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Ecological Control of Subtropical Nutrient Concentrations
Jan 31st, 2010

Ecological Control of Subtropical Nutrient Concentrations

story by Helen Hill and Stephanie Dutkiewicz.

Figure 1: Multiple-Resource Experiment. (top) Emergent biogeographical provinces, defined by most dominant species, reminiscent of Longhurst (1995). (bottom) Biogeography of four major functional groups: (i) Diatom-analogs (red), (ii) other large phytoplankton (orange), (iii) <i>Prochlorococcus</i>-analogs (green), and (iv) other small phytoplankton (yellow-green).

Figure 1: Multiple-Resource Experiment. (top) Emergent biogeographical provinces, defined by most dominant species, reminiscent of Longhurst (1995). (bottom) Biogeography of four major functional groups: (i) Diatom-analogs (red), (ii) other large phytoplankton (orange), (iii)Prochlorococcus-analogs (green), and (iv) other small phytoplankton (yellow-green).

In this article we spotlight recent work by Darwin Project team members Stephanie Dutkiewicz, Mick Follows and Jason Bragg, who have been examining the utility of resource control theory to interpret the relationships between organisms and resources in a global coupled physical-biogeochemistry-ecosystem model built around MITgcm.

The team find that in regions of low seasonality, resource competition theory (Tilman, ‘77)  not only anticipates the competitive outcome amongst organisms but also provides a quantitative diagnostic of ecological control of nutrient concentrations. DFB’s sensitivity experiments clearly indicate control on the ambient nutrient by phytoplankton physiology as predicted by the theory. Read the rest of this entry »

Lake Modeling
Sep 20th, 2009

Modeling the Great Lakes

story by Helen Hill

 

This month we focus on the work of Galen McKinley and Val Bennington at the University of Wisconsin, Madison.

With a view to developing a quantitative understanding of the role such bodies of water may play in the terrestrial carbon cycle, Galen and Val have been using the MITgcm to put together a comprehensive,  up-to-date description of the general circulation and temporal variability of Lake Superior. Figure 1 shows the summer-time mean circulation from their model.

Figure 1. Summer-time, mean circulation. The plot shows depth integrated current (arrows) overlying column average water temperature (colored). Arrows illustrating vector flow are plotted every 5 grid-points.

Figure 1: Summer-time mean circulation from a simulation of Lake Superior using MITgcm.

Because of its large size (the lake is of order 500km long by 250km wide, with depths to 300 m) as well as difficulties associated with  fieldwork (particularly in winter), Lake Superior’s  general  circulation is rather poorly known. Believing the terrestrial ecosystem around the lake to be a substantial sink of CO2 from the atmosphere, but not knowing to what degree carbon is being transferred to the lake and fluxed back to the atmosphere, Bennington and McKinley set out to build a holistic model of the system; step one being to build an up-to-date general circulation model. Read the rest of this entry »

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