Search for: All records

Summary Plant functional traits are powerful ecological tools, but the relationships between plant traits and climate (or environmental variables more broadly) are often remarkably weak. This presents a paradox: Plant traits govern plant interactions with their environment, but the environment does not strongly predict the traits of plants living there. Unpacking this paradox requires differentiating the mechanisms of trait variation and potential confounds of trait–environment relationships at different evolutionary and ecological scales ranging from within species to among communities. It also necessitates a more integrated understanding of physiological and evolutionary equifinality among many traits and plant strategies, and challenges us to understand how supposedly ‘functional’ traits integrate into a whole‐organism phenotype in ways that may be largely orthogonal to environmental tolerances. 

Summary Predictive relationships between plant traits and environmental factors can be derived at global and regional scales, informing efforts to reorient ecological models around functional traits. However, in a changing climate, the environmental variables used as predictors in such relationships are far from stationary. This could yield errors in trait–environment model predictions if timescale is not accounted for.Here, the timescale dependence of trait–environment relationships is investigated by regressingin situtrait measurements of specific leaf area, leaf nitrogen content, and wood density on local climate characteristics summarized across several increasingly long timescales.We identify contrasting responses of leaf and wood traits to climate timescale. Leaf traits are best predicted by recent climate timescales, while wood density is a longer term memory trait. The use of sub‐optimal climate timescales reduces the accuracy of the resulting trait–environment relationships.This study concludes that plant traits respond to climate conditions on the timescale of tissue lifespans rather than long‐term climate normals, even at large spatial scales where multiple ecological and physiological mechanisms drive trait change. Thus, determining trait–environment relationships with temporally relevant climate variables may be critical for predicting trait change in a nonstationary climate system. 

Abstract Terrestrial photosynthesis requires the evaporation of water (transpiration) in exchange for CO₂needed to form sugars. The water for transpiration is drawn up through plant roots, stem, and branches via a water potential gradient. However, this flow of water—or sap ascent—requires energy to lift the water to the canopy and to overcome the resistance of the plant’s water transporting xylem. Here, we use a combination of field measurements of plant physiology (hydraulic conductivity) and state‐of‐the‐science global estimates of transpiration to calculate how much energy is passively harvested by plants to power the sap ascent pump across the world’s terrestrial vegetation. Globally, we find that 0.06 W/m²is consumed in sap ascent over forest dominated ecosystems or 9.4 PWh/yr (equal to global hydropower energy production). Though small in comparison to other components of the Earth’s surface energy budget, sap ascent work in forests represents 14.2% of the energy compared to the energy consumed to create sugars through photosynthesis, with values up to 18% in temperate rainforests. The power needed for sap ascent generally increases with photosynthesis, but is moderated by both climate and plant physiology, as the most work is consumed in regions with large transpiration fluxes (such as the moist tropics) and in areas where vegetation has low conductivity (such as temperate rainforests dominated by conifer trees). Here, we present a bottom‐up analysis of sap ascent work that demonstrates its significant role in plant function across the globe. 

Abstract Climate change‐driven drought stress has triggered numerous large‐scale tree mortality events in recent decades. Advances in mechanistic understanding and prediction are greatly limited by an inability to detect in situ where trees are likely to die in order to take timely measurements and actions. Thus, algorithms of early warning and detection of drought‐induced tree stress and mortality could have major scientific and societal benefits. Here, we leverage two consecutive droughts in the southwestern United States to develop and test a set of early warning metrics. Using Landsat satellite data, we constructed early warning metrics from the first drought event. We then tested these metrics' ability to predict spatial patterns in tree physiological stress and mortality from the second drought. To test the broader applicability of these metrics, we also examined a separate drought in the Amazon rainforest. The early warning metrics successfully explained subsequent tree mortality in the second drought in the southwestern US, as well as mortality in the independent drought in tropical forests. The metrics also strongly correlated with spatial patterns in tree hydraulic stress underlying mortality, which provides a strong link between tree physiological stress and remote sensing during the severe drought and indicates that the loss of hydraulic function during drought likely mediated subsequent mortality. Thus, early warning metrics provide a critical foundation for elucidating the physiological mechanisms underpinning tree mortality in mature forests and guiding management responses to these climate‐induced disturbances. 

