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Universal access to education and family planning ...

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Universal access to education and family planning ...

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This 3 min video explains how access for women to a full education and family planning is the most impactful solution to climate change

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Think of the potential innovations by women and girls, were they to receive a full education

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How advancing health & education can reduce greenhouse gases

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Advancing universal education and family planning can cut up to 70 GT of greenhouse gases by 2050, enhancing gender equality, health, and climate resilience.

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soaks up CO2

provides soakage during floods

reduces traffic noise and air pollution

Think about where green spaces and tree planting tends to be in cities: low income or high income areas?

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spaces for urban wildlife, promoting biodiversity

regulate building temperature so less heating and air-conditioning used

..lowering energy costs

become recreational spaces

regulate city temperatures in a heat-wave

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use wasted space for food production

bring communities together

help urban populations to connect with their food

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Walkable cities are an impactful solution for reducing carbon emissions and slowing down climate change

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Think about how being in green spaces makes you feel..

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Switching from fossil fuel to renewable energies...

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Switching from fossil fuel to renewable energies...

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dramatically reduces emissions

reduces air pollution, improving health (+ reducing the 1,300 deaths/year caused by air pollution in Ireland)

promotes energy sovereignty + security (and therefore political sovereignty + security)

...which prevents energy crises like we're experiencing currently

reduces household energy bills ... preventing energy poverty!!

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Energy Poverty

Affects 1 in 3 Irish households

Especially impacts low-income families, single-parent homes (80% women-led), the elderly, people of colour, and the traveller community

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Banners at the Cost of Living Protest, Dublin, September 2022

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Another energy solution is retrofitting...

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Another energy solution is retrofitting...

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including retrofiitting for renters + those in social housing, to

slash energy demand.. and bills

improve comfort and quality of life

create green local jobs

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Indigenous groups in Brazil protest for land rights

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Indigenous people care for over a quarter of the world’s land surface, including 40% of protected terrestrial landscapes which includes 80% of all the world’s biodiversity.

However, indigenous people's right to this land is often not recognised and threatened.

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https://www.unep.org/news-and-stories/story/indigenous-rights-solution

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Securing indigenous people's land ownership over land they already live on and manage...

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Securing indigenous people's land ownership over land they already live on and manage...

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reduces deforestation

...leading to more CO2 sequestration

prevents mineral, oil and gas extraction

protects biodiversity

safeguards rich cultures and indigenous knowledge of eco-systems

promotes the rights of marginalised and vulnerable groups

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Overview

Forests store carbon in biomass and soils and serve as carbon sinks, taking up an estimated 12.8 Gt CO₂‑eq/yr (including mangroves and forested peatlands; Pan et al., 2024). Carbon stored in forests is released into the atmosphere through deforestation and degradation, which refer to forest clearing or reductions in ecosystem integrity from human influence (DellaSala et al., 2025). Humans cleared an average of 0.4% (16.3 Mha) of global forest area annually from 2001-2019 (excluding wildfire but including mangroves and forested peatlands; Hansen et al., 2013). This produced a gross flux of 7.4 Gt CO₂‑eq/yr (Harris et al., 2021), equivalent to ~14% of total global GHG emissions over that period (Dhakal et al., 2022). Different forest types store varying amounts of carbon and experience different rates of clearing; in this analysis, we individually evaluate forest protection in boreal, temperate, subtropical, and tropical regions. We included woodlands in our definition of forests because they are not differentiated in the satellite-based data used in this analysis.

We consider forests to be protected if they 1) are formally designated as PAs (UNEP-WCMC and IUCN, 2024), or 2) are mapped as Indigenous peoples' lands in the global study by Garnett et al. (2018). The International Union for Conservation of Nature defines PAs as areas managed primarily for the long-term conservation of nature and ecosystem services. They are disaggregated into six levels of protection, ranging from strict wilderness preserves to sustainable-use areas that allow for some natural resource extraction, including logging. We included all levels of protection in this analysis, primarily because not all PAs have been classified into these categories. We rely on existing maps of Indigenous peoples' lands but emphasize that much of their extent has not been fully mapped nor recognized for its conservation benefits (Garnett et al., 2018). Innovative and equity-driven strategies for forest protection that recognize the land rights, sovereignty, and stewardship of Indigenous peoples and local communities are critical for achieving just and effective forest protection globally (Dawson et al., 2024; Fa et al., 2020; FAO, 2024; Garnett et al., 2018; Tran et al., 2020; Zafra-Calvo et al., 2017).

Indigenous peoples' lands and PAs reduce, but do not eliminate, forest clearing relative to unprotected areas (Baragwanath et al., 2020; Blackman & Viet 2018; Li et al., 2024; McNicol et al., 2023; Sze et al. 2022; Wolf et al., 2023; Wade et al., 2020). We rely on estimates of how effective PA are currently for this analysis but highlight that improving management to further reduce land use change within PAs is a critical component of forest protection (Jones et al., 2018; Meng et al., 2023; Vijay et al., 2018; Visconti et al., 2019; Watson et al., 2014).

