MAAP #220: Carbon across the Amazon (part 3): Key Cases of Carbon Loss & Gain

Graph 1. The Amazon biome functions as a narrow carbon sink from 2013 to 2022. Data: Planet, ACA/MAAP.

In part 1 of this series (MAAP #215), we introduced a critical new dataset (Planet’s Forest Carbon Diligence) with wall-to-wall estimates for aboveground carbon at an unprecedented 30-meter resolution between 2013 and 2022. This data uniquely merges machine learning, satellite imagery, airborne lasers, and a global biomass dataset from GEDI, a NASA mission.

In part 2 (MAAP #217), we highlighted which parts of the Amazon are currently home to the highest (peak) aboveground carbon levels and the importance of protecting these high-integrity forests (see Annex 1).

Here, in part 3, we focus on aboveground carbon loss and gain across the Amazon over the 10 years for which we have data (2013-22; see Base Map below).

The Amazon loses carbon to the atmosphere due to deforestation, logging, human-caused fires, and natural disturbances, while it gains carbon from forest regeneration and old-growth forests continuing to sequester atmospheric carbon.4

Overall, we find that the Amazon still narrowly functions as a carbon sink (meaning the carbon gain is greater than the loss) during this period, gaining 64.7 million metric tons of aboveground carbon between 2013 and 2022 (see Graph 1).

This finding underscores the importance of both primary and secondary forests in countering widespread deforestation. Moreover, it highlights the critical potential of primary forests to continue accumulating carbon if left undisturbed.

This gain, however, is quite small relative to the total 56.8 billion metric tons of aboveground carbon contained in the Amazon biome (that is, a gain of just +0.1%), reinforcing concerns that the Amazon could flip to a carbon source in the coming years (with carbon loss becoming greater than its gain) due to increasing deforestation, degradation, and fires.1  See Annex 2 for more details, including how the Amazon became a carbon sink following the 2015 drought, but since rebounded.

The countries with the largest carbon gain are 1) Brazil, 2) Colombia, 3) Suriname, 4) Guyana, and 5) French Guiana. In contrast, the countries with the greatest carbon loss are 1) Bolivia, 2) Venezuela, 3) Peru, and 4) Ecuador.

Zooming in to the site level yields additional insights. For example, we can now estimate the carbon loss from major deforestation events across the Amazon from 2013 to 2022. On the flip side, we can also calculate the carbon gain from both secondary and primary forests.

Areas with carbon gain in intact areas indicate excellent candidates for the High Integrity Forest (HIFOR) initiative, a new financing instrument uniquely focused on maintaining intact tropical forests.2 Importantly, a HIFOR unit represents a hectare of high-integrity tropical forest within a high-integrity landscape that has been “well-conserved” for over a decade.Intact areas with carbon gain between 2013-22 may indicate decadally “well-conserved” areas that can be overlapped with areas of high ecological integrity.

Below, we illustrate these findings with a series of novel maps zooming in on emblematic cases of large carbon loss and gain across the Amazon from 2013 – 2022. These cases include forest loss driven by agriculture, gold mining, and roads, as well as forest gain in remote primary forests.

Base Map – Amazon Carbon Loss & Gain (2013-2022)

The Base Map shows wall-to-wall estimates of aboveground carbon loss and gain across the Amazon between 2013 and 2022.

Carbon loss is indicated by yellow to red, indicating low to high carbon loss. Carbon gain is indicated by light to dark green, indicating low to high carbon gains.

Below, we present a series of notable cases of high carbon loss and gain indicated in Insets A-I.

Base Map. Areas of major carbon loss and gain across the Amazon between 2013 and 2022. Source: Amazon Conservation/MAAP, Planet.

Emblematic Cases of Carbon Loss & Gain

Figure 1 highlights emblematic cases of carbon loss (Insets A-F in red) and carbon gain (Insets G-I in green). Below we highlight a series of emblematic cases.

Figure 1. Emblematic cases of carbon loss and gain across the Amazon. Source: Amazon Conservation/MAAP, Planet.

Carbon Loss

We can now estimate the carbon loss from major deforestation events across the Amazon during the past ten years, directly from a single dataset. These cases include forest loss from agriculture, gold mining, and roads. Note that the presented values represent just the carbon loss featured in the selected area.

A. Colombia – Arc of Deforestation

Figure 1A. Carbon loss in the Colombian Amazon’s arc of deforestation. Source: Amazon Conservation/MAAP, Planet.

Figure 1A shows the extensive carbon emissions (39.5 million metric tons) associated with the major deforestation within and surrounding protected areas and Indigenous territories in the Colombian Amazon‘s arc of deforestation.

The carbon loss within the protected areas and Indigenous territories is likely from illegal deforestation.

See MAAP #211 for more details.

 

 

 

 

 

 

 

 

 

B. Peru – Mennonite Colonies

Figure 1B. Carbon loss by new Mennonite colonies in the Peruvian Amazon. Source: Amazon Conservation/MAAP, Planet.

Figure 1B shows the carbon emissions of 224,300 metric tons associated with the recent deforestation carried out by new Mennonite colonies arriving in the central Peruvian Amazon starting in 2017.

See MAAP #188 for more details, including information regarding the legality of  the deforestation causing the carbon loss.

 

 

 

 

 

 

 

 

 

 

C. Peru – Gold Mining

Figure 1C. Carbon loss associated with gold mining deforestation in  southern Peruvian Amazon. Source: ACA/MAAP, Planet.

Figure 1C shows the extensive carbon emissions (11.3 million metric tons) associated with gold mining deforestation in the southern Peruvian Amazon.

Most of the carbon loss within the protected areas (and their buffer zones) and Indigenous territories is likely from illegal deforestation.

See MAAP #208 for more information, including details regarding the legality of the deforestation causing the carbon loss.

 

 

 

 

 

 

 

 

 

D. Brazil – Road BR-364

Figure 1D. Carbon loss along BR-364 in the southwest Brazilian Amazon. Source: ACA/MAAP, Planet.

Figure 1D shows the carbon emissions along road BR-364 that crosses the state of Acre in the southwest Brazilian Amazon.

This road was opened in the 1960s and paved in the 1980s.

 

 

 

 

 

 

 

 

 

 

 

E. Brazil – Road BR-319

Figure 1E. Carbon loss along paved roads. Source: ACA/MAAP, Planet.

Figure 1E shows a controversial road paving project that would effectively link the arc of deforestation to the south with more intact forests to the north in Amazonas and Roraima states.

Note that the current carbon loss is concentrated along the paved roads.

The paving of road BR-319 has recently caused headlines as President Luiz Inácio Lula da Silva recently authorized the paving of 20 km of the road and plans to bid for an additional 32 km (thus, paving of 52 km in total).

Modeling studies predict extensive new deforestation from this road construction, and thus additional associated carbon loss.

 

 

 

 

 

 

 

 

F. Brazil – Road BR-163

Figure 1F. Carbon loss along BR-163 in the eastern Brazilian Amazon. Source: ACA/MAAP, Planet.

Figure 1F shows the extensive carbon emissions (71.4 million metric tons) along a recently paved stretch of road BR-163 which crosses the state of Pará in the eastern Brazilian Amazon.

Importantly, this stretch of road has been presented as a case study of what may happen along road BR-319 if it is paved.

 

 

 

 

 

 

 

 

 

 

 

Carbon Gain

We can also calculate the carbon gain from both secondary and primary forests. These cases include forest gain from remote primary forests that may be good candidates for the HIFOR initiative.

Figure 1G. Carbon gains in the southeast Colombian Amazon. Source: ACA/MAAP, Planet.

G. Southeast Colombia

Figure 1G shows the carbon gain of over 52.5 million metric tons in the remote southeast Colombian Amazon.

This area is anchored by three national parks and several large indigenous territories.

 

 

 

 

 

 

 

 

 

 

Figure 1H. Carbon gains along the border of eastern Ecuador and northern Peru. Source: ACA/MAAP, Planet.

H. Ecuador – Peru border

Figure 1H shows the carbon gain of nearly 40 million metric tons along the border in eastern Ecuador and northern Peru.

Note this area is anchored by numerous protected areas, including Yasuni National Park in Ecuador and Pucacuro National Reserve in Peru, and Indigenous territories.

 

 

 

 

 

 

 

 

 

Figure 1I. Carbon gains in the tri-border region of the northeast Amazon. Source: ACA/MAAP, Planet.

I. Northeast Amazon

Figure 1I shows the carbon gain of 164.7 million metric tons in the tri-border region of the northeast Amazon (northern Brazil, French Guiana, and Suriname).

For example, note the carbon gains in Montanhas do Tumucumaque National Park and Tumucumaque Indigenous territory in northeast Brazil.

Also note that this was an Amazonian “peak carbon area,” as described in MAAP #217.

 

 

 

 

 

 

 

 

 

Annex 1

Annex 1. Peak carbon areas in relation to the carbon loss and gain data. Source: Amazon Conservation/MAAP, Planet.

In part 2 of this series (MAAP #217), we highlighted which parts of the Amazon are currently home to the highest (peak) aboveground carbon levels.

