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Forests sequester ∼25% of anthropogenic carbon (C) emissions annually and are of increasing interest for their potential as Nature‐based Climate Solutions (NbCS). Emergent from the need to assess terrestrial ecosystem health and quantify C storage and fluxes, several gridded products documenting terrestrial C and changes in C stocks over time have been developed. However, researchers have not yet systematically compared C distributions across products, or developed a clear path forward for investigating and leveraging this cross‐product uncertainty in estimates of terrestrial C. Alaniz et al. (2022,https://doi.org/10.1029/2021EF002560) synthesize multiple published products to constrain the distribution of forest C stocks and fluxes globally. Building off of their results, we comment on opportunities for advancing both basic science and NbCS policy recommendations through systematic product cross‐comparisons and targeting of areas with differing levels of uncertainties in the terrestrial C sink.

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.

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.

Forests 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.

Carbon 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 (R_a). CUE varies across space with climate and species composition, but how CUE will respond to climate change is largely unknown due to uncertainty inR_aat 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 inR_a. Our results highlight that future forest resilience is nuanced and controlled by multiple competing mechanisms.

Forests are currently a substantial carbon sink globally. Many climate change mitigation strategies leverage forest preservation and expansion, but rely on forests storing carbon for decades to centuries. Yet climate‐driven disturbances pose critical risks to the long‐term stability of forest carbon. We quantify the climate drivers that influence wildfire and climate stress‐driven tree mortality, including a separate insect‐driven tree mortality, for the contiguous United States for current (1984–2018) and project these future disturbance risks over the 21st century. We find that current risks are widespread and projected to increase across different emissions scenarios by a factor of >4 for fire and >1.3 for climate‐stress mortality. These forest disturbance risks highlight pervasive climate‐sensitive disturbance impacts on US forests and raise questions about the risk management approach taken by forest carbon offset policies. Our results provide US‐wide risk maps of key climate‐sensitive disturbances for improving carbon cycle modeling, conservation and climate policy.

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.

Read the freePlain Language Summaryfor this article on the Journal blog.

Carbon offsets are widely used by individuals, corporations, and governments to mitigate their greenhouse gas emissions on the assumption that offsets reflect equivalent climate benefits achieved elsewhere. These climate‐equivalence claims depend on offsets providing real and additional climate benefits beyond what would have happened, counterfactually, without the offsets project. Here, we evaluate the design of California's prominent forest carbon offsets program and demonstrate that its climate‐equivalence claims fall far short on the basis of directly observable evidence. By design, California's program awards large volumes of offset credits to forest projects with carbon stocks that exceed regional averages. This paradigm allows for adverse selection, which could occur if project developers preferentially select forests that are ecologically distinct from unrepresentative regional averages. By digitizing and analyzing comprehensive offset project records alongside detailed forest inventory data, we provide direct evidence that comparing projects against coarse regional carbon averages has led to systematic over‐crediting of 30.0 million tCO₂e (90% CI: 20.5–38.6 million tCO₂e) or 29.4% of the credits we analyzed (90% CI: 20.1%–37.8%). These excess credits are worth an estimated $410 million (90% CI: $280–$528 million) at recent market prices. Rather than improve forest management to store additional carbon, California's forest offsets program creates incentives to generate offset credits that do not reflect real climate benefits.

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.