Effectively halt deforestation, other forms of conversion, and degradation across terrestrial ecosystems

Photo by Marcelo Perez del Carpio/Climate Visuals Countdown

Not only is land-use change across forests, peatlands, grasslands and coastal wetlands the leading direct driver of terrestrial biodiversity loss, but it also releases substantial emissions and weakens these ecosystems’ ability to sequester carbon.

Land-use change is the principal direct driver of terrestrial biodiversity loss — and effectively halting it across the world’s forests, peatlands, grasslands and coastal wetlands represents a critical step toward reversing rapid declines in nature.

Agricultural expansion is the leading driver of deforestation and degradation

Agricultural expansion poses the most significant threat to these ecosystems, with urbanization, mining and afforestation exerting smaller but increasingly acute pressures. Clearing forests to make way for croplands and pasturelands drove nearly 95% of deforestation globally between 2016 and 2025, while aquaculture, rice cultivation and palm oil production collectively spurred roughly 43% of mangrove losses between 2000 and 2020. Similarly, agricultural activities are primarily responsible for degradation across peatlands and grasslands, with recent years seeing a sharp rise across the tropics.

How deforestation, other forms of ecosystem conversion, and degradation threaten biodiversity

These land-use changes ultimately shrink, fragment or otherwise degrade thousands of species’ habitats, which reduces their total abundance and richness across terrestrial ecosystems and heightens the risk of local and global extinctions. Subsequent changes in the composition of species — and how they interact with each other — can also alter ecosystem functions and undermine the delivery of vital ecosystem services to humanity. These losses in species, ecosystem functions and ecosystem services are not always linear and can accelerate quite rapidly. They can also be quite difficult to recover — and in some instances may be irreversible.

How land-use change exacerbates climate change by disrupting carbon sequestration and storage

By disrupting carbon cycling across forests, peatlands, grasslands and coastal wetlands, land-use change is also exacerbating climate change. Together, these ecosystems hold roughly 1,800 gigatons of carbon (GtC) — more than triple the total amount of carbon emitted from fossil fuels since 1850.

One estimate indicates almost a quarter of these carbon stocks (~440 GtC) are highly vulnerable to human disturbances and would be released following conversion to croplands, urban development or other land-uses. Some of these carbon losses can occur quite rapidly, such as when large-scale commodity producers clear-cut forests for agricultural production.

Once lost, much of this carbon would be difficult for ecosystems to recover in time to help the world reach net zero by around mid-century. For example, fully rebuilding depleted carbon stocks could take 6-10 decades for forests, well over a century for mangroves and centuries to millennia for peatlands. Therefore, effectively halting deforestation, other forms of ecosystem conversion and ecosystem degradation, can deliver the lion’s share of mitigation needed from the land sector through 2050.

The world has largely fallen short in halting deforestation and degradation

Despite the significant role that protecting terrestrial ecosystems — particularly those that are intact and relatively undisturbed by human activities — can play in combatting the climate and biodiversity crises, global efforts to effectively halt deforestation, other forms of ecosystem conversion and degradation remain vastly inadequate. Across all indicators with sufficient data and near-term targets, recent rates of change are either well off track or heading in the wrong direction entirely. And even where data is too limited to assess global progress, available evidence suggests that current actions are falling short and dramatic changes are urgently needed to get on track.

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Tracking progress on global outcomes

11868: Deforestation, as measured by the annual rate of gross tree cover losses that are likely permanent

Status: Well Off Track

Historical Data Methodology and Challenges:

To approximate deforestation globally, we estimated gross tree cover loss (Mha/yr) that likely resulted in permanent conversion of forest cover to new, non-forested land cover or land uses. We relied on a combination of three datasets available on Global Nature Watch: tree cover loss from Hansen et al. 2013 updated to the most recent year of data, tree cover loss by dominant direct driver from Sims et al. 2025 updated to the most recent year of data, and humid tropical primary forest extent from Turubanova et al. 2018. More specifically, we summed the area of all tree cover loss from Hansen et al. 2013 within areas whose dominant direct driver, as defined by Sims et al. 2025 was classified as permanent agriculture, hard commodities (e.g., mining and energy infrastructure), and settlements and infrastructure, as well as all tree cover loss due to the expansion of shifting cultivation as defined by Sims et al. 2025 within humid tropical primary forests as identified by Turubanova et al. 2018, as these losses are likely to represent permanent deforestation. We excluded the shifting cultivation class outside of humid tropical primary forests as identified by Turubanova et al. 2018, as well as the logging, wildfire and other natural disturbance classes, as these are likely to be more temporary in nature and followed by forest regrowth. Note that when fire is used to clear land for agriculture, the land cleared for agriculture is included in the relevant agriculture class (permanent agriculture or shifting cultivation). Finally, we removed any areas that overlapped with our data on mangrove loss as defined by Murray et al. 2022 to avoid double-counting.

Our deforestation proxy indicator has several limitations. The Sims et al. 2025 data on global forest loss drivers, which we used to filter the tree cover loss data for this indicator, represents the dominant driver of loss at 1 kilometer (km) resolution over the entire time series from 2001 to 2025. It does not show multiple drivers if they occur in close proximity at a scale smaller than 1 km, nor does it detail the sequence of drivers if multiple occurred at different times within the period. As a result, the driver of some small-scale loss events when multiple drivers occur in close proximity may not always be captured. The data also does not distinguish between the loss of natural, managed or planted forests. Therefore, loss due to permanent agriculture may include some management of tree crop or agroforestry systems. Additionally, the Hansen et al. 2013 tree cover loss data may underestimate smaller-scale forest clearings due to the limitations of detecting such losses with medium-resolution satellite data, and the accuracy of the data varies by biome. Finally, the Hansen et al. 2013 tree cover loss dataset has undergone improvements over time, including algorithm adjustments that increase sensitivity to the detection of smaller-scale disturbances, as well as changes in satellite image availability with the launch of new Landsat satellites. However, changes to the methodology have been minimal since 2015. Detailed assessments of the accuracy of each dataset used for the deforestation proxy can be found in the source publications.

Target Methodology:

Targets to Limit Warming to 1.5°C: We did not use the avoided deforestation area estimate associated with Roe et al. 2021’s bottom-up, cost-effective mitigation potential (3.56 GtCO₂e/yr from 2020 to 2050) because one of the source papers used does not exclude temporary cycles of forest loss associated with managed forests in its baseline. This is inconsistent with other estimates and prior State of Climate Action reports, which constrain this measure to the permanent conversion of forests to other land uses.

