2 resultados para concentration quenching model

em DigitalCommons - The University of Maine Research


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Ocean observing systems and satellites routinely collect a wealth of information on physical conditions in the ocean. With few exceptions, such as chlorophyll concentrations, information on biological properties is harder to measure autonomously. Here, we present a system to produce estimates of the distribution and abundance of the copepod Calanus finmarchicus in the Gulf of Maine. Our system uses satellite-based measurements of sea surface temperature and chlorophyll concentration to determine the developmental and reproductive rates of C. finmarchicus. The rate information then drives a population dynamics model of C. finmarchicus that is embedded in a 2-dimensional circulation field. The first generation of this system produces realistic information on interannual variability in C. finmarchicus distribution and abundance during the winter and spring. The model can also be used to identify key drivers of interannual variability in C. finmarchicus. Experiments with the model suggest that changes in initial conditions are overwhelmed by variability in growth rates after approximately 50 d. Temperature has the largest effect on growth rate. Elevated chlorophyll during the late winter can lead to increased C. finmarchicus abundance during the spring, but the effect of variations in chlorophyll concentrations is secondary to the other inputs. Our system could be used to provide real-time estimates or even forecasts of C. finmarchicus distribution. These estimates could then be used to support management of copepod predators such as herring and right whales.

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SeaWiFS (Sea-viewing Wide Field-of-view Sensor) chlorophyll data revealed strong interannual variability in fall phytoplankton dynamics in the Gulf of Maine, with 3 general features in any one year: (1) rapid chlorophyll increases in response to storm events in fall; (2) gradual chlorophyll increases in response to seasonal wind-and cooling-induced mixing that gradually deepens the mixed layer; and (3) the absence of any observable fall bloom. We applied a mixed-layer box model and a 1-dimensional physical-biological numerical model to examine the influence of physical forcing (surface wind, heat flux, and freshening) on the mixed-layer dynamics and its impact on the entrainment of deep-water nutrients and thus on the appearance of fall bloom. The model results suggest that during early fall, the surface mixed-layer depth is controlled by both wind-and cooling-induced mixing. Strong interannual variability in mixed-layer depth has a direct impact on short-and long-term vertical nutrient fluxes and thus the fall bloom. Phytoplankton concentrations over time are sensitive to initial pre-bloom profiles of nutrients. The strength of the initial stratification can affect the modeled phytoplankton concentration, while the timing of intermittent freshening events is related to the significant interannual variability of fall blooms.