Country: Brazil

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

Posted on by dcadmin
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.3  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

Posted on by dcadmin
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)

Posted on by dcadmin
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 #214: Agriculture in the Amazon: New data reveals key patterns of crops & cattle pasture

Posted on by dcadmin
Figure 1. Agricultural and pasture data in a section of the Brazilian Amazon.

A burst of new data and online visualization tools are revealing key land use patterns across the Amazon, particularly regarding the critical topic of agriculture. This type of data is particularly important because agriculture is the leading cause of overall Amazonian deforestation.

These new datasets include:

  • Crops. The International Food Policy Research Institute (IFPRI), a leading agriculture and food systems research authority, recently launched the latest version of their innovative crop monitoring product, the Spatial Production Allocation Model (SPAM).1 This latest version, developed with support from WRI’s Land & Carbon Lab, features spatial data for 46 crops, including soybean, oil palm, coffee, and cocoa. This data is mapped at 10-kilometer resolution across the Amazon and updated through 2020.2
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  • Cattle pasture. The Atlas of Pastures,3 developed by the Federal University of Goiás, facilitates access to data regarding Brazilian cattle pastures generated by MapBiomas. This data is mapped at 30-kilometer resolution and updated through 2022. We use Collection 5 from Mapbiomas for the rest of the Amazonian countries.4
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  • Gold mining. New mining data is included for additional context. Amazon Mining Watch uses machine learning to map open-pit gold mining.5 This data is mapped at 10-kilometer resolution across the Amazon and updated through 2023.

We merged and analyzed these new datasets to provide our first overall estimate of Amazonian land use, the most detailed effort to date across all nine countries of the biome. Figure 1 shows an example of this merged data in a section of the Brazilian Amazon.

Below, we present and illustrate the following major findings across the Amazon, and then zoom in on several regions across the Amazon to show the data in greater detail.

Major Findings

The Base Map illustrates several major findings detailed below.

Base Map. Overview of the merged datasets noted above for crops, pasture, and gold mining. Double-click to enlarge. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

1) Crops
We found that 40 crops in the SPAM dataset overlap with the Amazon, covering over 106 million hectares (13% of the Amazon biome).

Soybean covers over 67.5 million hectares, mostly in southern Brazil and Bolivia. Maize covers slightly more area (70 million hectares) but we consider this a secondary rotational crop with soy (thus, there is considerable overlap between these two crops).

Oil palm covers nearly 8 million hectares, concentrated in eastern Brazil, central Peru, northern Ecuador, and northern Colombia.

In the Andean Amazon zones of Peru, Ecuador, and Colombia, cocoa covers over 8 million hectares and the two types of coffee (Arabica and Robusta) cover 6.7 million hectares.

Other major crops across the Amazon include rice (13.8 million hectares), sorghum (10.9 million hectares), cassava (9.8 million hectares), sugarcane (9.6 million hectares), and wheat (5.8 million hectares).

2) Cattle Pasture
Cattle Pasture covers 76.3 million hectares (9% of the Amazon biome). The vast majority (92%) of the pasture is in Brazil, followed by Colombia and Bolivia.

3) Crops & Cattle Pasture
Overall, accounting for overlaps between the data, we estimate that crops and pasture combined cover 115.8 million hectares. This total is the equivalent of 19% of the Amazon biome.

In comparison, open-pit gold mining covered 1.9 million hectares (0.23% of the Amazon biome).

Zooms across the Amazon

Eastern Brazilian Amazon

Figure 2 shows the transition from the soy frontier to the cattle pasture frontier in the eastern Brazilian Amazon. Also note a mix of other crops, such as oil palm, sugarcane, and cassava, and some gold mining.

Figure 2. Eastern Brazilian Amazon. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

Andean Amazon (Peru and Ecuador)

Figure 3. Andean Amazon. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

The land use patterns are quite different in the Andean Amazon regions of Peru and Ecuador.

Figure 3 shows, that instead of soy and cattle pasture, there is instead oil palm, rice, coffee, and cocoa.

Also note the extension of the cattle pasture frontier in the western Brazilian Amazon, towards Peru and Bolivia.

 

 

 

 

 

 

 

 

 

 

 

 

Northeast Amazon (Venezuela, Guyana, Suriname, French Guiana)

Figure 4 shows the general lack of crops in the core Amazon regions Guyana, Suriname, and French Guiana, which is surely a major factor they are all considered High Forest cover, Low Deforestation countries (HFLD). In contrast, note there is abundant gold mining activity throughout this region.

