• Energy Research

The response of forests to climate change depends in part on whether the photosynthetic benefit from increased atmospheric CO2(∆Ca= future minus historic CO2) compensates for increased physiological stresses from higher temperature (∆T). We predicted the outcome of these competing responses by using optimization theory and a mechanistic model of tree water transport and photosynthesis. We simulated current and future productivity, stress, and mortality in mature monospecific stands with soil, species, and climate sampled from 20 continental US locations. We modeled stands with and without acclimation to ∆Caand ∆T, where acclimated forests adjusted leaf area, photosynthetic capacity, and stand density to maximize productivity while avoiding stress. Without acclimation, the ∆Ca-driven boost in net primary productivity (NPP) was compromised by ∆T-driven stress and mortality associated with vascular failure. With acclimation, the ∆Ca-driven boost in NPP and stand biomass (C storage) was accentuated for cooler futures but negated for warmer futures by a ∆T-driven reduction in NPP and biomass. Thus, hotter futures reduced forest biomass through either mortality or acclimation. Forest outcomes depended on whether projected climatic ∆Ca/∆T ratios were above or below physiological thresholds that neutralized the negative impacts of warming. Critically, if forests do not acclimate, the ∆Ca/∆T must be aboveca. 89 ppm⋅°C−1to avoid chronic stress, a threshold met by 55% of climate projections. If forests do acclimate, the ∆Ca/∆T must rise aboveca. 67 ppm⋅°C−1for NPP and biomass to increase, a lower threshold met by 71% of projections.

AbstractPlant 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.

SummaryForests are a critical carbon sink and widespread tree mortality resulting from climate‐induced drought stress has the potential to alter forests from a carbon sink to a source, causing a positive feedback on climate change. Process‐based vegetation models aim to represent the current understanding of the underlying mechanisms governing plant physiological and ecological responses to climate. Yet model accuracy varies across scales, and regional‐scale model predictive skill is frequently poor when compared with observations of drought‐driven mortality. I propose a framework that leverages differences in model predictive skill across spatial scales, mismatches between model predictions and observations, and differences in the mechanisms included and absent across models to advance the understanding of the physiological and ecological processes driving observed patterns drought‐driven mortality.

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.

Forests play a major role in the global carbon cycle. Previous studies on the capacity of forests to sequester atmospheric CO 2 have mostly focused on carbon uptake, but the roles of carbon turnover time and its spatiotemporal changes remain poorly understood. Here, we used long-term inventory data (1955 to 2018) from 695 mature forest plots to quantify temporal trends in living vegetation carbon turnover time across tropical, temperate, and cold climate zones, and compared plot data to 8 Earth system models (ESMs). Long-term plots consistently showed decreases in living vegetation carbon turnover time, likely driven by increased tree mortality across all major climate zones. Changes in living vegetation carbon turnover time were negatively correlated with CO 2 enrichment in both forest plot data and ESM simulations. However, plot-based correlations between living vegetation carbon turnover time and climate drivers such as precipitation and temperature diverged from those of ESM simulations. Our analyses suggest that forest carbon sinks are likely to be constrained by a decrease in living vegetation carbon turnover time, and accurate projections of forest carbon sink dynamics will require an improved representation of tree mortality processes and their sensitivity to climate in ESMs.

AbstractCarbon use efficiency (CUE) represents how efficient a plant is at translating carbon gains through gross primary productivity (GPP) into net primary productivity (NPP) after respiratory costs (Ra). CUE varies across space with climate and species composition, but how CUE will respond to climate change is largely unknown due to uncertainty in Ra at novel high temperatures. We use a plant physiological model validated against global CUE observations and LIDAR vegetation canopy height data and find that model‐predicted decreases in CUE are diagnostic of transitions from forests to shrubland at dry range edges. Under future climate scenarios, we show mean growing season CUE increases in core forested areas, but forest extent decreases at dry range edges, with substantial uncertainty in absolute CUE due to uncertainty in Ra. Our results highlight that future forest resilience is nuanced and controlled by multiple competing mechanisms.

AbstractForest 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 CO2 fertilization 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 CO2 concentration 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.