Annex 1 shows these peak carbon areas in relation to the carbon loss and gain data presented above.

Note that both peak carbon areas (southeast and northeast Amazon) are largely characterized by carbon gain.

 

 

 

 

 

 

 

 

 

Annex 2

Annex 2. Amazon biome functions as a narrow carbon sink from 2013 to 2022, but became a source in between. Data: Planet, ACA/MAAP.

Annex 2 shows all ten years of aboveground carbon data grouped by two-year intervals (thus, it is an extension of Graph 1 above, adding data for the intermediate years).

In this context, black indicates our baseline of 2013-14, red indicates a decrease from the baseline (carbon source), and green indicates an increase from the baseline (carbon sink).

Importantly, there was a decrease in aboveground carbon from 2015-18, which likely reflects the severe droughts of 2015 and 2016 and subsequent severe fire seasons of 2016 and 2017. Aboveground carbon rebounded from 2019-22.

This trend supports the hypothesis that the Amazon biome is teetering on being an aboveground carbon source vs sink.

It also raises the possibility that the Amazon may return to being a carbon source following the intense drought and fires of 2024.

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Notes

1 In part 1 of this series (MAAP #215), we found the Amazon “is still functioning as a critical carbon sink”. As pointed out in a companion blog by Planet, however, the net carbon sink of +64 million metric tons is quite small relative to the total estimate of 56.8 billion metric tons of aboveground carbon across the Amazon. That is a net positive change of just +0.1%. As the blog notes, that’s a “very small buffer” and there’s “reason to worry that the biome could flip from sink to source with ongoing deforestation.”

2 High Integrity Forest (HIFOR) units are a new, non-offset asset that recognizes and rewards the essential climate services and biodiversity conservation that intact tropical forests provide, including ongoing net removal of CO2 from the atmosphere. HIFOR rewards the climate services that intact tropical forests provide, including ongoing net carbon removal from the atmosphere, and complements existing instruments to reduce emissions from deforestation and degradation (REDD+) by focusing on tropical forests that are largely undegraded. A HIFOR unit represents a hectare of well-conserved, high-integrity tropical forest where ‘well-conserved’ means that high ecological integrity is maintained over a decade of monitoring as part of equitable, effective management of a site and ‘high ecological integrity’ means a score of >9.6 on the Forest Landscape Integrity Index. For more information see https://www.wcs.org/our-work/climate-change/forests-and-climate-change/hifor

3 Two additional important references regarding HIFOR methodology and application:

High Integrity Forest Investment Initiative, Methodology for HIFOR units, April 2024. Downloaded from https://www.wcs.org/our-work/climate-change/forests-and-climate-change/hifor

Forest Landscape Integrity Index metric used by HIFOR: www.forestintegrity.com

4 In Planet’s Forest Carbon Diligence product, carbon loss and gain are detected via changes in canopy cover and canopy height during the given periods (in this case, 2013 vs 2022).

Acknowledgments

Through a generous sharing agreement with the satellite company Planet, we have been granted access to this data across the entire Amazon biome for the analysis presented in this series.

We also thank D. Zarin (WCS) for helpful comments regarding the implications of our findings for the HIFOR initiative.

Citation

Finer M, Mamani N, Anderson C, Rosenthal A (2024) Carbon across the Amazon (part 3): Key Cases of Carbon Loss & Gain. MAAP: 220.

MAAP #217: Carbon across the Amazon (part 2): Peak Carbon Areas

Figure 1. Example of peak carbon areas in southern Peru and adjacent western Brazil. Data: Planet.

In part 1 of this series (MAAP #215), we introduced a critical new resource (Planet Forest Carbon Diligence) that provides wall-to-wall estimates for aboveground carbon density at an unprecedented 30-meter resolution. This data uniquely merges machine learning, satellite imagery, airborne lasers, and a global biomass dataset from GEDI, a NASA mission.4

In that report, we showed that the Amazon contains 56.8 billion metric tons of aboveground carbon (as of 2022), and described key patterns across all nine countries of the Amazon biome over the past decade.

Here, in part 2, we focus on the peak carbon areas of the Amazon that are home to the highest aboveground carbon levels.

These peak carbon areas correspond to the upper one-third of aboveground carbon density levels (>140 metric tons per hectare).1

They likely have experienced minimal degradation (such as selective logging, fire, and edge/fragmentation effects)2 and are thus a good proxy for high-integrity forests.

Figure 1 shows an important example of peak carbon areas in southern Peru and adjacent western Brazil.

The peak carbon areas are often found in the remote primary forests of protected areas and Indigenous territories, but some are located in forestry concessions (specifically, logging concessions) or undesignated lands (also referred to as undesignated public forests).

Our goal in this report is to leverage unprecedented aboveground carbon data to reinforce the importance of these designated areas and draw attention to the remaining undesignated lands.

For example, peak carbon areas would be excellent candidates for the High Integrity Forest (HIFOR) initiative, a new financing instrument that uniquely focuses on maintaining intact tropical forests.3 HIFOR rewards the climate services that intact tropical forests provide, including ongoing net carbon removal from the atmosphere, and complements existing instruments to reduce emissions from deforestation and degradation (REDD+) by focusing on tropical forests that are largely undegraded.

Below, we detail the major findings and then zoom in on the peak carbon areas in the northeast and southwest Amazon.

Peak Carbon Areas in the Amazon   

The Base Map below illustrates our major findings.

The peak carbon areas (>140 metric tons per hectare; indicated in pink) are concentrated in the southwest and northeast Amazon, covering 27.8 million hectares (11 million ha in the southwest and 16.8 million ha in the northeast).
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Base Map. Planet Forest Carbon Diligence across the Amazon biome for the year 2022. Data: Planet.

In the southwest Amazon, peak carbon levels are found in southern & central Peru, and adjacent western Brazil.

In the northeast Amazon, peak carbon levels are found in northeast Brazil, much of French Guiana, and parts of Suriname.

By country, Brazil and Peru have the largest area of peak carbon (10.9 million and 10.1 million hectares respectively), followed by French Guiana (4.7 million ha), and Suriname (2.1 million ha).

Protected areas and Indigenous territories cover much (61%) of the peak carbon area (16.9 million hectares).

The remaining 39% remains unprotected, and arguably threatened, in undesignated lands (9.4 million hectares) and forestry concessions (1.5 million ha), respectively.

In addition, high carbon areas (>70 metric tons per hectare; indicated by the greenish-yellow coloration in the Base Map) are found in all nine countries of the Amazon biome, notably Colombia, Ecuador, Bolivia, Venezuela, and Guyana.

Southwest Amazon

­Southern Peru

Figure 2a. Peak carbon area in the southern Peruvian Amazon. Data: Planet, SERNANP, RAISG.

Figure 2a zooms in on the peak carbon area covering 7.9 million hectares in southern Peru (regions of Madre de Dios, Cusco, and Ucayali) and adjacent southwest Brazil (Acre).

Several protected areas (such as Manu and Alto Purús National Parks, and Machiguenga Communal Reserve) anchor this area.

It is also home to numerous Indigenous territories (such as Mashco Piro, Madre de Dios, and Kugapakori, Nahua, Nanti & Others Indigenous Reserves).

 

 

 

 

 

 

 

 

 

 

Figure 2b highlights the major land designations within the peak carbon area of southern Peru.

Figure 2b. Peak carbon areas (outlined in pink), categorized by land designation in southern Peru and adjacent western Brazil. Data: Planet, NICFI, SERNANP, SERFOR, RAISG.

Protected areas and Indigenous territories cover 77% of this area (green and brown, respectively).

The remaining 23% could be considered threatened, as they are located in forestry concessions or undesignated lands (orange and red, respectively). Thus, these areas are ideal candidates for increased protection to maintain their peak carbon levels.

 

 

 

 

 

 

 

 

 

 

 

Central Peru

Figure 3a. Peak carbon area in the central Peruvian Amazon. Data: Planet, SERNANP, RAISG.

Figure 3a zooms in on the peak carbon area in the central Peruvian Amazon, which covers 3.1 million hectares in the regions of Ucayali, Loreto, Huánuco, Pasco, and San Martin.

Several protected areas (including Sierra del Divisor, Cordillera Azul, Rio Abiseo, and Yanachaga–Chemillén National Parks, and El Sira Communal Reserve) anchor this area.

It is also home to numerous Indigenous territories (such as Kakataibo, Isconahua, and Yavarí Tapiche Indigenous Reserves).

 

 

 

 

 

 

 

 

 

 

Figure 3b. Peak carbon areas (outlined in pink), categorized by land designation in central Peru. Data: Planet, NICFI, SERNANP, SERFOR, RAISG.

Figure 3b highlights the major land designations within the peak carbon area of central Peru.

Protected areas and Indigenous territories cover 69% of this area (green and brown, respectively).

The remaining 31% could be considered threatened, as they are located in forestry concessions or undesignated lands (orange and red, respectively), and are ideal candidates for increased protection.

