## 5 Conclusions  
This study systematically investigated the spatiotemporal dynamics of gross primary productivity (GPP) and its responses to normal and extreme climatic conditions in the desert steppe of NFYS during 2001-2023. The lagged responses of GPP to historical climate variations and its potential responses to future climate scenarios derived from CMIP6 projections were analyzed based on the random forest and partial least squares regression models. The conclusions were drawn as follows:  
The GPP in the desert steppe of NFYS exhibited a significantly increasing trend (\(p<0.05\)) at a rate of 1.25 g C/m\({}^{2}\)/yr, displaying a distinct spatial gradient with higher values in the southeast gradually decreasing toward the northwest. Notably, 88.65% of the statistically significant growth areas (\(p<0.05\)) were concentrated in the central-western and northeastern regions.  
The region exhibited a pronounced warming and drying trend, characterized by decreasing precipitation and increasing temperatures during 2001-2023. The extreme climate characteristics show a significant increase in extremely high-temperature events and a relatively high frequency of heavy precipitation days.  
Statistical analysis indicated strong correlations (r > 0.6) between GPP and over 90% of extreme climate indices. GPP exhibited immediate responses to temperature than to precipitation variations. In addition to the conventional T\({}_{\rm max}\), T\({}_{\rm min}\), and PP, ID\({}_{0}\), T\({}_{\rm X90p}\), T\({}_{\rm N90p}\), CDD, and R\({}_{\rm 55}\) are the most significant extreme climate indicators that affect GPP.  
Future projections under both SSP2-RCP4.5 and SSP5-RCP8.5 scenarios indicate sustained GPP increases, with significantly higher values under the SSP5-RCP8.5 scenario compared to SSP2-RCP4.5. The hysteresis effect was found to amplify the inhibitory impacts of extreme weather on GPP through long-term cumulative processes while attenuating the promotive effects of average climate conditions.  
The following supporting information can be downloaded at: [[https://www.mdpi.com/article/10.3390/land14040884/s1](https://www.mdpi.com/article/10.3390/land14040884/s1)]([https://www.mdpi.com/article/10.3390/land14040884/s1](https://www.mdpi.com/article/10.3390/land14040884/s1)).  
Methodology, Y.W. ([PERSON]); software, S.C.; validation, M.Z., E.G. and Y.W. ([PERSON]); formal analysis, M.Z., Y.W. ([PERSON]) and T.K.; resources, S.C.; data curation, M.Z., E.G. and S.C.; writing--original draft preparation, M.Z. and Y.W. ([PERSON]); writing--review and editing, S.Z., M.Z., Y.W. ([PERSON]) and T.K.; visualization, M.Z.; supervision, S.Z. and E.G.; review and editing, Y.W. ([PERSON]) and T.K.; funding acquisition, S.Z. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the IWHR Research & Development Support Program, grant number No. MKKH2024 JK020 and No. MK0145B022021, First-Class Discipline Research Special Project, grant number YLXKZX-NSD-027, the Inner Mongolia Autonomous Region Science and Technology Support Program, grant number No. 2023 JBGS0007, No. 2024 MS04002, No. 2023 YFSH0002, No. 2023 MS05023, the Basic Scientific Research Business Fee of Directly-affiliated Universities in Inner Mongolia Autonomous Region, grant number No. BR231516, Inner Mongolia Autonomous Region's Start-up Support Program Project for Returned Overseas Students' Innovation and Entrepreneurship and the IWHR Internationally oriented Talents Program.  
The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding authors.  
We would like to thank [PERSON] from the Remote Sensing Center of Canada for review and editing, and validation.