Key points are not available for this paper at this time.
Abstract The superimposed fluctuations of temperature, precipitation, and CO 2 concentration are crucial for the Alpine Vegetation Carbon Flux on the Qinghai-Tibet Plateau. This study updates the Lund-Potsdam-Jena Model (LPJ) with plant functional types native to alpine regions and assimilates the daily LAI remote sensing datasets. And, the influence of climate factors and CO 2 concentration on Alpine Vegetation carbon fluxes was simulated. Validation against field data shows the model accurately simulates daily GPP with R 2 of 0.8332 and 0.8608, RMSE of 1.96 and 1.485 for 2013–2014, respectively. For NEP, the RMSE are 1.15 and 1.19 for the same years. The research reveals the pronounced spatiotemporal variations of carbon fluxes were highly responsive to temperature changes. Precipitation shows a more consistent interannual variation relationship with carbon fluxes than temperature does. Notably, NPP/GPP increase only with concurrent rises in CO 2 and precipitation, highlighting the superimposed implications of climate-induced carbon flux changes in Alpine vegetation.
Dong et al. (Fri,) studied this question.