Diagnosing Linearity Along the Carbon Cascade in Terrestrial Biosphere Models and Observations

Area of Science:

• Earth System Science
• Ecology
• Climate Change Research

Background:

• Elevated carbon dioxide (eCO2) enhances photosynthesis (gross primary production, GPP), acting as a fertilizer for plants.
• The propagation of increased GPP through the carbon (C) cascade to net primary production (NPP) and vegetation C stocks (Cveg) under eCO2 is not well understood.
• Existing vegetation models may be overly sensitive to photosynthesis (source-driven) and neglect crucial sink-driven processes that influence C dynamics.

Purpose of the Study:

• To introduce and apply an analytical framework to diagnose the linearity (L) of changes in linked carbon fluxes and pools within the terrestrial carbon cycle.
• To assess how effectively increased GPP under eCO2 translates to NPP and Cveg across different plant compartments using a multi-model ensemble.
• To compare model-based linearity patterns with observation-based estimates of CO2 sensitivities.

Main Methods:

• Developed an analytical framework to calculate linearity (L) as the ratio of relative changes in linked carbon fluxes and pools.
• Applied this framework to 16 vegetation models from the TRENDY v11 ensemble.
• Analyzed observation-based estimates of CO2 sensitivities for comparison with model results.

Main Results:

• Found significant variations in linearity patterns (L) across models and geographical regions.
• Six models indicated increased vegetation carbon use efficiency (L_NPP:GPP > 1) in most grid cells, while only three showed the opposite.
• Model results for the linearity of Cveg to NPP (L_Cveg*:NPP) and root C to Cveg (L_Croot:Cveg) showed considerable spread, with some models aligning with field evidence and others diverging.

Conclusions:

• Individual models exhibit strong nonlinear behaviors in response to eCO2, leading to diverse patterns in the carbon cascade.
• Despite individual model variability, the ensemble mean suggests an overall linear behavior in terrestrial carbon cycle representations.
• Further research and improved model validation against observational data are needed to refine our understanding of carbon C cascade dynamics under eCO2.