Dryness controls temperature-optimized gross primary productivity across vegetation types - Archive ouverte HAL
Article Dans Une Revue Agricultural and Forest Meteorology Année : 2022

Dryness controls temperature-optimized gross primary productivity across vegetation types

Bingxue Wang
  • Fonction : Auteur
Weinan Chen
  • Fonction : Auteur
Junhu Dai
  • Fonction : Auteur
Zhaolei Li
  • Fonction : Auteur
Sangeeta Sarmah
  • Fonction : Auteur
Yiqi Luo
  • Fonction : Auteur
Shuli Niu
  • Fonction : Auteur

Résumé

Temperature response of gross primary productivity (GPP) is a well-known property of ecosystem, but GPP at the optimum temperature (GPP_Topt) has not been fully discussed. Our understanding of how GPP_Topt responds to warming and water availability is highly limited. In this study, we analyzed data at 326 globally distributed eddy covariance sites (79oN-37oS), to identify controlling factors of GPP_Topt. Although GPP_Topt was significantly influenced by soil moisture, global solar radiation, mean annual temperature, and vapor pressure deficit in a non-linear pattern (R2 = 0.47), the direction and magnitude of these climate variables’ effects on GPP_Topt depend on the dryness index (DI), a ratio of potential evapotranspiration to precipitation. The spatial pattern showed that soil moisture did not affect GPP_Topt across energy-limited sites with DI < 1 while dominated GPP_Topt across water-limited sites with DI >1. The temporal pattern showed that GPP_Topt was lowered by warming or low precipitation in water-limited sites while energy-limited sites tended to maintain a stable GPP_Topt regardless of changes in air temperature. Vegetation types in humid climates tended to have higher GPP_Topt and were more likely to benefit from a warmer climate since it was not restricted by water conditions. This study highlights that the response of GPP_Topt to global warming depends on the dryness conditions, which explains the nonlinear control of water and temperature over GPP_Topt. Our finding is essential to realistic prediction of terrestrial carbon uptake under future climate and vegetation conditions.

Dates et versions

hal-03738350 , version 1 (26-07-2022)

Identifiants

Citer

Bingxue Wang, Weinan Chen, Junhu Dai, Zhaolei Li, Zheng Fu, et al.. Dryness controls temperature-optimized gross primary productivity across vegetation types. Agricultural and Forest Meteorology, 2022, 323, pp.109073. ⟨10.1016/j.agrformet.2022.109073⟩. ⟨hal-03738350⟩
29 Consultations
0 Téléchargements

Altmetric

Partager

More