Instead, we derived 2030 and 2050 targets from Roe et al. 2019’s “land sector roadmap for 2050,” which identifies the reductions in greenhouse gas (GHG) emissions from deforestation needed to achieve a similar mitigation potential (3.6 GtCO₂e/yr in 2050). This mitigation potential estimate was constrained to account for meeting humanity’s food and fiber needs. More specifically, this roadmap calls for reducing GHG emissions from deforestation by 70% by 2030 and 95% by 2050, relative to 2018 levels. To derive the area-based targets for this indicator, we assumed that the area of deforestation will also need to be reduced by 70% by 2030 and 95% by 2050, following the same approach used in the State of Climate Action 2021. We then used data from Global Nature Watch to calculate the 2030 and 2050 targets based on these percentage reductions from the 2018 level (6.2 Mha). Finally, to establish a 2035 target, we assumed a linear ramp down in deforestation between the 2030 and 2050 area-based targets. Because the mitigation potential for deforestation is roughly similar in Roe et al. 2019 (3.6 GtCO₂e/yr in 2050) and Roe et al. 2021 (3.56 GtCO₂ e/yr from 2020 to 2050), we assumed that these targets will still provide the bottom-up, cost-effective mitigation potential estimated by Roe et al. 2021.
Targets to Minimize Biodiversity Loss: We did not set a separate target focused on minimizing biodiversity losses because the 1.5°C-aligned target is derived from a technical potential constrained by social and environmental safeguards. One limitation of this approach is that targets derived from bottom-up estimates of mitigation potential that rely on geospatial analysis to optimize carbon benefits may differ from those that prioritize biodiversity conservation.

Progress Assessment Methodology:

Covering roughly 4 billion hectares, forests contain much of the world’s terrestrial biodiversity. By one estimate, these ecosystems are home to about 80% of amphibian species, 75% of bird species and 68% of mammal species. Forests also deliver many ecosystem services upon which humanity depends. They purify water and air, regulate surface and groundwater flows, sustain rainfall patterns, prevent landslides, control floods, serve as important cultural sites and provide life-saving medicines, food, forage and fodder to communities near and far.

Among the many contributions forests provide for people, one of the most important is their vital role in regulating the climate. Accounting for both human-caused and naturally occurring removals, these ecosystems take up an average of 14.4 gigatonnes of carbon dioxide (GtCO₂) from the atmosphere each year and store a total of roughly 870 gigatonnes of carbon (GtC) — nearly twice as much as the total amount of carbon emitted from fossil fuels since 1850. Notably, tropical forests provide additional climate benefits that extend far beyond carbon sequestration and storage by sustaining biophysical mechanisms like evapotranspiration that cool the Earth’s surface and near-surface air.

Despite the enormous benefits they offer, forests face significant pressures. Driven primarily by agricultural expansion, deforestation accounts for the majority of net anthropogenic emissions from land use, land-use change and forestry. To help limit warming to 1.5 degrees C (2.7 degrees F) and conserve terrestrial biodiversity, the world must effectively halt deforestation. Annual deforestation rates need to decline sharply to 1.9 million hectares per year (Mha/yr) by 2030, 1.5 Mha/yr by 2035 and 0.31 Mha/yr by 2050.

Global efforts to achieve these targets remain well off track. Although deforestation rates dropped from a record high of 11 Mha/yr in 2017 to 7.0 Mha/yr in 2025, the past five years have witnessed a small spike in deforestation — up to 8.4 Mha/yr in 2023. Consequently, the average annual rate of deforestation between 2016 and 2025 has fallen only slightly, at just 0.3 Mha/yr. To get on track for 2030, these declines must accelerate threefold.

11869: Primary forest loss, as measured by the annual rate of gross tree cover losses in humid tropical primary forests and in temperate and boreal intact forest landscapes

Status: Wrong Direction

Historical Data Methodology and Challenges:

Primary forests have been comprehensively mapped only in the humid tropics, and data measuring gross losses of global primary forest extent is not available. Given these limitations, we follow the Global Forest Review in relying on a combination of datasets available on Global Nature Watch to estimate all tree cover losses, including those from fires, in tropical, temperate, and boreal primary forests.

To approximate losses of tropical primary forests, we rely on two datasets: tree cover loss from Hansen et al. 2013 updated to the most recent year of data, and humid tropical primary forests from Turubanova et al. 2018, which the authors define as “mature natural humid tropical forest cover that has not been completely cleared and regrown in recent history.” This data excludes losses in primary forests across the dry tropics (e.g., western Madagascar), as well as in primary forests across boreal and temperate regions.
To approximate losses of temperate and boreal primary forests, we also rely on two datasets: tree cover loss from Hansen et al. 2013 updated to the most recent year of data, and intact forest landscapes from Potapov et al. 2017 updated to the most recent year of data in temperate and boreal regions. One limitation of relying on the Potapov et al. 2017 data is that, because it uses a minimum area threshold of 50,000 ha in defining intact forest landscapes, the data presented here may exclude tree cover losses in smaller patches of temperate and boreal primary forests.

Target Methodology:

Targets to Limit Warming to 1.5°C: 1.5°C-compatible targets focused on reducing primary forest loss are not available.
Targets to Minimize Biodiversity Loss: Díaz et al. 2020 synthesize the available evidence and, based on their expert evaluation, map out a high-ambition road to recovery needed to deliver the vision of the Global Biodiversity Framework. Within this “road to recovery,” Díaz et al. 2020 call for no loss in area or integrity of critical ecosystems between 2020 and 2030, with safeguards that avoid substitution between ecosystems. We interpret this goal as no gross losses in critical ecosystems over this period and, though not specified, likely beyond it. Primary forests constitute “critical ecosystems,” following the definition outlined in a report that many authors of Díaz et al. 2020 presented to the Subsidiary Body on Scientific, Technical and Technological Advice under the Convention on Biological Diversity.

Progress Assessment Methodology:

While tree cover losses across all forests trigger biodiversity loss and greenhouse gas (GHG) emissions, those within primary forests are particularly concerning. These old-growth forests have experienced little to no recent human disturbances and their ecological structure and functions remain intact. As a result, primary forests, especially those in the tropics, contain disproportionately high levels of species abundance and richness, and tend to sequester and store more carbon than other forests.

