## 5 Conclusions  
In this study, we investigated the relationships between NDVI and GPP across different aridity gradients and various PFTs in China. By analyzing NDVI and GPP products, we found that the eastern regions of China had lower R\({}^{2}\) between NDVI and GPP compared to the western regions. In most regions of China, the mean R\({}^{2}\) of the inter-annual growing season NDVI-GPP relationship was quite low, indicating a weak dependency of GPP on NDVI. Overall, the relationship between NDVI-GPP decreased as AI increased in more humid regions. Among all PFTs, grasslands demonstrated the strongest relationship, with an R\({}^{2}\) of 0.20. Additionally, we observed that the insensitivity of the NDVI-GPP relationship increased as the AI gradient increased. As AI increased from 0 to 1, the slopes decreased from 0.12 to 0.01. Moreover, the IAV of GPP showed a steady decline, while the IAV of NDVI exhibited fluctuating changes, particularly in semi-arid, dry sub-humid, humid gradients, suggesting that the NDVI was more variable than GPP. Our findings can help improve our understanding of the relationships between VIs and productivity, enhancing their application in monitoring ecosystem responses to varying environmental conditions.  
All authors contributed to the present paper's preparation. Methodology, Y.L. and X.Y.; validation, X.Y.; data curation, L.Z., W.Z. and Y.Z.; writing--original draft preparation, Y.L.; writing--review and editing, X.Y. All authors have read and agreed to the published version of the manuscript.  
This research is supported by the Open Foundation of the State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences (G2023-02-04); the National Natural Science Foundation of China (42205127); the Talent Training Project of the Chinese Academy of Sciences (Grant No. E1500103 and No. E3150101); and the National Youth Talent Project (Grant No. 2023000308).  
**Data Availability Statement**: NDVI data can be sourced from [[https://cmre.earthdata.nasa.gov/search/concepts/C2759076389-ORNL_CLOUD.html](https://cmre.earthdata.nasa.gov/search/concepts/C2759076389-ORNL_CLOUD.html)]([https://cmre.earthdata.nasa.gov/search/concepts/C2759076389-ORNL_CLOUD.html](https://cmre.earthdata.nasa.gov/search/concepts/C2759076389-ORNL_CLOUD.html)) (accessed on 18 May 2023). The monthly global NIRv_GPP product can be accessed at [[https://data.tpdc.ac.cn/zh-hans/data/d6](https://data.tpdc.ac.cn/zh-hans/data/d6) df40f-5 dbd-4f2-d-ac96-55827 ab93 cc5]([https://data.tpdc.ac.cn/zh-hans/data/d6](https://data.tpdc.ac.cn/zh-hans/data/d6) df40f-5 dbd-4f2-d-ac96-55827 ab93 cc5) (accessed on 20 May 2023). Monthly precipitation data can be accessed at [[https://www.geodata.cn/data/datadetails.html?dataguid=1928918](https://www.geodata.cn/data/datadetails.html?dataguid=1928918)]([https://www.geodata.cn/data/datadetails.html?dataguid=1928918](https://www.geodata.cn/data/datadetails.html?dataguid=1928918)) 52410344&dcd=2218 (accessed on 1 August 2023). Monthly evapotranspiration data can be accessed at [[https://www.geodata.cn/data/datadetails.html?dataguid=34595274939620&dcd=1751](https://www.geodata.cn/data/datadetails.html?dataguid=34595274939620&dcd=1751)]([https://www.geodata.cn/data/datadetails.html?dataguid=34595274939620&dcd=1751](https://www.geodata.cn/data/datadetails.html?dataguid=34595274939620&dcd=1751)) (accessed on 1 August 2023).  
**Conflicts of Interest**: The authors declare no conflicts of interest.