## 5 Conclusions  
Ecosystem WUE serves as an excellent proxy for examining the coupling between carbon-water fluxes in terrestrial ecosystems. Estimating WUE enables the quantification of carbon-water exchange and the detection of its response to drought disturbances. Based on a remote sensing-driven GPP dataset and a component of terrestrial evapotranspiration, specifically the AET driven by GLEAM dataset estimates, we comprehensively examined the impacts of the monthly SPEI-6 on long-term GPP/WUE variability over the ME for the period 1982-2017. We focused on coupling analysis between the WUE/GPP and SPEI, as well as spatial heterogeneity. The ability of an ecosystem to tolerate drought disturbances was considered based on DS as a drought intensification function, along with whether various ecosystem types have varying responses. The main findings are as follows:  
1. The ecosystem GPP is sensitive to drought in semi-arid ecosystems (BSh), and the GPP of croplands and shrub-covered areas recorded the highest positive significant correlations and were more sensitive to SPEI variability. The ecosystem WUE is sensitive to drought in temperate climates (Cf), followed by arid climate patterns (BW), and the WUE of bare soil and shrub-covered areas recorded the highest negative significant correlations and were more sensitive to the SPEI.
2. The ecosystem GPP and WUE declined significantly during the 2008 extreme drought (D1) in the north of Iraq and northeast of Syria, where the sWUEA of bare soil and shrub-covered areas had the highest positive response to DS years, whereas the sGPPA of croplands, grassland, and tree-covered areas had clear and high negative values with the DS group, with D1 having the highest negative values for these land cover types.
3. The ecosystem GPP and WUE in the ME are sensitive to drought disturbances and present a contrasting response regionally. The results of our study pointed out that the WUE fluctuation in arid ecosystems is mostly controlled by evaporation. In semi-arid or sub-humid environments, WUE variability is generally controlled by biological activities (i.e., assimilation).  
Therefore, additional observation and simulation are still required to underestimate the divergences and potential uncertainty. Additionally, it is still troublesome to precisely reproduce GPP and AET. As such, the dataset combination from diverse and independent models can facilitate reaching more reliable conclusions when evaluating the responses of GPP and WUE to drought disturbance at a regional scale. Future investigations should pay more attention to the processes of ET and GPP, parameterization selection, and output optimal representation in model modification, which may impact the ET and GPP, which are conclusive for an in-depth understanding of the relationships between GPP-WUE and drought disturbances.  
Conceptualization, K.A.; methodology, K.A.; formal analysis, K.A.; investigation, K.A.; data curation, K.A.; writing--original draft preparation, K.A., H.G.A., A.M. and S.M.; writing--review and editing, S.M., B.B., A.A. and W.C.; visualization, K.A.; supervision, W.C. All authors have read and agreed to the published version of the manuscript.  
This work was supported by the Researchers Supporting Project, grant number (RSP2024R296), King Saud University, Riyadh, Saudi Arabia.  
The data availability upon request.  
The authors would like to express their gratitude to Xiamen University and King Saud University for their support. The authors would also like to thank the EuroFlux, GLEAM, and GLASS teams for sharing the datasets.  
The authors declare no conflicts of interest.