Integrating functional diversity, food web processes, and biogeochemical carbon fluxes into a conceptual approach for modeling the upper ocean in a high-CO2 world

Legendre, Louis and Rivkin, Richard B. (2005) Integrating functional diversity, food web processes, and biogeochemical carbon fluxes into a conceptual approach for modeling the upper ocean in a high-CO2 world. Journal of Geophysical Research, 110 (9). pp. 1-17. ISSN 2156-2202

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Abstract

Marine food webs influence climate by channeling carbon below the permanent pycnocline, where it can be sequestered. Because most of the organic matter exported from the euphotic zone is remineralized within the "upper ocean" (i.e., the water column above the depth of sequestration), the resulting CO2 would potentially return to the atmosphere on decadal timescales. Thus ocean-climate models must consider the cycling of carbon within and from the upper ocean down to the depth of sequestration, instead of only to the base of the euphotic zone. Climate-related changes in the upper ocean will influence the diversity and functioning of plankton functional types. In order to predict the interactions between the changing climate and the ocean's biology, relevant models must take into account the roles of functional biodiversity and pelagic ecosystem functioning in determining the biogeochemical fluxes of carbon. We propose the development of a class of models that consider the interactions, in the upper ocean, of functional types of plankton organisms (e.g., phytoplankton, heterotrophic bacteria, microzooplankton, large zooplankton, and microphagous macrozooplankton), food web processes that affect organic matter (e.g., synthesis, transformation, and remineralization), and biogeochemical carbon fluxes (e.g., photosynthesis, calcification, respiration, and deep transfer). Herein we develop a framework for this class of models, and we use it to make preliminary predictions for the upper ocean in a high-CO2 world, without and with iron fertilization. Finally, we suggest a general approach for implementing our proposed class of models.

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