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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 Tropical forest diversity governs forest structures, compositions, and influences the ecosystem response to environmental changes. Better representation of forest diversity in ecosystem demography (ED) models within Earth system models is thus necessary to accurately capture and predict how tropical forests affect Earth system dynamics subject to climate changes. However, achieving forest coexistence in ED models is challenging due to their computational expense and limited understanding of the mechanisms governing forest functional diversity. This study applies the advanced Multi‐Objective Population‐based Parallel Local Surrogate‐assisted search (MOPLS) optimization algorithm to simultaneously calibrate ecosystem fluxes and coexistence of two physiologically distinct tropical forest species in a size‐ and age‐structured ED model with realistic representation of wood harvest. MOPLS exhibits satisfactory model performance, capturing hydrological and biogeochemical dynamics observed in Barro Colorado Island, Panama, and robustly achieving coexistence for the two representative forest species. This demonstrates its effectiveness in calibrating tropical forest coexistence. The optimal solution is applied to investigate the recovery trajectories of forest biomass after various intensities of clear‐cut deforestation. We find that a 20% selective logging can take approximately 40 years for aboveground biomass to return to the initial level. This is due to the slow recovery rate of late successional trees, which only increases by 4% over the 40‐year period. This study lays the foundation to calibrate coexistence in ED models. MOPLS can be an effective tool to help better represent tropical forest diversity in Earth system models and inform forest management practices. 

Extending and safeguarding tropical forest ecosystems is critical for combating climate change and biodiversity loss. One of its constituents, lianas, is spreading and increasing in abundance on a global scale. This is particularly concerning as lianas negatively impact forests’ carbon fluxes, dynamics, and overall resilience, potentially exacerbating both crises. While possibly linked to climate-change-induced atmospheric CO₂elevation and drought intensification, the reasons behind their increasing abundance remain elusive. Prior research shows distinct physiological differences between lianas and trees, but it is unclear whether these differences confer a demographic advantage to lianas with climate change. Guided by extensive datasets collected in Panamanian tropical forests, we developed a tractable model integrating physiology, demography, and epidemiology. Our findings suggest that CO₂fertilization, a climate change factor promoting forest productivity, gives lianas a demographic advantage. Conversely, factors such as extreme drought generally cause a decrease in liana prevalence. Such a decline in liana prevalence is expected from a physiological point of view because lianas have drought-sensitive traits. However, our analysis underscores the importance of not exclusively relying on physiological processes, as interactions with demographic mechanisms (i.e., the forest structure) can contrast these expectations, causing an increase in lianas with drought. Similarly, our results emphasize that identical physiological responses between lianas and trees still lead to liana increase. Even if lianas exhibit collinear but weaker responses in their performance compared to trees, a temporary liana prevalence increase might manifest driven by the faster response time of lianas imposed by their distinct life-history strategies than trees. 

Abstract Lianas, woody vines acting as structural parasites of trees, have profound effects on the composition and structure of tropical forests, impacting tree growth, mortality, and forest succession. Remote sensing could offer a powerful tool for quantifying the scale of liana infestation, provided the availability of robust detection methods. We analyze the consistency and global geographic specificity of spectral signals—reflectance across wavelengths—from liana‐infested tree crowns and forest stands, examining the underlying mechanisms of these signals. We compiled a uniquely comprehensive database, including leaf reflectance spectra from 5424 leaves, fine‐scale airborne reflectance data from 999 liana‐infested canopies, and coarse‐scale satellite reflectance data covering 775 ha of liana‐infested forest stands. To unravel the mechanisms of the liana spectral signal, we applied mechanistic radiative transfer models across scales, establishing a synthesis of the relative importance of different mechanisms, which we corroborate with field data on liana leaf chemistry and canopy structure. We find a consistent liana spectral signal at canopy and stand scales across globally distributed sites. This signature mainly arises at the canopy level due to direct effects of more horizontal leaf angles, resulting in a larger projected leaf area, and indirect effects from increased light scattering in the near and short‐wave infrared regions, linked to lianas' less costly leaf construction compared with trees on average. The existence of a consistent global spectral signal for lianas suggests that large‐scale quantification of liana infestation is feasible. However, because the traits responsible for the liana canopy‐reflectance signal are not exclusive to lianas, accurate large‐scale detection requires rigorously validated remote sensing methods. Our models highlight challenges in automated detection, such as potential misidentification due to leaf phenology, tree life history, topography, and climate, especially where the scale of liana infestation is less than a single remote sensing pixel. The observed cross‐site patterns also prompt ecological questions about lianas' adaptive similarities in optical traits across environments, indicating possible convergent evolution due to shared constraints on leaf biochemical and structural traits. 

Synopsis Classic debates in community ecology focused on the complexities of considering an ecosystem as a super-organ or organism. New consideration of such perspectives could clarify mechanisms underlying the dynamics of forest carbon dioxide (CO2) uptake and water vapor loss, important for predicting and managing the future of Earth’s ecosystems and climate system. Here, we provide a rubric for considering ecosystem traits as aggregated, systemic, or emergent, i.e., representing the ecosystem as an aggregate of its individuals or as a metaphorical or literal super-organ or organism. We review recent approaches to scaling-up plant water relations (hydraulics) concepts developed for organs and organisms to enable and interpret measurements at ecosystem-level. We focus on three community-scale versions of water relations traits that have potential to provide mechanistic insight into climate change responses of forest CO2 and H2O gas exchange and productivity: leaf water potential (Ψcanopy), pressure volume curves (eco-PV), and hydraulic conductance (Keco). These analyses can reveal additional ecosystem-scale parameters analogous to those typically quantified for leaves or plants (e.g., wilting point and hydraulic vulnerability) that may act as thresholds in forest responses to drought, including growth cessation, mortality, and flammability. We unite these concepts in a novel framework to predict Ψcanopy and its approaching of critical thresholds during drought, using measurements of Keco and eco-PV curves. We thus delineate how the extension of water relations concepts from organ- and organism-scales can reveal the hydraulic constraints on the interaction of vegetation and climate and provide new mechanistic understanding and prediction of forest water use and productivity. 

Many tropical regions are experiencing an intensification of drought, with increasing severity and frequency of the events. However, the forest ecosystem response to these changes is still highly uncertain. It has been hypothesized that on short time scales (from diurnal to seasonal), tropical forests respond to water stress by physiological controls, such as stomata regulation and phenological adjustment, to control increasing atmospheric water demand and cope with reduced water supply. However, the interactions among biological processes and co-varying environmental factors that determine the ecosystem-level fluxes are still unclear. Furthermore, climate variability at longer time scales, such as that generated by ENSO, produces less predictable effects, which might vary among forests and ecoregions within the tropics. This study will present some emerging patterns of response to water stress from five years of observations of water, carbon, and energy fluxes on the seasonal tropical forest in Barro Colorado Island (Panama), including an increase in productivity during the 2015 El Niño. We will show how these responses will depend critically on the combination of environmental factors experienced by the forest along the seasonal cycle. These results suggest a critical role of plant hydraulics in mediating the response to water stress on a broad range of temporal scales, including during the wet seasons when water availability is not a limiting factor. The study also found that the response to large-scale drought events is contingent and might produce a different outcome in different tropical forest areas.