BIOME3: An equilibrium terrestrial biosphere model based on ecophysiological constraints, resource availability, and competition among plant functional types

Abstract

The equilibrium terrestrial biosphere model BIOME3 simulates vegetation distribution and biogeochemistry, and couples vegetation distribution directly to biogeochemistry. Model inputs consist of latitude, soil texture class, and monthly climate (temperature, precipitation, and sunshine) data on a 0.5° grid. Ecophysiological constraints determine which plant functional types (PFTs) may potentially occur. A coupled carbon and water flux model is then used to calculate, for each PFT, the leaf area index (LAI) that maximizes net primary production (NPP), subject to the constraint that NPP must be sufficient to maintain this LAI. Competition between PFTs is simulated by using the optimal NPP of each PFT as an index of competitiveness, with additional rules to approximate the dynamic equilibrium between natural disturbance and succession driven by light competition. Model output consists of a quantitative vegetation state description in terms of the dominant PFT, secondary PFTs present, and the total LAI and NPP for the ecosystem. Canopy conductance is treated as a function of the calculated optimal photosynthetic rate and water stress. Regional evapotranspiration is calculated as a function of canopy conductance, equilibrium evapotranspiration rate, and soil moisture using a simple planetary boundary layer parameterization. This scheme results in a two‐way coupling of the carbon and water fluxes through canopy conductance, allowing simulation of the response of photosynthesis, stomatal conductance, and leaf area to environmental factors including atmospheric CO 2 . Comparison with the mapped distribution of global vegetation shows that the model successfully reproduces the broad‐scale patterns in potential natural vegetation distribution. Comparison with NPP measurements, and with an FPAR (fractional absorbed photosynthetically active radiation) climatology based on remotely sensed greenness measurements, provides further checks on the model's internal logic. The model is envisaged as a tool for integrated analysis of the impacts of changes in climate and CO 2 on ecosystem structure and function.

Keywords

Affiliated Institutions

• Lund University SE

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