Mature and old-growth (MOG) forests are superior to younger forests for mitigating the climate and biodiversity crises. MOG forests store far more carbon per hectare than younger forests, and continue to accumulate carbon for centuries if not logged or severely disturbed. However, forest and climate policies have not fully protected older forests and large trees for these benefits despite public concerns. Here, we document our novel approach to link remote sensing of MOG structural stages with the USDA Forest Service's Forest Inventory and Analysis (FIA) data to estimate forest area and carbon stocks by conterminous U.S. regions, landowner class, protection status, and maturity class. We found the greatest stock of carbon and area in mature forests (31.5B Mg, 156.5 M ha), followed by young forests (12.8B Mg, 71.9 M ha), and old-growth forests (7.9B Mg C, 35.3 M ha). Old-growth forests had the greatest carbon density (224 MgC ha-1), followed by mature (201 MgC ha-1), and young (178 MgC ha-1). Only about 18 % of the current stock of carbon in MOG forests is protected from logging. Protecting MOG from commercial timber harvest, while allowing mature forests to grow into old-growth forests, could increase accumulated forest carbon stocks by 10.8B Mg this century, comparable to 8 years of fossil fuel emissions in the United States. Stricter prohibitions from logging on Inventoried Roadless Areas of National Forests would account for 2.9B MgC increase. Avoiding logging of old-growth forests and large trees in mature forests would protect and increase this valuable carbon stock that cannot be replaced in the near term.

Fire is a natural disturbance capable of altering plant distributions and community assemblages, influencing species evolution through the selection of traits and strategies, and affecting biogeochemical cycles. This powerful tool of landscape transformation can negatively impact even a fire-dependent ecosystem when natural fire regimes are altered. In recent times, interactions between human activities in the Cerrado (e.g., deforestation and intentional fires used to clear land), and a hotter and drier climate (due to climate change), have altered natural fire regimes causing more frequent and intense fire events, negatively impacting biodiversity, human health, and the regional climate. These fire-disturbed areas are widespread and highly vulnerable to future degradation from compounding disturbances, but they still harbour valuable biodiversity and carbon stocks that deserve protection and restoration. Monitoring the impacts of fire disturbance on vegetation structure and the potential pathways of recovery is critical to understand and protect resilient ecosystems under a rapidly changing climate. Robust monitoring requires the integration of modelled and field-based data tools and techniques. Field inventories alone are insufficient to capture the spatiotemporal variability of impacts of fire on native vegetation and should be coupled with remotely sensed data, among which, LiDAR (light detection and ranging) is unparalleled in characterising 3-D vegetation structure. Thus, the combination of LiDAR and forest inventory data is ideally suited for scaling the impacts of fire on forest vegetation and associated carbon stocks. In this study, we are assessing key metrics of vegetation structure derived from a combination of LiDAR and field data collected at the Experimental Station Serra das Araras, Mato Grosso state, Brazil. This field site comprises Cerrado vegetation that has been subject to three experimental fire treatments: every year, every two years, and every three years beginning in 2017, as well as fire suppression for over three decades. We are investigating whether key vegetation structural metrics can capture different fire treatments and identify spatial patterns of disturbance. We are also assessing if these patterns are different when comparing LiDAR data collected with a handheld scanner versus an airborne drone. This study aims to refine our methods and improve our understanding of vegetation structure responses across a gradient of fire disturbance regimes and potential post-fire recovery trajectories, which are key not only for ecological studies but also for emerging carbon markets – one of several mechanisms aimed at achieving climate change mitigation, conservation, and sustainable development outcomes. We hope to improve the process of carbon stock mapping in disturbed ecosystems and use the outputs to drive scenarios modelling at larger scales, providing a more comprehensive assessment of what future Cerrado carbon dynamics might look like under a range of possible disturbance/recovery dynamics.

