Abstract The integrity of forest-based climate solutions and carbon credits requires persistent carbon storage, but climate change is increasing the risk of natural disturbances that release carbon back into the atmosphere. Using global satellite data, disturbance modeling, and machine learning, we provide the first spatially explicit and scenario-based maps of long-term probability of carbon loss in global forests under different disturbance severities and climate scenarios. We find that North American conifer forests, tropical rainforests, and Asian (sub)tropical dry forests face the greatest risks, and that Eurasian temperate forests, African (sub)tropical dry forests face the lowest. Globally, the likelihood of reversals over 100 years is 31%−42% across all scenarios. Our work helps to maximize the benefits of forest-based climate solutions by informing more strategic project placement and more robust reversal-risk compensation mechanisms, such as buffer pools, and highlights critical additional science to better understand and manage risks of these essential climate solutions. Plain Language Summary Forests can help slow and lessen climate impacts. However, in places this benefit is becoming less reliable as climate change increases natural disturbances such as wildfires, drought, storms, and insect outbreaks, which can release stored carbon back into the atmosphere. In this study, we created the first scenario-based global maps of risks and found that the risk of carbon loss is widespread and highly variable across regions, with especially high vulnerability in North American conifer forests, tropical rainforests, and Asian tropical and subtropical dry forests. Our study highlights the importance of considering disturbance risks when siting forest projects for climate mitigation, and developing protocols for carbon markets, such as in voluntary programs and under the UNFCCC Paris Agreement. Key Points A demographic model framework estimates the reversal risk from natural disturbances over 100 years in global forests Spatially explicit maps under different severity scenarios show variation in the integrated 100-year risk of carbon reversal Spatially explicit maps estimate the required buffer pool needed to compensate for disturbance-driven reversals in global forests

Abstract Reforestation is a leading climate solution for removing carbon dioxide from the atmosphere, but generally decreases surface albedo, which diminishes its climate mitigation value. Knowing how quickly this albedo effect unfolds relative to carbon removal is critical for planning climate mitigation actions, yet the temporal changes in albedo are poorly described. This study uses satellite observations to characterize temporal changes in albedo with stand development for different forest types and ecoclimatic settings around the world. We find that about half of the climate warming effect from decreased albedo occurs within 40 years, but that it takes anywhere from 50 to 120 years to reach 80% of the full effect. The slowest declines occur in extra‐tropical regions and broadleaf forests and woody savannas. The fastest declines occur in tropical environments, and for needleleaf or mixed broadleaf‐needleleaf forests. Results were recast as a global map to help inform reforestation practitioners about the time it takes for reforestation's albedo‐driven warming to approach its maximum effect.

Although the reduction of fossil fuel emissions remains of the utmost importance to mitigate climate change, maintaining and enhancing carbon sinks in forests have been widely promoted as nature-based climate solutions1-4. However, disturbances that could result in losses of forest carbon stocks are poorly accounted for when estimating the potential role of forests in climate mitigation5-7. This makes it difficult to appropriately size 'buffer pools': a mechanism designed to compensate for unintended carbon losses in carbon crediting projects8,9. Here we use forest inventory, satellite data, disturbance modelling and machine learning to map reversal (carbon loss) risk in the contiguous United States (CONUS) from natural disturbance. Across CONUS forests, we show that climate change increases the 100-year risk of carbon losses from natural disturbance, particularly in California and the Intermountain West. The current buffer pool of the largest CONUS forest climate mitigation programme is likely too small by an average factor of 6.3, and this could range from 2.2- to 8.0-fold too small when considering uncertainties around future climate scenarios, disturbance severity and other carbon pools. We provide spatially explicit maps of the long-term risks to forest carbon losses from natural disturbances, which highlight that current methodologies used for constructing carbon offset buffer pools require revisions to succeed under climate change.