Market-based strategies and other policies can complement legal protections by increasing the value of intact forests and reducing incentives for clearing (e.g., Garett et al., 2019; Golub et al., 2021; Heilmayr et al., 2020; Lambin et al., 2018; Levy et al., 2023; Macdonald et al., 2024; Marin et al., 2022; Villoria et al., 2022; West et al., 2023). The estimates in this report are based on legal protection alone because the effectiveness of market-based strategies is difficult to quantify, but strategies such as sustainable commodities programs, reducing or redirecting agricultural subsidies, and strategic infrastructure planning will be further discussed in a future update.

Maps

The adoption, potential adoption, and effectiveness of forest protection are highly geographically variable. While forest protection can help avoid emissions anywhere that forests occur, areas with high rates of forest loss from human drivers and particularly carbon-rich forests have the greatest potential for avoiding emissions via forest protection. The tropics and subtropics are high-priority areas for forest protection as they contain 55% of currently unprotected forest area, forest loss due to agricultural expansion is particularly concentrated in these regions (Curtis et al., 2018; West et al., 2014; Gibbs et al., 2010), and tend to have larger biomass carbon stocks than boreal forests (Harris et al., 2021).

Developed countries also have significant potential to protect remaining old and long unlogged forests and foster recovery in secondary natural forests. The top 10 forested countries include Canada, the USA, Russia and even Australia, with the latter moving towards ending commodity production in its natural forests and increasing formal protection. Restoration of degraded forests is addressed in the Forest Restoration solution, but including regenerating forests in well designed protected areas is well within the capacity of every developed country.

Buffering and reconnecting existing high integrity forests is a low risk climate solution that increases current and future forest ecosystem resilience and adaptive capacity (Brennan et al., 2022; Brink et al., 2017; Grantham et al., 2020; Rogers et al., 2022). Forests with high ecological integrity provide outsized benefits for carbon storage and biodiversity and have greater resilience, making them top priorities for protection (Grantham et al., 2020; Rogers et al., 2022). Within a given forest, large-diameter trees similarly provide outsized carbon storage and biodiversity benefits, comprising only 1% of trees globally but storing 50% of the above ground forest carbon (Lutz et al., 2018). Additionally, forests that improve protected area connectivity (Brennan et al., 2022; Brink et al., 2017), areas at high risk of loss (particularly to expansion of commodity agriculture; Curtis et al., 2018; Hansen et al., 2013), and areas with particularly large or specialized benefits for biodiversity, ecosystem services, and human well-being (Dinerstein et al., 2024; Sarira et al., 2022; Soto-Navarro et al., 2020) may be key targets for forest protection.

Global Forest Watch (2023). Global peatlands [Data set]. Retrieved December 6, 2024 from Link to source: https://data.globalforestwatch.org/datasets/gfw::global-peatlands/about

Hansen, M.C., Potapov, P.V., Moore, R., Hancher, M., Turubanova, S.A., Tyukavina, A., Thau, D., Stehman, S.V., Goetz, S.J., Loveland, T.R., Kommareddy, A., Egorov, A., Chini, L., Justice, C.O., and Townshend, J.R.G. (2013). High-resolution global maps of 21st-century forest cover change [Data set]. Science 342 (15 November): 850-53. Link to source: https://glad.earthengine.app/view/global-forest-change

UNEP-WCMC (2025). Ocean+ habitats (version 1.3) [Data set]. Retrieved November 2024 from habitats.oceanplus.org

Global Forest Watch (2023). Global peatlands [Data set]. Retrieved December 6, 2024 from Link to source: https://data.globalforestwatch.org/datasets/gfw::global-peatlands/about

Hansen, M.C., Potapov, P.V., Moore, R., Hancher, M., Turubanova, S.A., Tyukavina, A., Thau, D., Stehman, S.V., Goetz, S.J., Loveland, T.R., Kommareddy, A., Egorov, A., Chini, L., Justice, C.O., and Townshend, J.R.G. (2013). High-resolution global maps of 21st-century forest cover change [Data set]. Science 342 (15 November): 850-53. Link to source: https://glad.earthengine.app/view/global-forest-change

UNEP-WCMC (2025). Ocean+ habitats (version 1.3) [Data set]. Retrieved November 2024 from habitats.oceanplus.org

The Details

Current State

Effectiveness

We estimated that one ha of forest protection provides total carbon benefits of 0.299-2.204 t CO₂‑eq/yr depending on the biome (Table 1a-d; Appendix). This effectiveness estimate includes avoided emissions and preserved sequestration capacity attributable to the reduction in forest loss conferred by protection (Equation 1). First, we calculated the difference between the rate of human-caused forest loss outside of PAs ( Forest lossbaseline) and the rate inside of PAs ( Forest lossprotected). We then multiplied the annual rate of avoided forest loss by the sum of the carbon stored in one hectare of forest ( Carbonstock) and the amount of carbon that one hectare of intact forest takes up over a 30-yr timeframe ( Carbonsequestration).

\[ Effectiveness = (Forest\text{ }loss_{baseline} - Forest\text{ }loss_{protected})\times(Carbon_{stock} + Carbon_{sequestration}) \]

Each of these factors varies across biomes. Based on our definition, for instance, the effectiveness of forest protection in boreal forests is lower than that in tropical and subtropical forests primarily because the former face lower rates of human-caused forest loss (though greater wildfire impacts). Importantly, the effectiveness of forest protection as defined here reflects only a small percentage of the carbon stored (394 t CO₂‑eq ) and absorbed (4.25 t CO₂‑eq/yr ) per hectare of forest (Harris et al., 2021). This is because humans clear ~0.4% of forest area annually, and forest protection is estimated to reduce human-caused forest loss by an average of 40.5% (Curtis et al., 2018; Wolf et al., 2023).