Figure 4. Northeastern Amazon. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

Methods

For the SPAM data, we used the physical area, which is measured in a hectare and represents the actual area where a crop is grown (not counting how often production was harvested from it). We only considered values ​​greater than or equal to 100 ha per pixel.

For the Base Map, due to their importance as primary economic crops, we layered soybean and oil palm as the top two layers, respectively. From there, crops were layered in order of their total physical area across the Amazon. Thus, the full extensions of some crops are not shown if they overlap pixels with other crops that have greater physical area. For overlaps with crops and pasture, we favored the crops.

Notes & Data Sources

1 International Food Policy Research Institute (IFPRI), 2024, “Global Spatially-Disaggregated Crop Production Statistics Data for 2020 Version 1.0” https://doi.org/10.7910/DVN/SWPENT, Harvard Dataverse, V1

Spatial Production Allocation Model (SPAM)
SPAM 2020 v1.0 Global data (Updated 2024-04-16)

2 Note that the spatial resolution is rather low (10-kilometers) so all crop coverage data above should be interpreted as referential only.

3 The Atlas of Pastures (Atlas das Pastagens), open to the public, was developed by the Image Processing and Geoprocessing Laboratory of the Federal University of Goiás (Lapig/UFG), to facilitate access to results and products generated within the MapBiomas initiative, regarding Brazilian pastures.

https://atlasdaspastagens.ufg.br/

4 MapBiomas Collection 5;  https://amazonia.mapbiomas.org/en/

5 See MAAP #212 for more information on Amazon Mining Watch.

Citation

Finer M, Ariñez A (2024) Agriculture in the Amazon: New data reveals key patterns of crops & cattle pasture. MAAP: 214.

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

Posted on by dcadmin
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)
    k
  • 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.

2 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

Posted on by dcadmin
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 #200: State of the Amazon in 2023

Posted on by dcadmin

The first MAAP report, published in March 2015, took a detailed look at the escalating gold mining deforestation in the Peruvian Amazon.

Figure 1. Most recent cloud-free view of the entire Amazon biome (2023, quarter 3). Data: Planet, NICFI, ACA/MAAP.

The following 198 reports, over the past 8.5 years, continued to examine the most urgent deforestation-related issues across the Amazon.

For our 200th report, we provide our rapid assessment of the current state of the Amazon.

Overall, the situation is dire, with the Amazon nearing two critical deforestation-induced tipping points. The first is the widely feared conversion of moist rainforests to drier savannahs, due to decreased moisture recycling across the Amazon (see MAAP #164). The second is the more newly feared conversion of the Amazon as a critical carbon sink buffering global climate change, to a carbon source fueling it (see MAAP #144).

There is cause for hope, however. It is possible in the long term to protect the core Amazon, as nearly half is now designated as protected areas and indigenous territories, both of which have much lower deforestation rates than surrounding areas (see MAAP #183). Also, new NASA data reveals the Amazon is still home to abundant carbon reserves in these core areas (see MAAP #160 and MAAP #199).

Also on the positive news front, we recently reported a major reduction (over one-half) in primary forest loss between the current year 2023 and last year 2022 across the Amazon, especially in Brazil and Colombia (MAAP #201).

Much is made about Amazon fires in the media, but over the past several years we have revealed that the vast majority of major fires across the Amazon (namely, in Brazil, Bolivia, Peru, and Colombia) are actually burning recently deforested areas (MAAP #168). It is only during intense dry seasons that some of these fires escape and become actual forest fires.

Figure 1 shows the most recent cloud-free view of the entire Amazon biome. On the positive, one can clearly see the core Amazon still stands. On the negative, however, the expanding deforestation around the edges is evident.

Major Deforestation Fronts – 2023

In this section, we review the current major deforestation fronts across the Amazon.

Figure 2 indicates these fronts (insets A-H) in relation to deforestation hotspot data over the past 8 years during MAAP’s active monitoring timeframe (2015-2022). Below we describe each deforestation area, by country. Common drivers across numerous Amazon countries include roads (MAAP #157), agriculture (MAAP #161), cattle, and gold mining (MAAP #178).

Also note that further below, in the Annex, we show the relative order of total Amazon primary forest loss by country over the past two years: Brazil by far the highest, followed by a middle pack of Bolivia, Peru, and Colombia, followed by lower levels in Venezuela, Ecuador, Suriname, Guyana, and French Guiana.

Figure 2. Amazon forest loss hotspots, 2015-2022. Data: UMD, Planet/NICFI, ACA/MAAP.

 

Brazilian Amazon

Figure 3. Major forest loss hotspots in the Brazilian Amazon. Data: UMD, Planet/NICFI, ACA/MAAP.