Any loss of these critical ecosystems — permanent or temporary — risks triggering long-term and potentially irreversible ecological changes. Even if forest regrowth occurs, it may take decades (if not longer) for these ecosystems to regain species diversity, ecosystem structure and ecosystem functions, all of which impact carbon cycling and GHG fluxes.

Ending primary forest loss immediately would deliver substantial climate and biodiversity benefits. Yet tree cover losses across these ecosystems are heading in the wrong direction, increasing by an average of 0.15 million hectares per year (Mha/yr) between 2016 and 2025. In total over this 10-year period, the world lost 75 Mha of primary forests, an area roughly the size of Zambia.

Roughly 60% of these losses over the past 10 years occurred in humid tropical primary forests, which saw annual rates of tree cover loss reach an all-time-high of 6.7 Mha/yr in 2024 before declining slightly to 4.3 Mha/yr in 2025. In recent years, fires, primarily ignited by humans to clear land for agricultural production but exacerbated by drought, have played an increasingly large role in humid tropical primary forests, accounting for nearly half of losses in 2024 and just over a third in 2025.

Trends in temperate and boreal primary forests remain more uncertain. To date, no comprehensive spatial dataset exists for these primary forests, but tree cover losses in intact forest landscapes offer a useful approximation. According to that data, a total of 30 Mha of temperate and boreal intact forest landscapes — an area nearly the size of Italy — experienced tree cover losses in the last 10 years, with annual rates rising from 2.7 Mha/yr in 2016 to 3.4 Mha/yr in 2025. Russia and Canada saw the highest levels of tree cover losses in intact forest landscapes, primarily driven by logging and fires.

11873: Forest loss in Key Biodiversity Areas, as measured by the annual rate of gross tree cover losses within these areas

Status: Right Direction

Historical Data Methodology and Challenges:

Following the Global Forest Review, we rely on a combination of two datasets — tree cover loss from Hansen et al. 2013 updated to the most recent year of data and the KBA Dashboard — to approximate all forest losses in forested KBAs, including those from fires. This data is published on Global Nature Watch and the KBA Dashboard. We similarly rely on tree cover loss from Hansen et al. 2013 updated to the most recent year of data and the Global AZE Map to approximate all forest losses within forested AZEs, including those from fires. One limitation of relying on this data is that it does not distinguish between naturally occurring and anthropogenic disturbances, and not all tree cover loss from naturally occurring disturbances are ecologically harmful.

Target Methodology:

Targets to Limit Warming to 1.5°C: 1.5°C-compatible targets focused on reducing forest loss within KBAs, including AZEs, are not available.
Targets to Minimize Biodiversity Loss: Díaz et al. 2020 synthesizes the available evidence and, based on their expert evaluation, map out a high-ambition road to recovery needed to deliver the vision of the Global Biodiversity Framework. Within this “road to recovery,” Díaz et al. 2020 calls for no loss in area or integrity of critical ecosystems between 2020 and 2030, with safeguards that avoid substitution between ecosystems. We interpret this goal as no gross losses in critical ecosystems over this period and, though not specified, likely beyond it. Forested KBAs, including AZEs, constitute “critical ecosystems,” following the definition outlined in a report that many authors of Díaz et al. 2020 presented to the Subsidiary Body on Scientific, Technical and Technological Advice under the Convention on Biological Diversity.

Progress Assessment Methodology:

Key Biodiversity Areas (KBAs) play a critical role in sustaining all facets of biodiversity at the genetic level, among species and across ecosystems. These sites are essentially irreplaceable because they contribute significantly to the global persistence of species facing the threat of extinction and ecosystems at risk of collapse; geographically restricted species and ecosystems; ecologically intact communities that sustain large-scale ecological processes; and/or areas that sustain vital ecological processes like providing refugia for threatened species or nursery grounds.

A subset of KBAs that contain the last remaining populations of one or more species assessed as Endangered or Critically Endangered by the International Union for Conservation of Nature — also known as Alliance for Zero Extinction (AZE) sites — are especially important to protect. Thus far, over 8,300 KBAs have been identified across nearly 820 million hectares (Mha) of the world’s terrestrial ecosystems, with just over 12% of these KBAs qualifying as AZE sites.

The loss of even a small fraction of these areas can have an outsized impact on global conservation efforts. This is particularly true for KBAs and AZEs within forests, given that these ecosystems contain much of the world’s terrestrial biodiversity. Between 2016 and 2025, tree cover losses within KBAs — a best available proxy for forest habitat loss in these areas — declined slightly by an annual average of 36,000 hectares per year (ha/yr), falling from 2.7 Mha/yr in 2016 to 2.0 Mha/yr in 2025. Over this ten-year period, the world lost a total of roughly 22 Mha of tree cover, 14% of which occurred in AZEs. Getting on track to immediately end forest loss in KBAs, and especially in AZEs, will require sustained and sharper declines in these losses.

11886: Forest degradation, as measured by the global net extent of forests that transitioned to a lower integrity class

Status: Right Direction

11876: Forest degradation due to fire, as measured by the annual rate of gross tree cover losses caused by fire

Status: Wrong Direction

Historical Data Methodology and Challenges:

To approximate forest degradation caused by fires, we use the tree cover loss from fire data, from Tyukavina et al. 2022 updated to the most recent year. This data is published on Global Nature Watch.

Global data that fully captures the multiple dimensions and complexities of forest degradation is not available. Other datasets like the Forest Landscape Integrity Index (see Forest degradation) offer a partial proxy for the global extent of forest degradation; however, this data may underestimate forest degradation because it does not account for all naturally occurring disturbances like floods or fires that can also spur substantial, long-term losses in ecosystem integrity in forests not adapted to these extreme events. Tracking tree cover losses from fires, then, complements this dataset. However, it is important to note that not all tree cover loss from fires in fire-adapted forests results in degradation.

Target Methodology:

1.5°C-compatible targets for reducing fires are not available. Similarly, there is no scientific consensus on what constitutes a sufficiently ambitious target for terrestrial biodiversity conservation, and the literature generally lacks quantitative and time-bound targets for this indicator. Accordingly, we can only indicate the direction of change required, as informed by IPBES 2019 and IPCC 2022.

Progress Assessment Methodology:

Increasingly extreme wildfires — driven in part by climate change, deforestation and inappropriate fire regimes — are burning some of the world’s most carbon-rich, biodiverse ecosystems, from old-growth, boreal forests across Canada and Siberia to humid tropical primary forests in the Amazon and Congo Basins.