 

 

 

 

 

 

 

 

 

 

 

 

 

Northeast Amazon

Figure 4a. Peak carbon area in the tri-border region of the northeast Amazon. Data: Planet, RAISG.

Figure 4a zooms in on the peak carbon area in the tri-border region of the northeast Amazon, which covers 16.8 million hectares in northern Brazil, French Guiana, and Suriname.

Several protected areas (including Montanhas do Tumucumaque National Park in northeast Brazil, Amazonien de Guyane National Park in French Guiana, and Central Suriname Nature Reserve) anchor this area.

It is also home to numerous Indigenous territories (such as Tumucumaque, Rio Paru de Este, and Wayãpi in northeast Brazil).

 

 

 

 

 

 

Figure 4b. Peak carbon areas (outlined in pink), categorized by land designation in northeast Amazon. Data: Planet, NICFI, RAISG.

Figure 4b highlights the major land designations within the peak carbon area of the northeast Amazon.

Protected areas and Indigenous territories cover just over half (51%) of this area (green and brown, respectively).

The remaining 49% could be considered threatened, as they are located in undesignated lands, and are ideal candidates for increased protection.

 

 

 

 

 

 

 

 

 

Notes

1 We selected this value (upper 33%) to capture the highest aboveground carbon areas and include a range of high carbon areas. Additional analyses could target different values, such as the highest 10% or 20% of aboveground carbon.

2  A recent paper documented a strong relationship between selective logging and aboveground carbon loss (Csillik et al. 2024, PNAS). The link between forest edges and carbon is presented in Silva Junior et al, Science Advances.

3 High Integrity Forest (HIFOR) units are a new tradable asset that recognizes and rewards the essential climate services and biodiversity conservation that intact tropical forests provide, including ongoing net removal of CO2 from the atmosphere. For more information see https://www.wcs.org/our-work/climate-change/forests-and-climate-change/hifor

4 For more information, see the “What is Forest Carbon Diligence?” section in this recent blog from Planet.

Citation

Finer M, Mamani N, Anderson C, Rosenthal A (2024) Carbon across the Amazon (part 2): Peak Carbon Areas. MAAP #217.

MAAP #215: Unprecedented Look at Carbon across the Amazon (part 1)

Figure 1. Example of Planet Forest Carbon Diligence, focused on southern Peru and adjacent western Brazil.

The Amazon biome has long been one of the world’s largest carbon sinks, helping stabilize the global climate.

Precisely estimating this carbon, however, has been a challenge. Fortunately, new satellite-based technologies are providing major advances, most notably NASA’s GEDI mission (see MAAP #213) and, most recently, Planet Forest Carbon Diligence.1

Here, we focus on the latter, analyzing Planet’s cutting-edge new dataset, featuring a 10-year historical time series (2013 – 2022) with wall-to-wall estimates for aboveground carbon density at 30-meter resolution.

As a result, we can produce high-resolution aboveground carbon maps and estimates for anywhere and everywhere across the vast Amazon (see Figure 1).

Through a generous sharing agreement with Planet, we have been granted access to this data across the entire Amazon biome for the analysis presented in the following three-part series:

  1. Estimate and illustrate total aboveground forest carbon across the Amazon biome in unprecedented detail (see results of this first report, below).
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  2. Highlight which parts of the Amazon are home to the highest aboveground carbon levels, including protected areas and Indigenous territories (see second report, MAAP #217).
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  3. Present emblematic deforestation cases that have resulted in the highest aboveground carbon emissions across the Amazon (see third report, MAAP #220).

Major Results

Carbon across the Amazon

Based on our analysis of Planet Forest Carbon Diligence, we estimate that the Amazon contained 56.8 billion metric tons of aboveground carbon, as of 2022 (see Base Map). Applying a standard root-to-shoot ratio conversion (26%), this estimate increases to 71.5 billion metric tons of above and belowground carbon. This total is equivalent to nearly two years of global carbon dioxide emissions at the peak 2022 level (37.15 billion metric tons).5

The peak carbon levels are largely concentrated in the southwest Amazon (southern Peru and adjacent western Brazil) and northeast Amazon (northeast Brazil, French Guiana, and Suriname).

Base Map. Planet Forest Carbon Diligence across the Amazon biome.

Total Carbon by Country

As shown in Graph 1, countries with the most aboveground carbon are 1) Brazil (57%; 32.1 billion metric tons), 2) Peru (15%; 8.3 billion metric tons), 3) Colombia (7%; 4 billion metric tons), 4) Venezuela (6%; 3.3 billion metric tons), and 5) Bolivia (6%; 3.2 billion metric tons). These countries are followed by Guyana (3%; 2 billion metric tons), Suriname (3%; 1.6 billion metric tons), Ecuador (2%; 1.2 billion metric tons), and French Guiana (2%; 1.1 billion metric tons).

Overall, we documented the total gain of 64.7 million metric tons of aboveground carbon across the Amazon during the ten years between 2013 and 2022.2 In other words, the Amazon is still functioning as a critical carbon sink.

The countries with the most aboveground carbon gain over the past ten years are 1) Brazil, 2) Colombia, 3) Suriname, 4) Guyana, and 5) French Guiana. Note that we show Brazil as a carbon sink (gain of 102.8 million metric tons), despite other recent studies showing it as a carbon source.3 Also note the important gains in aboveground carbon across several key High Forest cover, Low Deforestation (HFLD) countries, namely Colombia, Suriname, Guyana, and French Guiana.4

In contrast, the countries with the most aboveground carbon loss over the past ten years are 1) Bolivia, 2) Venezuela, 3) Peru, and 4) Ecuador.

Graph 1. Planet Forest Carbon Diligence data across the Amazon biome, comparing 2013-14 with 2021-22. Note that a “+” symbol indicates that the country gained aboveground carbon, while a “-“ symbol indicates that the country lost aboveground carbon.

Carbon Density by Country

Standardizing for area, Graph 2 shows that countries with the highest aboveground carbon density (that is, aboveground carbon per hectare as of 2021-22) are located in the northeast Amazon: French Guiana (134 metric tons/hectare), Suriname (122 metric tons/hectare), and Guyana (85 metric tons/hectare). Ecuador is also high (94 metric tons/hectare).

Note that countries in the northeast Amazon (French Guiana, Suriname, and Guyana) have lower total aboveground carbon due to their smaller size (Graph 1), but high aboveground carbon density per hectare (Graph 2). This also applies to Ecuador.

Graph 2. Planet Forest Carbon Diligence data for aboveground carbon density by country across the Amazon, comparing 2013-14 with 2021-22. Note that a “+” symbol indicates that the country gained aboveground carbon, while a “-“ symbol indicates that the country lost aboveground carbon.

Notes & Citations

1 Anderson C (2024) Forest Carbon Diligence: Breaking Down The Validation And Intercomparison Report. https://www.planet.com/pulse/forest-carbon-diligence-breaking-down-the-validation-and-intercomparison-report/

2 In terms of uncertainty, the data contains pixel-level estimates, but not yet at national levels. To minimize annual uncertainty at the country level, we averaged 2013 and 2014 for the baseline and 2021 and 2022 for the current state.

3 Recently, in MAAP #144, we showed Brazil as a carbon source, based on data from 2001 to 2020. In contrast, Planet Forest Carbon Diligence is based on data from 2013 to 2022. Thus, one interpretation of the difference is that most carbon loss occurred in the first decade of the 2000s, which is consistent with historical deforestation data showing peaks in the early 2000s. It also highlights the likely importance of the interplay between forest loss/degradation (carbon loss) and forest regeneration (carbon gain) in terms of whether a country is a carbon source or sink during a given timeframe.

4 HFDL, or “High Forest cover, Low Deforestation” describes countries with both a) high forest cover (>50%) and low deforestation rates (<0.22% per year). For more information on HFDL, see https://www.conservation.org/blog/what-on-earth-is-hfld-hint-its-about-forests

5 Annual carbon dioxide (CO₂) emissions worldwide from 1940 to 2023

Citation

Finer M, Mamani N, Anderson C, Rosenthal A (2024) Unprecedented Look at Carbon across the Amazon. MAAP  #215.

 

MAAP #213: Estimating Carbon in Amazon Protected Areas & Indigenous Territories

Intro Image. Screenshot of OBI-WAN forest carbon reporting app.

In a recent report (MAAP #199), we presented the updated version of NASA’s GEDI data,1 which uses lasers aboard the International Space Station to provide cutting-edge estimates of aboveground carbon globally, including our focal area, the Amazon.

These lasers, however, have not yet achieved full coverage, leaving considerable gaps in the data and resulting maps.

Here, we feature two new tools that allow us to fill in these gaps and provide detailed wall-to-wall estimates of aboveground biomass for specific areas, which can then be converted to aboveground carbon estimates.

The first is the OBI-WAN forest carbon reporting app (see Intro Image), which uses statistical inference to produce mean, total, and uncertainty estimates for biomass baselines at any given scale (from local to worldwide).2

The second is a fused product from GEDI and TanDEM-X missions.3 The combination of lidar (GEDI) and radar (TanDEM-X) has started to produce unmatched maps that combine the ability of lidar to retrieve forest structure and the ability of radar to offer wall-to-wall coverage at multiple resolutions (see Figures 1-5 below for examples at 25m resolution).