Accurate assessment of forest carbon dynamics is a critical element of appraising forest-based Natural Climate Solutions. National forest inventory and analysis (FIA) data provide valuable pool-based estimates of carbon stocks, but have been underutilized to inform carbon cycle modeling for forest carbon dynamics with stand development. This study introduces a hierarchical data assimilation (HDA) framework to optimize modeling parameters by incrementally assimilating measured carbon pool data into the model. We found that most carbon stocks could be reproduced by constrained parameters after each HDA step. Using aboveground live biomass (AGB) alone in HDA was able to reproduce the AGB trajectories but introduced biases in estimating the downstream dead biomass and soil carbon pools. Assimilating dead biomass measurements narrowed the posterior space of parameter solutions and improved consistency between measured and modeled carbon dynamics. The HDA framework also reduced uncertainties on modeled carbon fluxes. Young stands were found to release less carbon when the model was informed by dead biomass compared to simulations guided by aboveground biomass alone. The remaining mismatches between modeled and FIA pool estimates could be attributed to wide uncertainty in some FIA estimates, differing definitions of functional carbon pools, and structural rigidity in the model. Together, this study underscores the importance of pool-based measurements in forest carbon modeling, which improves the model-observation fit and reduces process-model uncertainty.

Biological nitrogen fixation (BNF) is the largest natural source of new nitrogen (N) that supports terrestrial productivity1,2, yet estimates of global terrestrial BNF remain highly uncertain3,4. Here we show that this uncertainty is partly because of sampling bias, as field BNF measurements in natural terrestrial ecosystems occur where N fixers are 17 times more prevalent than their mean abundances worldwide. To correct this bias, we develop new estimates of global terrestrial BNF by upscaling field BNF measurements using spatially explicit abundances of all major biogeochemical N-fixing niches. We find that natural biomes sustain lower BNF, 65 (52-77) Tg N yr-1, than previous empirical bottom-up estimates3,4, with most BNF occurring in tropical forests and drylands. We also find high agricultural BNF in croplands and cultivated pastures, 56 (54-58) Tg N yr-1. Agricultural BNF has increased terrestrial BNF by 64% and total terrestrial N inputs from all sources by 60% over pre-industrial levels. Our results indicate that BNF may impose stronger constraints on the carbon sink in natural terrestrial biomes and represent a larger source of agricultural N than is generally considered in analyses of the global N cycle5,6, with implications for proposed safe operating limits for N use7,8.

The climate benefits of some Voluntary Carbon Market projects may be overestimated due to a lack of accounting for albedo change. Here we analyze 172 Afforestation, Reforestation, and Revegetation projects within the market and find more than 10% occur in places where albedo may entirely negate the climate mitigation benefit, and a quarter occur in places where albedo may halve the mitigation benefit. Yet, the majority are concentrated where albedo changes are expected to be minimal, and 9% of projects occur where albedo would augment the mitigation benefit. Recent data are making albedo accounting possible, and we outline an iterative approach for incorporating albedo considerations into carbon crediting protocols to prioritize projects with greater climate benefit and more accurately quantify credits that may be used to address unabated emissions. We also call on the scientific community to create tools to enable accounting for other important biophysical changes, such as evapotranspiration, which is not yet quantifiable within the Voluntary Carbon Market.

Reforestation is a prominent climate change mitigation strategy, but available global maps of reforestation potential are widely criticized and highly variable, which limits their ability to provide robust estimates of both the locations and total area of opportunity. Here we develop global maps that address common critiques, build on a review of 89 reforestation maps created at multiple scales, and present eight reforestation scenarios with varying objectives, including providing ecosystem services, minimizing social conflicts, and delivering government policies. Across scenarios, we find up to 195 Mha (million hectares) are available (2225 TgCO2e (teragrams of carbon dioxide equivalent) per year total net mitigation potential), which is 71-92% smaller than previous estimates because of conservative modeling choices, incorporation of safeguards, and use of recent, high-resolution datasets. This area drops as low as 6 Mha (53 TgCO2e per year total net mitigation potential) if only statutorily protected areas are targeted. Few locations simultaneously achieve multiple objectives, suggesting that a mix of lands and restoration motivations will be needed to capitalize on the many potential benefits of reforestation.

