Risks to mitigation potential of forests: Much recent attention has focused on the potential of trees and forests to mitigate ongoing climate change by acting as sinks for carbon. Anderegg et al. review the growing evidence that forests' climate mitigation potential is increasingly at risk from a range of adversities that limit forest growth and health. These include physical factors such as drought and fire and biotic factors, including the depredations of insect herbivores and fungal pathogens. Full assessment and quantification of these risks, which themselves are influenced by climate, is key to achieving science-based policy outcomes for effective land and forest management. Science , this issue p. eaaz7005

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.

Forests are major components of the carbon cycle, and disturbances are important influences of forest carbon. Our objective was to contribute to the understanding of forest carbon cycling by quantifying the amount of carbon in trees killed by two disturbance types, fires and bark beetles, in the western United States in recent decades. We combined existing spatial data sets of forest biomass, burn severity, and beetle-caused tree mortality to estimate the amount of aboveground and belowground carbon in killed trees across the region. We found that during 1984-2010, fires killed trees that contained 5-11 Tg C year-1 and during 1997-2010, beetles killed trees that contained 2-24 Tg C year-1 , with more trees killed since 2000 than in earlier periods. Over their periods of record, amounts of carbon in trees killed by fires and by beetle outbreaks were similar, and together these disturbances killed trees representing 9% of the total tree carbon in western forests, a similar amount to harvesting. Fires killed more trees in lower-elevation forest types such as Douglas-fir than higher-elevation forest types, whereas bark beetle outbreaks also killed trees in higher-elevation forest types such as lodgepole pine and Engelmann spruce. Over 15% of the carbon in lodgepole pine and spruce/fir forest types was in trees killed by beetle outbreaks; other forest types had 5-10% of the carbon in killed trees. Our results document the importance of these natural disturbances in the carbon budget of the western United States.

Insect outbreaks cause significant tree mortality across western North America, including in high-elevation whitebark pine forests. These forests are under several threats, which include attack by insects and white pine blister rust, as well as conversion to other tree species as a result of fire suppression. Mapping tree mortality is critical to determining the status of whitebark pine as a species. Satellite remote sensing builds upon existing aerial surveys by using objective, repeatable methods that can result in high spatial resolution monitoring. Past studies concentrated on level terrain and only forest vegetation type. The objective of this study was to develop a means of classifying whitebark pine mortality caused by a mountain pine beetle infestation in rugged, remote terrain using high spatial resolution satellite imagery. We overcame three challenges of mapping mortality in this mountainous region: (1) separating non-vegetated cover types, green and brown herbaceous cover, green (live) tree cover, and red-attack (dead) tree cover; (2) variations in illumination as a result of variations in slope and aspect related to the mountainous terrain of the study site; and (3) the difficulty of georegistering the imagery for use in comparing field measurements. Quickbird multi-spectral imagery (2.4 m spatial resolution) was used, together with a maximum likelihood classification method, to classify vegetation cover types over a 6400 ha area. To train the classifier, we selected pixels in each cover class from the imagery guided by our knowledge of the study site. Variables used in the maximum likelihood classifier included the ratio of red reflectance to green reflectance as well as green reflectance. These variables were stratified by solar incidence angle to account for illumination variability. We evaluated the results of the classified image using a reserved set of image-derived class members and field measurements of live and dead trees. Classification results yielded high overall accuracy (86% and 91% using image-derived class members and field measurements respectively) and kappa statistics (0.82 and 0.82) and low commission (0.9% and 1.5%) and omission (6.5% and 15.9%) errors for the red-attack tree class. Across the scene, 700 ha or 31% of the forest was identified as in the red-attack stage. Severity (percent mortality by canopy cover) varied from nearly 100% for some areas to regions with little mortality. These results suggest that high spatial resolution satellite imagery can provide valuable information for mapping and monitoring tree mortality even in rugged, mountainous terrain.

In the western United States, forest ecosystems are subject to a variety of forcing mechanisms that drive dynamics, including climate change, land‐use/land‐cover change, atmospheric pollution, and disturbance. To understand the impacts of these stressors, it is crucial to develop assessments of forest properties to establish baselines, determine the extent of changes, and provide information to ecosystem modeling activities. Here we report on spatial patterns of characteristics of forest ecosystems in the western United States, including area, stand age, forest type, and carbon stocks, and comparisons of these patterns with those from satellite imagery and simulation models. The USDA Forest Service collected ground‐based measurements of tree and plot information in recent decades as part of nationwide forest inventories. Using these measurements together with a methodology for estimating carbon stocks for each tree measured, we mapped county‐level patterns across the western United States. Because forest ecosystem properties are often significantly different between hardwood and softwood species, we describe patterns of each. The stand age distribution peaked at 60–100 years across the region, with hardwoods typically younger than softwoods. Forest carbon density was highest along the coast region of northern California, Oregon, and Washington and lowest in the arid regions of the Southwest and along the edge of the Great Plains. These results quantify the spatial variability of forest characteristics important for understanding large‐scale ecosystem processes and their controlling mechanisms. To illustrate other uses of the inventory‐derived forest characteristics, we compared them against examples of independently derived estimates. Forest cover compared well with satellite‐derived values when only productive stands were included in the inventory estimates. Forest types derived from satellite observations were similar to our inventory results, though the inventory database suggested more heterogeneity. Carbon stocks from the Century model were in good agreement with inventory results except in the Pacific Northwest and part of the Sierra Nevada, where it appears that harvesting and fire in the 20th century (processes not included in the model runs) reduced measured stand ages and carbon stocks compared to simulations.