Employing these two tools, we focus on estimating aboveground carbon for select examples of two critical land designations in the Amazon: protected areas and indigenous territories. Both are critical to the long-term conservation of the core Amazon (MAAP #183). We hope that providing precise carbon data will provide additional incentives for their long-term conservation.

We select 5 focal areas (3 National Parks and 2 Indigenous Territories; see list below) across the Amazon to demonstrate the power of these datasets. Together, these five areas are currently home to over 1.4 billion metric tons of aboveground carbon.

  • Protected Areas (National Parks)
    Chirbiquete National Park (Colombian Amazon)
    Manu National Park (Peruvian Amazon)
    Madidi National Park (Bolivian Amazon)
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  • Indigenous Territories
    Kayapó Indigenous Territory (Brazilian Amazon)
    Barranco Chico Indigenous Territory (Peruvian Amazon)

Focal Areas

As noted above, the aboveground carbon estimates below are based on the aboveground biomass estimates from the OBI-WAN forest carbon reporting app and GEDI-TanDEM-X data. Figures 1 – 5 are based on GEDI-TanDEM-X, at 25 meter resolution.

National Parks

Chirbiquete National Park (Colombian Amazon)

Chirbiquete National Park covers over 4.2 million hectares in the heart of the Colombian Amazon (Guaviare and Caqueta departments). Both datasets converge in the estimate of around 600 metric tons of aboveground biomass, equating to over 300 million metric tons of aboveground carbon across the park (80.5 tons of carbon per hectare). Figure 1 shows the detailed spatial distribution of this biomass across Chirbiquete National Park. Note that the GEDI-TanDEM-X data misses the western tip of the park.

Figure 1. Aboveground biomass across Chiribiquete National Park (Colombian Amazon). Data: GEDI-TanDEM-X

 

Manu National Park (Peruvian Amazon)

Figure 2. Aboveground biomass across Manu National Park (Peruvian Amazon). Data: GEDI-TanDEM-X

Manu National Park covers over 1.7 million hectares in the southern Peruvian Amazon (Madre de Dios and Cusco regions).

Both datasets converge in the estimate of over 450 metric tons of aboveground biomass, equating to over 215 million metric tons of aboveground carbon across the territory (126.8 tons of carbon per hectare).

Figure 2 shows the detailed spatial distribution of this biomass across Manu National Park.

 

 

 

 

 

 

 

 

 

 

 

Madidi National Park (Bolivian Amazon)

Figure 3. Aboveground biomass across Madidi National Park (Bolivian Amazon). Data: GEDI-TanDEM-X

Madidi National Park and Integrated Management Area covers over 1.8 million hectares in the western Bolivian Amazon (La Paz department).

Both datasets converge in the estimate of over 350 metric tons of aboveground biomass, equating to over 160 million metric tons of aboveground carbon across the park (85.3 tons of carbon per hectare).

Figure 3 shows the detailed spatial distribution of this biomass across Madidi National Park. Note that the GEDI-TanDEM-X data misses the southern tip of the park.

 

 

 

 

 

 

 

 

 

 

Indigenous Territories

Kayapó Indigenous Territory (Brazilian Amazon)

Kayapó Indigenous Territory covers over 3.2 million hectares in the eastern Brazilian Amazon (Pará state). Both datasets converge in the estimate of over 413,000 metric tons of aboveground biomass, equating to over 198 million metric tons of aboveground carbon across the territory. Figure 4 shows the detailed spatial distribution of this biomass across Kayapó and four neighboring Indigenous Territories. Totaling across these five territories (10.4 million hectares), the data sets converge on over 1.5 billion metric tons of aboveground biomass, and 730 million metric tons of aboveground carbon (70 tons per hectare).

Figure 4. Aboveground biomass across Kayapó and neighboring Indigenous Territories (Brazilian Amazon). Data: GEDI-TanDEM-X

Barranco Chico Indigenous Territory (Peruvian Amazon)

Barranco Chico Indigenous Territory covers over 12,600 hectares in the southern Peruvian Amazon (Madre de Dios region). Both datasets converge in the estimate of over 2 million metric tons of aboveground biomass, equating to over 1 million metric tons of aboveground carbon. Figure 5 shows the detailed spatial distribution of this biomass across Barranco Chico and two neighboring Indigenous Territories (Puerto Luz and San Jose de Karene). Totaling across these three territories (nearly 90,000 hectares), the data sets converge on over 19 million metric tons of aboveground biomass, and over 9 million metric tons of aboveground carbon (102 tons per hectare).

Figure 5. Aboveground biomass across Barranco Chico and neighboring Indigenous Territories (Peruvian Amazon). Data: GEDI-TanDEM-X

Notes

1 GEDI L4B Gridded Aboveground Biomass Density, Version 2.1. This data is measured in megagrams of aboveground biomass per hectare (Mg/ha) at a 1-kilometer resolution, with the period of April 2019 – March 2023. This serves as our estimate for aboveground carbon reserves, with the science-based assumption that 48% of recorded biomass is carbon.

The approach relies on the foundational paper from Patterson et al., (2019) and it is used by the GEDI mission to estimate mean and total biomass worldwide (Dubayh et al., 2022, Armston et al., 2023). The method considers the spatial distribution of GEDI tracks within a given user-specify boundary to infer the sampling error component of the total uncertainty that also includes the error from the GEDI L4A models used to predict biomass from canopy height estimates (Keller et al., 2022). For more information on the OBI-WAN app, see Healey and Yang 2022.

3 GEDI-TanDEM-X (GTDX) is a fusion of GEDI Version 2 and TanDEM-X (TDX) Interferometric Synthetic Aperture Radar (InSAR) images (from Jan 2011 to December 2020). It also incorporates annual forest loss data to account for deforestation during this time. The GTDX aboveground biomass maps were produced based on a generalized hierarchical model-based (GHMB) framework that utilizes GEDI biomass as training data to establish models for estimating biomass based on the GTDX canopy height. The combination of lidar (GEDI) and radar (TanDEM-X) has started to produce unmatched maps that combine the ability of lidar to retrieve forest structure and the ability of radar to offer wall-to-wall coverage (Qi et al.,2023, Dubayah et a;., 2023). This fused product is a wall-to-wall gap-free map that was produced at multiple resolutions: 25m, 100m and 1ha. Ongoing processing over the Pantropic region will be made available over the next months but some geographies have been already mapped such as most of the Amazon Basin (Dubayah et al., 2023). The data we used is publicly available.

References

Armston, J., Dubayah, R. O., Healey, S. P., Yang, Z., Patterson, P. L., Saarela, S., Stahl, G., Duncanson, L., Kellner, J. R., Pascual, A., & Bruening, J. (2023). Global Ecosystem Dynamics Investigation (GEDI)GEDI L4B Country-level Summaries of Aboveground Biomass [CSV]. 0 MB. https://doi.org/10.3334/ORNLDAAC/2321

Dubayah, R. O., Armston, J., Healey, S. P., Yang, Z., Patterson, P. L., Saarela, S., Stahl, G., Duncanson, L., Kellner, J. R., Bruening, J., & Pascual, A. (2023). Global Ecosystem Dynamics Investigation (GEDI)GEDI L4B Gridded Aboveground Biomass Density, Version 2.1 [COG]. 0 MB. https://doi.org/10.3334/ORNLDAAC/2299

Dubayah, R., Armston, J., Healey, S. P., Bruening, J. M., Patterson, P. L., Kellner, J. R., Duncanson, L., Saarela, S., Ståhl, G., Yang, Z., Tang, H., Blair, J. B., Fatoyinbo, L., Goetz, S., Hancock, S., Hansen, M., Hofton, M., Hurtt, G., & Luthcke, S. (2022). GEDI launches a new era of biomass inference from space. Environmental Research Letters, 17(9), 095001. https://doi.org/10.1088/1748-9326/ac8694

Dubayah, R., Blair, J. B., Goetz, S., Fatoyinbo, L., Hansen, M., Healey, S., Hofton, M., Hurtt, G., Kellner, J., Luthcke, S., Armston, J., Tang, H., Duncanson, L., Hancock, S., Jantz, P., Marselis, S., Patterson, P. L., Qi, W., & Silva, C. (2020). The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography. Science of Remote Sensing, 1, 100002. https://doi.org/10.1016/j.srs.2020.100002

Healey S, Yang Z (2022) The OBIWAN App: Estimating Property-Level Carbon Storage Using NASA’s GEDI Lidar. https://www.fs.usda.gov/research/rmrs/understory/obiwan-app-estimating-property-level-carbon-storage-using-nasas-gedi-lidar

Kellner, J. R., Armston, J., & Duncanson, L. (2022). Algorithm Theoretical Basis Document for GEDI Footprint Aboveground Biomass Density. Earth and Space Science, 10(4), e2022EA002516. https://doi.org/10.1029/2022EA002516

