Chicken

Coffee

Palm oil

Wood pulp

Argentina

Brazil

Colombia

Côte d'Ivoire

Ghana

Indonesia

Paraguay

Gross emissions attributable to deforestation. Estimates are based on the total biomass removal stored in the native vegetation. The numbers are subsequently transformed in CO₂-eq by multiplying carbon stock per 3.67.

Argentina - Emissions from deforestation

Total deforestation per jurisdiction for a given year.

Argentina - Deforestation

Number of chickens (heads) slaughtered per jurisdiction of origin.

Brazil - Chickens slaughtered

Soy harvested area derived from Instituto Brasileiro de Geografia e Estatística (IBGE, 2022).

Brazil - Soy area

Soy production tons derived from Instituto Brasileiro de Geografia e Estatística (IBGE, 2022).

Brazil - Soy production

Soy yield was derived from Instituto Brasileiro de Geografia e Estatística (IBGE, 2022).

Brazil - Soy yield

Production of coffee per jurisdiction in a given year.

Colombia - Production of coffee

Average coffee yield per jurisdiction in a given year.

Colombia - Coffee yield

Gross CO₂-eq. emissions from deforestation, estimated from the loss of above- and below-ground biomass (excluding soil carbon) from the EC JRC Tropical Moist Forest dataset (Vancutsem et al., 2021). Carbon stocks were converted to CO₂-eq. by multiplying by 3.67. Note that values for the most recent 2 years may change in the future when new versions of the Tropical Moist Forest dataset are released, updated to reflect whether recent forest change shows temporary degradation or permanent deforestation.

Gross (greenhouse gas) emissions from territorial deforestation (tonnes of CO2-eq) were calculated by estimating the maximum CO2-eq potentially emitted due to the full removal of the biomass as a result of territorial deforestation, estimated in a given year. This metric is calculated by multiplying the area of territorial deforestation by an estimate of the carbon stock contained in each hectare of converted land. Carbon stocks represent the total carbon stored in above- and below-ground biomass, but does not include carbon stocks in the soil. We create local estimates of biomass density (carbon stocks per hectare) using data from (Soto-Navarro et al., 2020). Carbon is converted into CO₂-eq emissions by multiplying by a factor of 44/12 ( or 3.67), based on the ratio between the molecular weight of C and CO₂ following (Pachauri et al., 2015).

Côte d’Ivoire - Gross greenhouse gas emissions from deforestation

Deforestation of undisturbed Tropical Moist Forest derived from EC JRC Tropical Moist Forest dataset (Vancutsem et al., 2021). Note that values for the most recent 2 years may change in the future when new versions of the Tropical Moist Forest dataset are released, updated to reflect whether recent forest change shows temporary degradation or permanent deforestation.

Deforestation maps were derived from the European Commission's Joint Research Centre 's TMF dataset Version 1 from 2023 (Vancutsem et al., 2021) using 41 years of Landsat time series at 30 metre spatial resolution and aggregated at department level. Deforestation refers to the year of change in land cover, from undisturbed or degraded forest (see above) to non-forest (Vancutsem et al., 2021).

Côte d’Ivoire - Deforestation

Degradation of Tropical Moist Forest derived from EC JRC Tropical Moist Forest dataset (Vancutsem et al., 2021). Note that values for the most recent 2 years may change in the future when new versions of the Tropical Moist Forest dataset are released, updated to reflect whether recent forest change shows temporary degradation or permanent deforestation.

Maps of degraded forest were derived from the European Commission's Joint Research Centre's TMF dataset Version 1 from 2023  (Vancutsem et al., 2021) using 41 years of Landsat time series at 30 metre spatial resolution and aggregated at department level. Forest degradation was defined as a disturbance in the tree cover canopy  visible from space over a short time period (< 2.5 years). A 'forest degradation' pixel remains forested land; i.e.,  covered by existing or regrowing trees, whereas a 'deforestation' pixel leads to the long-term (visible > 2.5 years) conversion into non-forested land  (Vancutsem et al., 2021).

Côte d’Ivoire - Degradation

Area of undisturbed Tropical Moist Forest derived from EC JRC Tropical Moist Forest dataset (Vancutsem et al., 2021). Note that values for the most recent 2 years may change in the future when new versions of the Tropical Moist Forest dataset are released, updated to reflect whether recent forest change shows temporary degradation or permanent deforestation.