Terrestrial ecosystems could contribute to climate mitigation through nature-based climate solutions (NbCS), which aim to reduce ecosystem greenhouse gas emissions and/or increase ecosystem carbon storage. Forests have the largest potential for NbCS, aligned with broader sustainability benefits, but-unfortunately-a broad body of literature has revealed widespread problems in forest NbCS projects and protocols that undermine the climate mitigation of forest carbon credits and hamper efforts to reach global net zero. Therefore, there is a need to bring better science and policy to improve NbCS climate mitigation outcomes going forward. Here we synthesize challenges to crediting forest NbCS and offer guidance and key next steps to make improvements in the implementation of these strategies immediately and in the near-term. We structure our Perspective around four key components of rigorous forest NbCS, illuminating key science and policy considerations and providing solutions to improve rigour. Finally, we outline a 'contribution approach' to support rigorous forest NbCS that is an alternative funding mechanism that disallows compensation or offsetting claims.

CO2 fertilization of the terrestrial biosphere is limited by nitrogen. Biological nitrogen fixation (BNF) is the dominant natural nitrogen source to the terrestrial biosphere and can alleviate nitrogen limitation but is poorly constrained in Earth system models (ESMs). Here, we compare terrestrial BNF from an ensemble of ESMs of the 6th Coupled Model Intercomparison Project to a new global synthesis of observations across natural and agricultural biomes. We find that compared to observations, ESMs underestimate agricultural BNF but overestimate natural BNF in the present day by over 50%. Natural BNF is overestimated in the most productive ecosystems that contribute most to the terrestrial carbon sink (forests and grasslands). ESMs with different BNF representations yield a range of BNF responses to CO2 enrichment. Some ESMs with phenomenological representations of BNF predict a natural BNF increase in response to a doubling of CO2 that aligns with a meta- analysis of CO2 enrichment experiments (31% increase) but fail to account for the substantial carbon cost of BNF. In contrast, ESMs with mechanistic representations of BNF account for its carbon cost as well as its regulation by nitrogen limitation but overestimate the BNF response to a doubling of CO2 (135% increase). Overall, all current BNF representations in ESMs fall short of fully capturing its response to rising atmospheric CO2. Finally, we find a positive correlation between modeled present- day natural BNF and the CO2 fertilization effect across ESMs, suggesting that overestimated natural BNF translates to an exaggerated CO2 fertilization effect of approximately 11% in ESMs.

Nature-based climate solutions (NbCSs) could play an important role in meeting the goals of the Paris Agreement. The contribution approach offers an alternative model to carbon offsetting for funding NbCSs. This paper presents three crucial design principles to help ensure the contribution approach results in high-quality climate and other benefits and avoids harms.

Restoring tree cover changes albedo, which is the fraction of sunlight reflected from the Earth’s surface. In most locations, these changes in albedo offset or even negate the carbon removal benefits with the latter leading to global warming. Previous efforts to quantify the global climate mitigation benefit of restoring tree cover have not accounted robustly for albedo given a lack of spatially explicit data. Here we produce maps that show that carbon-only estimates may be up to 81% too high. While dryland and boreal settings have especially severe albedo offsets, it is possible to find places that provide net-positive climate mitigation benefits in all biomes. We further find that on-the-ground projects are concentrated in these more climate-positive locations, but that the majority still face at least a 20% albedo offset. Thus, strategically deploying restoration of tree cover for maximum climate benefit requires accounting for albedo change and we provide the tools to do so.