Dubayah, R.O., W. Qi, J. Armston, T. Fatoyinbo, K. Papathanassiou, M. Pardini, A. Stovall, C. Choi, and V. Cazcarra-Bes. 2023. Pantropical Forest Height and Biomass from GEDI and TanDEM-X Data Fusion. ORNL DAAC, Oak Ridge, Tennessee, USA. https://doi.org/10.3334/ORNLDAAC/2298

Qi, W., J. Armston, C. Choi, A. Stovall, S. Saarela, M. Pardini, L. Fatoyinbo, K. Papathanasiou, and R. Dubayah. 2023. Mapping large-scale pantropical forest canopy height by integrating GEDI lidar and TanDEM-X InSAR data. Research Square. https://doi.org/10.21203/rs.3.rs-3306982/v1

Krieger, G., M. Zink, M. Bachmann, B. Bräutigam, D. Schulze, M. Martone, P. Rizzoli, U. Steinbrecher, J. Walter Antony, F. De Zan, I. Hajnsek, K. Papathanassiou, F. Kugler, M. Rodriguez Cassola, M. Younis, S. Baumgartner, P. López-Dekker, P. Prats, and A. Moreira. 2013. TanDEM-X: A radar interferometer with two formation-flying satellites. Acta Astronautica 89:83–98. https://doi.org/10.1016/j.actaastro.2013.03.008

Acknowledgments

We greatly thank the University of Maryland’s GEDI team for data access and reviewing this report. In particular, we thank Ralph Dubayah, Matheus Nunes, and Sean Healey.

Citation

Mamani N, Pascual A, Finer M (2024) Estimating Carbon in Amazon Protected Areas & Indigenous Territories. MAAP: 213

MAAP #212: Machine learning to detect mining deforestation across the Amazon

Amazon Mining Watch. Screen shot of the interactive mining deforestation map, displaying data for 2023.

Gold Mining is one of the major deforestation drivers across the Amazon.*

It often targets remote areas, thus impacting carbon-rich primary forests. Moreover, in most cases, this mining is illegal, given that it is occurring in protected areas and indigenous territories.

Given the vastness of the Amazon, however, it has been a challenge to accurately monitor mining deforestation across the entire biome in a timely manner.

Here we present, for the first time, the results of a new machine learning based tool (known as Amazon Mining Watch)  that analyzes satellite imagery archives to detect mining deforestation across the entire Amazon.

Specifically, the tool produces 10-meter resolution mining deforestation alerts based on the European Space Agency’s Sentinel-2 satellite imagery. The alerts currently cover each year annually from 2018 to 2023.

This data reveals that gold mining is actively causing deforestation in all nine countries of the Amazon Biome (see Base Map below). The countries with the most overall mining deforestation are 1) Brazil, 2) Guyana, 3) Suriname, 4) Venezuela, and 5) Peru.

*Note that in this report we focus on mining activity that is causing deforestation. Additional critical gold mining areas in rivers (such as in northern Peru, southeast Colombia, and northwest Brazil; see MAAP #197), are not included in this report or detected/displayed in Amazon Mining Watch.

Major Findings

The Base Map below presents the mining deforestation data across the entire Amazon. Note that yellow indicates the historical mining footprint as of 2018, while red indicates the more recent mining deforestation between 2019 and 2023.

Although the alerts are pixels and not designed for precise area measurements, they can be used to give general estimates. For example, we estimate that as of 2018, there was a historical mining deforestation footprint of over 963,000 hectares across the entire Amazon. Between 2019 and 2023, we estimate that the mining deforestation footprint grew by over 944,000 hectares (2.3 million acres).

Thus, of the total accumulated mining deforestation footprint of over 1.9 million hectares (4.7 million acres), about half has occurred in just the past five years (see Annex).

In addition, we estimate that 38% (725,498 hectares) of the total mining deforestation occurred within protected areas and Indigenous territories.

Graph 1 shows, of the total accumulated mining, over half has occurred in Brazil (55%, covering over 1 million hectares), followed by Guyana (15%), Suriname (12%), Venezuela (7%), and Peru (7%, covering 135,625 hectares).

Base Map. Mining deforestation across the Amazon, based on data from Amazon Mining Watch, for the years 2018-2023. Data: AMW, ACA/MAAP.
Graph 1. Mining deforestation across the Amazon, by country. Data: AMW, ACA/MAAP.

Case Studies

In this section, we show a number of case studies highlighting the power of this data to see the evolution of mining deforestation in the following critical areas (see Insets A-E on Base Map). In these examples, note that yellow indicates the historical mining footprint as of 2018, purple indicates the expansion from 2019-2021, and red indicates the more recent mining deforestation between 2022 and 2023.

A. Southern Peruvian Amazon
B. Brazilian Amazon – Yanomami Indigenous Territory
C. Brazilian Amazon – Kayapó Indigenous Territory
D. Venezuelan Amazon – Yapacana National Park
E. Ecuadorian Amazon – Punino zone

A. Southern Peruvian Amazon

In southern Peru is one of the largest, and likely most emblematic, mining sites in the Amazon (see Inset A in Base Map). Figure 1 shows the dynamic evolution in this area, from several large core mining zones as of 2018, with more recent concentration in the designated Mining Corridor (large area where small-scale mining is permitted by the government as part of a formalization process).

Overall, we recorded over 135,000 hectares (333,590 acres) of mining deforestation in this area. Of this total, 62% (84,000 ha) was present as of 2018, while 38% (51,000 ha) has occurred in just the past five years (2019-2023).

We also highlight that of the total mining deforestation (135,000 ha), 59% has occurred within the Mining Corridor, while 41% (55,000 hectares) is outside the corridor and likely illegal. Note how mining deforestation threatens several protected areas, especially Tambopata National Reserve and Amarakaeri Communal Reserve.

See MAAP #208 for more information about mining deforestation at this site, and how illegal mining also threatens Native Communities.

Figure 1. Evolution of mining deforestation in the southern Peruvian Amazon. Data: AMW, ACA/MAAP.

B. Brazilian Amazon – Yanomami Indigenous Territory

In the northern Brazilian Amazon, the national government recently launched a series of raids against illegal gold mining in Yanomami Indigenous Territory (see Inset B in Base Map). Figure 2 shows a major escalation and expansion of gold mining deforestation since 2018, especially along the Uraricoera and Mucajai Rivers.

Specifically, we documented the total mining deforestation of over 19,000 hectares (47,000 acres) in Yanomami Indigenous Territory. It is critical to emphasize that the vast majority (93%) has occurred in just the past five years (2019-2023).

See MAAP #181 for more information about mining deforestation at this site.

Figure 2. Evolution of mining deforestation in Yanomami Indigenous Territory in Brazil. Data: AMW, ACA/MAAP.

C. Brazilian Amazon – Kayapó Indigenous Territory

In the eastern Brazilian Amazon, the Kayapó Indigenous Territory is also facing ongoing illegal mining (see Inset C in Base Map). Figure 3 shows the continuing expansion of mining deforestation, mostly in the eastern section of the territory.

We documented the total mining deforestation of nearly 50,000 hectares (123,550 acres) in Kayapó Indigenous Territory. Of this total, 60% (30,000 has) has occurred in just the past five years (2019-2023).

See MAAP #116 for more information about mining deforestation at this site, along with nearby Munduruku Indigenous Territory.

Figure 3. Evolution of mining deforestation in Kayapo Indigenous Territory in Brazil. Data: AMW, ACA/MAAP.

D. Venezuelan Amazon – Yapacana National Park

In Venezuela, we see the continued expansion of mining deforestation in Yapacana National Park (see Inset D in Base Map). Indeed, Figure 4 shows the steady expansion of gold mining deforestation at several sites in the southern section of the protected area.

We documented the total mining deforestation of over 6,000 hectares (14,800 acres) in Yapacana National Park. Of this total, just over half (52%; 3,000 has) has occurred in just the past five years (2019-2023).

See MAAP #173 and MAAP #207 for more information about mining deforestation at this site.

Figure 4. Evolution of mining deforestation in Yapacana National Park in Venezuela. Data: AMW, ACA/MAAP.

E. Ecuadorian Amazon – Punino River

In a series of reports, we have been showing the rapid increase in mining deforestation in the Ecuadorian Amazon (see MAAP #182). One of the main sites is around the Punino River in northern Ecuador (see Inset E in Base Map). Figure 5 shows the sudden emergence of gold mining deforestation near the river.

We documented the total mining deforestation of over 500 hectares (1,235 acres) in the Punino River area. Of this total, 100% is new, all starting in 2023.

See MAAP #206 for more information about mining deforestation at this site.

Figure 5. Evolution of mining deforestation in along the Punino River in Ecuador. Data: AMW, ACA/MAAP.

Annex

As noted above, of the total accumulated mining deforestation footprint of over 1.9 million hectares (4.7 million acres), about half has occurred in just the past five years.

Methods

All data for this report were obtained from Amazon Mining Watch. We only utilized patches with greater than 0.6 mean score. We used the 2018 data as our baseline. For 2019, we masked the previously reported 2018 data to only highlight the new mining that year. We then repeated this process for each subsequent year. For example, the 2023 data masked the 2018-2022 data, indicating only new mining deforestation that year.