Undisturbed forest maps were derived from the European Commission's Joint Research Centre's forest cover change in tropical moist forests (TMF) dataset Version 1 from 2023 (Vancutsem et al., 2021) using 41 years of Landsat time series at 30 metre spatial resolution and aggregated at department level. Undisturbed forest was defined as a closed evergreen or semi-evergreen forest without any disturbance observed over the full Landsat historical dataset (Vancutsem et al., 2021).

Côte d’Ivoire - Undisturbed forest

Ghana - Gross greenhouse gas emissions from deforestation

Ghana - Deforestation

Ghana - Degradation

Ghana - Undisturbed forest

Gross greenhouse gas emissions from territorial deforestation. Estimates are based on the total biomass removal stored in above- and below-ground biomass in forests (excl. soil carbon). CO₂-eq were derived by multiplying carbon stocks by 3.67.

Gross greenhouse gas emissions from territorial deforestation (tonnes of CO2-eq) were calculated by estimating the maximum CO2-eq potentially emitted due to the full removal of the biomass as a result of territorial deforestation. This metric is calculated by multiplying territorial deforestation by the estimated carbon stock per hectare of converted land. Carbon stocks include above and below-ground biomass, excluding soil biomass. We derived local above-ground woody biomass density (carbon stocks per hectare) from Harris et al. (2021). We estimated below-ground biomass density from the above-ground biomass based on the ratio of below-ground to above-ground biomass derived from Spawn et al. (2010). We converted biomass to carbon using conversion factors of 0.47 t C t-1 for above-ground and 0.39 t C t-1 for below-ground, respectively (Diop et al., 2016). Finally, we converted carbon to CO2-eq emissions by multiplying the carbon estimates by a factor of 44/12 (or 3.67), based on the ratio between the molecular weight of C and CO₂ following IPCC (2014).

Indonesia - Gross emissions from deforestation

Greenhouse gas emissions from peat subsidence linked to palm oil production in a given year. The emissions are calculated based on the area of industrial oil palm plantations located on peatland multiplied by an emission factor of 90 t CO₂-eq./ha, following Cooper et al. (2020).

GHG emissions from peat subsidence in a given year were estimated based on the area of industrial oil palm plantations located on peat soils within each FFB production unit for the target year. This area was multiplied by an emission factor of 90 t CO₂ eq ha⁻¹ yr⁻¹, averaged over a 30-year plantation cycle, to account for methane, nitrous oxide, and carbon dioxide emissions resulting from peat oxidation and subsidence after drainage (Cooper et al., 2020). 

Indonesia - Emissions from peat subsidence

Gross greenhouse gas emissions from land converted to industrial oil palm plantations in a given year, including both forest and non-forest areas. Emissions were estimated by multiplying the converted area by the estimated carbon stocks per hectare, using above-ground biomass data from Harris et al. (2021) and applying root-to-shoot ratios from Spawn et al. (2020) to estimate below-ground biomass. Estimates are based on total biomass removal (above- and below-ground) and exclude soil carbon. CO₂-equivalents were calculated by multiplying total carbon stocks by 3.67.

Gross greenhouse gas emissions from industrial palm oil conversion (tonnes of CO2-eq) were calculated within a given year by estimating all of the CO2-eq potentially emitted due to annual oil palm land use change, including both from natural forest and non-forest land covers (as defined in Gaveau et al. (2022). This metric is calculated by multiplying the area converted each year to palm oil by an estimate of the carbon stock (above and below ground, excluding soil carbon stocks) contained in each hectare of converted land. Above-ground woody biomass density (carbon stocks per hectare) was derived from Harris et al. (2021). Below-ground biomass density was estimated based on Harris et al.’s above-ground biomass density and the ratio of below-ground to above-ground biomass derived from Spawn et al. (2020). To convert biomass to carbon density, we used conversion factors of 0.47 t C t-1 for aboveground and 0.39 t C-1 for belowground, respectively (Diop et al., 2016). Carbon is converted into CO₂-eq emissions by multiplying by a factor of 44/12 (or 3.67), based on the ratio between the molecular weight of C and CO₂ following IPCC (2014).

Indonesia - Gross emissions from land-use change

Net greenhouse gas emissions from land-use change were calculated as the difference between gross emissions from oil palm plantation expansion and carbon sequestration in new industrial oil palm plantations in the target year. Values may be negative if oil palm plantations are established on non-forest land.

