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Modeling iron limitation of primary production in the coastal Gulf of Alaska
Institution:1. Center for Coastal Physical Oceanography, Old Dominion University, Norfolk, VA 23529, USA;2. Woods Hole Oceanographic Institution, Woods Hole, MA02543, USA;3. Department of Ocean, Earth, and Atmospheric Sciences, Old Dominion University, Norfolk, VA 23529, USA;1. Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, MA 02137, USA;2. Ocean Sciences Department, University of California, 1156 High Street, Santa Cruz, CA 96064, USA
Abstract:A lower trophic level NPZD ecosystem model with explicit iron limitation on nutrient uptake is coupled to a three-dimensional coastal ocean circulation model to investigate the regional ecosystem dynamics of the northwestern coastal Gulf of Alaska (CGOA). Iron limitation is included in the NPZD model by adding governing equations for two micro-nutrient compartments: dissolved iron and phytoplankton-associated iron. The model has separate budgets for nitrate (the limiting macro-nutrient in the standard NPZD model) and for iron, with iron limitation on nitrate uptake being imposed as a function of the local phytoplankton realized Fe:C ratio. While the ecosystem model represents a simple approximation of the complex lower trophic level ecosystem of the northwestern CGOA, simulated chlorophyll concentrations reproduce the main characteristics of the spring bloom, high shelf primary production, and “high-nutrient, low-chlorophyll” (HNLC) environment offshore. Over the 1998–2004 period, model-data correlations based on spatially averaged, monthly mean chlorophyll concentrations are on average 0.7, with values as high as 0.9 and as low as 0.5 for individual years. The model also provides insight on the importance of micro- and macro-nutrient limitation on the shelf and offshore, with the shelfbreak region acting as a transition zone where both nitrate and iron availability significantly impact phytoplankton growth. Overall, the relative simplicity of the ecosystem model provides a useful platform to perform long-term simulations to investigate the seasonal and interannual CGOA ecosystem variability, as well as to conduct sensitivity studies to evaluate the robustness of simulated fields to ecosystem model parameterization and forcing. The ability of the model to differentiate between nitrate-limited, and iron-limited growth conditions, and to identify their spatial and temporal occurrences, is also a first step towards understanding the role of environmental gradients in shaping the complex CGOA phytoplankton community structure.
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