Simulation and Prediction of Vegetation Carbon Flux under SSP Scenarios in Beijing
To reveal the dynamic characteristics of ecosystem carbon flux and its response to meteorological factors, this study employed the Biome-BGC model to simulate gross primary productivity (GPP) and net primary productivity (NPP) of vegetation in Beijing for historical (2001–2014) and future (2051–2070) periods under SSP126 and SSP585 scenarios, using multi-source data including regional meteorology, vegetation type, and soil texture. The Mann-Kendall (M-K) test and Empirical Orthogonal Function (EOF) analysis were applied to examine spatiotemporal patterns and carbon use efficiency (CUE). Results indicate that Biome-BGC accurately reproduces historical carbon flux characteristics. Temporally, annual mean GPP and NPP exhibited fluctuating upward trends, ranging from 584 to 777 g C m−2 a−1 and 238 to 388 g C m−2 a−1, respectively. Spatially, GPP and NPP displayed both same-phase and opposite-phase distribution patterns. Annual mean temperature was the dominant factor influencing GPP and NPP trends, followed by solar radiation and precipitation. Under future scenarios, both GPP and NPP are projected to increase, with SSP585 showing greater enhancement. By 2070, GPP is expected to rise by 171 and 376 g C m−2 a−1 under SSP126 and SSP585, respectively, while NPP increases by 71.8 and 137 g C m−2 a−1. The spatial distribution of GPP and NPP exhibits a 'low-center, high-periphery' pattern, with multi-year means of 969 and 425 g C m−2 a−1. Future CUE is approximately 0.45, indicating substantial carbon sequestration potential of Beijing's vegetation under climate change.