Machine learning-based investigation of forest evapotranspiration, net ecosystem productivity, water use efficiency and their climate controls at meteorological station level

Author:

Shi HaiyangORCID,Zhang Yu,Luo GepingORCID,Hellwich OlafORCID,Zhang Wenqiang,Xie Mingjuan,Gao Ruixiang,Kurban Alishir,De Maeyer Philippe,Van de Voorde Tim

Funder

Zhejiang Provincial Program for the Cultivation of High-Level Innovative Health Talents

CAS

University of Chinese Academy of Sciences

NSFC

Science Fund for Distinguished Young Scholars of Xinjiang Autonomous Region

National Aerospace Science Foundation of China

Publisher

Elsevier BV

Reference67 articles.

1. Heat and drought impact on carbon exchange in an age-sequence of temperate pine forests;Arain;Ecol. Process.,2022

2. Species-specific water use by forest tree species: From the tree to the stand;Aranda;Agricultural Water Management, for a Better Use and Distribution of Water,2012

3. Ball, J.T., Woodrow, I.E., Berry, J.A., 1987. A Model Predicting Stomatal Conductance and its Contribution to the Control of Photosynthesis under Different Environmental Conditions, in: Biggins, J. (Ed.), Progress in Photosynthesis Research: Volume 4 Proceedings of the VIIth International Congress on Photosynthesis Providence, Rhode Island, USA, August 10–15, 1986. Springer Netherlands, Dordrecht, pp. 221–224. 10.1007/978-94-017-0519-6_48.

4. Quantifying the effect of forest age in annual net forest carbon balance;Besnard;Environ. Res. Lett.,2018

5. Mapping global forest age from forest inventories, biomass and climate data;Besnard;Earth Syst. Sci. Data,2021

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