Citation

Finer M, Ariñez A (2024) Machine learning to detect mining deforestation across the Amazon. MAAP: #212.

MAAP #199: Amazon Carbon Update, based on NASA’s GEDI Mission

As we approach the COP28 climate summit, starting in Dubai in late November, we provide here a concise update on the current state of remaining Amazon carbon reserves.

We present the newly updated version of NASA’s GEDI data1, which uses lasers aboard the International Space Station to provide cutting-edge estimates of aboveground biomass density on a global scale.

Here, we zoom in on the Amazon and take a first look at the newly updated data, which covers the time period of April 2019 – March 2023.2

This data, which is measured in megagrams of aboveground biomass per hectare (Mg/ha) at a 1-kilometer resolution, serves as our estimate for aboveground carbon reserves.

Figure 1 displays aboveground biomass across the Amazon biome. Note the highest carbon densities (indicated in bright yellow) are located in both the northeast Amazon and southwest Amazon.

Aboveground Biomass across the Amazon

Figure 2 also displays aboveground biomass across the Amazon biome, but this time with country boundaries and labels added.

Note that the peak biomass concentrations in the northeast Amazon include Suriname, French Guiana, and the northeast corner of Brazil. The peak biomass concentrations in the southwest Amazon are centered in southern Peru. Also note that many parts of Ecuador, Colombia, Venezuela, Guyana, Bolivia, Brazil, and northern Peru have high carbon densities as well.

Figure 2. Aboveground biomass density (carbon estimate) across the Amazon biome, with country boundaries. Data: NASA/GEDI, NICFI.

Carbon Estimates

We calculated over 78 billion metric tons of aboveground biomass across the Amazon biome (78,184,161,090 metric tons to be exact). Using a general assumption that 48% of this biomass is carbon3, we estimate over 37 billion metric tons of carbon across the Amazon (37,528,397,323 metric tons).

Note that these totals are likely underestimates given that the laser-based data has not yet achieved full coverage across the Amazon (that is, there are many areas where the lasers have not yet recorded data, leaving visible blanks in the maps above).

This is consistent with a previous study based on another independent dataset, where we estimated 6.7 billion metric tons of carbon in the Peruvian Amazon as of 2013 (MAAP #148). The current GEDI data estimates at least 5.3 billion metric tons in the Peruvian Amazon.

Carbon Sink

In a previous report, we showed that the Brazilian Amazon has become a net carbon source, whereas the total Amazon is still a net carbon sink (MAAP #144). Our current report goes one step further in terms of showing just how much carbon is left in that sink.

Notes

1GEDI L4B Gridded Aboveground Biomass Density, Version 2.1. https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=2299

2Note that we previously reported on the initial data release, which covered the time period of April 2019 – August 2021 (see MAAP #160).

3Domke et al (2022) How Much Carbon is in Tree Biomass?. USDA/Forest Service.

Acknowledgements

This work was supported by NORAD (Norwegian Agency for Development Cooperation) and ICFC (International Conservation Fund of Canada).

Citation

Mamani N, Finer M, Ariñez A (2022) Amazon Carbon Update, based on NASA’s GEDI Mission. MAAP: 199.

MAAP #197: Illegal Gold Mining Across the Amazon

Example of major gold mining zone in the Peruvian Amazon. Data: Planet.

Illegal Gold Mining continues to be one of the major issues facing nearly all Amazonian countries.

In fact, following the recent high-level summit of the Amazon Cooperation Treaty Organization, the nations’ leaders signed the Belém Declaration, which contains a commitment to prevent and combat illegal mining, including strengthened regional and international cooperation (Objective 32).

Illegal gold mining is a major threat to the Amazon because it impacts both primary forests and rivers, often in remote and critical areas such as protected areas & indigenous territories.

That is, illegal gold mining is both a major deforestation driver and a source of water contamination (especially mercury) across the Amazon.

Previously, in MAAP #178, we presented a large-scale overview of the major gold mining deforestation hotspots across the entire Amazon biome. We found that gold mining is actively causing deforestation in nearly all nine countries of the Amazon.

Here, we update this analysis with two important additions. First, we add to the overview major gold mining operations taking place in rivers, in addition to those causing deforestation (see Figure 1).

Second, we present a new map of likely illegal gold mining sites, based on information from partners and location with protected areas and indigenous territories (see Figure 2).

Finally, we show a series of high-resolution satellite images of key examples of illegal Amazon gold mining.

Updated Amazon Gold Mining Map

Figure 1 is our updated Amazon gold mining map.

The orange dots indicate areas where gold mining is currently causing deforestation of primary forests. The blue dots indicate areas where gold mining is occurring in rivers. Combined, we documented 58 active forest and river-based mining sites across the Amazon.

The dots outlined in red indicate the mining sites that are likely illegal, for both forest and river-based mining. We found at least 49 cases of illegal mining across the Amazon, the vast majority of the active mining sites noted above.

Note the concentrations of illegal mining causing deforestation in southern Peru, across eastern Brazil, and across Ecuador. Similarly, note the concentrations of illegal mining in rivers in northern Peru and adjacent Colombia and Brazil.

Figure 1. Updated Amazon gold mining map. Data: ACA/MAAP. Click to enlarge.

Protected Areas & Indigenous Territories

Figure 2 adds protected areas and indigenous territories. We found at least 36 conflictive overlaps: 16 in protected areas and 20 in indigenous territories. We also found an additional two conflicts with Brazilian National Forests.

We highlight a number of high-conflict zones. For protected areas: Podocarpus National Park in Ecuador; Madidi National Park in Bolivia; Canaima, Caura, and Yapacana National Parks in Venezuela. We note that the Peruvian government has been effectively minimizing invasions in protected areas in the southern region of Madre de Dios (Tambopata National Reserve and Amarakaeri Communal Reserve).

For indigenous territories: Kayapo, Menkragnoti, Yanomami, and Mundurucu in Brazil; Pueblo Shuar Arutam in Ecuador, and a number of communities in southern Peru.

Figure 2. Amazon gold mining map., with protected areas and indigenous territories. Data: ACA/MAAP, RAISG. Click to enlarge.

Methods

The forest-based mining sites displayed in Figure 1 are largely based on information obtained over the last several years of our deforestation monitoring work. The river-based sites are largely based on information obtained from partners in country and on the ground.

We complemented this information with automated, machine-based data from Amazon Mining Watch, and data from RAISG.

For these sources, we checked recent imagery and only included sites that appeared to still be active.

Classification as an illegal mining site is largely based on location within protected areas or indigenous territories, or clearly
outside of an authorized mining zone

Citation

Finer M, Mamani N, Arinez A, Novoa S, Larrea-Alcázar D, Villa J (2023) Illegal Gold Mining Across the Amazon. MAAP: 197.

 

MAAP #187: Amazon Deforestation & Fire Hotspots 2022

2022 Amazon Forest Loss Base Map. Deforestation and fire hotspots across the full Amazon biome. Data: UMD/GLAD, ACA/MAAP.

We present a detailed look at the major 2022 Amazon forest loss hotspots, based on the final annual data recently released by the University of Maryland (and featured on Global Forest Watch).

This dataset is unique in that it is consistent across all nine countries of the Amazon, and distinguishes forest loss from fire, leaving the rest as a proxy for deforestation (but also includes natural loss).

Thus, we are able to present both deforestation and fire hotspots across the Amazon.

The Base Map (see right) and Results Graph (see below) reveal several key findings:

  • In 2022, we estimate the deforestation of 1.98 million hectares (4.89 million acres). This represents a major 21% increase from 2021, and is the second highest on record, behind only the peak in 2004.
    k
  • Deforestation hotspots were especially concentrated along roads in the Brazilian Amazon, the soy frontier in the southeast Bolivian Amazon, and near protected areas in northwest Colombian Amazon.
    k
  • The vast majority of the deforestation occurred in Brazil (72.8%), followed by Bolivia (12.4%)Peru (7.3%), and Colombia (4.9%). Note that deforestation in Bolivia was the highest on record, and in Brazil the highest since the early 2000s.
    k
  • Fires impacted an additional 491,223 hectares (1.2 million acres) of primary forest. This total represents a 1.6% increase from 2021, and the 4th highest on record (behind only intense fire seasons of 2016, 2017, and 2020). Moreover, each of the seven most intense fire seasons has occurred in the past seven years. Nearly 93% of the fire impact occurred in just two countries: Brazil and Bolivia.
    k
  • In total, 2.47 million hectares (6.1 million acres) of primary forest were impacted by deforestation and fire. This total represents the third highest on record, only behind the post-El Niño years of 2016 and 2017.
    k
  • Since 2002, we estimate the deforestation of 30.7 million hectares (75.9 million acres) of primary forest, greater than the size of Italy or the U.S. state of Arizona.

Below, we zoom in on the six countries with the highest deforestation (Brazil, Bolivia, Peru, Colombia, Ecuador, and Venezuela) with additional maps and analysis.

