Land Use: Protected Areas

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

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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 #185: Gold Mining Deforestation in the Southern Peruvian Amazon: 2021-2022 Update

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Base Map. Gold Mining Deforestation in the Southern Peruvian Amazon, 2021-2022 update. Zooms indicated by insets A-F. Click on image to enlarge. Data: ACA/MAAP, CINCIA.

Gold mining continues to be one of the main causes of deforestation in the southern Peruvian Amazon, especially in the Madre de Dios region.

Here, we provide a comprehensive look at the most recent (2021-2022) gold mining-related deforestation in the area, combining two important types of data for the first time:

  1. Deforestation within the Mining Corridor, a large area delimited by the Peruvian government to organize and promote mining. Mining activity in this corridor, officially known as the “Small-scale and Artisanal Mining Zone in the department of Madre de Dios,” can be formal, informal, or illegal.1
    j
  2. Deforestation outside the Mining Corridor, which represents our estimate of illegal mining. According to current regulations (Legislative Decree No. 1336), illegal mining occurs in one or more territorial categories such as protected natural areas, indigenous reserves, and natural bodies of water (such as lakes or rivers). Therefore, for this report, the presence of mining-related deforestation in protected natural areas and their buffer zones, as well as indigenous communities, is considered an indicator of illegality. However, it is important to recognize the possibility that some of these findings may be covered by current regulations regarding mining formalization.2 Therefore, it is recommended to consider the findings of illegal deforestation as referential.

These two study areas cover a total of 1.38 million hectares and include all detected mining areas in the southern Peruvian Amazon.

We highlight several important findings (see Base Map and Table 1):

  • Table 1. Data: ACA/MAAP.

    We estimate a total deforestation of 18,421 hectares (45,520 acres) due to gold mining in the southern Peruvian Amazon in the last two years (2021-2022).
    l

  • Of this total, the majority of mining-related deforestation (76.6%, or 14,117 hectares) occurred within the Mining Corridor.
    l
  • The remaining deforestation (23.4%, or 4,304 hectares) took place outside the Mining Corridor. Breaking down this percentage, 15% is found in indigenous communities, 4.8% in buffer zones of protected natural areas, 0.8% in forest concessions, and 2.8% in non-zoned areas.
    j
  • Furthermore, we found that mining within protected natural areas, such as the Tambopata National Reserve and the Amarakaeri Communal Reserve, has been effectively controlled by the Peruvian government through the National Service of Protected Natural Areas (SERNANP).
    j
  • It is important to highlight that mining has stopped in the core of La Pampa (the most critical zone during the years 2014-2018) following Operation Mercury in early 2019 and the subsequent Restoration Plan in 2021.
    j
  • Compared to the years prior to Operation Mercury (2017-2018), there has been an approximate decrease of 4.5% (866 hectares) in mining-related deforestation. Most notably, there has been a major reduction in mining outside the corridor (from 47.7% to 23.4%), and a greater concentration within the corridor (from 52.3 to 76.6%).3  That is, an apparent major reduction in illegal mining.

Mining Corridor

Our main finding is that the vast majority (76.6%) of gold mining-related deforestation in the southern Peruvian Amazon occurred within the Mining Corridor.

We estimate that the deforestation due to mining is 14,117 hectares within the Mining Corridor in the last two years (2021-2022). Below, we present a series of zooms of some emblematic examples of recent mining-related deforestation in the corridor (Images A-C).

Image A: Mining Corridor

Image B: Mining Corridor

Image C: Mining Corridor

Outside of the Mining Corridor

The remaining deforestation due to mining (23.4%) is located outside the Mining Corridor. Breaking this down, 15% (2,769 hectares) occurred within indigenous territories, 4.8% (876 hectares) in buffer zones of protected areas, 0.8% (141 hectares) in forest concessions (for Brazil nuts), and 2.8% (517 hectares) in non-zoned areas during the last two years.

Regarding indigenous communities, the most affected were Barranco Chico (816 hectares) and San José de Karene (602 hectares), followed by Tres Islas (482 hectares), San Jacinto (177 hectares), Kotsimba (174 hectares), Puerto Luz (171 hectares), Boca Inambari (140 hectares), Shiringayoc (126 hectares), Arazaire (57 hectares), and El Pilar (23 hectares).

Regarding the buffer zones of protected areas, the most affected were the buffer zones of the Tambopata National Reserve, the Bahuaja Sonene National Park, and the Amarakaeri Communal Reserve. On the other hand, it has been found that mining within the actual protected areas, such as the Tambopata National Reserve and the Amarakaeri Communal Reserve, has been effectively controlled by the Peruvian government through the National Service of Natural Protected Areas (SERNANP).

