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Abstract Realistic simulation of leaf photosynthetic and respiratory processes is needed for accurate prediction of the global carbon cycle. These two processes systematically acclimate to long‐term environmental changes by adjusting photosynthetic and respiratory traits (e.g., the maximum photosynthetic capacity at 25°C (V_cmax,25) and the leaf respiration rate at 25°C (R₂₅)) following increasingly well‐understood principles. While some land surface models (LSMs) now account for thermal acclimation, they do so by assigning empirical parameterizations for individual plant functional types (PFTs). Here, we have implemented an Eco‐Evolutionary Optimality (EEO)‐based scheme to represent the universal acclimation of photosynthesis and leaf respiration to multiple environmental effects, and that therefore requires no PFT‐specific parameterizations, in a standard version of the widely used LSM, Noah MP. We evaluated model performance with plant trait data from a 5‐year experiment and extensive global field measurements, and carbon flux measurements from FLUXNET2015. We show that observedR₂₅andV_cmax,25vary substantially both temporally and spatially within the same PFT (C.V.>20%). Our EEO‐based scheme captures 62% of the temporal and 70% of the spatial variations inV_cmax,25(73% and 54% of the variations inR₂₅). The standard scheme underestimates gross primary production by 10% versus 2% for the EEO‐based scheme and generates a larger spread inr(correlation coefficient) across flux sites (0.79 ± 0.16 vs. 0.84 ± 0.1, mean ± S.D.). The standard scheme greatly overestimates canopy respiration (bias: ∼200% vs. 8% for the EEO scheme), resulting in less CO₂uptake by terrestrial ecosystems. Our approach thus simulates climate‐carbon coupling more realistically, with fewer parameters. 

Summary Leaf dark respiration (R_d) acclimates to environmental changes. However, the magnitude, controls and time scales of acclimation remain unclear and are inconsistently treated in ecosystem models.We hypothesized thatR_dand Rubisco carboxylation capacity (V_cmax) at 25°C (R_d,25,V_cmax,25) are coordinated so thatR_d,25variations supportV_cmax,25at a level allowing full light use, withV_cmax,25reflecting daytime conditions (for photosynthesis), andR_d,25/V_cmax,25reflecting night‐time conditions (for starch degradation and sucrose export). We tested this hypothesis temporally using a 5‐yr warming experiment, and spatially using an extensive field‐measurement data set. We compared the results to three published alternatives:R_d,25declines linearly with daily average prior temperature;R_dat average prior night temperatures tends towards a constant value; andR_d,25/V_cmax,25is constant.Our hypothesis accounted for more variation in observedR_d,25over time (R² = 0.74) and space (R² = 0.68) than the alternatives. Night‐time temperature dominated the seasonal time‐course ofR_d, with an apparent response time scale ofc.2 wk.V_cmaxdominated the spatial patterns.Our acclimation hypothesis results in a smaller increase in globalR_din response to rising CO₂and warming than is projected by the two of three alternative hypotheses, and by current models.