Contents Summary 35 I. Introduction 36 II. Tree CH ₄ fluxes 36 III. Tree emissions of soil‐produced CH ₄ 40 IV. Tree‐produced CH ₄ 42 V. Trees in forest CH ₄ budgets 44 VI. Conclusions 46 Acknowledgements 48 Author contributions 48 References 48 Summary: Forest ecosystem methane ( CH ₄ ) research has focused on soils, but trees are also important sources and sinks in forest CH ₄ budgets. Living and dead trees transport and emit CH ₄ produced in soils; living trees and dead wood emit CH ₄ produced inside trees by microorganisms; and trees produce CH ₄ through an abiotic photochemical process. Here, we review the state of the science on the production, consumption, transport, and emission of CH ₄ by living and dead trees, and the spatial and temporal dynamics of these processes across hydrologic gradients inclusive of wetland and upland ecosystems. Emerging research demonstrates that tree CH ₄ emissions can significantly increase the source strength of wetland forests, and modestly decrease the sink strength of upland forests. Scaling from stem or leaf measurements to trees or forests is limited by knowledge of the mechanisms by which trees transport soil‐produced CH ₄ , microbial processes produce and oxidize CH ₄ inside trees, a lack of mechanistic models, the diffuse nature of forest CH ₄ fluxes, complex overlap between sources and sinks, and extreme variation across individuals. Understanding the complex processes that regulate CH ₄ source–sink dynamics in trees and forests requires cross‐disciplinary research and new conceptual models that transcend the traditional binary classification of wetland vs upland forest.

Summary: Tree stems from wetland, floodplain and upland forests can produce and emit methane (CH₄). Tree CH₄ stem emissions have high spatial and temporal variability, but there is no consensus on the biophysical mechanisms that drive stem CH₄ production and emissions. Here, we summarize up to 30 opportunities and challenges for stem CH₄ emissions research, which, when addressed, will improve estimates of the magnitudes, patterns and drivers of CH₄ emissions and trace their potential origin. We identified the need: (1) for both long‐term, high‐frequency measurements of stem CH₄ emissions to understand the fine‐scale processes, alongside rapid large‐scale measurements designed to understand the variability across individuals, species and ecosystems; (2) to identify microorganisms and biogeochemical pathways associated with CH₄ production; and (3) to develop a mechanistic model including passive and active transport of CH₄ from the soil–tree–atmosphere continuum. Addressing these challenges will help to constrain the magnitudes and patterns of CH₄ emissions, and allow for the integration of pathways and mechanisms of CH₄ production and emissions into process‐based models. These advances will facilitate the upscaling of stem CH₄ emissions to the ecosystem level and quantify the role of stem CH₄ emissions for the local to global CH₄ budget.

The Amazon Basin is at the center of an intensifying discourse about deforestation, land-use, and global change. To date, climate research in the Basin has overwhelmingly focused on the cycling and storage of carbon (C) and its implications for global climate. Missing, however, is a more comprehensive consideration of other significant biophysical climate feedbacks [i.e., CH₄, N₂O, black carbon, biogenic volatile organic compounds (BVOCs), aerosols, evapotranspiration, and albedo] and their dynamic responses to both localized (fire, land-use change, infrastructure development, and storms) and global (warming, drying, and some related to El Niño or to warming in the tropical Atlantic) changes. Here, we synthesize the current understanding of (1) sources and fluxes of all major forcing agents, (2) the demonstrated or expected impact of global and local changes on each agent, and (3) the nature, extent, and drivers of anthropogenic change in the Basin. We highlight the large uncertainty in flux magnitude and responses, and their corresponding direct and indirect effects on the regional and global climate system. Despite uncertainty in their responses to change, we conclude that current warming from non-CO₂ agents (especially CH₄ and N₂O) in the Amazon Basin largely offsets—and most likely exceeds—the climate service provided by atmospheric CO₂ uptake. We also find that the majority of anthropogenic impacts act to increase the radiative forcing potential of the Basin. Given the large contribution of less-recognized agents (e.g., Amazonian trees alone emit ~3.5% of all global CH₄), a continuing focus on a single metric (i.e., C uptake and storage) is incompatible with genuine efforts to understand and manage the biogeochemistry of climate in a rapidly changing Amazon Basin.

