Incorporating the acclimation of photosynthesis and leaf respiration in the Noah-MP land surface model: model development and evaluation

Leaf photosynthetic and respiratory processes are important for the terrestrial carbon cycle. Leaf physiological traits, such as the maximum carboxylation rate and leaf respiration rate at 25˚C (V_cmax,25, R₂₅), the key parameters affecting photosynthesis and respiration rate, acclimate to environmental changes. However, many land surface models (LSMs) assume a constant R₂₅ and V_cmax,25 by plant functional types (PFTs) due to limited understanding of plant acclimation processes. Here, we incorporated the acclimation of photosynthesis and leaf respiration into a land surface model (Noah MP) using the Eco-Evolutionary Optimality principle (Noah MP-EEO), and evaluated the performances of the EEO and standard schemes to simulate photosynthesis and respiration using global plant trait measurements and data from FLUXNET. We demonstrate that R₂₅ and V_cmax,25 varied temporally and spatially within the same PFT (C.V. >20%). This behaviour is captured by the EEO scheme (R² =0.69 and 0.62 for temporal and spatial variations) but ignored by the standard scheme. At the FLUXNET sites, the standard scheme underestimates gross primary production (GPP) but this is reduced in the EEO scheme. The EEO scheme explains 66% of the variation of site-annual GPP compared to 55% in the standard scheme. The EEO scheme also simulates the variation of leaf respiration (R_leaves) better than the standard scheme (R² increases from 0.45 to 0.77). The EEO scheme shows less temperature sensitivity than the standard scheme because of acclimation. This study indicates that adopting EEO approaches that do not require PFT-specific parameters improves carbon cycle predictions and could be used in Earth system models for better understanding the climate-carbon feedback.