Regarding forest concessions, deforestation due to mining was identified in 141 hectares within Brazil nut concessions in the Pariamanu and Pariamarca river basins.

Next, we continue with a series of zooms showing some emblematic examples of recent deforestation due to mining in the following prohibited areas: indigenous communities (Barranco Chico, Image D), buffer zone of the Bahuaja Sonene National Park (Chaspa, Image E), and Brazil nut concessions (Pariamanu, Image F).

We also present an important area in the buffer zone of the Tambopata National Reserve known as La Pampa (Image G). La Pampa was the epicenter of destructive deforestation due to gold mining between 2014 and 2018. We show that after Operation Mercury, which began in early 2019, the expansion of gold mining in La Pampa was essentially halted.

Image D: Barranco Chico (Indigenous Community)

Image E: Chaspa (Buffer Zone of Bahuaja Sonene National Park)

Image F: Pariamanu (Brazil Nut Concession)

Image G: La Pampa (Buffer Zone of Tambopata National Reserve)

Annex

We show a version of the Basemap without the zoom insets.

Base Map (without insets). Deforestation by Gold Mining in the Southern Peruvian Amazon, with Update 2021-22. Click image to enlarge. Data: ACA/MAAP, CINCIA.

Notes

1The Mining Corridor, designated by Legislative Decree No. 1100 as the “Zone for small-scale and artisanal mining in the department of Madre de Dios,” categorizes mining activities as follows:

  • Formal: Completed formalization process with approved environmental and operational permits.
  • Informal: In the process of formalization; Operates only in authorized extraction areas, uses permitted machinery, and is considered an administrative offense, not a crime.
  • Illegal: Operates in prohibited areas such as bodies of water (e.g., rivers or lakes), uses prohibited machinery, is considered a criminal offense, and is punishable by imprisonment.

2 Due to the possibility that these activities could be existing operations prior to the declaration of Natural Protected Areas and their buffer zones.

3 The data for 2017-2018 were obtained from the Amazonian Scientific Innovation Center – CINCIA.

Methodology

Mining Corridor

We used LandTrendR, a temporal segmentation algorithm that identifies changes in pixel values over time, to detect forest loss within the Mining Corridor in 2021 and 2022 using the Google Earth Engine platform. It is important to note that this method was originally designed for Landsat images with moderate resolution (30 meters)1, but we adapted it for higher spatial resolution NICFI-Planet monthly mosaics (4.7 meters).2

Additionally, we created a baseline for the period 2016-2020 to eliminate old deforested areas (prior to 2021) due to rapid changes in the natural regrowth process.

Finally, we manually separated forest loss due to mining and other causes in 2021 and 2022 to specifically report on direct impacts related to mining. For this part of the analysis, we used various resources to aid the manual process, such as radar image alerts (RAMI) from the SERVIR Amazonia program, historical data from CINCIA from 1985 to 2020, forest loss data from the Peruvian government (National Forest Conservation Program for Climate Change Mitigation), and the University of Maryland.

  1. Kennedy, R.E., Yang, Z., Gorelick, N., Braaten, J., Cavalcante, L., Cohen, W.B., Healey, S. (2018). Implementation of the LandTrendr Algorithm on Google Earth Engine. Remote Sensing. 10, 691.
  2.  Erik Lindquist, FAO, 2021

Outside the Mining Corridor

These places were identified as the main active fronts of deforestation due to gold mining, based on historical data from the Amazon Scientific Innovation Center – CINCIA and automatic alerts of forest loss generated by both the University of Maryland (GLAD alerts) and the Peruvian government platform (PNCBMCC-Geobosques).

The analysis combines the LandTrendr method (described earlier) with a photo interpretation based on high-resolution satellite images from Planet (3 meters). In each of the sites, we have detected, identified, and analyzed deforestation due to gold mining between 2021 and 2022. For areas with overlap between native communities and buffer zones, priority was given to the areas of the native communities.

Acknowledgements

We thank S. Novoa, C. Zavala, O. Liao, K. Nielsen, S. Otoya, and C. Ipenza for their valuable contributions and comments to this report, and R. McMullen for translation. We also thank C. Ascorra and M. Pillaca from the Amazon Scientific Innovation Center – CINCIA for providing us with historical mining data from 1985 to 2021.

This report was prepared with the technical support of USAID through the Prevent Project. Prevent (Proyecto Prevenir in Spanish) works with the Government of Peru, civil society, and the private sector to prevent and combat environmental crimes for the conservation of the Peruvian Amazon, particularly in the regions of Loreto, Madre de Dios, and Ucayali.

Disclaimer: This publication is made possible by the generous support of the American people through USAID. The contents are the sole responsibility of the authors and do not necessarily reflect the views of USAID or the United States Government.