Cost

We estimated that forest protection costs approximately US$2/t CO₂‑eq (Table 2). Data related to the costs of forest protection are limited, and these estimates are uncertain. The costs of forest protection include up-front costs of land acquisition and ongoing costs of management and enforcement. The market price of land reflects the opportunity cost of not using the land for other purposes (e.g., agriculture or logging). Protecting forests also generates revenue, notably through increased tourism. Costs and revenues vary across regions, depending on the costs of land and enforcement and potential for tourism.

The cost of land acquisition for ecosystem protection was estimated by Dienerstein et al. (2024), who found a median cost of US$988/ha (range: US$59-6,616/ha), which we amortized over 30 years. Costs of PA maintenance were estimated at US$9-17/ha/yr (Bruner et al., 2004; Waldron et al., 2020). These estimates reflect the costs of effective enforcement and management, but many existing PAs do not have adequate funds for effective enforcement (Adams et al., 2019; Barnes et al., 2018; Burner et al., 2004). Tourism revenues directly attributable to forest protection were estimated to be US$43/ha/yr (Waldron et al., 2020), not including downstream revenues from industries that benefit from increased tourism. Inclusion of a tourism multiplier would substantially increase the estimated economic benefits of forest protection.

Learning Curve

A learning curve is defined here as falling costs with increased adoption. The costs of forest protection do not fall with increasing adoption, so there is no learning curve for this solution.

Speed of Action

Speed of action refers to how quickly a climate solution physically affects the atmosphere after it is deployed. This is different from speed of deployment, which is the pace at which solutions are adopted.

At Project Drawdown, we define the speed of action for each climate solution as emergency brake, gradual, or delayed.

Protect Forests is an EMERGENCY BRAKE climate solution. It has the potential to deliver a more rapid impact than gradual and delayed solutions. Because emergency brake solutions can deliver their climate benefits quickly, they can help accelerate our efforts to address dangerous levels of climate change. For this reason, they are a high priority.

Adoption

Current Adoption

We estimated that approximately 1,673 Mha of forests are currently recognized as PAs or Indigenous peoples' lands (Table 3e; Garnett et al., 2018; UNEP-WCMC and IUCN, 2024). Using two different maps of global forests that differ in their methodologies and definitions (ESA CCI, 2019; Hansen et al., 2013), we found an upper-end estimate of 1,943 Mha protected and a lower-end estimate of 1,404 Mha protected. These two maps classify forests using different thresholds for canopy cover and vegetation height, different satellite data, and different classification algorithms (see the Appendix for details).

Based on our calculations, tropical forests make up the majority of forested PAs, with approximately 936 Mha under protection (Table 3d), followed by boreal forests (467 Mha, Table 3a), temperate forests (159 Mha, Table 3b), and subtropical forests (112 Mha, Table 3c). We estimate that 49% of all forests have some legal protection, though only 7% of forests are under strict protection (IUCN class I or II), with the remaining area protected under other IUCN levels, as OECMs, or as Indigenous peoples' lands.

Adoption Trend

We calculated the rate of PA expansion based on the year the PA was established. We do not have data on the expansion rate of Indigenous peoples' lands, so the calculated adoption trend reflects only PAs. An average of 19 Mha of additional forests were protected each year between 2000 and 2020 (Table 4a-e; Figure 1), representing a roughly 2% increase in PAs per year (excluding Indigenous peoples' lands that are not located in PAs). There were large year-to-year differences in how much new forest area was protected over this period, ranging from only 6.4 Mha in 2020 to over 38 Mha in both 2000 and 2006. Generally, the rate at which forest protection is increasing has been decreasing, with an average increase of 27 Mha/yr between 2000-2010 declining to 11 Mha/yr between 2010-2020. Recent rates of forest protection (2010-2020) are highest in the tropics (5.6 Mha/yr), followed by temperate regions (2.4 Mha/yr) and the boreal (2.0 Mha/yr), and lowest in the subtropics (0.7 Mha/yr).

Figure 1. Trend in forest protection by climate zone. These values reflect only the area located within PAs; Indigenous peoples' lands, which were not included in the calculation of the adoption trend, are excluded.

Adoption Ceiling

We estimated an adoption ceiling of 3,370 Mha of forests globally (Table 5e), defined as all existing forest areas, excluding peatlands and mangroves. Of the calculated adoption ceiling, 469 Mha of boreal forests (Table 5a), 282 Mha of temperate forests (Table 5b), 211 Mha of subtropical forests (Table 5c), and 734 Mha of tropical forests (Table 5d) are currently unprotected. The high and low values represent estimates of currently forested areas from two different maps of forest cover that use different methodologies and definitions (ESA CCI, 2019; Hansen et al., 2013). While it is not socially, politically, or economically realistic that all existing forests could be protected, these values represent the technical upper limit to adoption of this solution. Additionally, some PAs allow for ongoing sustainable use of resources, enabling some demand for wood products to be met via sustainable use of trees in PAs.