Approximately 2.5 × 106 square kilometers of the Amazon forest are currently degraded by fire, edge effects, timber extraction, and/or extreme drought, representing 38% of all remaining forests in the region. Carbon emissions from this degradation total up to 0.2 petagrams of carbon per year (Pg C year-1), which is equivalent to, if not greater than, the emissions from Amazon deforestation (0.06 to 0.21 Pg C year-1). Amazon forest degradation can reduce dry-season evapotranspiration by up to 34% and cause as much biodiversity loss as deforestation in human-modified landscapes, generating uneven socioeconomic burdens, mainly to forest dwellers. Projections indicate that degradation will remain a dominant source of carbon emissions independent of deforestation rates. Policies to tackle degradation should be integrated with efforts to curb deforestation and complemented with innovative measures addressing the disturbances that degrade the Amazon forest.

Aboveground biomass (AGB) is an essential variable in the study of the carbon cycle, and remote sensing provides the only viable means for mapping and monitoring biomass at large scales in time and space. Still, inconsistencies in biomass estimates are large which necessitates methods to achieve consistent mapping of biomass over time and space. In this study, we combine Lidar-derived biomass-estimates from GLAS measurements, time series analysis of 20 years of Landsat data, and machine learning algorithms to map biomass for a study area in the Amazon basin. The results show that we are able to map AGB consistently over space and time at annual intervals between 1999 and 2019, with a root-mean-square error (RMSE) of 64 to 92 Mg AGB ha−1 (depending on the evaluation methodology used) for the best performing models, with AGB estimates ranging between 0 to 600 Mg AGB ha−1. Models run with the Extreme gradient boosting (XGBoost) resulted in the lowest errors. The presented methodological approach makes it possible to map biomass over time in large areas with wide biomass ranges, and without saturation below 400 Mg AGB ha−1.

Mature and old-growth forests (collectively “mature”) and larger trees are important carbon sinks that are declining worldwide. Information on the carbon value of mature forests and larger trees in the United States has policy relevance for complying with President Joe Biden’s Executive Order 14072 directing federal agencies to define and conduct an inventory of them for conservation purposes. Specific metrics related to maturity can help land managers define and maintain present and future carbon stocks at the tree and forest stand level, while making an important contribution to the nation’s goal of net-zero greenhouse gas emissions by 2050. We present a systematic method to define and assess the status of mature forests and larger trees on federal lands in the United States that if protected from logging could maintain substantial carbon stocks and accumulation potential, along with myriad climate and ecological co-benefits. We based the onset of forest maturity on the age at which a forest stand achieves peak net primary productivity. We based our definition of larger trees on the median tree diameter associated with the tree age that defines the beginning of stand maturity to provide a practical way for managers to identify larger trees that could be protected in different forest ecosystems. The average age of peak net primary productivity ranged from 35 to 75 years, with some specific forest types extending this range. Typical diameter thresholds that separate smaller from larger trees ranged from 4 to 18 inches (10–46 cm) among individual forest types, with larger diameter thresholds found in the Western forests. In assessing these maturity metrics, we found that the unprotected carbon stock in larger trees in mature stands ranged from 36 to 68% of the total carbon in all trees in a representative selection of 11 National Forests. The unprotected annual carbon accumulation in live above-ground biomass of larger trees in mature stands ranged from 12 to 60% of the total accumulation in all trees. The potential impact of avoiding emissions from harvesting large trees in mature forests is thus significant and would require a policy shift to include protection of carbon stocks and future carbon accumulation as an additional land management objective on federal forest lands.

The 6.7 M ha Tongass National Forest in southeast Alaska, USA, supports a world-class salmon fishery, is one of the world’s most intact temperate rainforests, and is recognized for exceptional levels of carbon stored in woody biomass. We quantified biomass and soil organic carbon (C) by land use designation, Inventoried Roadless Areas (IRAs), young and productive old-growth forests (POGs), and 77 priority watersheds. We used published timber harvest volumes (roundwood) to estimate C stock change across five time periods from early historical (1909–1951) through future (2022–2100). Total soil organic and woody biomass C in the Tongass was 2.7 Pg, representing ~20% of the total forest C stock in the entire national forest system, the equivalent of 1.5 times the 2019 US greenhouse gas emissions. IRAs account for just over half the C, with 48% stored in POGs. Nearly 15% of all C is within T77 watersheds, >80% of which overlaps with IRAs, with half of that overlapping with POGs. Young growth accounted for only ~5% of the total C stock. Nearly two centuries of historical and projected logging would release an estimated 69.5 Mt CO2e, equivalent to the cumulative emissions of ~15 million vehicles. Previously logged forests within IRAs should be allowed to recover carbon stock via proforestation. Tongass old growth, IRAs, and priority watersheds deserve stepped-up protection as natural climate solutions.