Amazon Primary Forest Loss (Combined), 2002-2022

Amazon Forest Loss Results Graph, 2002-22. Data: UMD/GLAD, ACA/MAAP.

Amazon Primary Forest Loss (By Country), 2002-2022

Brazilian Amazon

Brazil Base Map, 2022. Deforestation and fire hotspots in the Brazilian Amazon in relation to major roads. Data: UMD/GLAD, ACA/MAAP.

In 2022, the Brazilian Amazon lost 1.4 million hectares (3.56 million acres) of primary forest to deforestation. Fires directly impacted an additional 348,824 hectares.

The deforestation rose 20.5% from 2021, and was the highest on record since the peak years of 2002 – 2005.

The fire impact was the 4th highest on record, only behind the intense fire years of 2016, 2017, and 2020.

The deforestation was concentrated along the major road networks, especially roads 230 (Trans-Amazonian Highway), 364, 319, and 163 in the states of Amazonas, Pará, Rondônia, and Acre (see Brazil Base Map).

The direct fire impacts were concentrated in the soy frontier, located in southeastern state of Mato Grosso

 

 

 

 

 

 

Bolivian Amazon

Bolivia Base Map, 2022. Deforestation and fire hotspots in Bolivian Amazon. Data: UMD/GLAD, ACA/MAAP.

In 2022, the Bolivian Amazon lost 245,177 hectares of primary forest to deforestation. Fires directly impacted an additional 106,922 hectares.

We highlight that this deforestation was 47% higher than 2021, and the highest on record (by far).

The fire impact was also up from last year, and the second-highest on record behind just the intense year of 2020.

Both the deforestation and fires were concentrated in the soy frontier located in southeastern department of Santa Cruz (see Bolivia Base Map).

 

 

 

 

 

 

 

 

 

 

Peruvian Amazon

Peru Base Map, 2022. Deforestation and fire hotspots in the Peruvian Amazon. Data: UMD/GLAD, ACA/MAAP.

In 2022, the Peruvian Amazon lost 144,682 hectares of primary forest to deforestation. Fires directly impacted an additional 16,408 hectares.

Deforestation increased 6.7% from 2021, and was the 5th highest on record. Fire impact decreased from last year, but was still relatively high.

The deforestation was concentrated in the central and southern Amazon (Ucayali and Madre de Dios regions, respectively) (see Peru Base Map).

In the central Amazon, we highlight the rapid deforestation for a new Mennonite colony (see MAAP #166).

In the southern Amazon, gold mining deforestation continues to be an issue in indigenous communities and within the official Mining Corridor.

 

 

 

 

 

 

 

Colombian Amazon

Colombia Base Map, 2022. Deforestation and fire hotspots in northwest Colombian Amazon. Data: UMD/GLAD, ACA/MAAP, FCDS.

In 2022, the Colombian Amazon lost 97,417 hectares of primary forest to deforestation. Fires directly impacted an additional 12,880 hectares.

Deforestation decreased 2% from 2021, but it was still relatively high (5th highest on record), continuing the trend of elevated forest loss since the FARC peace agreement in 2016.

Fire impact increased from last year and was actually the highest on record, edging out 2018 and 2019.

As described in previous reports (see MAAP #120), the Colombia Base Map shows there continues to be an “arc of deforestation” in the northwest Colombian Amazon (Caqueta, Meta, and Guaviare departments).

This arc impacts numerous Protected Areas (particularly Tinigua and Chiribiquete National Parks) and Indigenous Reserves (particularly Yari-Yaguara II and Nukak Maku).

 

 

 

 

Ecuadorian Amazon

Ecuador Base Map, 2022. Deforestation and fire hotspots in the Ecuadorian Amazon. Data: UMD/GLAD, ACA/MAAP.

Although accounting for just 1% of total loss across the Amazon, deforestation in the Ecuadorian Amazon was the highest on record in 2022 (18,902 hectares), up a striking 80% since 2021.

There are several deforestation hotspots caused by gold mining (see MAAP #182), oil palm plantation expansion, and small-scale agriculture.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Venezuelan Amazon

In the Venezuelan Amazon, deforestation was on par with last year (12,584 hectares).

There is a deforestation hotspot caused by gold mining in Yapacana National Park (see MAAP #173, MAAP #156, MAAP #169).

There are also hotspots in the Orinoco Mining Arc caused by mining and agriculture.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Methodology

The analysis was based on 30-meter resolution annual forest loss data produced by the University of Maryland and also presented by Global Forest Watch.

This data was complemented with the Global Forest Loss due to fire dataset that is unique in terms of being consistent across the Amazon (in contrast to country specific estimates) and distinguishes forest loss caused directly by fire (note that virtually all Amazon fires are human-caused). The values included were ‘medium’ and ‘high’ confidence levels (code 3-4).

The remaining forest loss serves as a likely close proxy for deforestation, with the only remaining exception being natural events such as landslides, wind storms, and meandering rivers. The values used to estimate this category was ‘low’ certainty of forest loss due to fire (code 2), and forest loss due to other ‘non-fire’ drivers (code 1).

For the baseline, it was defined to establish areas with >30% tree canopy density in 2000. Importantly, we applied a filter to calculate only primary forest loss by intersecting the forest cover loss data with the additional dataset “primary humid tropical forests” as of 2001 (Turubanova et al 2018). For more details on this part of the methodology, see the Technical Blog from Global Forest Watch (Goldman and Weisse 2019).

Our geographic range for the Amazon is a hybrid designed for maximum inclusion: biogeographic boundary (as defined by RAISG) for all countries, except for Bolivia and Peru, where we use the watershed boundary, and Brazil, where we use the Legal Amazon boundary.

To identify the deforestation hotspots, we conducted a kernel density estimate. This type of analysis calculates the magnitude per unit area of a particular phenomenon, in this case, forest cover loss. We conducted this analysis using the Kernel Density tool from the Spatial Analyst Tool Box of ArcGIS. We used the following parameters:

Search Radius: 15000 layer units (meters)
Kernel Density Function: Quartic kernel function
Cell Size in the map: 200 x 200 meters (4 hectares)
Everything else was left to the default setting.

For the Base Map, we used the following concentration percentages: High: 3-14%; Very High: >14%.

Acknowledgements

We thank colleagues at Global Forest Watch (GFW), an initiative of the World Resources Institute (WRI) for comments and access to data.

This work was supported by Norad (Norwegian Agency for Development Cooperation) and ICFC (International Conservation Fund of Canada).

Citation

Finer M, Mamani N (2023) Amazon Deforestation & Fire Hotspots 2022. MAAP: 187

MAAP #183: Protected Areas & Indigenous Territories Effective Against Deforestation Across Amazon

Base Map. Primary forest loss (2017-21) across the Amazon, in relation to protected areas and indigenous territories.

As deforestation continues to threaten primary forest across the Amazon, key land use designations are one of the best hopes for the long-term conservation of critical remaining intact forests.

Here, we evaluate the impact of two of the most important: protected areas & indigenous territories.

Our study looked across all nine countries of the Amazon biome, a vast area of 883.7 million hectares (see Base Map).

We calculated primary forest loss over the past 5 years (2017-2021).

For the first time, we were able to distinguish fire vs non-fire forest loss. For non-fire, while this does include natural events (such as landslides and wind storms), we consider this our best proxy for human-caused deforestation.

We analyzed the results across three major land use categories:

1) Protected Areas (national and state/department levels), which cover 197 million hectares (23.6% of Amazon).

2) Indigenous Territories (official), which cover 163.8 million hectares (19.6% of Amazon).

3) Other (all remaining areas outside protected areas and indigenous territories), which cover 473 million hectares (56.7% of Amazon).

In summary, we found that deforestation was the primary driver of forest loss, with fire always being a smaller subset. Averaged across all 5 years, protected areas and indigenous territories had similar levels of effectiveness, reducing primary forest loss rate by 3x compared to areas outside of these designations.

Below, we show the key results across the Amazon in greater detail, including a breakdown for the western Amazon (Bolivia, Colombia, Ecuador, and Peru) and the Brazilian Amazon.

Key Findings

Amazon Biome

We documented the loss of 11 million hectares of primary forests across all nine countries of the Amazon biome between 2017 and 2021. Of this total, 71% was non-fire (deforestation and natural) and 29% was fire.

For the major land use categories, 11% of the forest loss occurred in both protected areas and indigenous territories, respectively, while the remaining 78% occurred outside these designations.

To standardize these results for the varying area coverages, we calculated annual primary forest loss rates (loss/total area of each category). Figure 1 displays the results for these rates across all nine countries of the Amazon biome.

Figure 1. Primary forest loss rates across the Amazon, 2017-21.

Broken down by year, 2017 had the highest forest loss rates, with both a severe deforestation and fire season. In addition, 2021 had the second highest deforestation rate, while 2020 had the second highest fire loss rate.

Averaged across all five years, protected areas (green) had the lowest overall primary forest loss rate (0.12%), closely followed by indigenous territories (0.14%).