Achievable Adoption

We defined the lower end of the achievable range for forest protection as all high integrity forests in addition to forests in existing PAs and Indigenous peoples' lands, totaling 2,297 Mha (Table 6a-e). We estimated that there are 624 Mha of unprotected high integrity forests, based on maps of forest integrity developed by Grantham et al. (2020). High integrity forests have experienced little disturbance from human pressures (i.e., logging, agriculture, and buildings), are located further away from areas of human disturbance, and are well-connected to other forests. High integrity forests are a top priority for protection as they have particularly high value with respect to biodiversity and ecosystem service provisioning. These forests are also not currently being used to meet human demand for land or forest-derived products, and thus their protection may be more feasible.

To estimate the upper end of the achievable range, we excluded the global areas of planted trees and tree crops from the adoption ceiling (Richter et al., 2024), comprising approximately 335 Mha globally (Table 6a-e). Planted trees include tree stands established for crops such as oil palm, products such as timber and fiber production, and those established as windbreaks or for ecosystem services such as erosion control. These stands are often actively managed and are unlikely to be protected.

Impacts

Climate Impact

We estimated that forest protection currently avoids approximately 2.00 Gt CO₂‑eq/yr, with potential impacts of 2.49 Gt CO₂‑eq/yr at the low-achievable scenario, 3.62 Gt CO₂‑eq/yr at the high-achievable scenario, and 4.10 Gt CO₂‑eq/yr at the adoption ceiling (Table 7a-e). Although not directly comparable due to the inclusion of different land covers, these values are aligned with Griscom et al. (2017) estimates that forest protection could avoid 3.6 Gt CO₂‑eq/yr and the IPCC estimate that protection of all ecosystems could avoid 6.2 Gt CO₂‑eq/yr (Nabuurs et al., 2022).

Note that the four adoption scenarios vary only with respect to the area under protection. Increases in either the rate of forest loss that would have occurred if the area had not been protected or in the effectiveness of PAs at avoiding forest loss would substantially increase the climate impacts of forest protection. For instance, a hypothetical 50% increase in the rate of forest loss outside of PAs would increase the carbon impacts of the current adoption, low achievable, high achievable, and adoption ceiling scenarios to 3.0, 3.7, 5.4, and 6.1 Gt CO₂‑eq/yr, respectively. Similarly, if legal forest protection reduced forest loss twice as much as it currently does, the climate impacts of the four scenarios would increase to 3.9, 4.8, 7.0, and 7.8 Gt CO₂‑eq/yr, respectively.

Additional Benefits

Extreme Weather Events

Protected forests are more biodiverse and therefore more resilient and adaptable, providing higher-quality ecosystem services to surrounding communities (Gray et al., 2016). Protected forests can also buffer surrounding areas from the effects of extreme weather events. By increasing plant species richness, forest preservation can contribute to drought and fire tolerance (Buotte et al., 2020). Forests help regulate local climate by reducing temperature extremes (Lawrence et al., 2022). Studies have shown that the extent of forest coverage helps to alleviate vulnerability associated with heat effects (Walton et al., 2016). Tropical deforestation threatens human well-being by removing critical local cooling effects provided by tropical forests, exacerbating extreme heat conditions in already vulnerable regions (Seymour et al., 2022).

Income and Work

For a description of the Income and Work benefits, please refer to Food Security and Health sections below.

Food Security

Protecting forests in predominantly natural areas can improve food security by supporting crop pollination of nearby agriculture. Sarira et al. (2022) found that protecting 58% of threatened forests in Southeast Asia could support the dietary needs of about 305,000-342,000 people annually. Forests also provide a key source of income and livelihoods for subsistence households and individuals (de Souza et al., 2016; Herrera et al., 2017; Naidoo et al., 2019). By maintaining this source of income through forest protection, households can earn sufficient income that contributes to food security.

Health

Protected forests can benefit the health and well-being of surrounding communities through impacts on the environment and local economies. Herrera et al. (2017) found that in rural areas of low- and middle-income countries, household members living downstream of higher tree cover had a lower probability of diarrheal disease. Proximity to PAs can benefit local tourism, which may provide more economic resources to surrounding households. Naidoo et al. (2019) found that households near PAs in low- and middle-income countries were more likely to have higher levels of wealth and were less likely to have children who were stunted. Reducing deforestation can improve health by lowering vector-borne diseases, mitigating extreme weather impacts, and improving air quality (Reddington et al., 2015).