Understanding vegetation recovery after fire is critical for predicting vegetation-mediated ecological dynamics in future climates. However, information characterizing vegetation recovery patterns after fire and their determinants over large geographical extents is limited. This study uses Moderate Resolution Imaging Spectroradiometer (MODIS) leaf area index (LAI) and albedo to characterize patterns of post-fire biophysical dynamics across the western United States (US) and further examines the influence of topo-climatic variables on the recovery of LAI and albedo at two different time horizons, 10 and 20 years post-fire, using a random forest model. Recovery patterns were derived for all wildfires that occurred between 1986 and 2017 across seven forest types and 21 level III ecoregions of the western US. We found differences in the characteristic trajectories of post-fire vegetation recovery across forest types and eco-climatic settings. In some forest types, LAI had recovered to only 60 %-70 % of the pre-fire levels by 25 years after the fire, while it recovered to 120 %-150 % of the pre-fire levels in other forest types, with higher absolute post-fire changes observed in forest types and ecoregions that had a higher initial pre-fire LAI. Our random forest results showed very little influence of fire severity on the recovery of both summer LAI and albedo at both post-fire time horizons. Post-fire vegetation recovery was most strongly controlled by elevation, with faster rates of recovery at lower elevations. Similarly, annual precipitation and average summer temperature had significant impacts on the post-fire recovery of vegetation. Full recovery was seldom observed when annual precipitation was less than 500 mm and average summer temperature was above the optimal range, i.e., 15-20 degrees C. Climate influences, particularly annual precipitation, were a major driver of post-fire summer albedo change through its impact on ecological succession. This study provides quantitative measures of primary controls that could be used to improve the modeling of ecosystem dynamics post-fire.

Structures from the Stone Age can provide unique insights into Late Glacial and Mesolithic cultures around the Baltic Sea. Such structures, however, usually did not survive within the densely populated Central European subcontinent. Here, we ...The Baltic Sea basins, some of which only submerged in the mid-Holocene, preserve Stone Age structures that did not survive on land. Yet, the discovery of these features is challenging and requires cross-disciplinary approaches between archeology and ...

Datasets and scripts (MATLAB and R) used to document patterns of post-fire biophysical dynamics in seven forest types and 21 Level III ecoregions of the western United States.

The replacement of natural lands with urban structures has multiple environmental consequences, yet little is known about the magnitude and extent of albedo-induced warming contributions from urbanization at the global scale in the past and future. Here, we apply an empirical approach to quantify the climate effects of past urbanization and future urbanization projected under different shared socioeconomic pathways (SSPs). We find an albedo-induced warming effect of urbanization for both the past and the projected futures under three illustrative scenarios. The albedo decease from urbanization in 2018 relative to 2001 has yielded a 100-year average annual global warming of 0.00014 [0.00008, 0.00021] °C. Without proper mitigation, future urbanization in 2050 relative to 2018 and that in 2100 relative to 2018 under the intermediate emission scenario (SSP2-4.5) would yield a 100-year average warming effect of 0.00107 [0.00057,0.00179] °C and 0.00152 [0.00078,0.00259] °C, respectively, through altering the Earth’s albedo.

This study examines the post-fire biogeophysical and biochemical dynamics after several high-severity wildfires that occurred in mixed conifer and ponderosa pine forest types in the Sierra Nevada and Klamath Mountains regions between 1986 and 2017. We found a consistent pattern of reduced leaf area index (LAI) in the first year after fire, followed by gradual recovery over the subsequent 25 years. Recovery rate varied between forest types. For example, average summer LAI for 16-25 years post-fire was 88% of the pre-fire average for mixed conifers in the Sierra Nevada, 64% for ponderosa pine in the Sierra Nevada, and 83% for mixed conifers in Klamath Mountains (63, 35, and 64% in winter, respectively). The slower recovery of LAI in ponderosa pine could be due to poor species diversity and drier climate. Summer and winter albedo increased progressively until 12 years post-fire in Sierra Nevada, while it continued to increase until 25 years post-fire in Klamath Mountains. Ponderosa pine had the highest summer (0.148 +/- 0.001) and winter (0.5 +/- 0.0033) albedos. Post-fire changes in evapotranspiration (ET) and gross primary productivity (GPP) were consistent with the changes in LAI. Both summer and winter ET and GPP returned to pre-fire levels by 25 years after fire in mixed conifers of both regions, while the ET and GPP did not recover to pre-fire levels in ponderosa pine. Wildfires increased the land surface temperature (LST) immediately after fire in summer. This effect was significantly higher in mixed conifers of the Sierra Nevada (11 +/- 0.03 degrees C) compared to Klamath Mountains (7 +/- 0.01 degrees C). Our results suggest that reduced ET, consistent with less leaf area and its associated reduced evaporative cooling is the main factor controlling the immediate post-fire warming effect of wildfires in these regions. The findings reported here can be used to understand ecological responses to wildfire in these and nearby ecoregions as they represent mean historical behavior across multiple wildfire events.

