YANG Rongjuan, LIU Ronggao, LIU Yang, CHEN Jingming, XU Mingzhu, HE Jiaying, 2025. Light Use Efficiency Model Based on Chlorophyll Content Better Captures Seasonal Gross Primary Production Dynamics of Deciduous Broadleaf Forests. Chinese Geographical Science, 35(1): 55−72. DOI: 10.1007/s11769-024-1482-1
Citation: YANG Rongjuan, LIU Ronggao, LIU Yang, CHEN Jingming, XU Mingzhu, HE Jiaying, 2025. Light Use Efficiency Model Based on Chlorophyll Content Better Captures Seasonal Gross Primary Production Dynamics of Deciduous Broadleaf Forests. Chinese Geographical Science, 35(1): 55−72. DOI: 10.1007/s11769-024-1482-1

Light Use Efficiency Model Based on Chlorophyll Content Better Captures Seasonal Gross Primary Production Dynamics of Deciduous Broadleaf Forests

  • Gross primary production (GPP) is a crucial indicator representing the absorption of atmospheric CO2 by vegetation. At present, the estimation of GPP by remote sensing is mainly based on leaf-related vegetation indexes and leaf-related biophysical parameter leaf area index (LAI), which are not completely synchronized in seasonality with GPP. In this study, we proposed chlorophyll content-based light use efficiency model (CC-LUE) to improve GPP estimates, as chlorophyll is the direct site of photosynthesis, and only the light absorbed by chlorophyll is used in the photosynthetic process. The CC-LUE model is constructed by establishing a linear correlation between satellite-derived canopy chlorophyll content (Chlcanopy) and FPAR. This method was calibrated and validated utilizing 7-d averaged in-situ GPP data from 14 eddy covariance flux towers covering deciduous broadleaf forest ecosystems across five different climate zones. Results showed a relatively robust seasonal consistency between Chlcanopy with GPP in deciduous broadleaf forests under different climatic conditions. The CC-LUE model explained 88% of the in-situ GPP seasonality for all validation site-year and 56.0% of in-situ GPP variations through the growing season, outperforming the three widely used LUE models (MODIS-GPP algorithm, Vegetation Photosynthesis Model (VPM), and the eddy covariance-light use efficiency model (EC-LUE)). Additionally, the CC-LUE model (RMSE = 0.50 g C/(m2·d)) significantly improved the underestimation of GPP during the growing season in semi-arid region, remarkably decreasing the root mean square error of averaged growing season GPP simulation and in-situ GPP by 75.4%, 73.4%, and 37.5%, compared with MOD17 (RMSE = 2.03 g C/(m2·d)), VPM (RMSE = 1.88 g C/(m2·d)), and EC-LUE (RMSE = 0.80 g C/(m2·d)) model. The chlorophyll-based method proved superior in capturing the seasonal variations of GPP in forest ecosystems, thereby providing the possibility of a more precise depiction of forest seasonal carbon uptake.
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