Equality

Indigenous peoples have a long history of caring for and shaping landscapes that are rich with biodiversity (Fletcher et al., 2021). Indigenous communities provide vital ecological functions for preserving biodiversity, like seed dispersal and predation (Bliege Bird & Nimmo, 2018). Indigenous peoples also have spiritual and cultural ties to their lands (Garnett et al., 2018). Establishing protected areas must prioritize the return of landscapes to Indigenous peoples so traditional owners can feel the benefits of biodiversity. However, the burden of conservation should not be placed on Indigenous communities without legal recognition or support (Fa et al., 2020). In fact, land grabs and encroachments on Indigenous lands have led to greater deforestation pressure (Sze et al., 2022). Efforts to protect these lands must include legal recognition of Indigenous ownership to support a just and sustainable conservation process (Fletcher et al., 2021).

Nature Protection

Forests are home to a wide range of species and habitats and are essential for safeguarding biodiversity. Forests have high above- and below-ground carbon density, high tree species richness, and often provide habitat to threatened and endangered species (Buotte et al., 2020). PAs can aid in avoiding extinctions by protecting rare and threatened species (Dinerstein et al. 2024). In Southeast Asia, protecting 58% of threatened forests could safeguard about half of the key biodiversity areas in the region (Sarira et al., 2022).

Water Quality

Forests act as a natural water filter and can maintain and improve water quality (Melo et al., 2021). Forests can also retain nutrients from polluting the larger watershed (Sweeney et al., 2004). For example, forests can uptake excess nutrients like nitrogen, reducing their flow into surrounding water (Sarira et al., 2022). These excessive nutrients can cause eutrophication and algal blooms that negatively impact water quality and aquatic life.

Other

Caveats

Additionality, or the degree to which emissions reductions are above and beyond a baseline, is a key caveat for emissions avoided through forest protection (e.g., Fuller et al., 2020; Ruseva et al., 2017). Emissions avoided via forest protection are only considered additional if that forest would have been cleared or degraded without protection (Delacote et al., 2022; Delacote et al., 2024; Gallemore et al., 2020). In this analysis, additionality is addressed by using baseline rates of forest loss outside of PAs in the effectiveness calculation. Additionality is particularly important when forest protection is used to generate carbon offsets. However, the likelihood of forest removal in the absence of protection is often difficult to determine at the local level.

Permanence, or the durability of stored carbon over long timescales, is another important consideration not directly addressed in this solution. Carbon stored in forests can be compromised by natural factors, like drought, heat, flooding, wildfire, pests, and diseases, which are further exacerbated by climate change (Anderegg et al., 2020; Dye et al., 2024). Forest losses via wildfire in particular can create very large pulses of emissions (e.g., Kolden et al. 2024; Phillips et al. 2022) that negate accumulated carbon benefits of forest protection. Reversal of legal protections, illegal forest clearing, biodiversity loss, edge effects from roads, and disturbance from permitted uses can also cause forest losses directly or reduce ecosystem integrity, further increasing vulnerability to other stressors (McCallister et al., 2022).

Risks

Ecosystem protection initiatives that are not led by or undertaken in close collaboration with local communities can compromise community sovereignty and create injustice and inequity (Baragwanath et al., 2020; Blackman & Viet 2018; Dawson et al., 2024; Fa et al., 2020; FAO, 2024; Garnett et al. 2018; Sze et al. 2022; Tauli-Corpuz et al., 2020). Forest protection has the potential to be a win-win for climate and communities, but only if PAs are established with respect to livelihoods and other socio-ecological impacts, ensuring equity in procedures, recognition, and the distribution of benefits (Zafra-Calvo et al., 2017).

Leakage is a key risk of relying on forest protection as a climate solution. Leakage occurs when deforestation-related activities move outside of PA boundaries, resulting in the relocation of, rather than a reduction in, emissions from forest loss. If forest protection efforts are not coupled with policies to reduce incentives for forest clearing, leakage will likely offset some of the emissions avoided through forest protection. Additional research is needed to comprehensively quantify the magnitude of leakage effects, though two regional-scale studies found only small negative effects (Fuller et al., 2020; Herrera et al., 2019).

Interactions with Other Solutions

Reinforcing

Other intact and degraded ecosystems often occur within areas of forest protection. Therefore, forest protection can facilitate natural restoration of these other degraded ecosystems, and increase the health of adjacent ecosystems.

Reducing the demand for agricultural land will reduce barriers to forest protection.

Competing

Forest protection will decrease the availability and increase the prices of wood feedstocks for other applications.

Evidence Base

Consensus of effectiveness in reducing emissions and maintaining carbon removal : High

There is high scientific consensus that forest protection is a key strategy for reducing forest loss and addressing climate change. Rates of forest loss are lower inside of PAs and Indigenous peoples' lands than outside of them. Globally, Wolf et al. (2021) found that rates of forest loss inside PAs are 40.5% lower on average than in unprotected areas, and Li et al. (2024) estimated that overall forest loss is 14% lower in PAs relative to unprotected areas. Regional studies find similar average effects of PAs on deforestation rates. For instance, McNichol et al. (2023) reported 39% lower deforestation rates in African woodlands in PAs relative to unprotected areas, and Graham et al. (2021) reported 69% lower deforestation rates in PAs relative to unprotected areas in Southeast Asia. In the tropics, Sze et al. (2022) found that rates of forest loss were similar between Indigenous lands and PAs, with forest loss rates reduced 17-29% relative to unprotected areas. Baragwanath & Bayi (2020) reported a 75% decline in deforestation in the Brazilian Amazon when Indigenous peoples are granted full property rights.