Protected Areas (PAs) represent a broad spectrum of outcomes and governance systems. Among PAs, Community Managed PAs have emerged from communities that are not exclusively indigenous and have developed social organizations to acquire land rights, participate in forest governance, and in some cases, engage in REDD+. However, regardless of the scale or counterfactual, there is no clear consensus about Community Managed PAs’ effectiveness in forest conservation and climate change mitigation. Furthermore, previous studies have been devoted to estimating PAs’ effects on deforestation before REDD+ projects began to operate. Based on Community Concessions in Petén (Guatemala) and Extractive Reserves in Acre (Brazil), we analyzed Community Managed PAs’ temporal and spatial effects on carbon stocks and avoided emissions relative to unprotected lands, other Sustainable Use PAs (IUCN V-VI), and Strict PAs (I-IV). We used carbon density maps, matching methods, geographic discontinuity designs, and sensitivity analysis between 2003 and 2015. After controlling for the influence of market access and agriculture suitability, our analysis shows that Community Managed PAs were more effective than Other Lands (i.e., unprotected) and Sustainable Use PAs, and at least as effective as Strict PAs, in preserving carbon stocks and avoiding emissions. For instance, relative to Other Lands between 2011 and 2015, Community Managed PAs resulted in net avoided emissions of 4.6 tCO2-eq/ha in Petén (Guatemala) and 2.15 tCO2-eq/ha in Acre (Brazil). While these net avoided emissions were lower than in previous years, they seem to be driven by a reduction in carbon emissions outside Community Managed PAs. Spatially, the boundaries of Community Managed PAs varied across jurisdictions. For example, the boundaries of Acre’s Community Managed PAs’ have become less effective in avoiding emissions, which translates into reduced effects on conserving carbon stocks. Our results highlight the need to assess temporal effects to exhibit jurisdiction-wide land-use dynamics and spatial effects to identify local land-use pressures emerging inside or around the boundaries of PAs. Our analysis also shows that decentralized governance in Community Managed PAs may contribute to climate change mitigation through REDD+ and forest conservation targets.

This repository contains spatial and tabular data central to the analysis reported by Walker et al. (2022) on the global potential for increased storage of carbon on land. All maps provided here are global (excluding Antarctica) in geographic scope at a spatial resolution of ca. 500 meters in the MODIS sinusoidal projection (SR-ORG:6842). Maps are stored individually as single-band GeoTIFFs. Grid cell units for carbon density maps are megagrams of carbon per hectare (MgC/ha). Water has been masked out as NoData (-32768). Associated computer code is available for download from https://github.com/whrc/Global-Potential-Carbon.

