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Cyclonic storms, or hurricanes, are expected to intensify as ocean heat energy rises due to climate change. Ecological theory suggests that tropical forest resistance to hurricanes should increase with forest age and wood density. However, most data on hurricane effects on tropical forests come from a limited number of well‐studied long‐term monitoring sites, restricting our capacity to evaluate the resistance of tropical forests to hurricanes across broad environmental gradients.

Intraspecific variation in functional traits may mediate tree species' drought resistance, yet whether trait variation is due to genotype (G), environment (E), or G×E interactions remains unknown. Understanding the drivers of intraspecific trait variation and whether variation mediates drought response can improve predictions of species' response to future drought.

Climate change‐triggered forest die‐off is an increasing threat to global forests and carbon sequestration but remains extremely challenging to predict. Tree growth resilience metrics have been proposed as measurable proxies of tree susceptibility to mortality. However, it remains unclear whether tree growth resilience can improve predictions of stand‐level mortality. Here, we use an extensive tree‐ring dataset collected at ~3000 permanent forest inventory plots, spanning 13 dominant species across the US Mountain West, where forests have experienced strong drought and extensive die‐off has been observed in the past two decades, to test the hypothesis that tree growth resilience to drought can explain and improve predictions of observed stand‐level mortality. We found substantial increases in growth variability and temporal autocorrelation as well declining drought resistance and resilience for a number of species over the second half of the 20th century. Declining resilience and low tree growth were strongly associated with cross‐ and within‐species patterns of mortality. Resilience metrics had similar explicative power compared to climate and stand structure, but the covariance structure among predictors implied that the effect of tree resilience on mortality could partially be explained by stand and climate variables. We conclude that tree growth resilience offers highly valuable insights on tree physiology by integrating the effect of stressors on forest mortality but may have only moderate potential to improve large‐scale projections of forest die‐off under climate change.

Forest productivity projections remain highly uncertain, notably because underpinning physiological controls are delicate to disentangle. Transient perturbation of global climate by large volcanic eruptions provides a unique opportunity to retrospectively isolate underlying processes. Here, we use a multi‐proxy dataset of tree‐ring records distributed over the Northern Hemisphere to investigate the effect of eruptions on tree growth and photosynthesis and evaluate CMIP6 models. Tree‐ring isotope records denoted a widespread 2–4 years increase of photosynthesis following eruptions, likely as a result of diffuse light fertilization. We found evidence that enhanced photosynthesis transiently drove ring width, but the latter further exhibited a decadal anomaly that evidenced independent growth and photosynthesis responses. CMIP6 simulations reproduced overall tree growth decline but did not capture observed photosynthesis anomaly, its decoupling from tree growth or the climate sensitivities of either processes, highlighting key disconnects that deserve further attention to improve forest productivity projections under climate change.

Climate change is stressing many forests around the globe, yet some tree species may be able to persist through acclimation and adaptation to new environmental conditions. The ability of a tree to acclimate during its lifetime through changes in physiology and functional traits, defined here as its acclimation potential, is not well known.

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Understanding the driving mechanisms behind existing patterns of vegetation hydraulic traits and community trait diversity is critical for advancing predictions of the terrestrial carbon cycle because hydraulic traits affect both ecosystem and Earth system responses to changing water availability. Here, we leverage an extensive trait database and a long-term continental forest plot network to map changes in community trait distributions and quantify “trait velocities” (the rate of change in community-weighted traits) for different regions and different forest types across the United States from 2000 to the present. We show that diversity in hydraulic traits and photosynthetic characteristics is more related to local water availability than overall species diversity. Finally, we find evidence for coordinated shifts toward communities with more drought-tolerant traits driven by tree mortality, but the magnitude of responses differs depending on forest type. The hydraulic trait distribution maps provide a publicly available platform to fundamentally advance understanding of community trait change in response to climate change and predictive abilities of mechanistic vegetation models.

Prediction of ecosystem responses to a changing climate is challenging at the landscape to regional scale, in part because topography creates various habitats and influences ecosystem productivity in complex ways. However, the effects of topography on ecosystem function remain poorly characterized and quantified. To address this knowledge gap, we developed a framework to systematically quantify and evaluate the effects of topographic convergence, elevation, aspect, and forest type on the long‐term (1986–2011) average and interannual variability of remotely sensed ecosystem productivity. In a forested watershed in the Rocky Mountains, spanning elevations from 1,800 to 4,000 m, we found a prevalent and positive influence of topographic convergence on long‐term productivity. Interannual growing season productivity was positively related to precipitation, with higher sensitivity in low elevation and highly productive areas and lower sensitivity in convergent areas. Our findings highlight the influence of topographic complexity on both long‐term and interannual variations of ecosystem productivity and have implications for understanding and prediction of ecosystem dynamics at hillslope to regional scales.

Plant functional traits provide a link in process‐based vegetation models between plant‐level physiology and ecosystem‐level responses. Recent advances in physiological understanding and computational efficiency have allowed for the incorporation of plant hydraulic processes in large‐scale vegetation models. However, a more mechanistic representation of water limitation that determines ecosystem responses to plant water stress necessitates a re‐evaluation of trait‐based constraints for plant carbon allocation, particularly allocation to leaf area. In this review, we examine model representations of plant allocation to leaves, which is often empirically set by plant functional type‐specific allometric relationships. We analyze the evolution of the representation of leaf allocation in models of different scales and complexities. We show the impacts of leaf allocation strategy on plant carbon uptake in the context of recent advancements in modeling hydraulic processes. Finally, we posit that deriving allometry from first principles using mechanistic hydraulic processes is possible and should become standard practice, rather than using prescribed allometries. The representation of allocation as an emergent property of scarce resource constraints is likely to be critical to representing how global change processes impact future ecosystem dynamics and carbon fluxes and may reduce the number of poorly constrained parameters in vegetation models.

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). These developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. Here, we review the developments that permit the representation of plant demographics inESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections but also allow models to be applied to new processes and questions concerning the dynamics of real‐world ecosystems. We argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first‐generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter‐disciplinary communication.