Reductions in forest loss lead to proportionate reductions in CO₂ emissions. The Intergovernmental Panel on Climate Change (IPCC) estimated that ecosystem protection, including forests, peatlands, grasslands, and coastal wetlands, has a technical mitigation potential of 6.2 Gt CO₂‑eq/yr, 4.0 Gt of which are available at a carbon price less than US$100 tCO₂‑eq/yr (Nabuurs et al., 2022). Similarly, Griscom et al. (2017) found that avoiding human-caused forest loss is among the most effective natural climate solutions, with a potential impact of 3.6 Gt CO₂‑eq/yr (including forests on peatlands), nearly 2 Gt CO₂‑eq/yr of which is achievable at a cost below US$10/t CO₂‑eq/yr.

The results presented in this document were produced through analysis of 12 global datasets. We recognize that geographic biases can influence the development of global datasets and hope this work inspires research and data sharing on this topic in underrepresented regions.

Take Action

Looking to get involved? Below are some key actions for this solution that can get you started, arranged according to different roles you may play in your professional or personal life.

These actions are meant to be starting points for involvement and are not intended to be prescriptive or necessarily suggest they are the most important or impactful actions to take. We encourage you to explore and get creative!

Dhakal, S., J.C. Minx, F.L. Toth, A. Abdel-Aziz, M.J. Figueroa Meza, K. Hubacek, I.G.C. Jonckheere, Yong-Gun Kim, G.F. Nemet, S. Pachauri, X.C. Tan, T. Wiedmann, 2022: Emissions Trends and Drivers. In IPCC, 2022: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [P.R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA. Link to source: https://doi.org/10.1017/9781009157926.004

ESA CCI (2019). Copernicus Climate Change Service, Climate Data Store: Land cover classification gridded maps from 1992 to present derived from satellite observation. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). Accessed November 2024. doi: 10.24381/cds.006f2c9a

FAO. 2024. The State of the World's Forests 2024 - Forest-sector innovations towards a more sustainable future. Rome. https://doi.org/10.4060/cd1211en

Nabuurs, G-J., R. Mrabet, A. Abu Hatab, M. Bustamante, H. Clark, P. Havlík, J. House, C. Mbow, K.N. Ninan, A. Popp, S. Roe, B. Sohngen, S. Towprayoon, 2022: Agriculture, Forestry and Other Land Uses (AFOLU). In IPCC, 2022: Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [P.R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, J. Malley, (eds.)]. Cambridge University Press, Cambridge, UK and New York, NY, USA. Link to source: https://doi.org/10.1017/9781009157926.009

UNEP-WCMC and IUCN (2024), Protected Planet: The World Database on Protected Areas (WDPA) and World Database on Other Effective Area-based Conservation Measures (WD-OECM) [Online], Accessed November 2024, Cambridge, UK: UNEP-WCMC and IUCN. Available at: www.protectedplanet.net.

In this analysis, we integrated global land cover data, maps of forest loss rates, shapefiles of PAs and Indigenous people's lands, country-scale data on reductions in forest loss inside of PAs, and biome-scale data on forest carbon stocks and sequestration rates to calculate currently protected forest area, total global forest area, and avoided emissions from forest protection. Forested peatlands and mangroves are excluded from this analysis and addressed in the Protect Peatlands and Protect Coastal Wetlands solutions, respectively.

Land cover data

We used two land cover data products to estimate forest extent inside and outside of PAs and Indigenous people's lands, including: 1) the Global Forest Watch (GFW) tree cover dataset (Hansen et al., 2013), resampled to 30 second resolution, and 2) the 2022 European Space Agency Climate Change Initiative (ESA CCI) land cover dataset at native resolution (300 m). For the ESA CCI dataset, all non-flooded tree cover classes (50, 60, 70, 80, 90) and the "mosaic tree and shrub (>50%)/herbaceous cover (<50%)" class (100) and associated subclasses were included as forests. Both products are associated with uncertainty, which we did not address directly in our calculations. We include estimates from both products in order to provide readers with a sense of the variability in values that can stem from different land cover classification methods, which are discussed in more detail below.

These two datasets have methodological differences that result in substantially different classifications of forest extent, including their thresholds for defining forests, their underlying satellite data, and the algorithms used to classify forests based on the satellite information. For example, the ESA CCI product classifies 300-meter pixels with >15% tree cover as forests (based on our included classes), attempts to differentiate tree crops, relies on a 2003-2012 baseline land cover map coupled with a change-detection algorithm, and primarily uses imagery from MERIS, PROBA-V, and Sentinel missions (ESA CCI 2019). In contrast, the Global Forest Watch product generally requires >30% tree cover at 30-meter resolution, does not exclude tree crops, relies on a regression tree model for development of a baseline tree cover map circa 2010, and primarily uses Landsat ETM+ satellite imagery (Hansen et al., 2013). We recommend that interested readers refer to the respective user guides for each data product for a comprehensive discussion of the complex methods used for their development.

