Abstract
AbstractLight‐use efficiency (LUE) is at the core of mechanistic modeling of global gross primary production (GPP). However, most LUE estimates in global models are satellite based and coarsely measured with emphasis on environmental variables. Others are from eddy covariance towers with much greater spatial and temporal data quality and emphasis on mechanistic processes, but in a limited number of sites. In this study, we conducted a comprehensive global study of tower‐based LUE from 237 FLUXNET towers, and scaled up LUEs from in situ tower level to global biome level. We integrated the tower‐based LUE estimates with key environmental and biological variables at 0.5° × 0.5° grid‐cell resolutions, using a random forest regression (RFR) approach. Then, we developed a RFR‐LUE‐GPP model using the grid‐cell LUE data. In order to calibrate the LUE model, we developed a data‐driven RFR‐GPP model using RFR method only. Our results showed LUE varies largely with latitude. We estimated a global area‐weighted average of LUE at 1.23 ± 0.03 g C·m−2·MJ−1 APAR, which led to an estimate of global GPP of 107.5 ± 2.5 Gt C/yr from 2001 to 2005. Large uncertainties existed in GPP estimations over sparsely vegetated areas covered by savannas and woody savannas at middle to low latitude (i.e., 20° S–40° S and 5° N–40° N) due to the lack of available data. Model results were improved by incorporating Köppen climate types to represent climate/meteorological information in machine‐learning modeling. This brought a new understanding to the recognized problem of climate dependence of spring onset of photosynthesis and the challenges in accurately modeling the biome GPP of evergreen broadleaf forests (EBF). The divergent responses of GPP to temperature and precipitation at middle to high latitudes and at middle to low latitudes echo the necessity of modeling GPP separately by latitudes.
Highlights
The terrestrial biosphere is a photosynthetic engine that converts sunlight into biochemical energy that can be later released to sustain living organisms
In central Africa around the Democratic Republic of Congo (Ko€ppen Af), where areas are covered by evergreen broadleaf forests (EBF), Light-use efficiency (LUE) values remained high for the entire year
The effects of biome types, seasonality, and their interaction on LUE are highly significant for modeling global gross primary production (GPP)
Summary
The terrestrial biosphere is a photosynthetic engine that converts sunlight into biochemical energy that can be later released to sustain living organisms. The working efficiency of the photosynthetic engine (i.e., light-use efficiency, LUE) can be affected by changes in climate including temperature, water availability, and atmospheric CO2 concentration. At a single leaf level, enzyme kinetic photosynthesis models, such as Farquhar-von Caemmerer-Berry model (Farquhar et al 1980), provide a quantitative base for understanding how photosynthetic processes are regulated by biotic and abiotic factors, such as atmospheric CO2 level, water availability, nutrient supply, temperature, and other factors. LUE models ignore these biochemical details and GPP is calculated as a product of the fraction of PAR being absorbed by the plant canopy (fPAR) and the LUE (e)
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