## 5 Conclusions  
In this study, we used the Copula functions to construct a CDHI for rubber plantations on Hainan Island and assessed the probability of GPP loss under compound drought and heatwave scenarios. The results showed that the negative correlation between SPEI-3 and STI-1 was the strongest. The constructed CDHI accurately identified severe CDHEs in rubber plantations on Hainan Island in 2001, 2003-2005, 2010, 2015-2016, and 2020. Temporally, in April and May, as CDHEs intensified, the probability of GPP loss in rubber plantations increased significantly, while the opposite was true from June to November. Spatially, the probability of GPP loss in rubber plantations in northwestern Hainan Island was significantly higher than in other regions. These results provide a scientific basis for assessing the adaptation mechanisms of tropical forests under climate change.  
**Supplementary Materials:** The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/f16071146/s1](https://www.mdpi.com/article/10.3390/f16071146/s1)]([https://www.mdpi.com/article/10.3390/f16071146/s1](https://www.mdpi.com/article/10.3390/f16071146/s1)), Figure S1: Spatial distribution of the significance of the correlation between SPEI-3 and STI-1 in rubber plantations on Hainan Island: (a) Pearson correlation; (b) Spearman correlation; Figure S2: The occurrence probability percentage of CDHEs of different intensities in different months. No: No compound drought and heatwave. MCDH: Mild compound drought and heatwave. ModCDH: Moderate compound drought and heatwave. SCDH: Severe compound drought and heatwave. ECDH: Extreme compound drought and heatwave; Figure S3: The variation in precipitation and maximum temperature from April to November in the rubber plantations of Hainan Island; Figure S4: Probability of GPP loss in rubber plantations from April to November under mild, moderate, severe, and extreme compound drought and heatwave scenarios.  
**Author Contributions:** Conceptualization, Q.B. and Z.S.; methodology, Q.B.; software, Q.B.; validation, Q.B. and Z.W.; formal analysis, Q.B.; data curation, Q.B. and Z.S.; writing--original draft preparation, Q.B.; writing--review and editing, Z.S.; visualization, Q.B.; supervision, Z.S.; project administration, Z.S.; funding acquisition, Z.S. All authors have read and agreed to the published version of the manuscript.  
**Funding:** This study was funded by the National Key Research and Development Program of China (Grant No. 2021 YFD2200404), the Hainan Province Science and Technology Innovation Talent Platform Project (Grant No. NHXKCXM202303), the National Natural Science Foundation of China (Grant No. 32160320), Supported by Hainan Province Science and Technology Special Fund (Grant No. ZDYF2024 SHF2078) and the Sanya Science and Technology Special Fund (2022 KJCX04).  
**Institutional Review Board Statement:** Not applicable.  
**Informed Consent Statement:** Not applicable.  
**Data Availability Statement:** The dataset of natural rubber plantation distribution changes on Hainan Island was acquired from China Scientific Data ([[http://csdata.org/](http://csdata.org/)]([http://csdata.org/](http://csdata.org/)) (accessed on 5 May 2025)), the environmental data are available from the NESSDC ([[http://www.geodata.cn](http://www.geodata.cn)]([http://www.geodata.cn](http://www.geodata.cn)) (accessed on 5 May 2025)), and the GPP data were obtained from NASA ([[https://lpdaac.usgs.gov](https://lpdaac.usgs.gov)]([https://lpdaac.usgs.gov](https://lpdaac.usgs.gov)) (accessed on 5 May 2025)).  
**Acknowledgments:** The authors would like to thank China Scientific Data, the National Earth System Science Data Center, and the National Aeronautics and Space Administration for providing valuable data. We also express our gratitude to the respected editor and anonymous reviewers for their valuable comments and suggestions, which will further improve the quality of this study.  
**Conflicts of Interest:** The authors declare no conflicts of interest.