## 5 Conclusions  
This study developed a robust model to predict the GPP using flux observations of GPP from rubber plantations at four different locations in China and Thailand, along with corresponding remote sensing indices. The model reconstructed the GPP time series from 2001 to 2020 for these four sites and assessed the impact of drought on the GPP of rubber plantation ecosystems.  
The results indicate that the GPP prediction model developed using remote sensing indices such as SIF, EVI, NDVI, NIRv, and PAR exhibits high accuracy and robustness. Among these indices, solar-induced chlorophyll fluorescence (SIF) is the most effective indicator for predicting vegetation GPP. Indices like NDVI, EVI, and PAR still provide additional information and can effectively complement SIF in monitoring vegetation growth conditions.  
Drought affects the GPP of rubber plantations, but the extent of the impact varies by region and season. In the rubber plantation areas of northern China and Thailand, both short-term (3 months) and long-term (12 months) droughs during the cool dry and warm dry seasons lead to reductions in GPP, with declines ranging from 4% to 29%. In addition, the decrease in GPP caused by drought may be compensated for by variations in other factors. During the rainy season with abundant precipitation across the four regions, and in the cool dry season with sufficient rainfall in southern Thailand (SR site), mild droughs have minimal impact on GPP, and may even lead to a slight increase in GPP due to enhanced photosynthetically active radiation.  
This study integrated multiple remote sensing indices into a mixed-effects model for GPP prediction, advancing the methods for assessing vegetation productivity. The analysis of GPP yield sequences derived from satellite remote sensing addresses the relationship between drought conditions and GPP in rubber plantations, overcoming the limitations of sparse flux observation sites and observation periods that cannot capture drought processes.  
Despite its advantages, this study has some limitations. The use of eight-day composite data for GPP and remote sensing index analysis may overlook subtle temporal variations in photosynthetic activity and drought impacts. Future research incorporating higher temporal and spatial resolution data could enhance understanding of short-term variations in GPP and drought impacts. Including additional environmental factors such as soil moisture, nutrient availability, and detailed climate variables could refine the prediction model and reduce uncertainty.  
W.L. and S.L.: Conceptualization, Funding acquisition, and Writing--review and editing. M.H.: Writing--original draft, Writing--review and editing, and Methodology. J.Z., H.Z., X.C., R.B., R.L. and W.H.: Data curation, Formal analysis, Methodology, and Visualization. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This research was funded by the National Natural Science Foundation of China Joint Foundation Program (U21A6001); National Key R&D Program of China (2022 YFD2301201); Natural Science Foundation of Hainan province (Grant No. 421 MS101); and Scientific Research Projects of Academication Innovation Platform in Hainan Province.  
**Data Availability Statement:** Data is contained within the article.  
**Conflicts of Interest:** The authors declare no conflicts of interest.