Brazil continues to be, by far, the leading source of Amazonian deforestation (MAAP #187), led by three major drivers: cattle pasture expansion near roads, soy plantations, and gold mining.

Deforestation for new cattle pasture is concentrated along the extensive road networks spanning the eastern and southern Brazilian Amazon (for example, Inset A).

Deforestation for expanding soy plantations is concentrated in the southeast Brazilian Amazon (Inset B; see MAAP #161).

Gold mining deforestation impacts numerous sites, including several indigenous territories (for example, Inset C; see MAAP #178).

Bolivian Amazon

Figure 4. Major forest loss hotspots in the Bolivian Amazon. Data: UMD, Planet/NICFI, ACA/MAAP.

Bolivia has emerged as the clear second-leading source of Amazonian deforestation, with a major increasing trend over the past two years (MAAP #187).

The deforestation is concentrated in the soy frontier located in the southeast (Inset D, see MAAP #179).

Note that, increasingly, this soy deforestation is carried out by Mennonite colonies (MAAP #180). We revealed that Mennonites caused the deforestation of over 210,000 hectares since 2001, including 33,000 hectares since 2017.

Peruvian Amazon

Figure 5. Major forest loss hotspots in the Peruvian Amazon. Data: UMD, Planet/NICFI, ACA/MAAP.

Peru is the third-leading source of Amazonian deforestation (MAAP #187).

In the central Amazon, we have been highlighting the rapid deforestation for new Mennonite colonies (see MAAP #188). MAAP reports revealed, in real-time, Mennonite deforestation growing from zero in 2016, to 3,400 hectares in 2021, to 4,800 hectares in 2022, to 7,032 hectares in 2023.

In the southern Amazon, gold mining deforestation continues to be a major cause of deforestation, primarily in indigenous communities, protected area buffer zones, and within the official Mining Corridor (MAAP #185). Most recently, we showed that gold mining has caused the deforestation on nearly 24,000 hectares between just 2021 and 2023 (MAAP #195).

Colombian Amazon

Figure 6. Major forest loss hotspots in the Colombian Amazon. Data: UMD, Planet/NICFI, ACA/MAAP.

Colombia is the fourth-leading source of Amazonian deforestation.

Deforestation in Colombia spiked following the 2016 peace agreement between the Colombian government and the FARC guerilla group (MAAP #120), but was the only country with a notable deforestation decrease in 2022 (MAAP #187).

Forest loss is concentrated in an “arc of deforestation” surrounding numerous Protected Areas (such as Chiribiquete, Tinigua, and Macarena National Parks) and Indigenous Reserves.

In Colombia, the major direct deforestation driver is cattle pasture, but this expansion is largely caused by land grabbing as a critical indirect driver. Coca plantations also continue to be an important direct driver in certain remote areas.

Both cattle and coca are impacting protected areas, especially Tinigua and Chiribiquete National Parks (cattle); and Macrarena National Park and Nukak National Nature Reserve (coca).

Ecuadorian Amazon

Figure 7. Major forest loss hotspots in the Ecuadorian Amazon. Data: UMD, Planet/NICFI, ACA/MAAP, RAISG.

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

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

Annex: Amazon Primary Forest Loss (By Country), 2021-2022

Acknowledgments

We deeply thank the following funders for supporting MAAP over the past 10 years:
International Conservation Fund of Canada (ICFC)
Norwegian Agency for Development Cooperation (NORAD)
United States Agency for International Development (USAID)
MacArthur Foundation
Andes Amazon Fund (AAF)
Wyss Foundation
Erol Foundation
Global Forest Watch/World Resources Institute
Overbrook Foundation
Global Conservation

We also thank our key data providers:
Planet (optical satellite imagery)
University of Maryland (automated forest loss alerts)
Global Forest Watch (portal featuring integrated forest loss alerts)
NICFI monthly mosaics
CLASlite (our original forest loss detection tool)

Citation

Finer M, Mamani N, Novoa S, Ariñez A (2023) State of the Amazon in 2023. MAAP: 200.

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

Posted on by Lauren deVilla

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

Posted on by Matt Finer
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 #189: Amazon Fire Season Heats Up

Posted on by dcadmin
Image 1. Example of 2023 (June 29) major fire in Brazilian Amazon.

The Amazon fire season is well under way: to date, we have detected over 260 major fires thus far in 2023 (see Base Map below).

This year is of special concern because scientists indicate we have entered a new El Niño episode. The most intense Amazon fire seasons on record, 2016 and 2017, immediately followed the last major El Niño event.