Climate policy has thus far focused solely on carbon stocks and sequestration to evaluate the potential of forests to mitigate global warming. These factors are used to assess the impacts of different drivers of deforestation and forest degradation as well as alternative forest management. However, when forest cover, structure and composition change, shifts in biophysical processes (the water and energy balances) may enhance or diminish the climate effects of carbon released from forest aboveground biomass. The net climate impact of carbon effects and biophysical effects determines outcomes for forest and agricultural species as well as the humans who depend on them. Evaluating the net impact is complicated by the disparate spatio-temporal scales at which they operate. Here we review the biophysical mechanisms by which forests influence climate and synthesize recent work on the biophysical climate forcing of forests across latitudes. We then combine published data on the biophysical effects of deforestation on climate by latitude with a new analysis of the climate impact of the CO 2 in forest aboveground biomass by latitude to quantitatively assess how these processes combine to shape local and global climate. We find that tropical deforestation leads to strong net global warming as a result of both CO 2 and biophysical effects. From the tropics to a point between 30°N and 40°N, biophysical cooling by standing forests is both local and global, adding to the global cooling effect of CO 2 sequestered by forests. In the mid-latitudes up to 50°N, deforestation leads to modest net global warming as warming from released forest carbon outweighs a small opposing biophysical cooling. Beyond 50°N large scale deforestation leads to a net global cooling due to the dominance of biophysical processes (particularly increased albedo) over warming from CO 2 released. Locally at all latitudes, forest biophysical impacts far outweigh CO 2 effects, promoting local climate stability by reducing extreme temperatures in all seasons and times of day. The importance of forests for both global climate change mitigation and local adaptation by human and non-human species is not adequately captured by current carbon-centric metrics, particularly in the context of future climate warming.

Significance Despite increased interest in land-based carbon storage as a climate solution, there are physical limits on how much additional carbon can be incorporated into terrestrial ecosystems. To effectively determine where and how to act, jurisdictions need robust data illustrating the magnitude and distribution of opportunities to increase carbon storage, as well as information on the actions available to achieve that storage. Here, we provide globally consistent maps for directing additional carbon storage under current and future climate, as well as a framework for determining how that storage could be gained through restoration, improved management, or maintenance of woody biomass and soil organic matter. Our estimates provide an upper bound on how improved land stewardship can mitigate the climate crisis.

Carbon losses from forest degradation and disturbances are significant and growing sources of emissions in the Brazilian Amazon. Between 2003 and 2019, degradation and disturbance accounted for 44% of forest carbon losses in the region, compared with 56% from deforestation (forest clearing). We found that land tenure played a decisive role in explaining these carbon losses, with Undesignated Public Forests and Other Lands (e.g., private properties) accounting for the majority (82%) of losses during the study period. Illegal deforestation and land grabbing in Undesignated Public Forests widespread and increasingly are important drivers of forest carbon emissions from the region. In contrast, indigenous Territories and Protected Natural Areas had the lowest emissions, demonstrating their effectiveness in preventing deforestation and maintaining carbon stocks. These trends underscore the urgent need to develop reliable systems for monitoring and reporting on carbon losses from forest degradation and disturbance. Together with improved governance, such actions will be crucial for Brazil to reduce pressure on standing forests; strengthen Indigenous land rights; and design effective climate mitigation strategies needed to achieve its national and international climate commitments.

Many national and intergovernmental policy frameworks, including those of the EU and UK, currently treat biomass energy as zero-carbon at the point of combustion. Accordingly, they grant it access to financial and regulatory support available for other renewable energy sources. These incentives have driven a rapid increase in the consumption of biomass for energy, even though its combustion may increase atmospheric concentrations of carbon dioxide (CO2) for years or even decades to come.

Indigenous Territories (ITs) with less centralized forest governance than Protected Areas (PAs) may represent cost-effective natural climate solutions to meet the Paris agreement. However, the literature has been limited to examining the effect of ITs on deforestation, despite the influence of anthropogenic degradation. Thus, little is known about the temporal and spatial effect of allocating ITs on carbon stocks dynamics that account for losses from deforestation and degradation. Using Amazon Basin countries and Panama, this study aims to estimate the temporal and spatial effects of ITs and PAs on carbon stocks. To estimate the temporal effects, we use annual carbon density maps, matching analysis, and linear mixed models. Furthermore, we explore the spatial heterogeneity of these estimates through geographic discontinuity designs, allowing us to assess the spatial effect of ITs and PAs boundaries on carbon stocks. The temporal effects highlight that allocating ITs preserves carbon stocks and buffer losses as well as allocating PAs in Panama and Amazon Basin countries. The geographic discontinuity designs reveal that ITs' boundaries secure more extensive carbon stocks than their surroundings, and this difference tends to increase towards the least accessible areas, suggesting that indigenous land use in neotropical forests may have a temporarily and spatially stable impact on carbon stocks. Our findings imply that ITs in neotropical forests support Nationally Determined Contributions (NDCs) under the Paris Agreement. Thus, Indigenous peoples must become recipients of countries' results-based payments.

