Country: Ecuador

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

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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 #219: Illegal mining expansion in the Ecuadorian Amazon (Punino area)

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Base Map. Mining deforestation in the heart of the Ecuadorian Amazon (Punino area). Data: ARCERNNR 2022, Planet-NICFI, EcoCiencia.

In a series of previous reports, we warned about the emergence and expansion of illegal mining deforestation in the heart of the Ecuadorian Amazon, in the area surrounding the ​​Punino River, located between the provinces of Napo and Orellana (MAAP #182, MAAP #151).

In the most recent report, we informed that this mining impact had reached 1,000 hectares (MAAP #206).

Here, we provide an update on the growing mining activity in and around the Punino River basin during the first half of 2024.

The Base Map shows an increase of 420 hectares in 2024 (indicated in red), bringing the total impact to 1,422 hectares (3,500 acres) since its inception in 2019 (yellow and red combined). This total is equivalent to more than 2,000 professional soccer fields.

The Base Map also shows that the vast majority (90%) of the mining deforestation is located outside the limits of the areas authorized for such activity (according to the mining registry updated to 2022). In other words, the vast majority of mining is likely illegal.

We emphasize that the mining deforestation has rapidly expanded to enter the limits of two protected areas: Sumaco-Napo Galeras National Park and El Chaco Municipal Conservation Area (see Figure 1, below).

In addition, the mining deforestation is actively expanding within the boundaries of Indigenous territories of the Kichwa nationality (see Figure 2, below).

Below we illustrate in more detail the rapid increase in mining deforestation, especially in these protected areas and Indigenous territories.

Mining expansion in the Punino area, 2019-2024

Chart 1 illustrates the steadily increasing mining deforestation in the Punino area over the past 5 years. The impact began in 2019, reaching 1,000 hectares by the end of 2023, and more recently reaching 1,422 hectares in June 2024.

Chart 1. Historical deforestation due to mining in the Punino area between November 2019 and June 2024

Expansion of illegal mining in protected areas

Figure 1 shows the expansion of mining deforestation in and around the two protected areas of the Punino zone. Note that mining has recently penetrated the boundaries of both Sumaco-Napo Galeras National Park (0.32 hectares) and El Chaco Municipal Conservation Area (144 hectares).

Figure 1. Protected areas affected by mining activity between 2019 and 2024 in the Punino area. Data: ARCERNNR 2022, MAATE 2024, NCI 2018, Planet-NICFI, EcoCiencia.

Figure 2 shows the initial encroachment (0.32 hectares) of mining deforestation in the boundaries of Sumaco Napo-Galeras National Park between September 2022 (left panel) and June 2024 (right panel).

Figure 2. Mining deforestation within the boundaries of Sumaco Napo-Galeras National Park, comparing September 2022 (left panel) with June 2024 (right panel). Data: MAATE 2024, Planet/NICFI, EcoCiencia.

Figure 3 shows the invasion and expansion of deforestation due to mining (144 hectares) within the boundaries of El Chaco Municipal Conservation Area between September 2023 (left panel) and June 2024 (right panel).

Figure 3. Mining deforestation within the boundaries of the El Chaco Municipal Conservation Area, comparing September 2023 (left panel) with June 2024 (right panel). Data: NCI 2018, Planet/NICFI, Ecociencia.

Expansion of illegal mining in indigenous territories

Figure 4 shows the expansion of mining deforestation (300 hectares) in relation to the Indigenous territories of the Kichwa nationality in the Punino area.

Figure 4. Indigenous territories affected by mining activity between 2019 and 2024 in the Punino area. Data: RAISG 2023, ARCERNNR 2022, Planet-NICFI, EcoCiencia.

Figure 5 shows the expansion of deforestation due to mining in the indigenous territories of the Kichwa nationality between September 2023 (left panel) and June 2024 (right panel).

Figure 5. Mining deforestation within indigenous territory of the Kichwa nationality, comparing September 2023 (left panel) with June 2024 (right panel). Data: RAISG 2023, Planet-NICFI, EcoCiencia.

Figure 6 shows the expansion of deforestation due to mining in indigenous territories of the Kichwa nationality south of the study area between November 2019 (left panel) and June 2024 (right panel).

Figure 6. Mining deforestation within indigenous territory of the Kichwa nationality, comparing November 2019 (left panel) with June 2024 (right panel). Data: RAISG 2023, Planet-NICFI, EcoCiencia.

 

Annex 1

Annex 1 shows the four watersheds impacted by mining activity: the Punino River basin and also the Sardinas River, Lumucha River and Supayacu River basins, which in turn form part of the Coca River macro-water system.

Annex 1. Water systems impacted by mining activity in the Punino area.

 

Annex 2

Annex 2 shows the construction of 91 kilometers of roads due to mining activity.

Annex 2. Construction of access roads associated with mining activity.