These fires are increasing in severity and frequency across both fire-adapted forest ecosystems, where fire plays an essential ecological role, and fire-sensitive forest ecosystems, where fires are often started by humans and can be ecologically disruptive. This increased fire frequency can create a harmful feedback loop in which fires drive forest degradation that not only heightens these ecosystems’ vulnerability to future fires but drives further degradation and even complete loss of forests.

Degradation from fires can bring catastrophic harm to biodiversity, carbon stores and soil health. For example, in fire-sensitive humid tropical primary forests, fires intensify during drought years, reducing forest canopy height. In the Amazon Basin, these fires not only reduce aboveground carbon stocks but slow the recovery of forest fauna. Similarly, in North American fire-adapted boreal forests, severe and frequent fires decrease these ecosystems’ carbon stores and impede natural regeneration.

Yet far too little attention has been paid to forest degradation, in part because it is challenging to define and measure. Different perceptions of which forest attributes (e.g., tree species composition, canopy cover, tree height) matter most can result in different definitions of this phenomenon. Furthermore, forest degradation tends to occur incrementally and often involves subtle changes from short-lived disturbances that can be difficult to detect for global forest monitoring systems relying on medium-resolution satellite imagery — for example, unless these images are taken shortly after the disturbance, canopy cover can quickly obscure changes in forest condition. Consequently, there is not yet a dataset that can fully capture the multiple dimensions and complexities of forest degradation.

Tree cover losses from fire offer a useful, though partial proxy for measuring forest degradation, particularly when tracked alongside other datasets that do not account for fires, like the Forest Landscape Integrity Index. Between 2016 and 2025, tree cover losses from fires increased by an annual average of 0.45 million hectares per year (Mha/yr), rising from 9.6 Mha/yr in 2016 to 11 Mha/yr in 2025. The world lost a total of 93 Mha of tree cover due to fires over this 10-year period, and just five countries — Canada, Russia, Brazil, the United States and Bolivia — accounted for roughly 90% of these losses in 2025. Recent changes are heading in the wrong direction for reducing and halting forest degradation caused by fires.

11850: Peatland degradation, as measured by the annual rate of gross drained organic soils

Status: Insufficient Data

Historical Data Methodology and Challenges:

We relied on FAOSTAT data on the area of histosols drained for agriculture (cropland and grassland), based on the methods of Conchedda and Tubiello 2020, as a helpful, albeit limited proxy for peatland degradation. More specifically, we calculated the net increase in the area of histosols drained for agriculture over the most recent 10 years of data (2012-2022) and divided the total increase in area by the number of years to determine the average annual rate of drainage.

While the area of histosols drained for agriculture represents a proxy for peatland degradation, this data may underestimate peatland degradation for several reasons. First, the data focuses on drainage of histosols solely for agricultural activities, and although agriculture is primarily responsible for peatland degradation globally, other direct drivers — such as road and infrastructure development, forestry, oil sands mining and peat extraction — are not included in the estimates from Conchedda and Tubiello 2020. Moreover, the threshold of peat depth used to define peatland varies by country, and some countries have yet to establish a nationally recognized definition of peatlands. In nations where this threshold is numerically lower than the depth of organic material used to define organic soil in Conchedda and Tubiello 2020, peatland degradation may not be included in these estimates of drained organic soils. As a result, the global extent of histosols is significantly lower than most recent estimates for peatland area (e.g., UNEP 2022), and estimates of the area of histosols drained for agricultural activities (25 Mha) are substantially lower than estimates of the global area of degraded peatlands (57 Mha).

Target Methodology:

Targets to Limit Warming to 1.5°C: We did not use the avoided peatland degradation area estimate associated with Roe et al. 2021’s bottom-up, cost-effective mitigation potential, because it is not defined relative to a historical baseline. Rather, it is the difference in peatland degradation in 2035 between two Shared Socioeconomic Pathway 2—Representative Concentration Pathway 2.6 (SSP2-RCP2.6) scenarios modeled in Humpenöder et al. 2020, using a model called MAgPIE that combines biophysical and economic approaches to simulate spatially explicit global land-use scenarios.

Instead, we followed Roe et al. 2019’s “land sector roadmap for 2050,” which identifies the reductions in GHG emissions from peatland degradation needed to help achieve the sector’s target of mitigating 14 GtCO₂e/yr in 2050. Roe et al. 2019 derived this GHG emissions reduction estimate from Griscom et al. 2017’s “maximum additional” mitigation potential for peatland degradation, which was estimated by assuming that recent rates of peatland degradation fall to 0 by 2030 and that no additional degradation occurs between 2030 and 2050. Finally, because the mitigation potential for this activity is higher in Roe et al. 2019 (0.75 GtCO₂e/yr in 2050) than in Roe et al. 2021 (0.21 GtCO₂e/yr from 2020 to 2050), we assumed that these targets are still in line with 1.5°C pathways. Neither estimate of mitigation potential includes avoided emissions from peat fires.
Targets to Minimize Biodiversity Loss: By calling for entirely halting peatland degradation by 2030, the 1.5°C-aligned targets already reflect the highest possible ambition by the end of this decade and, therefore, what is needed to minimize terrestrial biodiversity losses.

Progress Assessment Methodology:

Outcome indicators in this system experience high interannual variability in historical data due to both anthropogenic and natural causes. To account for this variability, 10 years instead of 5 years are used to calculate the linear trendline where possible. However, global data for peatland degradation is insufficient to assess.

Peatlands are global hotspots for carbon sequestration and long-term storage, covering just 3.8% of the planet’s land but containing roughly 610 gigatonnes of carbon (GtC) globally — more than the total amount of carbon emitted from fossil fuel combustion since preindustrial times. These ecosystems also hold large stores of organic nitrogen, as their waterlogged soils slow decomposition and allow carbon- and nitrogen-rich peat to accumulate over millennia.

But when peatlands lose water (e.g., when they are drained for agriculture), oxygen can enter the upper layers of the soil, spurring decomposition and leading to losses of stored carbon and nitrogen. These degraded peatlands then emit carbon dioxide and nitrous oxide for decades or even centuries, until all peat is lost or their soils are rewetted. Draining peatlands also increases the risk of peat fires, which can lead to additional and substantial greenhouse gas emissions (e.g., in the United Kingdom).

