Environment-sensitivity functions for gross primary productivity in light use efficiency models - INRAE - Institut national de recherche pour l’agriculture, l’alimentation et l’environnement Accéder directement au contenu
Article Dans Une Revue Agricultural and Forest Meteorology Année : 2021

Environment-sensitivity functions for gross primary productivity in light use efficiency models

Shanning Bao
  • Fonction : Auteur
  • PersonId : 1122319
Matthias Cuntz

Résumé

The sensitivity of photosynthesis to environmental changes is essential for understanding carbon cycle responses to global climate change and for the development of modeling approaches that explains its spatial and temporal variability. We collected a large variety of published sensitivity functions of gross primary productivity (GPP) to different forcing variables to assess the response of GPP to environmental factors. These include the responses of GPP to temperature; vapor pressure deficit, some of which include the response to atmospheric CO2 concentrations; soil water availability (W); light intensity; and cloudiness. These functions were combined in a full factorial light use efficiency (LUE) model structure, leading to a collection of 5600 distinct LUE models. Each model was optimized against daily GPP and evapotranspiration fluxes from 196 FLUXNET sites and ranked across sites based on a bootstrap approach. The GPP sensitivity to each environmental factor, including CO2 fertilization, was shown to be significant, and that none of the previously published model structures performed as well as the best model selected. From daily and weekly to monthly scales, the best model's median Nash-Sutcliffe model efficiency across sites was 0.73, 0.79 and 0.82, respectively, but poorer at annual scales (0.23), emphasizing the common limitation of current models in describing the interannual variability of GPP. Although the best global model did not match the local best model at each site, the selection was robust across ecosystem types. The contribution of light saturation and cloudiness to GPP was observed across all biomes (from 23% to 43%). Temperature and W dominates GPP and LUE but responses of GPP to temperature and W are lagged in cold and arid ecosystems, respectively. The findings of this study provide a foundation towards more robust LUE-based estimates of global GPP and may provide a benchmark for other empirical GPP products.
Fichier principal
Vignette du fichier
bao_et_al_agric_for_meteoro_2022.pdf (8.35 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte

Dates et versions

hal-03517042 , version 1 (07-01-2022)

Licence

Paternité

Identifiants

Citer

Shanning Bao, Thomas Wutzler, Sujan Koirala, Matthias Cuntz, Andreas Ibrom, et al.. Environment-sensitivity functions for gross primary productivity in light use efficiency models. Agricultural and Forest Meteorology, 2021, 312, pp.1-24. ⟨10.1016/j.agrformet.2021.108708⟩. ⟨hal-03517042⟩
49 Consultations
36 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More