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  • 1
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    Comparing food web structures and dynamics across a suite of global marine ecosystem models (2015)
    Elsevier
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    Publication Date: 2022-05-25
    Description: © The Author(s), 2013. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Ecological Modelling 261-262 (2013): 43–57, doi:10.1016/j.ecolmodel.2013.04.006.
    Description: Dynamic Green Ocean Models (DGOMs) include different sets of Plankton Functional Types (PFTs) and equations, thus different interactions and food webs. Using four DGOMs (CCSM-BEC, PISCES, NEMURO and PlankTOM5) we explore how predator–prey interactions influence food web dynamics. Using each model's equations and biomass output, interaction strengths (direct and specific) were calculated and the role of zooplankton in modeled food webs examined. In CCSM-BEC the single size-class adaptive zooplankton preys on different phytoplankton groups according to prey availability and food preferences, resulting in a strong top-down control. In PISCES the micro- and meso-zooplankton groups compete for food resources, grazing phytoplankton depending on their availability in a mixture of bottom-up and top-down control. In NEMURO macrozooplankton controls the biomass of other zooplankton PFTs and defines the structure of the food web with a strong top-down control within the zooplankton. In PlankTOM5, competition and predation between micro- and meso-zooplankton along with strong preferences for nanophytoplankton and diatoms, respectively, leads to their mutual exclusion with a mixture of bottom-up and top-down control of the plankton community composition. In each model, the grazing pressure of the zooplankton PFTs and the way it is exerted on their preys may result in the food web dynamics and structure of the model to diverge from the one that was intended when designing the model. Our approach shows that the food web dynamics, in particular the strength of the predator–prey interactions, are driven by the choice of parameters and more specifically the food preferences. Consequently, our findings stress the importance of equation and parameter choice as they define interactions between PFTs and overall food web dynamics (competition, bottom-up or top-down effects). Also, the differences in the simulated food-webs between different models highlight the gap of knowledge for zooplankton rates and predator–prey interactions. In particular, concerted effort is needed to identify the key growth and loss parameters and interactions and quantify them with targeted laboratory experiments in order to bring our understanding of zooplankton at a similar level to phytoplankton.
    Description: This work was supported with funding from Palmer LTER (NSF OPP-0823101) and C-MORE (NSF EF-0424599).
    Keywords: Dynamic Green Ocean Model ; Plankton Functional Types ; Zooplankton ; Food web dynamic ; Predator–prey interactions
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 2
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    Challenges of modeling depth-integrated marine primary productivity over multiple decades : a case study at BATS and HOT (2010)
    American Geophysical Union
    Details
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2010. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 24 (2010): GB3020, doi:10.1029/2009GB003655.
    Description: The performance of 36 models (22 ocean color models and 14 biogeochemical ocean circulation models (BOGCMs)) that estimate depth-integrated marine net primary productivity (NPP) was assessed by comparing their output to in situ 14C data at the Bermuda Atlantic Time series Study (BATS) and the Hawaii Ocean Time series (HOT) over nearly two decades. Specifically, skill was assessed based on the models' ability to estimate the observed mean, variability, and trends of NPP. At both sites, more than 90% of the models underestimated mean NPP, with the average bias of the BOGCMs being nearly twice that of the ocean color models. However, the difference in overall skill between the best BOGCM and the best ocean color model at each site was not significant. Between 1989 and 2007, in situ NPP at BATS and HOT increased by an average of nearly 2% per year and was positively correlated to the North Pacific Gyre Oscillation index. The majority of ocean color models produced in situ NPP trends that were closer to the observed trends when chlorophyll-a was derived from high-performance liquid chromatography (HPLC), rather than fluorometric or SeaWiFS data. However, this was a function of time such that average trend magnitude was more accurately estimated over longer time periods. Among BOGCMs, only two individual models successfully produced an increasing NPP trend (one model at each site). We caution against the use of models to assess multiannual changes in NPP over short time periods. Ocean color model estimates of NPP trends could improve if more high quality HPLC chlorophyll-a time series were available.
    Description: This research was supported by a grant from the National Aeronautics and Space Agency Ocean Biology and Biogeochemistry program (NNG06GA03G).
    Keywords: Marine primary productivity models ; BATS HOT trends ; Multidecadal climate forcing
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
    Format: text/plain
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  • 3
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    Response of ocean ecosystems to climate warming (2010)
    American Geophysical Union
    Details
    Publication Date: 2022-05-26
    Description: Author Posting. © American Geophysical Union, 2004. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 18 (2004): GB3003, doi:10.1029/2003GB002134.
    Description: We examine six different coupled climate model simulations to determine the ocean biological response to climate warming between the beginning of the industrial revolution and 2050. We use vertical velocity, maximum winter mixed layer depth, and sea ice cover to define six biomes. Climate warming leads to a contraction of the highly productive marginal sea ice biome by 42% in the Northern Hemisphere and 17% in the Southern Hemisphere, and leads to an expansion of the low productivity permanently stratified subtropical gyre biome by 4.0% in the Northern Hemisphere and 9.4% in the Southern Hemisphere. In between these, the subpolar gyre biome expands by 16% in the Northern Hemisphere and 7% in the Southern Hemisphere, and the seasonally stratified subtropical gyre contracts by 11% in both hemispheres. The low-latitude (mostly coastal) upwelling biome area changes only modestly. Vertical stratification increases, which would be expected to decrease nutrient supply everywhere, but increase the growing season length in high latitudes. We use satellite ocean color and climatological observations to develop an empirical model for predicting chlorophyll from the physical properties of the global warming simulations. Four features stand out in the response to global warming: (1) a drop in chlorophyll in the North Pacific due primarily to retreat of the marginal sea ice biome, (2) a tendency toward an increase in chlorophyll in the North Atlantic due to a complex combination of factors, (3) an increase in chlorophyll in the Southern Ocean due primarily to the retreat of and changes at the northern boundary of the marginal sea ice zone, and (4) a tendency toward a decrease in chlorophyll adjacent to the Antarctic continent due primarily to freshening within the marginal sea ice zone. We use three different primary production algorithms to estimate the response of primary production to climate warming based on our estimated chlorophyll concentrations. The three algorithms give a global increase in primary production of 0.7% at the low end to 8.1% at the high end, with very large regional differences. The main cause of both the response to warming and the variation between algorithms is the temperature sensitivity of the primary production algorithms. We also show results for the period between the industrial revolution and 2050 and 2090.
    Description: J. L. Sarmiento and R. Slater were supported by the NOAA Office of Global Programs grant NA56GP0439 to the Carbon Modeling Consortium for model development and by NSF grant OCE00973166 for model and observational interpretations as part of the JGOFS Synthesis and Modeling Project. R. Barber was supported by NSF grant OCE 0136270 as part of the JGOFS Synthesis and Modeling Project. S. Doney and J. Kleypas wish to thank the Community Climate System Model science team and the Climate Simulation Laboratory at NCAR and acknowledge support from NOAA-OGP grant NOAA-NA96GP0360S. Spall is funded through the UK Department for Environment, Food and Rural Affairs contract PECD 7/12/37.
    Keywords: Climate warming ; Ocean biogeochemistry
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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