The American quaking aspen (Populus tremuloides Michx.) and its close relative, the Eurasian quaking aspen (Populus tremula L.), cover a realm that is perhaps the most expansive of all tree species in the world. In North America, sudden aspen decline (SAD) is a growing concern that marks the rapid decline of quaking aspen trees leading to mortality at the stand and landscape scale. Research suggests that drought and water stress are the primary causes of SAD. Predisposing factors (age, structure, and landscape position), as well as associated stressors (i.e., pests and pathogens), have been linked to mortality in affected stands. The conflation of multiple interacting factors across the aspen’s broad geographic range in North America has produced significant debate over the classification of SAD as a disease and the proper management of affected stands. Interestingly, no such effects have been reported for the Eurasian aspen. We here review and synthesize the growing body of literature for North America and suggest that SAD is a novel decline disease resulting from multiple inciting and interacting factors related to climate, land-use history, and successional dynamics. We suggest that the range of aspen observed at the onset of the 21st Century was bolstered by a wet period in western North America that coincided with widespread regional cutting and clearing of late-successional forests for timber and grazing. No comparable land-use history, successional status, or age-class structure is apparent or linked for Eurasian forests. Eurasian aspen is either absent or young in managed forests, or old and decadent in parks in Fenno-Scandinavia, or it grows more intimately with a more diverse mixture of tree species that have arisen from a longer period of frequent timber cutting in Russia. Based on these insights we provide recommendations for practical management techniques that can promote stand resilience and recovery across a range of stand conditions in North America. Managers should attempt to identify SAD-prone stands using the presence of predisposing conditions and focus treatments such as coppice or prescribed fire on stands with suitable topographies, elevations, and climates. We conclude that SAD will persist throughout the coming decades, given the enormity of past cutting history, fire exclusion, and current changes in climate until a more active restoration agenda is implemented.

Soil organic carbon influences several landscape ecological processes, and soils are becoming recognized as a mechanism to mitigate the negative impacts of climate change. There is a need to define methods and technologies for addressing soils’ spatial variability as well as the time and cost of sampling soil organic carbon (SOC). Visible and near-infrared spectroscopy have been suggested as a sampling tool to reduce inventory cost. We sampled nineteen ranch properties totaling 17,347 ha across Oklahoma and Texas in 2019 to evaluate the effectiveness and accuracy of a handheld reflectometer (Our Sci, Ann Arbor, MI, USA) (370–940 nm) and existing remote sensing approaches to estimate SOC in semi-arid grazing lands. Our data suggest that the Our Sci Reflectometer estimated soil organic carbon with a precision of approximately (±0.3% SOC); however, it was least accurate at higher carbon concentrations. The Our Sci reflectometer, although consistently accurate at lower SOC concentrations, was still less accurate than a model built using only remote sensing and digital soil map data as predictors. Combining the two data sources was the most accurate means of determining SOC. Our results indicated that the Our Sci handheld Vis-NIR reflectometer tested may have only limited applications for reducing inventory costs at scale.

Soils comprise the largest pool of terrestrial carbon yet have lost significant stocks due to human activity. Changes to land management in cropland and grazing systems present opportunities to sequester carbon in soils at large scales. Uncertainty in the magnitude of this potential impact is largely driven by the difficulties and costs associated with measuring near-surface (0–30 cm) soil carbon concentrations; a key component of soil carbon stock assessments. Many techniques exist to optimize sampling, yet few studies have compared these techniques at varying sample intensities. In this study, we performed ex-ante, high-intensity sampling for soil carbon concentrations at four farms in the eastern United States. We used post hoc Monte-Carlo bootstrapping to investigate the most efficient sampling approaches for soil carbon inventory: K-means stratification, Conditioned Latin Hypercube Sampling (cLHS), simple random, and regular grid. No two study sites displayed similar patterns across all sampling techniques, although cLHS and grid emerged as the most efficient sampling schemes across all sites and strata sizes. The number of strata chosen when using K-means stratification can have a significant impact on sample efficiency, and we caution future inventories from using small strata n, while avoiding even allocation of sample between strata. Our findings reinforce the need for adaptive sampling methodologies where initial site inventory can inform primary, robust inventory with site-specific sampling techniques.