## 5 Conclusions  
This study focuses on the Yangtze River Basin and investigates the responses of terrestrial GPP to extreme compound heatwave and drought events of varying intensities. Using two independent GPP products and EVI data, we found that during the strongest extreme compound heatwave and drought event in 2022, GPP exhibited the largest decrease in magnitude and the widest spatial extent. During the less intense events in 2003 and 2013, the magnitude and extent of GPP reduction were significantly smaller than those in 2022. Notably, in 2013, the overall GPP even showed a slight increase. Our study also revealed significant differences in GPP responses across regions dominated by different vegetation types. During the most intense event of 2022, GPP reductions were most pronounced in shrub-dominated areas, followed by evergreen forests, while deciduous forests and mixed forests experienced relatively smaller decreases. However, during the weaker events of 2003 and 2013, these differences among vegetation types were less pronounced, with responses across vegetation types being more similar. These different responses of GPP in the whole Yangtze River Basin indicate that terrestrial ecosystems possess a certain degree of adaptability to mild and moderate extreme climate events. However, when the intensity of such events surpasses a certain threshold, this adaptability diminishes, highlighting the existence of a resilience tipping point in ecosystems. Our reported differences in the responses among vegetation types further enhance our understanding of the adaptive mechanisms of various vegetation types and help to identify vulnerable areas within ecosystems that are prone to disturbance. This enhancement provides an important scientific basis for developing more targeted ecological protection strategies and improving ecosystem resilience. This study emphasizes the variability in the responses of photosynthesis in the Yangtze River Basin's terrestrial ecosystems to extreme compound heatwave and drought events. These findings are of great significance for advancing the understanding of vegetation-climate coupling and for optimizing related vegetation and carbon cycle models. Methodology, [PERSON]; Formal analysis, [PERSON]; Data curation, [PERSON]; Writing--original draft, [PERSON]; Writing--review & editing, [PERSON]; Supervision, [PERSON]; Funding acquisition, [PERSON] All authors have read and agreed to the published version of the manuscript. **Funding:** This work was supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB0500303), the Youth Innovation Promotion Association of the Chinese Academy of Sciences (2022076), and the National large Scientific and Technological Infrastructure \"Earth System Numerical Simulation Facility\". **Data Availability Statement:** Data available in a publicly accessible repository (accessed on 12 June 2024): ERA5 is openly available in [[https://cds.climate.copernicus.eu](https://cds.climate.copernicus.eu)]([https://cds.climate.copernicus.eu](https://cds.climate.copernicus.eu)) [40]; GOSIF GPP is in [[http://data.globalecology.unh.edu/data/GOSIF-GPP_v2/](http://data.globalecology.unh.edu/data/GOSIF-GPP_v2/)]([http://data.globalecology.unh.edu/data/GOSIF-GPP_v2/](http://data.globalecology.unh.edu/data/GOSIF-GPP_v2/)) [41]; FluxSat GPP is in [[https://avdc.gsfc.nasa.gov/pub/tmp/FluxSat_GPP/](https://avdc.gsfc.nasa.gov/pub/tmp/FluxSat_GPP/)]([https://avdc.gsfc.nasa.gov/pub/tmp/FluxSat_GPP/](https://avdc.gsfc.nasa.gov/pub/tmp/FluxSat_GPP/)) [43]; MODIS fractional coverage of land plants is in [[https://modis.gsfc.nasa.gov/data/dataprod/mod12.php](https://modis.gsfc.nasa.gov/data/dataprod/mod12.php)]([https://modis.gsfc.nasa.gov/data/dataprod/mod12.php](https://modis.gsfc.nasa.gov/data/dataprod/mod12.php)) [44]; MODIS EVI is in [[https://modis.gsfc.nasa.gov/data/dataprod/mod13.php](https://modis.gsfc.nasa.gov/data/dataprod/mod13.php)]([https://modis.gsfc.nasa.gov/data/dataprod/mod13.php](https://modis.gsfc.nasa.gov/data/dataprod/mod13.php)) [45].