To constrain global warming, we must strongly curtail greenhouse gas emissions and capture excess atmospheric carbon dioxide1,2. Regrowing natural forests is a prominent strategy for capturing additional carbon3, but accurate assessments of its potential are limited by uncertainty and variability in carbon accumulation rates2,3. To assess why and where rates differ, here we compile 13,112 georeferenced measurements of carbon accumulation. Climatic factors explain variation in rates better than land-use history, so we combine the field measurements with 66 environmental covariate layers to create a global, one-kilometre-resolution map of potential aboveground carbon accumulation rates for the first 30 years of natural forest regrowth. This map shows over 100-fold variation in rates across the globe, and indicates that default rates from the Intergovernmental Panel on Climate Change (IPCC)4,5 may underestimate aboveground carbon accumulation rates by 32 per cent on average and do not capture eight-fold variation within ecozones. Conversely, we conclude that maximum climate mitigation potential from natural forest regrowth is 11 per cent lower than previously reported3 owing to the use of overly high rates for the location of potential new forest. Although our data compilation includes more studies and sites than previous efforts, our results depend on data availability, which is concentrated in ten countries, and data quality, which varies across studies. However, the plots cover most of the environmental conditions across the areas for which we predicted carbon accumulation rates (except for northern Africa and northeast Asia). We therefore provide a robust and globally consistent tool for assessing natural forest regrowth as a climate mitigation strategy. A one-kilometre-resolution map of aboveground carbon accumulation rates of forest regrowth shows 100-fold variation across the globe, with rates 32% higher on average than IPCC estimates.

Seasonally dry tropical forests (SDTFs) account for one-third of the interannual variability of global net primary productive (NPP). Large-scale shifts in dry tropical forest structure may thus significantly affect global CO2 fluxes in ways that are not fully accounted for in current projections. This study quantifies how changing climate might reshape one of the largest SDTFs in the world, the Caatinga region of northeast Brazil. We combine historical data and future climate projections under different representative concentration pathways (RCPs), together with spatially explicit aboveground biomass estimates to establish relationships between climate and vegetation distribution. We find that physiognomies, aboveground biomass, and climate are closely related in the Caatinga—and that the region’s bioclimatic envelope is shifting rapidly. From 2008–2017, more than 90% of the region has shifted to a dryer climate space compared to the reference period 1950–1979. An ensemble of global climate models (based on IPCC AR5) indicates that by the end of the 21st century the driest Caatinga physiognomies (thorn woodlands to non-vegetated areas) could expand from 55% to 78% (RCP 2.6) or as much as 87% (RCP8.5) of the region. Those changes would correspond to a decrease of 30%–50% of the equilibrium aboveground biomass by the end of the century (RCP 2.6 and RCP8.5, respectively). Our results are consistent with historic vegetation shifts reported for other SDTFs. Projected changes for the Caatinga would have large-scale impacts on the region’s biomass and biodiversity, underscoring the importance of SDTFs for the global carbon budget. Understanding such changes as presented in this study will be useful for regional planning and could help mitigate their negative social impacts.

This work is focused on characterizing and understanding the aboveground biomass of Caatinga in a semiarid region in northeastern Brazil. The quantification of Caatinga biomass is limited by the small number of field plots, which are inadequate for addressing the biome's extreme heterogeneity. Satellite-derived biomass products can address spatial and temporal changes but they have not been validated for seasonally dry tropical forests. Here we combine a compilation of published field phytosociological observations with a new 30m spatial resolution satellite biomass product. Both data were significantly correlated, satellite estimates consistently captured the wide variability of the biomass across the different physiognomies (2-272 Mg/ha). Based on the satellite product we show that in year 2000 about 50 percent of the region had very low biomass (<2 Mg/ha) and that the majority of the biomass (86%) is concentrated in only 27% of the area. Our work confirm other estimates of biomass 39 Mg/ha (9-61 Mg/ha) and carbon 0.79 PgC. The satellite products together with ground based estimates has the potential to improve forest management in Caatinga and other seasonally dry tropical forests through improved approximation of spatial variability, how they relate to climate, and support numerical modeling experiments in semiarid regions.