Acknowledgements

This report is part of a series focused on the Ecuadorian Amazon through a strategic collaboration between the EcoCiencia Foundation and Amazon Conservation, with the support of the Norwegian Agency for Development Cooperation (Norad).

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

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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

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Figure 1. Example of the merged agricultural and pasture data in a section of the Brazilian Amazon. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

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 #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).

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 #206: Rapid expansion of illegal mining in Ecuadorian Amazon

Posted on by Lauren deVilla

In a series of previous reports, we warned about the emergence of alluvial mining in the Ecuadorian Amazon, specifically in the area around the Punino River, located between the provinces of Napo and Orellana (MAAP #151, MAAP #182).

Here, we highlight the rapid growth of mining activity in the Punino area: 784 hectares in 2023, which represents a striking increase of 261%.

This mining activity is mainly dedicated to the extraction of gold.

The vast majority of the detected activity is illegal mining, as it is outside the limits of the areas authorized for mining. For example, note the threat that illegal mining represents for the newly created El Chaco Municipal Conservation Area (see Base Map).

 

 

 

 

Rapid expansion of mining deforestation in 2023

Image 1 emphasizes the rapid expansion of mining deforestation in the Punino area in 2023 (red), relative to the previous three years (yellow).

The yellow indicates the mining deforestation of 217 hectares between November 2019 and December 2022, while the red shows the rapid expansion of 784 hectares (1,937 acres) from January to December 2023.

Thus, in total, the forest area affected by mining activity is 1,001 hectares (2,474 acres), from 2019 to the present.

Moreover, Image 1 clearly shows that the majority of mining deforestation is located outside the limits of authorized mining areas (purple). Specifically, we estimate that 90.4% of the total affected area (904 hectares, or 2,234 acres) represent illegal mining.

Image 1. Dynamics of mining activity between 2019 and 2023 in the Punino area. Data: Planet-NICFI, EcoCiencia.

Graph 1 shows the rapid escalation of mining deforestation in 2023 (bars 2, 3 and 4) relative to the previous three years (bar 1).

Graph 1. Deforestation due to mining in the Punino area between 2019 and 2023

Image 2 shows, with high-resolution satellite images, the expansion of mining deforestation in the Punino area between December 2022 (left panel) and December 2023 (right panel). The red arrows indicate the main areas of mining expansion.

Image 2.

Acknowledgments

This report is part of a series focused on the Ecuadorian Amazon through a strategic collaboration between the organizations EcoCiencia Foundation and Amazon Conservation, with the support of the Norwegian Development Cooperation Agency (Norad).

MAAP #202: Protecting Strategic, Free-flowing River Corridors in the Ecuadorian Amazon

Posted on by Lauren deVilla
Aerial photo of a section of the proposed river conservation corridor, highlighting some of the key components of the proposal: free-flowing river, intact riparian forest, and sustainable, low-impact tourism. Photo credit: Wil Henkel

Here, we present a model river conservation strategy proposed by the Ecuadorian Rivers Institute, designed to protect strategic free-flowing river corridors with intact surrounding forests in the critical transition zone between the Andes mountains and the Amazon lowlands.

The vision is to conserve freshwater resources and their surrounding riparian forests, encourage sustainable economic alternatives, and preserve free-flowing ecological connectivity at the basin scale.

There are few remaining high-quality and ecologically intact Andean-Amazon watershed corridors in Ecuador, making their protection and management an urgent national priority, ideally as part of a larger global tropical river conservation strategy

The proposal targets strategic corridors that have three major characteristics:

  1. Free-flowing rivers with no dams, diversions, or channel modifications, and no mining or dredging.
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  2. High-quality rivers that are a reference for water quality and have exceptional natural and cultural values.
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  3. Forested riparian buffer zones to preserve the quality and integrity of the river corridor, enhance the ecological connectivity between protected areas, and preserve habitat throughout critical transition zones.

These core components provide the key elements that are needed to preserve, restore, and enhance the integrity of the freshwater biodiversity, aquatic ecosystems, and scenic landscapes of strategic, free-flowing river corridors in the tropical Andes.

Priorities for River Protection in Ecuador

Base Map. Proposed free-flowing and intact riparian forest corridors (highlighted in yellow) in the northern Ecuadorian Amazon. Data: ERI.

The Base Map illustrates two proposed pilot projects in the northern Ecuadorian Amazon. Both represent key habitats for native fisheries and migratory birds and are important destinations for sustainable ecotourism activities. Following these two examples, national, regional (Amazon-scale), and global river protection programs could be created to include additional watershed corridors.

Jondachi-Hollín-Misahuallí-Napo River Corridor

The Jondachi and Hollín Rivers are major free-flowing tributaries of the Misahuallí River sub-basin in the Napo River watershed. These rivers drain from the Antisana and the Sumaco Napo Galeras National Parks, and provide strategic connectivity in a critical transition zone between montane cloudforests and lowland rainforest.

