Photosynthesis, transpiration, and primary productivity: Scaling up from leaves to canopies and regions using process models and remotely sensed data

Abstract

Biophysical and physiological processes in plants and ecosystems occur over a wide range of spatial and temporal scales. Our knowledge (or models) of these processes is largely at small scales. It is, however, difficult to directly apply mechanistic process‐oriented models over large scales due to heterogeneities in the distributions of processes, and nonlinearities in the functional responses of processes to environmental variables. On the other hand, simple parametric/empirical models in which system complexity is lumped into a small number of parameters have been widely employed to describe processes at larger scales. The variation of these parameters in these simple parametric/empirical models depends on the underlying biophysical processes. In this work, we showed that detailed process models and simple parametric models for primary production and transpiration could be effectively combined to scale leaf photosynthesis and transpiration up to large spatial scales. The integrated process model, General Energy Mass Transfer Model (GEMTM), was used to identify major factors contributing to the variability of the parameters in the parametric models for regional transpiration and primary production and quantify their responses to these factors. Simulations with the GEMTM showed that net carbon assimilation was proportional to intercepted photosynthetically active radiation (IPAR), but the radiation use efficiency (RUE) changed with leaf N concentration, temperature, and atmospheric CO2 concentration; transpiration was linearly correlated with the product of net primary production (NPP) and atmospheric water vapor pressure deficit (VPD), and the slope varied with leaf N concentration. RUE increased with leaf N content asymptotically, and responded to temperature in an asymmetric bell shape pattern with a 22°C and 26°C optimal temperature under current ambient and doubled CO2 concentration, respectively. A simple parametric NPP model and a regional transpiration model (Tr model) were developed from the relationships and parameter values obtained using the GEMTM. The NPP model reasonably simulated the seasonal and interannual variations of accumulated NPP estimated from field data. Simulated regional distribution of NPP over the Central Grassland Region of the United States was consistent with estimates obtained using other models. NPP increased from 120 gC/m2/year in the northwest to 956 gC/m2/year in the southeast. Simulated regional transpiration had a similar spatial distribution pattern as NPP, ranging from about 16 cmH2O/year to 136 cmH2O/year. The transpiration model introduced in this study provides a mechanism to explicitly couple transpiration and NPP in large‐scale analyses, although more complete analysis and validation are required.