Degradation also impedes peatlands’ ability to sustain other vital ecosystem services like filtering out pollutants from water, absorbing floodwaters and regulating nutrient cycling. Additionally, peatlands are home to many endemic species, as well as threatened or Critically Endangered megafauna like orangutans, bonobos, western lowland gorillas and African forest elephants. These wetlands also provide habitat to a host of animals that use them intermittently, like migrating birds.

Limiting global warming to 1.5 degrees C (2.7 degrees F) and conserving biodiversity will require the annual rate of peatland degradation globally to fall to zero as soon as possible and by 2030 at the very latest, with no additional degradation from 2030 to 2050.

Despite recent advances in mapping peatlands, efforts to monitor degradation lag behind and data is still insufficient to track progress made toward this target. Global estimates of the area of organic soils drained for agriculture offer a helpful, though still quite limited proxy and show that an average of 0.06 Mha of organic soils were drained each year for crop cultivation and grazing between 1993 and 2018. More recent data from FAOSTAT show that this area of organic soils drained grew by an average of 0.04 Mha per year between 2012 and 2022. In total, 57 Mha of peatlands — an area roughly the size of Kenya — are currently degrading, such that they are no longer forming peat, and carbon-rich peat accumulated over centuries to millennia is disappearing.

11880: Mangrove conversion, as measured by the annual rate of gross losses in mangrove extent

Status: Wrong Direction

Historical Data Methodology and Challenges:

To monitor mangrove loss globally, we used a dataset on tidal wetland change that estimates gross area of loss of mangroves from Murray et al. 2022 that defines mangrove loss as the replacement of mangroves with non-intertidal ecosystems at the 30-meter pixel scale. This includes both natural and human-caused losses. Using this definition, we estimated mangrove loss in three-year epochs from 1999 to 2019. To convert these three-year epochs into annual rates of change, we divided the gross loss for each epoch by three to determine the average annual loss rate in hectares per year.

There are several limitations in using this data to assess progress toward our targets for reducing mangrove loss. Because the area of loss is estimated for three-year epochs, fewer data points are available from which to derive the historical trendline. We thus derived the trendline for this indicator from the area of mangrove loss across four epochs. Furthermore, this dataset may also underestimate changes that occur at smaller scales (e.g., fragmentation) or in narrow linear features such as waterways due to the limitations of detecting such changes with medium-resolution satellite imagery. A detailed assessment of the accuracy of this data can be found in Murray et al. 2022.

Finally, Global Mangrove Watch’s version 3.0 dataset, another commonly used dataset on mangrove extent and change, features estimates of mangrove extent from 1996 to 2020. However, Bunting et al. 2022 recommends using only its net change estimates, rather than gross loss or gain, due to mis-registration errors with the JAXA L-Band Synthetic Aperture Radar (SAR) data. JAXA is currently reprocessing all L-band SAR global mosaics, which will likely resolve this limitation in future versions of the Global Mangrove Watch data.

Target Methodology:

Targets to Limit Warming to 1.5°C: Roe et al. 2021 defines the bottom-up, cost-effective mitigation potential for avoided GHG emissions from mangrove loss (0.07 GtCO2e/yr from 2020 to 2050) as 90% adoption of the technical potential from Griscom et al. 2020, expanded to include nontropical countries. This technical potential was defined as avoiding all potential mangrove loss and estimated using average annual gross mangrove loss rates from 1996 to 2016. We therefore calculated a 90% reduction in this rate to derive our 1.5°C-aligned targets. Following ramp-down assumptions from Griscom et al. 2020, we set our 1.5°C-aligned target to achieve this reduction by 2030, with no further increase in the rate of loss between 2030 and 2050.
Targets to Minimize Biodiversity Loss: We derived this target from the technical potential as estimated by Roe et al. 2021, which entails entirely halting historical rates of loss. This is consistent with Díaz et al. 2020, which synthesizes the available evidence and, based on the authors’ expert evaluation, maps out a high-ambition road to recovery needed to deliver the vision of the Global Biodiversity Framework. Within this “road to recovery,” Díaz et al. 2020 calls for no loss in area or integrity of critical ecosystems between 2020 and 2030, with safeguards that avoid substitution between ecosystems. We interpret this goal as no gross losses in critical ecosystems over this period and, though not specified, likely beyond it. Mangroves constitute “critical ecosystems,” following the definition outlined in a report that many authors of Díaz et al. 2020 presented to the Subsidiary Body on Scientific, Technical and Technological Advice under the Convention on Biological Diversity.

Progress Assessment Methodology:

Outcome indicators in this system experience high interannual variability in historical data due to both anthropogenic and natural causes. To account for this variability, 10 years instead of 5 years are used to calculate the linear trendline where possible. For mangrove conversion, however, a 12-year trendline was calculated, using data from 2008 to 2019 to account for the full range of years included in four 3-year epochs from Murray et al. 2022.

Stretching across nearly 15 million hectares (Mha) of shoreline globally, mangroves are among the world’s most carbon-rich ecosystems, holding at least three times more carbon per hectare than the world’s forests. Accumulation of carbon within these coastal wetland soils occurs gradually over hundreds to thousands of years, as mangrove roots trap suspended organic matter during tidal flooding and biomass slowly decomposes in their waterlogged soils. Due to these ecosystems’ carbon density, the loss of even a small area of mangroves, particularly when their soils are dredged or excavated, can release a large amount of greenhouse gas (GHG) emissions, relative to other ecosystems.

Converting the world’s mangroves — for example, to aquaculture ponds, palm oil plantations, rice paddies or urban infrastructure — threatens not only their ability to continue sequestering and storing carbon but also their capacity to provide a wide range of ecosystem services to coastal communities. These wetlands are known for protecting shorelines from flooding, strong winds and extreme weather events like hurricanes; under the right conditions, they can also reduce erosion and increase accretion, such that they gain elevation to keep pace with sea level rise. Mangroves also provide nursery grounds to fisheries, as well as habitats for many endemic and threatened species. Recent studies are also beginning to challenge previous assumptions of low genetic and species diversity in these ecosystems.

Protecting mangroves is therefore critical to addressing both the climate and biodiversity crises. But the world’s shorelines have lost a total of 560,000 hectares (ha) since the turn of the century, and between 2008 to 2019, specifically, these losses increased at an annual average rate of almost 950 hectares per year (ha/yr). With these recent changes heading in the wrong direction entirely, a sharp reversal in action is needed to reduce these losses to no more than 4,900 ha/yr by 2030 to help limit warming to 1.5 degrees C (2.7 degrees F) and to zero as soon as possible and by 2030 at the latest to help conserve biodiversity.