We used the Forest Landscape Integrity Index map developed by Grantham et al. (2020), which classifies forests with integrity indices ≥9.6 as high integrity. These forests are characterized by minimal human disturbance and high connectivity. Mangroves and peatlands were excluded from this analysis. We used a map of mangroves from Giri et al. (2011) and a map of peatlands compiled by Global Forest Watch to define mangrove and peatland extent (accessed at https://data.globalforestwatch.org/datasets/gfw::global-peatlands/about). The peatlands map is a composite of maps from five publications: Crezee et al. (2022), Gumbricht et al. (2017), Hastie et al. (2022), Miettinen et al. (2016), and Xu et al. (2018). For each compiled dataset, the data were resampled to 30-second resolution by calculating the area of each grid cell occupied by mangroves or peatlands. For each grid cell containing forests, the "eligible" forest area was calculated by subtracting the mangrove and peatland area from the total forest area for each forest cover dataset (GFW, ESA CCI, and high-integrity forests).

Protected forest areas

We identified protected forest areas using the World Database on Protected Areas (WDPA, 2024), which contains boundaries for each PA and additional information, including their establishment year and IUCN management category (Ia to VI, not applicable, not reported, and not assigned). For each PA polygon, we extracted the forest area from the GFW, ESA CCI, and high-integrity dataset (after removing the peatland and mangrove areas).

Each protected area was classified into a climate zone based on the midpoint between its minimum and maximum latitude. Zones included tropical (23.4°N-23.4°S), subtropical (23.4°-35° latitude), temperate (35°-50° latitude), and boreal (>50° latitude) in order to retain some spatial variability in emissions factors. We aggregated protected forest cover areas (from each of the two forest cover datasets and the high-integrity forest data) by IUCN class and climate zone. To evaluate trends in adoption over time, we also aggregated protected areas by establishment year. We used the same method to calculate the forest area that could be protected, extracting the total area of each land cover type by climate zone (inside and outside of existing PAs).

We used maps from Garnett et al. (2018) to identify Indigenous people's lands that were not inside established PAs. We calculated the total forest area within Indigenous people's lands (excluding PAs, mangroves, and peatlands) using the same three forest area data sources.

Forest loss and emissions factors

Forest loss rates were calculated for unprotected areas using the GFW forest loss dataset for 2001-2022, resampled to 1 km resolution. Forest losses were reclassified according to their dominant drivers based on the maps originally developed by Curtis et al. (2018), with updates accessible through GFW. Dominant drivers of forest loss include commodity agriculture, shifting agriculture, urbanization, forestry, and wildfire. We classified all drivers except wildfire as human-caused forest loss for this analysis. We calculated the area of forest loss attributable to each driver within each climate zone, which represented the "baseline" rate of forest loss outside of PAs.

To calculate the difference in forest loss rates attributable to protection, we used country-level data from Wolf et al. (2021) on the ratio of forest loss in unprotected areas versus PAs, controlling for a suite of socio-environmental characteristics. We classified countries into climate zones based on their median latitude and averaged the ratios within climate zones. We defined the avoided forest loss attributable to protection as the product of the baseline forest loss rate and the ratio of forest loss outside versus inside of PAs.

We calculated the carbon benefits of avoided forest loss by multiplying avoided forest loss by average forest carbon stocks and sequestration rates. Harris et al. (2021) reported carbon stocks and sequestration rates by climate zone (boreal, temperate, subtropical, and tropical), and forest type. Carbon stocks and sequestration rates for primary and old secondary (>20 years old) forests were averaged for this analysis. We calculated carbon sequestration over a 20-yr period to provide values commensurate with the one-time loss of biomass carbon stocks.

Crezee, B. et al. Mapping peat thickness and carbon stocks of the central Congo Basin using field data. Nature Geoscience 15: 639-644 (2022). https://www.nature.com/articles/s41561-022-00966-7 . Data downloaded from https://congopeat.net/maps/ , using classes 4 and 5 only (peat classes).

Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A., & Hansen, M. C. (2018). Classifying drivers of global forest loss. Science, 361(6407), 1108-1111. https://doi.org/10.1126/science.aau3445

ESA CCI (2019). Copernicus Climate Change Service, Climate Data Store: Land cover classification gridded maps from 1992 to present derived from satellite observation. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). Accessed November 2024. doi: 10.24381/cds.006f2c9a

Garnett, S. T., Burgess, N. D., Fa, J. E., Fernández-Llamazares, Á., Molnár, Z., Robinson, C. J., Watson, J. E. M., Zander, K. K., Austin, B., Brondizio, E. S., Collier, N. F., Duncan, T., Ellis, E., Geyle, H., Jackson, M. V., Jonas, H., Malmer, P., McGowan, B., Sivongxay, A., & Leiper, I. (2018). A spatial overview of the global importance of Indigenous lands for conservation. Nature Sustainability, 1(7), 369-374. https://doi.org/10.1038/s41893-018-0100-6

Giri C, Ochieng E, Tieszen LL, Zhu Z, Singh A, Loveland T, Masek J, Duke N (2011). Status and distribution of mangrove forests of the world using earth observation satellite data (version 1.3, updated by UNEP-WCMC). Global Ecology and Biogeography 20: 154-159. doi: 10.1111/j.1466-8238.2010.00584.x . Data URL: http://data.unep-wcmc.org/datasets/4

