TESTING FOR OPTIMAL LARGE-SCALE VEGETATION PROPERTIES FOR MAXIMUM TERRESTRIAL PRODUCTIVITY AND QUANTIFYING FUTURE UNCERTAINTY OF VEGETATION RESPONSE TO ANTICIPATED CLIMATE CHANGE
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In this study, I present a new approach to quantifying a range of uncertainty associated with the carbon-climate feedback over the period 1850 to 2100 within an earth system model of intermediate complexity. The degree to which terrestrial vegetation adaptively self-organizes to shape its own climatic conditions is still an open question. Nonetheless, one can simulate a 'best case' scenario, in which terrestrial productivity is periodically maximized with respect to several macroscopic vegetation parameters, commonly held constant in other models such as maximum stomatal conductance. The results of this 'dynamically optimized' simulation are compared to a simulation where the vegetation parameters are held static at the values optimized for pre-industrial conditions. With this comparison, the degree to which terrestrial productivity is underestimated when vegetation parameterizations remain static compared to those reflecting optimal adaptation to new conditions can be quantified.