11881: Salt marsh conversion, as measured by the annual rate of gross losses in salt marsh extent

Status: Wrong Direction

Historical Data Methodology and Challenges:

To calculate gross losses in salt marsh extent globally, we used a dataset on tidal marsh change from Murray et al. 2022 that defines tidal marsh loss as the replacement of tidal marshes with non-intertidal ecosystems at the 30-meter pixel scale, which includes both natural and human-caused losses. Using this definition, we estimated tidal marsh loss in three-year epochs from 1999 to 2019. To convert these estimates to annual rates, we divided the gross loss for each epoch by three to determine the average annual loss rate in hectares per year.

There are several limitations in using this data to assess progress made in reducing salt marsh loss. Because the area of loss is estimated for three-year epochs, fewer data points are available from which to derive the historical trendline, and the trendline for this indicator was derived from the area of tidal marsh loss across four epochs. Furthermore, this dataset may also underestimate changes that occur at smaller scales or in narrow linear features, such as waterways, due to the limitations of detecting such changes with medium-resolution satellite imagery. A detailed assessment of the accuracy of this data can be found in Murray et al. 2022.

Target Methodology:

Targets to Limit Warming to 1.5°C: 1.5°C-compatible targets focused on reducing salt marsh loss are not available.
Targets to Minimize Biodiversity Loss: Díaz et al. 2020 synthesizes the available evidence and, based on the authors’ expert evaluation, maps out a high-ambition road to recovery needed to deliver the vision of the Global Biodiversity Framework. Within this “road to recovery,” Díaz et al. 2020 calls for no loss in area or integrity of critical ecosystems between 2020 and 2030, with safeguards that avoid substitution between ecosystems. We interpret this goal as no gross losses in critical ecosystems over this period and, though not specified, likely beyond it. Salt marshes constitute “critical ecosystems,” following the definition outlined in a report that many authors of Díaz et al. 2020 presented to the Subsidiary Body on Scientific, Technical and Technological Advice under the Convention on Biological Diversity.

Progress Assessment Methodology:

Outcome indicators in this system experience high interannual variability in historical data due to both anthropogenic and natural causes. To account for this variability, 10 years instead of 5 years are used to calculate the linear trendline where possible. For salt marsh loss, however, a 12-year trendline was calculated, using data from 2008 to 2019 to account for the full range of years included in four 3-year epochs from Murray et al. 2022.

While mangroves primarily grow along tropical and subtropical shorelines, salt marshes dominate across temperate and boreal shores. Covering at least 9 million hectares (Mha), these highly productive coastal wetlands sequester and store substantial amounts of carbon per hectare, with roughly double the carbon density of the world’s forests. Accumulation of carbon in these ecosystems’ soils occurs gradually over hundreds to thousands of years, as marsh vegetation traps suspended organic matter during tidal flooding and waterlogged soils slow decomposition. Due to salt marshes’ high carbon density, the loss of even a small area, particularly when their soils are dredged or excavated, can spur high greenhouse gas (GHG) emissions, relative to other ecosystems.

Historically, draining salt marshes for agriculture, industry and urban development — alongside other drivers of loss like sea level rise, increasingly limited sediment due to damming rivers, pollution and the spread of invasive, alien species — has threatened their capacity to provide life-sustaining ecosystem services, including carbon sequestration and storage. Like mangroves, these wetlands protect coastal communities from flooding, strong winds and extreme weather events like hurricanes. Under the right conditions, they can also reduce erosion and increase accretion, such that they gain elevation to keep pace with sea level rise. And while the relatively harsh environmental conditions of intertidal habitats like salt marshes make it difficult for many species to thrive, these ecosystems still provide refuge for endemic species and migratory birds, as well as nursery grounds for fisheries.

Salt marsh losses over past centuries are estimated to be quite large, and protecting these ecosystems from further disturbances will prove critical to combatting both the climate and biodiversity crises. Since the turn of the century, the world has lost a total of 106,000 ha of salt marshes, and between 2008 and 2019, specifically, the rate of gross losses ticked slightly upward. Recent rates of change are heading in the wrong direction entirely, and a step-change in action is needed to end salt marsh loss immediately to help mitigate climate change and conserve biodiversity.

11859: Grassland, savanna and shrubland conversion, as measured by the annual rate of gross losses in these ecosystems’ extent

Status: Wrong Direction

Historical Data Methodology and Challenges:

Loss, as a proxy for conversion, is found as the transition from grassland, shrubland and savanna to cropland, pastureland or a built-up area. To calculate this, we used three complementary datasets:

The grassland extent collection 1.1 by Global Pasture Watch (GPW), which provides annual, 30 meter (m) maps of grassland extent ecosystems from 2000-2024. A cross-validation assessment for this GPW product is available in the source publication, Parente et al. 2024.
The Global Land Analysis and Discovery (GLAD) land cover product, which consists of annual (2015-2024) maps of land cover at 30 m spatial resolution. An accuracy assessment of the GLAD land cover product is available in the source publication, Potapov et al. 2022.
The Global Forest Change (GFC) dataset, which is available on Global Nature Watch, provides tree cover loss from 2001 to 2024 at 30 m spatial resolution. An accuracy assessment of the GFC land cover product is available in the source publication, Hansen et al. 2013.

To calculate grassland, savanna and shrubland loss, we needed to separate temporary losses from those that are permanent or semipermanent, which are a proxy for conversion, by harmonizing the GPW and GLAD datasets into a single combined annual map. To that end, we reclassified the GLAD land cover from classes from Potapov et al. 2022 into seven categories: bare ground, short vegetation, trees, water, snow/ice, cropland, and built-up areas (Table 1). We then replaced the GLAD short vegetation class with the GPW grassland categories (cultivated and natural or seminatural), where available. This reclassification produced an annual combined GLAD-GPW product from 2015 to 2024 that enabled spatially explicit, annual tracking of grassland, savanna and shrubland loss and that can be regularly updated contingent on the continued availability of input data layers.

Additionally, since our definition of this ecosystem extent is very broad and overlaps with areas of tree cover, we applied a mask based on tree cover loss data (GFC) available on Global Nature Watch. We identified all pixels with >30% tree canopy cover in 2000 that experienced tree cover loss at any time between 2001 and 2024 and excluded them from the grassland, shrubland and savanna loss analysis. This ensures that we are not counting loss twice — once as forest loss and then again as grassland, shrubland and savanna loss. Qualitative assessment showed that at the global scale, the masking is conservative and does not reduce grassland loss notably.

