Decadal variations in the driving factors of increasing water-use efficiency in China's terrestrial ecosystems from 2000 to 2022 DOI Creative Commons
Zhongen Niu, Honglin He, Ying Zhao

et al.

Ecological Informatics, Journal Year: 2024, Volume and Issue: 84, P. 102895 - 102895

Published: Nov. 13, 2024

Language: Английский

Dissecting the characteristics and driver factors of potential vegetation water use efficiency in China DOI
Rui Kong, Bin Zhu, Zengxin Zhang

et al.

The Science of The Total Environment, Journal Year: 2024, Volume and Issue: 953, P. 176174 - 176174

Published: Sept. 12, 2024

Language: Английский

Citations

2

Impact of water productivity and irrigated area expansion on irrigation water consumption and food production in China in last four decades DOI Creative Commons
Xiaojin Li, Yonghui Yang, Xinyao Zhou

et al.

Agricultural Water Management, Journal Year: 2024, Volume and Issue: 304, P. 109100 - 109100

Published: Oct. 13, 2024

Language: Английский

Citations

2

Long-term variations in ecosystem water use efficiency in the Tibetan Plateau: Vegetation types, attribution methods and main drivers DOI Creative Commons
Liuming Wang, Junxiao Wang,

Xingong Li

et al.

Ecological Indicators, Journal Year: 2024, Volume and Issue: 166, P. 112492 - 112492

Published: Aug. 13, 2024

Ecosystem water use efficiency (WUE) is a key indicator for understanding the response of carbon–water processes to environmental changes. However, as affected by uncertainty WUE estimation and attribution, individual contributions drivers changes underlying mechanisms remain unclear on Tibetan Plateau (TP). Here, theory-based analytical model was modified introducing an optimal stomatal behavior model, used estimate monthly their during 1982–2018 main vegetation types Rationality three mainstream attribution methods—analytical-based partial derivative method (APDM), regression-based (NPDM), climate elasticity (CEM)—was examined. Furtherly, various variation trend were estimated types. Results indicate that: (1) The performed well in estimating against with observed at five eddy-covariance (EC) flux stations, which decreased estimation. increased significantly TP slope 0.49 × 10-2 g C kg−1 H2O yr−1 forests most rapidly; (2) Only APDM captured both magnitude trends, NPDM CEM failed reproduce though better than benefited from its nonlinear structure. Through comparing these methods, we found that direct effects forcing variables change could be higher indirect caused interactions. (3) There are some differences trends Increase mainly driven increase leaf area index (LAI) steppes meadows, while air vapor pressure deficit (VPD) elevated CO2 showed positive broad-leaf forests. distinct extremely scarce EC observations suggest more attention should paid TP. This study help selection methods coupling alpine ecosystems under changing climate.

Language: Английский

Citations

1

Decadal variations in the driving factors of increasing water-use efficiency in China's terrestrial ecosystems from 2000 to 2022 DOI Creative Commons
Zhongen Niu, Honglin He, Ying Zhao

et al.

Ecological Informatics, Journal Year: 2024, Volume and Issue: 84, P. 102895 - 102895

Published: Nov. 13, 2024

Language: Английский

Citations

1