Vegetal Optimality and Macro-Scale Dynamic Vegetation – Scaling from Leaf to Landscape

Abstract:

Macro-scale spatially distributed hydrologic models require extensive parameterization of both soil and vegetal properties. Proper parameterization of vegetation is critical for understanding vegetal response to hydro-climatic variability, as vegetation provides a key feedback to climate. A common practice for Dynamic Global Vegetation Models is to use plant functional types (PFTs), which limit vegetation to discrete classes. We present a physically based long-term macro-scale coupled vegetation and hydrology model capable of responding dynamically to climate variability, and parameterize it assuming vegetal optimality hypotheses. We hypothesize that canopy scale vegetation will adopt a strategy that maximizes the expected net assimilation, minus photosynthetic system construction and maintenance costs, over an annual basis. We perform stochastic multi-decadal simulations to estimate the expected fitness for a unique vegetal parameterization and water use strategy. As a result, optimal parameter sets are defined, which can be used instead of a PFT characterization of land cover. Estimates of evaporation, transpiration and gross primary production obtained using the optimal parameter sets over a range of climates are then compared against FLUXNET data.