Enhancing Ready-to-Implementation subseasonal crop growth predictions in central Southwestern Asia: A machine learning-climate dynamical hybrid strategy DOI Creative Commons
Tao Zhu, Mengqian Lu, Jing Yang

et al.

Agricultural and Forest Meteorology, Journal Year: 2025, Volume and Issue: 370, P. 110582 - 110582

Published: May 2, 2025

Language: Английский

Assessing vegetation resilience and vulnerability to drought events in Central Asia DOI
Liangliang Jiang,

Bing Liu,

Hao Guo

et al.

Journal of Hydrology, Journal Year: 2024, Volume and Issue: 634, P. 131012 - 131012

Published: March 7, 2024

Language: Английский

Citations

14

Ecological assessment and driver analysis of high vegetation cover areas based on new remote sensing index DOI Creative Commons
Xiaoyong Zhang, Weiwei Jia,

Shixin Lu

et al.

Ecological Informatics, Journal Year: 2024, Volume and Issue: 82, P. 102786 - 102786

Published: Aug. 23, 2024

Language: Английский

Citations

11

Dynamic process of ecosystem water use efficiency and response to drought in the Yellow River Basin, China DOI

SaiHua Liu,

Lianqing Xue,

Ying Xiao

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 934, P. 173339 - 173339

Published: May 17, 2024

Language: Английский

Citations

10

Assessing recovery time of ecosystems in China: insights into flash drought impacts on gross primary productivity DOI Creative Commons

Mengge Lu,

Huaiwei Sun, Yang Yong

et al.

Hydrology and earth system sciences, Journal Year: 2025, Volume and Issue: 29(3), P. 613 - 625

Published: Feb. 4, 2025

Abstract. Recovery time, referring to the duration that an ecosystem needs return its pre-drought condition, is a fundamental indicator of ecological resilience. Recently, flash droughts – characterised by rapid onset and development have gained increasing attention. Nevertheless, spatiotemporal patterns in gross primary productivity (GPP) recovery time factors influencing it remain largely unknown. In this study, we investigate terrestrial China based on GPP using random forest regression model SHapley Additive exPlanations (SHAP) method. A was developed analyse establish response functions through partial correlation for typical drought periods. The dominant driving were determined SHAP results reveal average across approximately 37.5 d, with central southern regions experiencing longest durations. Post-flash-drought radiation emerges as environmental factor, followed aridity index post-flash-drought temperature, particularly semi-arid sub-humid areas. Temperature exhibits non-monotonic relationship where both excessively cold hot conditions lead longer Herbaceous vegetation recovers more rapidly than woody forests, deciduous broadleaf forests demonstrating shortest time. This study provides valuable insights comprehensive water resource management contributes large-scale monitoring efforts.

Language: Английский

Citations

1

Rising temperature increases the response time of LAI and GPP to meteorological drought in China DOI
Yu‐Fei Wang, Peng Sun, Rui Yao

et al.

Atmospheric Research, Journal Year: 2025, Volume and Issue: unknown, P. 107989 - 107989

Published: Feb. 1, 2025

Language: Английский

Citations

1

Drought changes the dominant water stress on the grassland and forest production in the northern hemisphere DOI
Wenqiang Zhang, Geping Luo, Rafiq Hamdi

et al.

Agricultural and Forest Meteorology, Journal Year: 2023, Volume and Issue: 345, P. 109831 - 109831

Published: Dec. 2, 2023

Language: Английский

Citations

18

Nonlinear time effects of vegetation response to climate change: Evidence from Qilian Mountain National Park in China DOI

Qiuran Li,

Xiang Gao, Jie Li

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 933, P. 173149 - 173149

Published: May 11, 2024

Language: Английский

Citations

8

Grassland productivity in arid Central Asia depends on the greening rate rather than the growing season length DOI
Jianhao Li,

Wanqiang Han,

Jianghua Zheng

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 933, P. 173155 - 173155

Published: May 11, 2024

Language: Английский

Citations

7

Increasing influence of minimum temperature on grassland spring phenology in arid Central Asia DOI
Jianhao Li, Liang Liu,

Jianghua Zheng

et al.

Agricultural and Forest Meteorology, Journal Year: 2024, Volume and Issue: 355, P. 110122 - 110122

Published: June 14, 2024

Language: Английский

Citations

5

Quantifying the drought sensitivity of vegetation types in northern China from 1982 to 2022 DOI
Bo Yuan, Shanchuan Guo, Xingang Zhang

et al.

Agricultural and Forest Meteorology, Journal Year: 2024, Volume and Issue: 359, P. 110293 - 110293

Published: Nov. 1, 2024

Language: Английский

Citations

5