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Abstract Predicting tropical tree demography is a key challenge in understanding the future dynamics of tropical forests. Although demographic processes are known to be regulated by leaf trait diversity, only the effect of inter‐specific trait variation has been evaluated, and it remains unclear as to what degree the intra‐specific trait plasticity across light gradients (hereafter light plasticity) regulates tree demography, and how this will further shape long‐term community and ecosystem dynamics. By combining in situ trait measurements and forest census data with a terrestrial biosphere model, we evaluated the impact of observation‐constrained light plasticity on demography, forest structure, and biomass dynamics in a Panamanian tropical moist forest. Modeled leaf physiological traits vary across and within plant functional types (PFT), which represent the inter‐specific trait variation and the intra‐specific light plasticity, respectively. The simulation using three non‐plastic PFTs underestimated 20‐year average understory growth rates by 41%, leading to a biased forest size structure and leaf area profile, and a 44% underestimate in long‐term biomass. The simulation using three plastic PFTs generated accurate understory growth rates, resulting in a realistic forest structure and a smaller biomass underestimate of 15%. Expanding simulated trait diversity using 18 nonplastic PFTs similarly improved the prediction of demography and biomass. However, only the plasticity‐enabled model predicted realistic long‐term PFT composition and within‐canopy trait profiles. Our results highlight the distinct role of light plasticity in regulating forest dynamics that cannot be replaced by inter‐specific trait diversity. Accurately representing light plasticity is thus crucial for trait‐based prediction of tropical forest dynamics. 

Abstract The strength and persistence of the tropical carbon sink hinges on the long‐term responses of woody growth to climatic variations and increasing CO₂. However, the sensitivity of tropical woody growth to these environmental changes is poorly understood, leading to large uncertainties in growth predictions. Here, we used tree ring records from a Southeast Asian tropical forest to constrain ED2.2‐hydro, a terrestrial biosphere model with explicit vegetation demography. Specifically, we assessed individual‐level woody growth responses to historical climate variability and increases in atmospheric CO₂(C_a). When forced with historical C_a, ED2.2‐hydro reproduced the magnitude of increases in intercellular CO₂concentration (a major determinant of photosynthesis) estimated from tree ring carbon isotope records. In contrast, simulated growth trends were considerably larger than those obtained from tree rings, suggesting that woody biomass production efficiency (WBPE = woody biomass production:gross primary productivity) was overestimated by the model. The estimated WBPE decline under increasing C_abased on model‐data discrepancy was comparable to or stronger than (depending on tree species and size) the observed WBPE changes from a multi‐year mature‐forest CO₂fertilization experiment. In addition, we found that ED2.2‐hydro generally overestimated climatic sensitivity of woody growth, especially for late‐successional plant functional types. The model‐data discrepancy in growth sensitivity to climate was likely caused by underestimating WBPE in hot and dry years due to commonly used model assumptions on carbon use efficiency and allocation. To our knowledge, this is the first study to constrain model predictions of individual tree‐level growth sensitivity to C_aand climate against tropical tree‐ring data. Our results suggest that improving model processes related to WBPE is crucial to obtain better predictions of tropical forest responses to droughts and increasing C_a. More accurate parameterization of WBPE will likely reduce the stimulation of woody growth by C_arise predicted by biosphere models.