- 1Institute for Advanced Study & Space Science Center, Shenzhen University, Shenzhen 518060, China, (azfarhussayn@gmail.com)
- 2Institute of Karst Geology, Chinese Academy of Geological Sciences, Guilin, China
- 3Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- 4Department of Applied Mathematics, Chung Yuan Christian University, Chung-Li 32023, Taiwan
- 5School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, China
- 6Department of Earth Sciences, Institute for Advanced Studies in Basic Sciences, Zanjan 45137–66731, Iran
- 7Defense and Security, Rabdan Academy, Abu Dhabi 114646, United Arab Emirates
Understanding the relationship between vegetation and climatic drivers is essential for assessing terrestrial ecosystem patterns and managing future vegetation dynamics. This study examines the effects of local climatic factors and remote large-scale ocean–atmosphere circulations from the Pacific, Atlantic, and Arctic Oceans, as well as the East Asian and Indian summer monsoons, on the spatiotemporal variability of the Normalized Difference Vegetation Index (NDVI) in the karst region of southwest China (KRSC) using Mann-Kendall test, Sen’s slope, cross-correlation, and wavelet analysis. We observed a significant increase in NDVI over karst and non-karst regions from 1981 to 2019, with a notable abrupt shift from 2001 onwards, underscoring the importance of understanding the underlying drivers. The significant correlation and coherence of surface air (TMP) and soil temperatures (ST) with NDVI, especially when analyzed using wavelet methods, indicate their crucial role in vegetation dynamics. Additionally, the broad coherence patterns of AMO and WHWP with NDVI at annual and decadal cycles suggest that ocean–atmosphere interactions also play a significant part. At interannual periodicities, most large-scale indices displayed significant coherence with NDVI. These findings highlight the complexity of NDVI variability, which is better explained by the integration of multiple local and global factors rather than by single variables. The integrated local–global drivers, particularly TMP-ST-AMO-NP-WHWP and PCP-SM-AMO-NP-WHWP, with mean coherence of 0.90 and 0.89, respectively, showed the highest mean coherence, emphasizing the need for a multifaceted approach in understanding vegetation changes rather than a single local variable or atmospheric circulation index. These findings have significant implications for policy-makers, aiding in better planning and policy formulations considering climate change and atmospheric variability.
How to cite: Hussain, A., Cao, J., Abbas, H., Hussain, I., Zhou, J., Yang, H., Rezaei, A., Luo, Q., Ullah, W., and Liang, Z.: Characterizing the local and global climatic factors associated with vegetation dynamics in the karst region of southwest China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1955, https://doi.org/10.5194/egusphere-egu25-1955, 2025.