Net greenhouse gas emissions from industrial oil palm were calculated as the difference between gross emissions from oil palm plantation expansion and carbon sequestration in new industrial oil palm plantations. Carbon sequestration was estimated by multiplying the area of new industrial oil palm plantations in the target year by the biomass carbon stock of industrial oil palm plantations per hectare. We used values from Khasanah et al. (2015) for above-ground biomass and applied a 1:4 root-to-shoot ratio from Guillaume et al. (2018) to account for below-ground biomass. Carbon stocks were converted to CO₂-equivalent emissions using a factor of 3.67 (IPCC, 2014).

Indonesia - Net emissions from land-use change

The extent of productive industrial oil palm plantations identified by remote sensing and expert photo interpretation, following the definition of the TreeMap’s Nusantara Atlas (Gaveau et al., 2022).

Oil palm planted area is the extent of productive industrial oil palm. It was calculated using data provided by Gaveau et al. (2022), who mapped the year in which oil palm is first planted in a given location. This dataset can be viewed at Nusantara Atlas (The TreeMap, 2025). Oil palms were assumed to start producing fresh fruit bunches (FFB) in the third year after planting and continue to produce for up to 30 years. Based on these assumptions,the productive oil palm planted area assigned is the total area planted  three years before the target year. For example, the productive oil palm planted area in 2018 is represented by the total area mapped as oil palm plantation in 2015 by Gaveau et. al. (Gaveau et al., 2022).

Indonesia - Oil palm planted area

The total area of forest areas converted to industrial oil palm plantations in the selected year

Annual deforestation for industrial oil palm measures the forest area cleared for oil palm plantations in the target year, following the definition of rapid forest conversion to industrial oil palm in Gaveau et al. (2022). The data is derived from Gaveau et al. (Gaveau et al., 2022; The TreeMap, 2025) 

Indonesia - Annual palm deforestation (industrial)

Area of peatland of all depths planted with oil palm.

Oil palm on peatlands refers to the total area of oil palm (Gaveau et al., 2022; The TreeMap, 2025) planted on peatlands. Peatland areas were derived from Indonesia's official peatland map, which was published by the Indonesian Center for Agricultural Land Resources Research and Development within the Ministry of Agriculture in 2019 (Ministry of Agriculture, 2019). 

Indonesia - Oil palm planted on peat

Area of remaining natural forest, following the definition of The TreeMap’s Nusantara Atlas (Gaveau et al., 2021).

Natural forest area is the total area of remaining forest derived from Gaveau et al.(2022). Gaveau et al. (2022) combine primary forest cover in 2000 (Margono et al., 2014), and the global forest change data developed at the University of Maryland (Hansen et al., 2013). This definition of ‘forest’ excludes young regenerating forests, agroforests, scrublands, tree plantations, agricultural lands, grasslands, and non-vegetated areas (Gaveau et al., 2022). 

Indonesia - Natural forest

This metric represents the total deforestation of forests occurring in a single year (Gaveau et al., 2022; The TreeMap, 2025). To calculate territorial deforestation, Gaveau et al. (2022) combine primary forest in  2000 as identified by Margono et al. (2014) and the global forest change  data developed at the University of Maryland (Hansen et al., 2013). Excluding forest losses outside primary forest in 2000 (Margono et al. 2014), ensure that the deforestation reported measures forest area change rather than changes in planted trees 

Indonesia - Deforestation

Total area of natural forest converted to pulpwood plantations within the boundaries of a wood supplier’s concession in the selected year, following the definition of the TreeMap’s Nusantara Atlas (Gaveau et al., 2022). 

This metric represents total deforestation for conversion to pulpwood plantations in a single year, per concession. A subset of the annual deforestation metric, it is restricted to only those areas identified as natural forest one year before the target year and consistent with patterns of expansion of pulpwood plantations in the target year, according to the classification of Gaveau et al. (2022). 

Indonesia - Deforestation for planted pulpwood

Paraguay - Emissions from deforestation

Estimated area of deforestation for wood pulp that occurred on peatlands within the boundaries of a wood supplier’s concession in the selected year.

This metric represents total deforestation for conversion to pulpwood plantations in a single year, per concession occurring on peatlands (Ministry of Agriculture, 2019). 

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