanding of which may enable improved projections of biogeochemical responses to climate change.
    Description: U.S. National Science Foundation Grant Numbers: OPP-9011927, 9632763, 0217282, 0823101, GEO-PLR 1440435; NASA ROSES Grant Number: NNX14AL86G
    Description: 2017-03-17
    Keywords: Nutrient drawdown ; Phytoplankton bloom ; Climate variability ; Western Antarctic Peninsula ; Palmer LTER ; Biogeochemistry
    Repository Name: Woods Hole Open Access Server
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  • 5
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    Contributions of long-term research and time-series observations to marine ecology and biogeochemistry (2008)
    Details
    Publication Date: 2022-05-26
    Description: Author Posting. © The Author(s), 2009. This is the author's version of the work. It is posted here by permission of Annual Reviews for personal use, not for redistribution. The definitive version was published in Annual Review of Marine Science 1 (2009): 279-302, doi:10.1146/annurev.marine.010908.163801.
    Description: Time-series observations form a critical element of oceanography. New interdisciplinary efforts launched in the past two decades complement the few earlier, longer-running time series in building a better, though still poorly-resolved, picture of lower-frequency ocean variability, the climate processes driving it, and its implications for foodweb dynamics, carbon storage and climate feedbacks. Time-series also enlarge our understanding of ecological processes and are integral for improving models of physical-biogeochemical-ecological ocean dynamics. The major time-series observatories go well beyond simple monitoring of core ocean properties, although that important activity forms the critical center of all time-series efforts. Modern ocean time series have major process and experimental components, entrain ancillary programs and have integrated modeling programs for deriving better understanding of the observations and the changing, three-dimensional ocean in which the observatories are embedded.
    Description: HWD was supported by NSF grant OPP-0217282. SCD was supported by the Center for Microbial Oceanography Research and Education (C-MORE; NSF CCF-424599). DKS was supported by NSF grant OCE-0628444.
    Keywords: Climate change ; Biogeochemistry ; Plankton ecology ; Carbon cycle
    Repository Name: Woods Hole Open Access Server
    Type: Preprint
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