A triple tree-ring constraint for tree growth and physiology in a global land surface model

Autor: J. Barichivich, P. Peylin, T. Launois, V. Daux, C. Risi, J. Jeong, S. Luyssaert
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Biogeosciences, Vol 18, Pp 3781-3803 (2021)
Druh dokumentu: article
ISSN: 1726-4170
1726-4189
DOI: 10.5194/bg-18-3781-2021
Popis: Annually resolved tree-ring records extending back to pre-industrial conditions have the potential to constrain the responses of global land surface models at interannual to centennial timescales. Here, we demonstrate a framework to simultaneously constrain the representation of tree growth and physiology in the ORCHIDEE global land surface model using the simulated variability of tree-ring width and carbon (Δ13C) and oxygen (δ18O) stable isotopes in six sites in boreal and temperate Europe. We exploit the resulting tree-ring triplet to derive integrative constraints for leaf physiology and growth from well-known mechanistic relationships among the variables. ORCHIDEE simulates Δ13C (r=0.31–0.80) and δ18O (r=0.36–0.74) better than tree-ring width (r), with an overall skill similar to that of a tree-ring model (MAIDENiso) and another isotope-enabled global vegetation model (LPX-Bern). The comparison with tree-ring data showed that growth variability is not well represented in ORCHIDEE and that the parameterization of leaf-level physiological responses (stomatal control) to drought stress in the temperate region can be constrained using the interannual variability of tree-ring stable isotopes. The representation of carbon storage and remobilization dynamics emerged as a critical process to improve the realism of simulated growth variability, temporal carryover, and recovery of forest ecosystems after climate extremes. Simulated forest gross primary productivity (GPP) correlates with simulated tree-ring Δ13C and δ18O variability, but the origin of the correlations with tree-ring δ18O is not entirely physiological. The integration of tree-ring data and land surface models as demonstrated here should guide model improvements and contribute towards reducing current uncertainties in forest carbon and water cycling.
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