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Abstract The structure and dynamics of forest ecosystems are the outcome of differential performance playing out at the individual level. Interactions between the traits of an organism and its environment determine performance. Thus, our ability to understand and, ultimately, model forest dynamics critically relies on knowledge regarding the functional biology of the organisms. In tropical forests, this is a daunting challenge due to the diversity of the systems. This has driven ecologists to focus on identifying a handful of fundamentally important trade‐offs and a few traits that may indicate where a species falls along that trade‐off axis. In other cases, some ecologists have argued that species can be roughly binned into a handful of functional groups or guilds that capture most of the information needed to generate realistic models of forest dynamics. Here, we discuss the functional biology of tropical forest dynamics. We identify a series of key trade‐offs that should underpin forest dynamics and the traits ecologists have attempted to link to these trade‐offs. We then explore how far we can get by using functional groups or guilds to model tropical forest dynamics, the conceptual frameworks used for promoting such approaches, and what this modeling framework does not capture. We then use this to identify key gaps that should motivate the future of tropical tree functional ecology. 

Summary Allocation of leaf phosphorus (P) among different functional fractions represents a crucial adaptive strategy for optimizing P use. However, it remains challenging to monitor the variability in leaf P fractions and, ultimately, to understand P‐use strategies across diverse plant communities.We explored relationships between five leaf P fractions (orthophosphate P, P_i; lipid P, P_L; nucleic acid P, P_N; metabolite P, P_M; and residual P, P_R) and 11 leaf economic traits of 58 woody species from three biomes in China, including temperate, subtropical and tropical forests. Then, we developed trait‐based models and spectral models for leaf P fractions and compared their predictive abilities.We found that plants exhibiting conservative strategies increased the proportions of P_Nand P_M, but decreased the proportions of P_iand P_L, thus enhancing photosynthetic P‐use efficiency, especially under P limitation. Spectral models outperformed trait‐based models in predicting cross‐site leaf P fractions, regardless of concentrations (R² = 0.50–0.88 vs 0.34–0.74) or proportions (R² = 0.43–0.70 vs 0.06–0.45).These findings enhance our understanding of leaf P‐allocation strategies and highlight reflectance spectroscopy as a promising alternative for characterizing large‐scale leaf P fractions and plant P‐use strategies, which could ultimately improve the physiological representation of the plant P cycle in land surface models.