Interestingly, indigenous territories (orange) actually had a slightly lower deforestation rate compared to protected areas (0.7 vs 0.8%), but higher fire loss rate (o.7 vs .04%), resulting in the overall higher forest loss rate noted above.

Outside of these designations (red), the primary forest loss rate was triple (.36%), especially due to much higher deforestation.

Western Amazon

Breaking the results down specifically for the western Amazon (Bolivia, Colombia, Ecuador, and Peru), we documented the loss of 2.6 million hectares of primary forests between 2017 and 2021. Of this total, 80% was non-fire (deforestation and natural) and 20% was fire.

For the major land use categories, 9.6% occurred in protected areas, 15.6% in indigenous territories, and the remaining 74.8% occurred outside these designations.

Figure 2 displays the standardized primary forest loss rates across the western Amazon.

Figure 2. Primary forest loss rates across the Western Amazon, 2017-21.

Broken down by year, 2017 had the highest deforestation rate and overall forest loss rates. But 2020 had the highest fire loss rate, mainly due to extensive fires in Bolivia. 2021 also had a relatively high deforestation rate. Also, note the high level of fires in protected areas in 2020 and 2021, and indigenous territories in 2019.

Averaged across all five years, protected areas had the lowest overall primary forest loss rate (0.11%), followed by indigenous territories (0.16%).

Outside of these designations, the primary forest loss rate was .30%. That is, triple the protected areas rate and double the indigenous territories rate.

Brazilian Amazon

Breaking the results down specifically for the Brazilian Amazon, we documented the loss of 8.1 million hectares of primary forests between 2017 and 2021. Of this total, 68% was non-fire (deforestation and natural) and 32% was fire.

For the major land use categories, 9.4% occurred in indigenous territories, 11.2% occurred in protected areas, and the remaining 79.4% occurred outside these designations.

Figure 3 displays the standardized primary forest loss rates across the Brazilian Amazon.

Figure 3. Primary forest loss rates in the Brazilian Amazon, 2017-21.

Broken down by year, 2017 had the highest forest loss rate recorded in the entire study (.58%), due to both elevated deforestation and fire. Note that indigenous territories were particularly impacted by fire in 2017.

2020 had the next highest forest loss rate, also driven by an intense fire season. Fires were not as severe the following year in 2021, but deforestation increased.

Averaged across all five years, indigenous territories had the lowest overall primary forest loss rate (0.14%), closely followed by protected areas (0.15%).

Interestingly, indigenous territories had a lower deforestation rate compared to protected areas (0.5 vs 0.11%), but higher fire impact (0.09 vs 0.04%).

Outside of these designations (red), the primary forest loss rate was triple (.45%).

Methodology

To estimate deforestation across all three categories (protected areas, indigenous territories, and other), we used annual forest loss data (2017-21) from the University of Maryland (Global Land Analysis and Discovery GLAD laboratory) to have a consistent source across all countries (Hansen et al 2013).

We obtained this data, which has a 30-meter spatial resolution, from the “Global Forest Loss due to Fires 2000–2021” data download page. It is also possible to visualize and interact with the data on the main Global Forest Change portal.

The annual data is disaggregated into forest loss due to fire vs. non-fire (other disturbance drivers). It is important to note that the non-fire drivers include both human-caused deforestation and forest loss caused by natural forces (landslides, wind storms, etc.).

We also filtered this data for only primary forest loss, following the established methodology of Global Forest Watch. Primary forest is generally defined as intact forest that has not been previously cleared (as opposed to previously cleared secondary forest, for example). We applied this filter by intersecting the forest cover loss data with the additional dataset “primary humid tropical forests” as of 2001 (Turubanova et al 2018). Thus, we often use the term “primary forest loss” to describe this filtered data.

Data presented as primary forest loss rate is standardized per the total area covered of each respective category per year (annual). For example, to properly compare raw forest loss data in areas that are 100 hectares vs 1,000 hectares total size respectively, we divide by the area to standardize the result.

Our geographic range extends from the Andes to the Amazon plain and reaching the transitions with the Cerrado and the Pantanal. This range includes nine countries of the Amazon (or Pan-Amazon region as defined by RAISG) and consists of a combination of the Amazon watershed limit, the Amazon biogeographic limit and the Legal Amazon limit in Brazil. See Base Map above for delineation of this hybrid Amazon limit, designed for maximum inclusion.

Additional data sources include:

  • National and state/department level protected areas: RUNAP 2020 (Colombia), SNAP 2022 (Ecuador), SERNAP & ACEAA 2020 (Bolivia), SERNANP 2022 (Peru), INPE/Terrabrasilis 2022 (Brazil), SOS Orinoco 2021 (Venezuela), and RAISG 2020 (Guyana, Suriname, and French Guiana.)
  • Indigenous Territories: RAISG & Ecociencia 2022 (Ecuador), INPE/Terrabrasilis 2022 (Brazil), RAISG 2020 (Colombia, Bolivia, Venezuela, Guyana, Suriname, and French Guiana), and MINCU & ACCA 2021 (Peru). For Peru, this includes titled native communities and Indigenous/Territorial Reserves for indigenous groups in voluntary isolation.

For analysis, we categorized Protected Areas first, then Indigenous Territories to avoid overlapping areas. Each category was disaggregated by year created/recognized to match the annual report of forest loss, for example. If a Protected area was created in December 2018, it would be considered within the analysis for the year 2019.

Acknowledgements

This work was supported by the Andes Amazon Fund (AAF), Norwegian Agency for Development Cooperation (NORAD), and International Conservation Fund of Canada (ICFC).

We thank M. MacDowell and M. Cohen for helpful comments on this report.

Citation

Finer M, Mamani N (2023) Protected Areas & Indigenous Territories Effective Against Deforestation Across Amazon. MAAP: 176.

MAAP #178: Gold Mining Deforestation Across the Amazon

Base Map. Mining deforestation hotspots across the Amazon. Letters A-J indicate locations of case studies below. Click image to enlarge.

Gold Mining is one of the major deforestation drivers across the Amazon.

Although not typically at the scale of agricultural deforestation, gold mining has the potential to severely impact critical areas such as protected areas & indigenous territories.

Relatedly, gold mining often targets remote areas, thus impacting largely intact and carbon-rich primary forests.

Here, for the first time, we present a large-scale overview of the major gold mining deforestation hotspots across the entire Amazon biome.

We found that gold mining is actively causing deforestation in nearly all nine countries of the Amazon (see Base Map).

In  this report, we focus on five countries: Peru, Brazil, Venezuela, Ecuador, and Bolivia, featuring case studies of the most severe active gold mining fronts.

In most cases, this mining is likely illegal given that it is occurring in protected areas and indigenous territories.

Note that we focus on mining activity that is causing deforestation of primary forests. There are additional critical gold mining areas that are occurring in rivers, such as in northern Peru and southern Colombia, that are not included in this report.

Below, we show a series high-resolution satellite images of the Amazon case studies. Each example highlights recent gold mining deforestation; that is comparing 2020 (left panel) with 2022 (right panel).

Case Studies, in High-resolution

Peruvian Amazon

Southern Peru (specifically, the region of Madre de Dios) is one of the most severe and emblematic examples of gold mining deforestation in the Amazon, clearing thousands of hectares of primary forest (see MAAP #154). The active mining fronts have evolved substantially over the past 20+ years. Most recently, gold mining has impacted areas such as Mangote and Pariamanu.

A. Mangote

B. Pariamanu

Brazilian Amazon

In the vast Brazilian Amazon, illegal gold mining deforestation is most severe across a number of indigenous territories, most notably: Munduruku (Pará state), Kayapó (Pará), and Yanomami (Roraima).

C. Munduruku Indigenous Territory


D. Kayapó Indigenous Territory


E. Yanomami Indigenous Territory

Venezuelan Amazon

Mining is one of the major deforestation drivers in the Venezuelan Amazon (MAAP #155). This mining impact is occurring in the designated Orinoco Mining Arc, but also key protected areas such as Caura, Canaima, and Yapacana National Parks.

F. Canaima National Park


G. Yapacana National Park

Ecuadorian Amazon

We have been documenting the numerous mining deforestation hotspots in the Ecuadorian Amazon that appear to be intensifying in recent years. Two key examples are along the Punino River (Napo and Orellana provinces) and further south in Podocarpus National Park.

H. Punino River

I. Podocarpus National Park

Bolivian Amazon

One of the newest gold mining deforestation hotspots is along the Tuichi River in Madidi National Park.

J. Madidi National Park

Methodology

Mining deforestation hotspots were identified based on MAAP’s ongoing monitoring efforts, and assisted by Amazon Mining Watch.

Acknowledgements

We thank A. Folhadella, S. Novoa, D. Larrea, C. De Ugarte, and M. Teran for helpful comments on this report, and Conservación Amazónica – ACCA for data on mining sites in northern Peru.

This work was supported by Norad (Norwegian Agency for Development Cooperation) and ICFC (International Conservation Fund of Canada).

Citation

Finer M, Ariñez A, Mamani N (2023) Mining Deforestation Across the Amazon. MAAP: 178.