## 4 Discussion
### Biodiversity Recovery, Ecosystem Functioning, and Sustainability  
In the context of improving GPP (gross primary productivity) simulations under drought conditions, the incorporation of soil moisture (SM) and vegetation indices such as LSWI significantly enhances the accuracy of carbon flux predictions. Furthermore, these improvements have profound implications for understanding biodiversity recovery,ecosystem functioning, and long-term sustainability, offering critical scientific insights and decision-making support. Drought poses significant challenges to ecosystem resilience and biodiversity conservation, and accurate GPP modeling provides a quantitative framework for assessing ecosystem recovery processes under drought stress [52; 53]. Grass-type ecosystems, due to their shallow root systems, are more reliant on surface SM and are particularly vulnerable to water deficits [54; 55]. By integrating SM and LSWI into light-use efficiency (LUE) models, this study achieves a more precise simulation of productivity changes in these ecosystems during recovery periods. Such an approach enables more effective identification of critical periods and regions affected by drought stress, thereby informing restoration strategies, including optimized irrigation practices, vegetation coverage adjustments, or the introduction of drought-tolerant species. Moreover, accurately identifying water stress conditions across ecosystems facilitates the prioritization of restoration efforts in biodiversity hotspots, providing a scientific basis for protecting and rehabilitating critical habitats. The varying responses of different ecosystems to drought stress indicators reflect the complex interactions among vegetation structure, root system distribution, photosynthetic physiology, and water-use strategies. By integrating SM and LSWI, this study elucidates the response mechanisms of ecosystem functioning to water stress. For instance, the carbon sequestration capacity of grass-type ecosystems is particularly sensitive to surface water availability during drought periods, as evidenced by improved GPP simulations. This highlights the dependency of grass-type ecosystems' primary productivity and carbon cycling on short-term hydrological conditions, especially dynamic changes in surface soil moisture [56]. In contrast, forest ecosystems exhibit a stronger correlation between GPP and vapor pressure deficit (VPD), which underscores the importance of atmospheric moisture dynamics in influencing their photosynthetic efficiency and water-use strategies. Additionally, the complex light environment within forest canopies (e.g., the distribution and varying light saturation points of sunlit and shaded leaves) plays a significant role in carbon flux processes. The ability of LUE models to differentiate these complex mechanisms not only deepens our understanding of ecosystem processes but also offers new pathways for further model optimization. In the face of intensifying global climate change and increasing drought frequency, achieving sustainable ecosystem management is a critical challenge. The incorporation of SM and LSWI into LUE models not only improves simulation accuracy but also provides quantitative insights for evaluating and managing ecosystem services. For grass-type ecosystems, where GPP is highly sensitive to surface SM, sustainable practices such as soil conservation, water resource management, and irrigation optimization become essential for enhancing drought resilience. Specific measures, including soil mulching, increasing water storage capacity, and regulating irrigation schedules, can strengthen the adaptive capacity of grass-type ecosystems. For forest ecosystems, the study suggests that adaptive strategies focusing on atmospheric water dynamics (e.g., VPD) and canopy microenvironments may be more effective in mitigating drought stress.