Hengshuo Zhang Xizhi Lv ^* Yongxin Ni Qiufen Zhang Jianwei Wang Li Ma

• Yellow River Institute of Hydraulic Research, Zhengzhou, China

Vegetation productivity and ecosystem carbon sink capacity are significantly influenced by seasonal weather patterns. The time lags between changes in these patterns and ecosystem (including vegetation) responses is a critical aspect in vegetation-climate and ecosystem-climate interactions. These lags can vary considerably due to the spatial heterogeneity of vegetation and ecosystems. In this study focused on the source regions of the Yangtze and Yellow Rivers (SCRYR), we utilized long-term datasets of Net Primary Productivity (NPP) and model-estimated Net Ecosystem Productivity (NEP) from2015 to 2020, combined with reconstructed 8-day scale climate sequences, to conduct partial correlation regression analysis (isolating the influence of individual meteorological factors on the lag effects). The study found that the length of lag effects varies depending on regional topography, vegetation types, and the sensitivity of their ecological environments to changes in meteorological factors. In the source region of the Yangtze River (SCR), the lag times for NPP and NEP in response to temperature (Tem) are longer, compared to the source region of the Yellow River (SYR), where the lags are generally less than 10 days. The long lag effects of NPP with precipitation (Pre), ranging from 50 to 60 days, were primarily concentrated in the northwestern part of the SCR, while the long lag effects of NEP with precipitation, ranging from 34 to 48 days, covered a broad region in the western part of the study area. NPP exhibits the least sensitivity to changes in solar radiation (SR), with lag times exceeding 54 days in 99.30% of the region. In contrast, NEP showed varying lag effects with respect to SR: short lag effects (ranging from 0 to 15 days) were observed in carbon source areas, while long lag effects (ranging from 55 to 64 days) were evident in carbon sink areas. The sensitivity of vegetation to meteorological changes is highest for SVL, followed by C3A, PW, BDS, and C3 in descending order. This study examined the spatiotemporal impacts of climatic drivers on NPP and NEP from both vegetation and ecosystem perspectives. The findings are crucial for enhancing vegetation productivity and ecosystem carbon sequestration capacity in China.