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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 Forest health is critical for sustaining ecosystem services like carbon sequestration. Heart rot, a widespread disease in upland northern hardwood forests, may affect greenhouse gas (CO₂and CH₄) fluxes, but its impacts remain poorly measured.Using non‐destructive tomography and direct gas flux measurements, we quantified the effects of heart rot on sugar maple (Acer saccharumMarshall) stems and surrounding soils.Heart rot increased CH₄emissions from stems but did not affect CO₂fluxes from stems or soils, nor CH₄fluxes from soils. All stems emitted CO₂and CH₄, while soils absorbed CH₄and emitted CO₂. Stem CH₄fluxes strongly correlated with decay severity, but CO₂fluxes did not. CH₄was produced in the heartwood, CO₂in the sapwood, and methanogens were present in all stems. Severe heart rot often caused bark fractures, enhancing CH₄diffusion to the atmosphere and creating emission hotspots.These findings show that forest health influences carbon cycling. Capturing stem CH₄hotspots requires direct measurement, and fungal diseases like heart rot may shift forests from CH₄sinks to sources, with implications for atmospheric greenhouse gas dynamics. 

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. 

Abiotic environments and biotic neighbourhoods interact to influence plant growth and community assembly. However, the nature of this interaction depends very much on how biotic neighbourhoods are measured, including their relatedness to focal plants. In a tropical seasonal rainforest, we examine the growth of a dominant canopy species in response to environmental factors, the densities and relatedness of conspecific and heterospecific neighbours, and their interactions. We find significant environmental effects and conspecific negative density dependence on growth. Furthermore, conspecific neighbour density has stronger negative effects on growth under high light and soil water resource levels, but weaker negative effects under low light and soil water resource levels. In addition, more closely related heterospecifics in the neighbourhood have negative effects on growth under high soil phosphorus availability, but positive effects under low soil phosphorus availability. In contrast, more closely related conspecifics in the neighbourhood have negative effects on growth under low soil potassium availability, but positive effects under high soil potassium availability. Our study emphasizes the importance of both intra- and interspecific neighbourhood composition and their interactions with resource levels for understanding tree growth. This enhances our understanding of the complex processes in community assembly and species coexistence within forest communities. 

Abstract Tropical tree communities are among the most diverse in the world. A small number of genera often disproportionately contribute to this diversity. How so many species from a single genus can co‐occur represents a major outstanding question in biology. Niche differences are likely to play a major role in promoting congeneric diversity, but the mechanisms of interest are often not well‐characterized by the set of functional traits generally measured by ecologists.To address this knowledge gap, we used a functional genomic approach to investigate the mechanisms of co‐occurrence in the hyper‐diverse genusFicus. Our study focused on over 800 genes related to drought and defence, providing detailed information on how these genes may contribute to the diversity ofFicusspecies.We find widespread and consistent evidence of the importance of defence gene dissimilarity in co‐occurring species, providing genetic support for what would be expected under the Janzen‐Connell mechanism. We also find that drought‐related gene sequence similarity is related toFicusco‐occurrence, indicating that similar responses to drought promote co‐occurrence.Synthesis. We provide the first detailed functional genomic evidence of how drought‐ and defence‐related genes simultaneously contribute to the local co‐occurrence in a hyper‐diverse genus. Our results demonstrate the potential of community transcriptomics to identify the drivers of species co‐occurrence in hyper‐diverse tropical tree genera. 

Summary Leaf dark respiration (R_dark), an important yet rarely quantified component of carbon cycling in forest ecosystems, is often simulated from leaf traits such as the maximum carboxylation capacity (V_cmax), leaf mass per area (LMA), nitrogen (N) and phosphorus (P) concentrations, in terrestrial biosphere models. However, the validity of these relationships across forest types remains to be thoroughly assessed.Here, we analyzedR_darkvariability and its associations withV_cmaxand other leaf traits across three temperate, subtropical and tropical forests in China, evaluating the effectiveness of leaf spectroscopy as a superior monitoring alternative.We found that leaf magnesium and calcium concentrations were more significant in explaining cross‐siteR_darkthan commonly used traits like LMA, N and P concentrations, but univariate trait–R_darkrelationships were always weak (r² ≤ 0.15) and forest‐specific. Although multivariate relationships of leaf traits improved the model performance, leaf spectroscopy outperformed trait–R_darkrelationships, accurately predicted cross‐siteR_dark(r² = 0.65) and pinpointed the factors contributing toR_darkvariability.Our findings reveal a few novel traits with greater cross‐site scalability regardingR_dark, challenging the use of empirical trait–R_darkrelationships in process models and emphasize the potential of leaf spectroscopy as a promising alternative for estimatingR_dark, which could ultimately improve process modeling of terrestrial plant respiration. 

Abstract Forest trees provide critical ecosystem services for humanity that are under threat due to ongoing global change. Measuring and characterizing genetic diversity are key to understanding adaptive potential and developing strategies to mitigate negative consequences arising from climate change. In the area of forest genetic diversity, genetic divergence caused by large-scale changes at the chromosomal level has been largely understudied. In this study, we used the RNA-seq data of 20 co-occurring forest trees species from genera including Acer, Alnus, Amelanchier, Betula, Cornus, Corylus, Dirca, Fraxinus, Ostrya, Populus, Prunus, Quercus, Ribes, Tilia, and Ulmus sampled from Upper Peninsula of Michigan. These data were used to infer the origin and maintenance of gene family variation, species divergence time, as well as gene family expansion and contraction. We identified a signal of common whole genome duplication events shared by core eudicots. We also found rapid evolution, namely fast expansion or fast contraction of gene families, in plant–pathogen interaction genes amongst the studied diploid species. Finally, the results lay the foundation for further research on the genetic diversity and adaptive capacity of forest trees, which will inform forest management and conservation policies.