Gumbricht, T. et al. An expert system model for mapping tropical wetlands and peatlands reveals South America as the largest contributor. Global Change Biology 23, 3581-3599 (2017). https://onlinelibrary.wiley.com/doi/full/10.1111/gcb.13689

Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T. R., Kommareddy, A., Egorov, A., Chini, L., Justice, C. O., & Townshend, J. R. G. (2013). High-Resolution Global Maps of 21st-Century Forest Cover Change. Science, 342(6160), 850-853. https://doi.org/10.1126/science.1244693 . Data available on-line from: http://earthenginepartners.appspot.com/science-2013-global-forest. Accessed through Global Forest Watch on 01/12/2024. www.globalforestwatch.org

Harris, N. L., Gibbs, D. A., Baccini, A., Birdsey, R. A., de Bruin, S., Farina, M., Fatoyinbo, L., Hansen, M. C., Herold, M., Houghton, R. A., Potapov, P. V., Suarez, D. R., Roman-Cuesta, R. M., Saatchi, S. S., Slay, C. M., Turubanova, S. A., & Tyukavina, A. (2021). Global maps of twenty-first century forest carbon fluxes. Nature Climate Change, 11(3), 234-240. https://doi.org/10.1038/s41558-020-00976-6

Hastie, A. et al. Risks to carbon storage from land-use change revealed by peat thickness maps of Peru. Nature Geoscience 15: 369-374 (2022). https://www.nature.com/articles/s41561-022-00923-4

Miettinen, J., Shi, C. & Liew, S. C. Land cover distribution in the peatlands of Peninsular Malaysia, Sumatra and Borneo in 2015 with changes since 1990. Global Ecological Conservation. 6, 67- 78 (2016). https://www.sciencedirect.com/science/article/pii/S2351989415300470

UNEP-WCMC and IUCN (2024), Protected Planet: The World Database on Protected Areas (WDPA) and World Database on Other Effective Area-based Conservation Measures (WD-OECM) [Online], Accessed November 2024, Cambridge, UK: UNEP-WCMC and IUCN. Available at: www.protectedplanet.net .

Wolf, C., Levi, T., Ripple, W. J., Zárrate-Charry, D. A., & Betts, M. G. (2021). A forest loss report card for the world's protected areas. Nature Ecology & Evolution, 5(4), 520-529. https://doi.org/10.1038/s41559-021-01389-0

Xu et al. PEATMAP: Refining estimates of global peatland distribution based on a meta-analysis. CATENA 160: 134-140 (2018). https://www.sciencedirect.com/science/article/pii/S0341816217303004

Biomethane

Biogas refined to the same quality as natural gas. CO₂ and impurities are removed, and the biomethane can be distributed and used in existing natural gas technologies.

Evapotranspiration

An ecological process that releases water into the atmosphere as a gas from soil and ice (evaporation) and plants (transpiration).

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Protect Forests is a Highly Recommended climate solution. Healthy forests take up and store carbon. Protecting Forests ensures that intact forests stay standing, avoiding GHG emissions and maintaining their ability to absorb carbon.

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Organised communities can recognise what needs they have and get them met: e.g. a lack of fresh healthy produce in an area could be helped by a community-organised garden, or a lack of free social spaces could result in community-organised film screenings, games nights, potlucks, etc.

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What if we all came together and shared what we have?

Communities can create resource libraries for things such as tools, materials, food, books (existing libraries are also wonderfully sustainable), clothes...

...reducing our levels of product consumption and our environmental impact.

The idea of sharing resources among people, giving away what you don't need and asking for help when you need it, extends to social issues too. People can't always afford to buy what they need, and this can have a devastating impact on quality of life.

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Moving back to local production of food, energy and goods

increases sustainability of communities through reducing imported goods and related emissions

increases the resilience of communities to the climate crisis as communities won't have external dependency

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Post Carbon Institute promotes the strategy of relocalization-building resilience-through strong local communities.

Relocalization is a strategy to build societies based on the local production of food, energy and goods, and the local development of currency, governance and culture. The main goals of relocalization are to increase community energy security, to strengthen local economies, and to improve environmental conditions and social equity. The relocalization strategy developed in response to the environmental, social, political and economic impacts of global over-reliance on cheap energy.

Resilience is commonly defined as the capacity of a system to absorb disturbance and re-organize while undergoing change so as to still retain essentially the same function, structure, identity, and feedbacks. Resilience is a rich and complex concept. It has roots in systems theory, and it has a variety of interpretations and applications including for ecosystems management, disaster preparedness, and even community planning. Our interpretation is based on the work of the Resilience Alliance, the leading scholarly body working on the resilience of social-ecological systems.

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Post Carbon Institute promotes the strategy of relocalization-building resilience-through strong local communities. What is relocalization? Relocalization is a strategy to build societies based on the local production of food, energy and goods, and the local development of currency, governance and culture. The main goals of relocalization are to increase community energy security, to [...]

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How do these solutions make you feel?

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Are people aware of these solutions? How can we make people more aware?