Storing carbon in forests is a leading land-based strategy to curb anthropogenic climate change, but its planetary cooling effect is opposed by warming from low albedo. Using detailed geospatial data from Earth-observing satellites and the national forest inventory, we quantify the net climate effect of losing forest across the conterminous United States. We find that forest loss in the intermountain and Rocky Mountain West causes net planetary cooling but losses east of the Mississippi River and in Pacific Coast states tend toward net warming. Actual U.S. forest conversions from 1986 to 2000 cause net cooling for a decade but then transition to a large net warming over a century. Avoiding these forest conversions could have yielded a 100-year average annual global cooling of 0.00088°C. This would offset 17% of the 100-year climate warming effect from a single year of U.S. fossil fuel emissions, underscoring the scale of the mitigation challenge.

Accurate quantification of forest carbon stocks and fluxes over regions is needed to monitor forest resources as they respond to changes in climate, disturbance and management, and also to evaluate contributions of forest sector to the regional and global carbon balances. In previous work we introduced a national forest carbon monitoring system (NFCMS) that combines forest inventory data, satellite remote sensing of stand biomass and forest disturbances, and an ecosystem carbon cycle model to assess contemporary forest carbon dynamics at a 30 m resolution. In this study, we evaluate the NFCMS estimates of biomass and carbon fluxes with available data products for the Pacific Northwest (PNW) region, and then analyze the regional carbon balance over the period 1986–2010. The biomass estimates have good agreements with evaluation datasets (eMapR, NBCD2000, and Hagen2005) at regional and forest type levels, and at spatial scales of 1 km2 and larger. Regionwide, PNW forests acted as a stable net sink for atmospheric CO2 (18.5 Tg C yr–1) within forestlands. However, harvesting activities removed significant amounts of carbon, equating to over 75% of annual net carbon sink, though only 25% of this (∼3.5 Tg C yr–1) is emitted to the atmosphere within 50 years. Wildfires contributed modestly to carbon emissions in most years, however, the severe fires of 2002 and 2006 released 16.6 and 7.1 Tg C, respectively. The study demonstrates the potential of the NFCMS framework to serve as a candidate measuring, reporting and verification system, informed by field and remotely sensed inventories, and tracking the carbon balance of the forest sector across the United States.

Understanding vegetation recovery after drought is critical for projecting vegetation dynamics in future climates. From 1997 to 2009, Australia experienced a long‐lasting drought known as the Millennium Drought (MD), which led to widespread reductions in vegetation productivity. However, vegetation recovery post‐drought and its determinants remain unclear. This study leverages remote sensing products from different sources—fraction of absorbed photosynthetically active radiation (FPAR), based on optical data, and canopy density, derived from microwave data—and random forest algorithms to assess drought recovery over Australian natural vegetation during a 20‐year period centered on the MD. Post‐drought recovery was prevalent across the continent, with 6 out of 10 drought events seeing full recovery within about 6 months. Canopy density was slower to recover than leaf area seen in FPAR. The probability of full recovery was most strongly controlled by drought return interval, post‐drought hydrological condition, and drought length. Full recovery was seldom observed when drought events occurred at intervals of 3 months or less, and moderately dry (standardized water balance anomaly [SWBA] within [−1, −0.76]) post‐drought conditions resulted in less complete recovery than wet (SWBA > 0.3) post‐drought conditions. Press droughts, which are long term but not extreme, delayed recovery more than pulse droughts (short term but extreme) and led to a higher frequency of persistent decline. Following press droughts, the frequency of persistent decline differed little among biome types but peaked in semi‐arid regions across aridity levels. Forests and savanna required the longest recovery times for press drought, while grasslands were the slowest to recover for pulse drought. This study provides quantitative thresholds that could be used to improve the modeling of ecosystem dynamics post‐drought.