Abstract Plants are critical mediators of terrestrial mass and energy fluxes, and their structural and functional traits have profound impacts on local and global climate, biogeochemistry, biodiversity, and hydrology. Yet, Earth System Models (ESMs), our most powerful tools for predicting the effects of humans on the coupled biosphere–atmosphere system, simplify the incredible diversity of land plants into a handful of coarse categories of “Plant Functional Types” (PFTs) that often fail to capture ecological dynamics such as biome distributions. The inclusion of more realistic functional diversity is a recognized goal for ESMs, yet there is currently no consistent, widely accepted way to add diversity to models, that is, to determine what new PFTs to add and with what data to constrain their parameters. We review approaches to representing plant diversity in ESMs and draw on recent ecological and evolutionary findings to present an evolution‐based functional type approach for further disaggregating functional diversity. Specifically, the prevalence of niche conservatism, or the tendency of closely related taxa to retain similar ecological and functional attributes through evolutionary time, reveals that evolutionary relatedness is a powerful framework for summarizing functional similarities and differences among plant types. We advocate that Plant Functional Types based on dominant evolutionary lineages (“Lineage Functional Types”) will provide an ecologically defensible, tractable, and scalable framework for representing plant diversity in next‐generation ESMs, with the potential to improve parameterization, process representation, and model benchmarking. We highlight how the importance of evolutionary history for plant function can unify the work of disparate fields to improve predictive modeling of the Earth system. 

Abstract Species often respond to human‐caused climate change by shifting where they occur on the landscape. To anticipate these shifts, we need to understand the forces that determine where species currently occur. We tested whether a long‐hypothesised trade‐off between climate and competitive constraints explains where tree species grow on mountain slopes. Using tree rings, we reconstructed growth sensitivity to climate and competition in range centre and range margin tree populations in three climatically distinct regions. We found that climate often constrains growth at environmentally harsh elevational range boundaries, and that climatic and competitive constraints trade‐off at large spatial scales. However, there was less evidence that competition consistently constrained growth at benign elevational range boundaries; thus, local‐scale climate‐competition trade‐offs were infrequent. Our work underscores the difficulty of predicting local‐scale range dynamics, but suggests that the constraints on tree performance at a large‐scale (e.g. latitudinal) may be predicted from ecological theory. 

Abstract Drought‐induced tree mortality is projected to increase due to climate change, which will have manifold ecological and societal impacts including the potential to weaken or reverse the terrestrial carbon sink. Predictions of tree mortality remain limited, in large part because within‐species variations in ecophysiology due to plasticity or adaptation and ecosystem adjustments could buffer mortality in dry locations. Here, we conduct a meta‐analysis of 50 studies spanning >100 woody plant species globally to quantify how populations within species vary in vulnerability to drought mortality and whether functional traits or climate mediate mortality patterns. We find that mortality predominantly occurs in drier populations and this pattern is more pronounced in species with xylem that can tolerate highly negative water potentials, typically considered to be an adaptive trait for dry regions, and species that experience higher variability in water stress. Our results indicate that climate stress has exceeded physiological and ecosystem‐level tolerance or compensating mechanisms by triggering extensive mortality at dry range edges and provides a foundation for future mortality projections in empirical distribution and mechanistic vegetation models. 

Summary Large intraspecific functional trait variation strongly impacts many aspects of communities and ecosystems, and is the medium upon which evolution works. Yet intraspecific trait variation is inconsistent and hard to predict across traits, species and locations.We measured within‐species variation in leaf mass per area (LMA), leaf dry matter content (LDMC), branch wood density (WD), and allocation to stem area vs leaf area in branches (branch Huber value (HV)) across the aridity range of seven Australian eucalypts and a co‐occurringAcaciaspecies to explore how traits and their variances change with aridity.Within species, we found consistent increases in LMA, LDMC and WD and HV with increasing aridity, resulting in consistent trait coordination across leaves and branches. However, this coordination only emerged across sites with large climate differences. Unlike trait means, patterns of trait variance with aridity were mixed across populations and species. Only LDMC showed constrained trait variation in more xeric species and drier populations that could indicate limits to plasticity or heritable trait variation.Our results highlight that climate can drive consistent within‐species trait patterns, but that patterns might often be obscured by the complex nature of morphological traits, sampling incomplete species ranges or sampling confounded stress gradients. 

Abstract Forest leaf area has enormous leverage on the carbon cycle because it mediates both forest productivity and resilience to climate extremes. Despite widespread evidence that trees are capable of adjusting to changes in environment across both space and time through modifying carbon allocation to leaves, many vegetation models use fixed carbon allocation schemes independent of environment, which introduces large uncertainties into predictions of future forest responses to atmospheric CO₂fertilization and anthropogenic climate change. Here, we develop an optimization‐based model, whereby tree carbon allocation to leaves is an emergent property of environment and plant hydraulic traits. Using a combination of meta‐analysis, observational datasets, and model predictions, we find strong evidence that optimal hydraulic–carbon coupling explains observed patterns in leaf allocation across large environmental and CO₂concentration gradients. Furthermore, testing the sensitivity of leaf allocation strategy to a diversity in hydraulic and economic spectrum physiological traits, we show that plant hydraulic traits in particular have an enormous impact on the global change response of forest leaf area. Our results provide a rigorous theoretical underpinning for improving carbon cycle predictions through advancing model predictions of leaf area, and underscore that tree‐level carbon allocation to leaves should be derived from first principles using mechanistic plant hydraulic processes in the next generation of vegetation models.