Table 1: Definitions for Global Pasture Watch class categories

Class	Short definition	Called here	Original source
Cultivated grassland	Areas where grasses and other forage plants have been intentionally planted and managed, as well as areas of native grassland-type vegetation where they clearly exhibit active and “heavy” management for specific human–directed uses, such as directed grazing of livestock.	Pastureland	Parente et al. 2024
Natural/seminatural grassland	Relatively undisturbed or sparsely managed native grasslands/short-height vegetation, such as open shrublands and savanna, as well as areas that have experienced varying degrees of human activity in the past, which may contain a mix of native and introduced species due to historical land use and natural processes.	Grasslands, shrublands and savannas	Parente et al. 2024
Bare ground	Land with 0-19% vegetation fraction.		Potapov et al. 2022
Short vegetation	Non–treed vegetation cover with 20% or more vegetation fraction.
Tree cover	An area with tree height ≥5 m at the Landsat pixel scale; includes wildland, managed, and planted forest, agroforestry, orchards and natural tree regrowth.
Water	Open surface water (inland) that covers ≥50% of a pixel for 20% or more of the year and is not obscured by tree canopy, floating vegetation, bridges or ice.
Snow/ice	Land covered by glaciers and snow that remains throughout the entire year.
Cropland	Land used to produce annual and perennial herbaceous crops for human consumption, forage, and biofuel; excludes tree crops, permanent pastures and shifting cultivation.
Built-up	Man-made land services associated with infrastructure, commercial and residential uses; defined as pixels containing any man-made surfaces even if they are not dominant.

We completed this analysis at 30-m spatial resolution globally from 2016 to 2024, with 2015 serving as a baseline year using the harmonized and masked dataset described above. To estimate annual grassland, shrubland and savanna loss, we summed the area of all pixels classified in the grassland, shrubland and savanna class that transitioned to pastureland, cropland or built-up areas, as these transitions were most likely to represent lasting, human-driven loss. We excluded all losses of grassland, shrubland and savanna to the remaining GLAD classes such as snow, ice, bare ground, short vegetation or water, as they were likely temporary. Such transitions are often driven by natural seasonal dynamics or interannual variability, such as melting snowpack, retreating glaciers or temporary drying of water bodies, and do not represent intentional or lasting ecosystem loss. This analysis also does not include transitions from grassland, shrubland or savanna to tree cover. While such transitions may represent ecosystem conversion in some contexts, the majority of changes between these classes in the data are associated with rotational plantation cycles or natural vegetation dynamics, such as secondary succession or regrowth following disturbance. As a result, these transitions were excluded to avoid overestimating permanent ecosystem loss. Together, this approach produces a conservative estimate of grassland, savanna and shrubland loss by requiring strong evidence of a lasting human-driven transition and filtering out ambiguous or post-deforestation changes.

Grassland, shrubland and savanna loss as a conversion proxy indicator has several limitations. It is subject to the errors of commission and omission present in the input GLAD and GPW datasets. Area estimates for this analysis were derived using pixel counting, which involves summing the number of 30 m pixels classified as grassland, shrubland and savanna and converting this count to an area estimate. However, this method does not account for classification uncertainties or biases. Gross losses capture the extent of land cover change from grassland, savanna and shrubland to cropland, pastureland or built-up areas.

While grassland, shrubland and savanna areas can and do support grazing by wild ruminants and domestic livestock, these areas can still retain significant ecological value. These ecosystems continue to provide carbon storage, biodiversity habitat and ecosystem services such as water regulation, pollination and soil stabilization. However, once converted to cropland or pasture (through intensive management actions like ploughing or planting), or built areas (e.g., cities or energy infrastructure), many of those benefits are lost or severely diminished.
Due to the exclusion of water from the analysis, some meaningful losses, such as ecosystems permanently inundated by the construction of new dams or reservoirs, are not captured.
Very long crop rotations or shifting cultivation systems may be captured in our analysis as loss events. While these land use changes may be temporary or part of cyclical agricultural practices, they can resemble permanent conversion in satellite-based land cover datasets, particularly when vegetation structure changes significantly or persists across multiple years.
This analysis does not capture the extent or severity of degradation within grassland, savanna and shrubland. While it is true that pixels with very heavy signs of livestock impact on the landscape tend to be classified as pastureland (and therefore are outside of the grassland, shrubland and savanna class), subtle or functionally degraded areas may remain within the grassland, shrubland and savanna class. For example, many forms of degradation, such as declines in plant diversity, aboveground productivity, soil health or subtle structural changes, may not result in a detectable land cover change and are therefore not reflected as loss in this analysis. As such, this indicator likely underrepresents the full extent of degradation occurring within these ecosystems.
Data for the most recent years is subject to greater uncertainty because classification relies on limited temporal context, making it more difficult to distinguish between temporary disturbances (such as shifting cultivation or short-term land use change) and permanent conversion. As additional years of data become available, some areas currently classified as loss may be reinterpreted as part of cyclical or reversible processes, leading to potential revisions in the final estimates.

Target Methodology:

1.5°C-compatible targets for reducing the conversion of grasslands, savannas and open shrublands are not available, while those focused on minimizing biodiversity losses are either outdated (e.g., Griscom et al. 2017 relies on data published more than two decades ago to estimate a technical potential for this measure), express benchmarks as the share of these ecosystems that are protected (e.g., Dinerstein et al. 2019) or define ambition as no net loss in area and integrity (e.g., Díaz et al. 2020) rather than a reduction in gross losses. Accordingly, we present directional, qualitative targets informed by this literature, as well as by IPBES 2019 and IPCC 2022.

Progress Assessment Methodology:

Outcome indicators in this system experience high interannual variability in historical data due to both anthropogenic and natural causes. To account for this variability, 10 years instead of 5 years are used to calculate the linear trendline where possible. However, due to data limitations, we calculated a linear trendline for this indicator with 9 years of data from 2016 to 2024.

Together, grasslands, savannas and shrublands cover almost half of the world’s land and, as some of the world’s most species-rich ecosystems, are hotspots for biodiversity. Montane grasslands in Argentina, for example, contain nearly 90 plant species per square meter, while some tropical grasslands have a vertebrate species richness comparable to tropical forests. Many of these species are endemic to specific regions or grassland ecosystem types and therefore are often rare or threatened, such as the wild horses in the Eurasian Steppe, the plains-wanderer birds of Australia or the African savanna elephants.