The proposed corridor would protect 200 km of free-flowing rivers and 19,050 hectares of riparian forest (with the application of 500m-wide buffers) within the Sumaco Biosphere Reserve. A significant portion of the corridor is within a forest reserve to provide enhanced connectivity and protection. The proposed corridor is an established destination for a variety of low-impact ecotourism activities that provide significant benefits to the local economy.

Piatúa River Corridor

The Piatúa River is another world-class paddle sports ecotourism destination that is renowned for its natural bathing areas with crystal clear water and sculpted granite boulders. The Piatúa River is a tributary of the Anzu River sub-basin of the Napo River watershed, which drains out of rugged paramo tundra and montane cloud forests deep within the Llanganates National Park, and provides critical ecosystem connectivity through a wide elevation range with high levels of endemic species.

The proposed corridor would protect 46 km of free-flowing rivers and tributaries and 947 hectares of riparian forest (with the application of a 100m-wide riparian buffer)

River Conservation Strategy

Guidelines for Protection

Legally binding frameworks are needed which restrict the development of intensive land-use activities and hydraulic infrastructure, and guarantee high-level, permanent protection of natural river corridors and natural instream flow regimes, with riparian buffer zones to preserve aquatic habitat and water quality. Ecuador has an existing framework which can be used to designate protected river corridors with the same status as national parks. However, until now it has only been applied to protect small catchment basin areas for sources of drinking water in headwater tributaries.

Management recommendations

Comprehensive management plans must be developed with meaningful public participation, and provisions for monitoring, control and enforcement of restricted activities. Independent monitoring and evaluation is necessary to ensure adequate compliance and implementation is achieved. Academic institutions should be encouraged to participate and develop research programs which reinforce the management objectives.

Social component

The successful implementation of the proposed river protection strategy depends on the active participation and endorsement by the local population and people who use the resource, along with adequate governance, and sufficient funding for management and incentives.

Protecting the river corridor ensures sustainable economic benefits for the inhabitants of the region through low-impact ecotourism activities (such as kayaking, rafting, mountain biking, bird watching, and hiking) which are compatible with the management of the resource.

However, additional financial incentives (such as land grants) are needed to reach other sectors of the population in order to take pressure off of the increasing encroachment into the forested riparian corridors for timber harvesting and subsistence-level agricultural expansion.

Ongoing support and guidance is also needed for local communities and landowners to identify employment opportunities and encourage other sustainable production activities in order to optimize the use of degraded areas outside of the protected riparian buffers.

In the case of plastic recycling, the population of Ecuador has responded favorably to adapting cultural and behavioral norms in response to small incentives created by a tax on plastic beverage containers, to address a significant waste management issue. This is a positive sign for what to expect if incentives are provided for protecting natural river corridors.

Financial mechanisms

Securing long-term financial commitments is a fundamental component to ensure the viability of any natural resource protection program. Most developing countries are burdened by foreign debt and are struggling to meet their fiscal obligations and priorities, which often lessens priorities for environmental management. However, experience has shown that the international community responds favorably to reinforce commitments made by host countries to preserve natural and cultural heritage of global significance, and debt forgiveness and debt reduction transactions for host country governments, from wealthy countries would be expected to provide some funding for the proposed strategy to protect strategic free-flowing river corridors in Ecuador.

The Government of Ecuador is facing a critical economic situation. However, water conservation funds have been successfully implemented to cover the cost of managing the protection of drinking water sources for metropolitan areas by including a small environmental management fee on monthly water bills. Some of these water conservation funds have generated substantial levels of endowment to the point where they could have the potential to provide funding for the protection of strategic river corridors, if that was authorized by the water fund consortium.

While the outcome of COP28 may have put a temporarily damper on the value of the nascent carbon credit market, once the programs are restructured to provide for improved accountability and implementation, the expectations for carbon credits to provide a source of long-term funding for the protection and management of strategic free-flowing river corridors as a climate mitigation strategy are quite encouraging, as are expectations for eventual funding allocations for river protection to be derived from the COP21 Paris Climate Accord, and the Global Environmental Facility (GEF).

Meanwhile, voluntary contributions from hydroelectric projects and extractive projects to offset their impacts by designating a percentage of annual income from the generation of electricity for the protection of free-flowing river corridors.

Likewise, voluntary contributions from international finance institutions based on a percentage of annual revenue disbursed through their investment portfolio could provide meaningful support for the protection of free-flowing river corridors, once these agreements are established.

Annex

Herre is a recent satellite image of the Jondachi-Hollín-Misahuallí-Napo River Corridor. Note the intact river and forest core to the east of the major road network, and north of the Napo River.

 

Citation

Terry M, Finer M, Ariñez A (2023) Protecting Free-flowing & Intact River Corridors in the Ecuadorian Amazon. MAAP: 202.

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 #187: Amazon Deforestation & Fire Hotspots 2022

Posted on by dcadmin
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.
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  • 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.
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  • 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.
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  • 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.
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  • 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.
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  • 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

Posted on by dcadmin
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.