While improved management of agricultural landscapes is promoted as a promising natural climate solution, available estimates of the mitigation potential are based on coarse assessments of both agricultural extent and aboveground carbon density. Here we combine 30 meter resolution global maps of aboveground woody carbon, tree cover, and cropland extent, as well as a 1 km resolution map of global pasture land, to estimate the current and potential carbon storage of trees in nonforested portions of agricultural lands. We find that global croplands currently store 3.07 Pg of carbon (C) in aboveground woody biomass (i.e., trees) and pasture lands account for an additional 3.86 Pg C across a combined 3.76 billion ha. We then estimate the climate mitigation potential of multiple scenarios of integration and avoided loss of trees in crop and pasture lands based on region‐specific biomass distributions. We evaluate our findings in the context of nationally determined contributions and find that the majority of potential carbon storage from integration and avoided loss of trees in crop and pasture lands is in countries that do not identify agroforestry as a climate mitigation technique.

Maintaining the abundance of carbon stored aboveground in Amazon forests is central to any comprehensive climate stabilization strategy. Growing evidence points to indigenous peoples and local communities (IPLCs) as buffers against large-scale carbon emissions across a nine-nation network of indigenous territories (ITs) and protected natural areas (PNAs). Previous studies have demonstrated a link between indigenous land management and avoided deforestation, yet few have accounted for forest degradation and natural disturbances-processes that occur without forest clearing but are increasingly important drivers of biomass loss. Here we provide a comprehensive accounting of aboveground carbon dynamics inside and outside Amazon protected lands. Using published data on changes in aboveground carbon density and forest cover, we track gains and losses in carbon density from forest conversion and degradation/disturbance. We find that ITs and PNAs stored more than one-half (58%; 41,991 MtC) of the region's carbon in 2016 but were responsible for just 10% (-130 MtC) of the net change (-1,290 MtC). Nevertheless, nearly one-half billion tons of carbon were lost from both ITs and PNAs (-434 MtC and -423 MtC, respectively), with degradation/disturbance accounting for >75% of the losses in 7 countries. With deforestation increasing, and degradation/disturbance a neglected but significant source of region-wide emissions (47%), our results suggest that sustained support for IPLC stewardship of Amazon forests is critical. IPLCs provide a global environmental service that merits increased political protection and financial support, particularly if Amazon Basin countries are to achieve their commitments under the Paris Climate Agreement.

Better land stewardship is needed to achieve the Paris Agreement's temperature goal, particularly in the tropics, where greenhouse gas emissions from the destruction of ecosystems are largest, and where the potential for additional land carbon storage is greatest. As countries enhance their nationally determined contributions (NDCs) to the Paris Agreement, confusion persists about the potential contribution of better land stewardship to meeting the Agreement's goal to hold global warming below 2°C. We assess cost-effective tropical country-level potential of natural climate solutions (NCS)—protection, improved management and restoration of ecosystems—to deliver climate mitigation linked with sustainable development goals (SDGs). We identify groups of countries with distinctive NCS portfolios, and we explore factors (governance, financial capacity) influencing the feasibility of unlocking national NCS potential. Cost-effective tropical NCS offers globally significant climate mitigation in the coming decades (6.56 Pg CO 2 e yr −1 at less than 100 US$ per Mg CO 2 e). In half of the tropical countries, cost-effective NCS could mitigate over half of national emissions. In more than a quarter of tropical countries, cost-effective NCS potential is greater than national emissions. We identify countries where, with international financing and political will, NCS can cost-effectively deliver the majority of enhanced NDCs while transforming national economies and contributing to SDGs. This article is part of the theme issue ‘Climate change and ecosystems: threats, opportunities and solutions’.