Most of the fires (54%) this year have occurred in the Brazilian Amazon.

Of these, the vast majority (73%) have burned r­­­­ecently deforested areas. This high number is consistent with previous years (see MAAP #168) and once again highlights the critical link between deforestation and fires in the Brazilian Amazon. That is, most major fires are burning the remnants of a recent deforestation event.

It is also worth noting that many of the fires in the Brazilian Amazon (42%) were burning areas recently deforested specifically for new soy plantations.

We have thus far detected 40 major fires in the Bolivian Amazon. The vast majority (88%) have been burning areas recently deforested specifically for new soy plantations.

We have detected an additional 30 major fires in the Peruvian Amazon, mostly burning high elevation grasslands.

Earlier in the year, between January and March, we detected 50 major fires in the Colombian Amazon. Notably, 100% of them were in burning recently deforested areas.

These findings are based on the unique data from the real-time Amazon Fires Monitoring app developed by our partner organization in Peru, Conservación Amazónica ACCA. In a novel approach, the app combines data from the atmosphere (aerosol emissions in smoke) and the ground (heat anomaly alerts) to quickly and precisely detect major fires, defined as fires burning abundant biomass. In short, the app filters out smaller fires (such as routine burning an old field) and highlights major fires (such as burning recently deforested areas, standing forest, or natural grasslands).

2023 Major Amazon Fires Base Map

Base Map. 2023 major Amazon fires (through July 2023). Data: ACCA, ACA/MAAP.

Amazon Fires Dashboard

We also present our new Amazon fires dashboard, which currently shows results for the 2022 fire season. The dashboard highlights a number of the key findings from last year:

  • We detected 983 major fires.
  • The vast majority (72%) were in Brazil, followed by Bolivia, Peru, and Colombia.
  • Importantly, 73% of the major fires burned recently deforested areas, followed by grasslands, forest fires, and pasture.

The dashboard was developed by the SAS Institute’s Data for Good Program.

Methodology

The reported results are based on an analysis of data generated by a unique real-time Amazon Fires Monitoring app during the year 2023, through July 13.

The app, hosted by Google Earth Engine, was developed and updated daily by the Peru-based organization Conservación Amazónica (ACCA). The resulting data was analyzed and recorded daily by the US-based organization Amazon Conservation. The app was created in 2019 and upgraded in 2020, with the current version launching in May 2021.

When fires burn, they emit gases and aerosols (aerosol definition: Suspension of fine solid particles or liquid droplets in air or another gas) as part of the outgoing smoke. A relatively new satellite (Sentinel-5P from the European Space Agency) detects these aerosol emissions.

The aerosol data, which has a spatial resolution of 7.5 sq km, is not impacted by cloud cover, thus enabling near real-time monitoring during all weather conditions. The app is typically updated each day in the late afternoon/early evening with data for that same day. Thus, there is a high potential for authorities and civil society to also use this app to respond to major fires in the field.

Importantly, the app distinguishes small fires (such as from clearing old fields and thus burning little biomass) from larger fires (such as burning recently deforested areas or standing forests and thus burning high amounts of biomass).

We define a “major fire” as one showing elevated aerosol emission levels on the app, thus indicating the burning of elevated levels of biomass. This typically translates to an aerosol index (AI) of >1 (or cyan-green to red on the app).

In a novel approach, the app combines this aerosol data from the atmosphere with heat anomaly data from the ground.

For all detected major fires, we cross-referenced the aerosol emissions pattern with the ground heat-based data to pinpoint the exact location of the fire source. Typically for major fires, there is a large cluster of heat-anomaly alerts aiding the process.

In a final step, the detected major fires are then analyzed with high-resolution optical satellite imagery from Planet Explorer. With this imagery, we can confirm the major fire (by observing smoke on the day of the fire or a burned area scar in the days following the fire) and estimate its size.

Moreover, with Planet’s extensive satellite imagery archive, we can determine the fire type. That is, by comparing imagery from the fire date to previous dates, we can determine whether the fire was burning a) a recently deforested area (defined as fires in areas recently deforested during the past three years), b) an older deforested area (typically long-standing pasture areas), c) standing forest (that is, a forest fire), or natural savannah.

In the app, we can also cross-reference if a major fire has occurred within a protected area or titled indigenous territory.

Note that the high values in the aerosol indices may also be due to other reasons such as emissions of volcanic ash or desert dust so it is important to cross-reference elevated emissions with heat data and optical imagery.

Acknowledgements

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

Citation

Finer M, Costa H, Villa L (2023) Amazon Fire Season Heats Up. MAAP: 189.