These ecosystems also deliver vital contributions to people, from filtering out pollutants from water and preventing flooding by absorbing heavy rainfall to providing food for livestock and protecting soil from erosion. Chief among these services is grassland’s capacity to store vast amounts of carbon — up to 90% of it belowground in roots and soil, with estimates ranging from roughly 96 to 340 gigatonnes of carbon (GtC). This wide range reflects methodological variation across studies, such as the carbon pools included, how grassland ecosystem extent is defined and the depth of soil measured.

Yet many of the world’s grasslands, savannas and shrublands are under threat. Conversion of these ecosystems to croplands and pastures is a primary driver of loss, alongside overgrazing, pollution, the spread of invasive, alien species, and afforestation. Sharply reducing direct land-use change can safeguard carbon stored within these ecosystems and help avoid further biodiversity loss. Using the land cover data available to us, we can track grassland conversion; however, due to lack of land use data, we cannot track changes within the grassland class itself. As a result, this indicator is not able to track the degradation of existing grasslands, savannas and shrublands, such as from overgrazing, invasive species, altered fire regimes and pollution, which are severe threats but harder to monitor. By one estimate, nearly half of the world’s grasslands have experienced some form of degradation.

Between 2016 and 2024, conversion was detected across a total of 124 million hectares (Mha) of grasslands, savannas and open shrublands — equivalent to an area roughly the size of South Africa. During this period, the annual rate of gross loss increased by roughly 230,000 ha per year, heading in the wrong direction entirely. A course correction is now needed to conserve these ecosystems.

Key enablers and barriers to change

Other shift Other shifts needed to transform the system

Restoring deforested and degraded ecosystems — including forests, peatlands, grasslands and coastal wetlands — can help limit global warming and reverse biodiversity loss. Done right, reforestation and other forms of ecosystem restoration can also deliver far-reaching, sustainable development benefits for communities around the world.

Unsustainable management of terrestrial ecosystems, particularly forests, grasslands, savannas and shrublands, is exacerbating the climate and biodiversity crises. When tailored to local contexts and implemented appropriately, improved management practices can reduce emissions, increase carbon sequestration and bolster climate resilience, all while supporting productivity and local livelihoods.

Sharply reducing pollution in forests, grasslands, peatlands and coastal wetlands is essential to halt biodiversity loss, maintain ecosystem services and protect human health. Key contaminants include heavy metals, persistent organic pollutants such as PFAS, pesticides, nutrient pollution, plastics and artificial light.

Human-driven overexploitation of wild species — including legal and illegal logging, hunting and trade — is a major driver of biodiversity loss and species extinction. Reversing this trend requires better monitoring of wild populations, stronger protection of threatened species, sustainable management of species use and effective regulation of wildlife trade.

Effectively halt deforestation, other forms of conversion, and degradation across terrestrial ecosystems

Agricultural expansion is the leading driver of deforestation and degradation

How deforestation, other forms of ecosystem conversion, and degradation threaten biodiversity

How land-use change exacerbates climate change by disrupting carbon sequestration and storage

The world has largely fallen short in halting deforestation and degradation

Tracking progress on global outcomes

Key enablers and barriers to change

Other shift Other shifts needed to transform the system

Restore deforested and degraded terrestrial ecosystems

Sustainably manage terrestrial ecosystems to reduce GHG emissions and enhance carbon removals

Sharply reduce pollution in terrestrial ecosystems

Halt the overexploitation of terrestrial wild species and ensure sustainable use

Agricultural expansion is the leading driver of deforestation and degradation

How deforestation, other forms of ecosystem conversion, and degradation threaten biodiversity

How land-use change exacerbates climate change by disrupting carbon sequestration and storage

The world has largely fallen short in halting deforestation and degradation

Tracking progress on global outcomes

11868: Deforestation, as measured by the annual rate of gross tree cover losses that are likely permanent

11869: Primary forest loss, as measured by the annual rate of gross tree cover losses in humid tropical primary forests and in temperate and boreal intact forest landscapes

11873: Forest loss in Key Biodiversity Areas, as measured by the annual rate of gross tree cover losses within these areas

11886: Forest degradation, as measured by the global net extent of forests that transitioned to a lower integrity class

11876: Forest degradation due to fire, as measured by the annual rate of gross tree cover losses caused by fire

11850: Peatland degradation, as measured by the annual rate of gross drained organic soils

11880: Mangrove conversion, as measured by the annual rate of gross losses in mangrove extent

11881: Salt marsh conversion, as measured by the annual rate of gross losses in salt marsh extent

11859: Grassland, savanna and shrubland conversion, as measured by the annual rate of gross losses in these ecosystems’ extent

Key enablers and barriers to change

12650: Demand-side deforestation regulations, as measured by the share of countries with regulations restricting imports of agricultural commodities linked to deforestation and forest degradation

12660: Strength of company commitments to halt deforestation and ecosystem conversion, as measured by the average score of deforestation commitments among companies most exposed to deforestation

12653: Ruminant meat consumption in high-consuming regions, as measured by ruminant meat availability in regions consuming over 60 kcal/cap/day in 2017

12658: Land and inland waters in protected areas or other effective area-based conservation measures

12663: Countries with at least one policy, law or regulation restricting agricultural land expansion into terrestrial ecosystems

12659: Integrated spatial planning, as measured by the share of the world’s land covered by a participatory, integrated and biodiversity-inclusive spatial plan

12656: Indigenous and community land rights, as measured by the share of land legally designated for or owned by Indigenous Peoples, Afro-descendant Peoples and local communities

12664: Countries upholding the right to free, prior and informed consent for Indigenous Peoples, Afro-descendent Peoples and local communities

12654: Lower levels of corruption, as measured by the share of countries scoring relatively highly on absence of corruption

12661: Stronger regulatory enforcement, as measured by the share of countries scoring relatively highly on regulatory enforcement

12662: Finance for halting ecosystem conversion and degradation, as measured by total climate finance for agriculture, forestry and other land uses

12651: Agricultural subsidies with conservation or climate objectives, as measured by public agricultural support for conservation, production retirement and other public goods across OECD members and select other countries

12657: Private finance misaligned with forest conservation, as measured by total finance that 150 financial institutions channeled to companies most exposed to deforestation

Other shift Other shifts needed to transform the system

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