Forestry – including afforestation (the planting of trees on land where they have not recently existed), reforestation, avoided deforestation, and forest management – can lead to increased sequestration of atmospheric carbon dioxide and has therefore been proposed as a strategy to mitigate climate change. However, forestry also influences land‐surface properties, including albedo (the fraction of incident sunlight reflected back to space), surface roughness, and evapotranspiration, all of which affect the amount and forms of energy transfer to the atmosphere. In some circumstances, these biophysical feedbacks can result in local climate warming, thereby counteracting the effects of carbon sequestration on global mean temperature and reducing or eliminating the net value of climate‐change mitigation projects. Here, we review published and emerging research that suggests ways in which forestry projects can counteract the consequences associated with biophysical interactions, and highlight knowledge gaps in managing forests for climate protection. We also outline several ways in which biophysical effects can be incorporated into frameworks that use the maintenance of forests as a climate protection strategy.

Mapping in situ eddy covariance measurements of terrestrial land–atmosphere fluxes to the globe is a key method for diagnosing the Earth system from a data-driven perspective. We describe the first global products (called X-BASE) from a newly implemented upscaling framework, FLUXCOM-X, representing an advancement from the previous generation of FLUXCOM products in terms of flexibility and technical capabilities. The X-BASE products are comprised of estimates of CO₂ net ecosystem exchange (NEE), gross primary productivity (GPP), evapotranspiration (ET), and for the first time a novel, fully data-driven global transpiration product (ET_T), at high spatial (0.05°) and temporal (hourly) resolution. X-BASE estimates the global NEE at −5.75 ± 0.33 Pg C yr⁻¹ for the period 2001–2020, showing a much higher consistency with independent atmospheric carbon cycle constraints compared to the previous versions of FLUXCOM. The improvement of global NEE was likely only possible thanks to the international effort to increase the precision and consistency of eddy covariance collection and processing pipelines, as well as to the extension of the measurements to more site years resulting in a wider coverage of bioclimatic conditions. However, X-BASE global net ecosystem exchange shows a very low interannual variability, which is common to state-of-the-art data-driven flux products and remains a scientific challenge. With 125 ± 2.1 Pg C yr⁻¹ for the same period, X-BASE GPP is slightly higher than previous FLUXCOM estimates, mostly in temperate and boreal areas. X-BASE evapotranspiration amounts to 74.7×10³ ± 0.9×10³ km³ globally for the years 2001–2020 but exceeds precipitation in many dry areas, likely indicating overestimation in these regions. On average 57 % of evapotranspiration is estimated to be transpiration, in good agreement with isotope-based approaches, but higher than estimates from many land surface models. Despite considerable improvements to the previous upscaling products, many further opportunities for development exist. Pathways of exploration include methodological choices in the selection and processing of eddy covariance and satellite observations, their ingestion into the framework, and the configuration of machine learning methods. For this, the new FLUXCOM-X framework was specifically designed to have the necessary flexibility to experiment, diagnose, and converge to more accurate global flux estimates.

Forest disturbances are major sources of carbon dioxide to the atmosphere, and therefore impact global climate. Biogeophysical attributes, such as surface albedo (reflectivity), further control the climate‐regulating properties of forests. Using both tower‐based and remotely sensed data sets, we show that natural disturbances from wildfire, beetle outbreaks, and hurricane wind throw can significantly alter surface albedo, and the associated radiative forcing either offsets or enhances the CO₂ forcing caused by reducing ecosystem carbon sequestration over multiple years. In the examined cases, the radiative forcing from albedo change is on the same order of magnitude as the CO₂ forcing. The net radiative forcing resulting from these two factors leads to a local heating effect in a hurricane‐damaged mangrove forest in the subtropics, and a cooling effect following wildfire and mountain pine beetle attack in boreal forests with winter snow. Although natural forest disturbances currently represent less than half of gross forest cover loss, that area will probably increase in the future under climate change, making it imperative to represent these processes accurately in global climate models.

We report on net ecosystem production (NEP) and key environmental controls on net ecosystem exchange (NEE) of carbon dioxide (CO₂) between a mangrove forest and the atmosphere in the coastal Florida Everglades. An eddy covariance system deployed above the canopy was used to determine NEE during January 2004 through August 2005. Maximum daytime NEE ranged from −20 to −25 μmol (CO₂) m⁻² s⁻¹ between March and May. Respiration (R_d) was highly variable (2.81 ± 2.41 μmol (CO₂) m⁻² s⁻¹), reaching peak values during the summer wet season. During the winter dry season, forest CO₂ assimilation increased with the proportion of diffuse solar irradiance in response to greater radiative transfer in the forest canopy. Surface water salinity and tidal activity were also important controls on NEE. Daily light use efficiency was reduced at high (>34 parts per thousand (ppt)) compared to low (<17 ppt) salinity by 46%. Tidal inundation lowered daytime R_d by ∼0.9 μmol (CO₂) m⁻² s⁻¹ and nighttime R_d by ∼0.5 μmol (CO₂) m⁻² s⁻¹. The forest was a sink for atmospheric CO₂, with an annual NEP of 1170 ± 127 g C m⁻² during 2004. This unusually high NEP was attributed to year‐round productivity and low ecosystem respiration which reached a maximum of only 3 g C m⁻² d⁻¹. Tidal export of dissolved inorganic carbon derived from belowground respiration likely lowered the estimates of mangrove forest respiration. These results suggest that carbon balance in mangrove coastal systems will change in response to variable salinity and inundation patterns, possibly resulting from secular sea level rise and climate change.

Disturbance processes of various types substantially modify ecosystem carbon dynamics both temporally and spatially, and constitute a fundamental part of larger landscape‐level dynamics. Forests typically lose carbon for several years to several decades following severe disturbance, but our understanding of the duration and dynamics of post‐disturbance forest carbon fluxes remains limited. Here we capitalize on a recent North American Carbon Program disturbance synthesis to discuss techniques and future work needed to better understand carbon dynamics after forest disturbance. Specifically, this paper addresses three topics: (1) the history, spatial distribution, and characteristics of different types of disturbance (in particular fire, insects, and harvest) in North America; (2) the integrated measurements and experimental designs required to quantify forest carbon dynamics in the years and decades after disturbance, as presented in a series of case studies; and (3) a synthesis of the greatest uncertainties spanning these studies, as well as the utility of multiple types of observations (independent but mutually constraining data) in understanding their dynamics. The case studies—in the southeast U.S., central boreal Canada, U.S. Rocky Mountains, and Pacific Northwest—explore how different measurements can be used to constrain and understand carbon dynamics in regrowing forests, with the most important measurements summarized for each disturbance type. We identify disturbance severity and history as key but highly uncertain factors driving post‐disturbance carbon source‐sink dynamics across all disturbance types. We suggest that imaginative, integrative analyses using multiple lines of evidence, increased measurement capabilities, shared models and online data sets, and innovative numerical algorithms hold promise for improved understanding and prediction of carbon dynamics in disturbance‐prone forests.