 

Citation

Finer M, Mamani N (2023) Gold Mining Deforestation in the Southern Peruvian Amazon: 2021-2022 Update. MAAP: 185.

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

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

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

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

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

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

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

We analyzed the results across three major land use categories:

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

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

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

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

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

Key Findings

Amazon Biome

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

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

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

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

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

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

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

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

Western Amazon

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

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

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

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

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

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

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

Brazilian Amazon

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

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

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

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

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

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

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

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

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

Methodology

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

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

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

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

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

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

Additional data sources include:

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

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

Acknowledgements

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

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

Citation

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

MAAP #178: Gold Mining Deforestation Across the Amazon

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

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

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

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

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

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

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

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

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

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

Case Studies, in High-resolution

Peruvian Amazon

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

A. Mangote

B. Pariamanu

Brazilian Amazon

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

C. Munduruku Indigenous Territory


D. Kayapó Indigenous Territory


E. Yanomami Indigenous Territory

Venezuelan Amazon

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

F. Canaima National Park


G. Yapacana National Park

Ecuadorian Amazon

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

H. Punino River

I. Podocarpus National Park

Bolivian Amazon

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

J. Madidi National Park

Methodology

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

Acknowledgements

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

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

Citation

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

MAAP #182: Gold Mining Deforestation in the Ecuadorian Amazon

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Base Map. Major cases of recent gold mining deforestation in Ecuadorian Amazon.

Gold mining is one of the major deforestation drivers across the Amazon, with well-known cases in Peru, Brazil, and Venezuela.

In a recent series of technical articles*, in collaboration with the Ecuadorian organization Foundation EcoCiencia, we have also shown that gold mining is escalating in the Ecuadorian Amazon.

Here, we summarize the results from the series and present 5 major cases of recent gold mining deforestation in Ecuador (see Base Map).

These cases, which include gold mining expansion in protected areas, indigenous territories, and primary forests, are:

  • Punino River, located between Napo and Orellana provinces, has experienced the rapid mining deforestation expansion of 217 hectares since 2019.
    l
  • Yutzupino, located in Napo province, has experienced mining deforestation of 125 hectares since 2021. Surrounding sites in Napo have added 490 hectares since 2017.
    l
  • Shuar Arutam Indigenous Territory, located in Morona Santiago province, has experienced 257 hectares of mining deforestation since 2021.
    l
  • Podocarpus National Park, located in Zamora Chinchipe province, has experienced 25 hectares of mining deforestation within the park since 2019.
    k
  • Upper Nangaritza River Protected Forest, also located in Zamora Chinchipe has experienced 545 hectares of mining deforestation since 2018.

In total, we have documented the recent gold mining deforestation of 1,660 hectares (4,102 acres) in the Ecuadorian Amazon. This is equivalent to 2,325 soccer fields.

For each case, we show high-resolution satellite images of the recent gold mining deforestation.

Case Studies – Recent Gold Mining Deforestation in the Ecuadorian Amazon

For each of the five cases presented below, we show both a high-resolution (3 meters) example of the recent mining deforestation (left panel) and very-high resolution (0.5 meters) zoom of the mining activity (right panel).

Punino River

Along the Punino River, located between Napo and Orellana provinces, we have documented the rapid mining deforestation expansion of 217 hectares since November 2019. Alarmingly, much of this activity (85%) occurred most recently in 2022. See MAAP #176 for more details.

Case 1. Punino River.

Yutzupino/Napo

In this area, located in Napo province, we have documented the mining deforestation of 125 hectares since October 2021, including major impacts along the Jatunyacu River. Surrounding sites in Napo have added 490 hectares since 2017. See MAAP #151 and MAAP #162 for more details.

Case 2. Yutzupino/Napo.

Upper Nangaritza River Protected Forest

In Upper Nangaritza River Protected Forest, also located in Zamora Chinchipe province, we have documented the mining deforestation of 545 hectares since 2018 along the Nangaritza River. See MAAP #167 for more details.

Case 3. Upper Nangaritza River Protected Forest.

Shuar Arutam Indigenous Territory

In the Shuar Arutam Indigenous Territory, located in Morona Santiago province, we have documented the mining deforestation of 257 hectares since 2021. See MAAP #170 for more details.

Case 4. Shuar Arutam Indigenous Territory.

Podocarpus National Park

In Podocarpus National Park, located in Zamora Chinchipe province, we have documented the mining deforestation of 25 hectares since 2019 within the park, including the presence of over 200 mining camps. See MAAP #172 for more details.

Case 5. Podocarpus National Park.

*MAAP Technical Reports

MAAP #176: Expansión Alarmante de Minería en la Amazonía Ecuatoriana (Caso Punino)
https://www.maaproject.org/2023/mineria-ecuador-punino/

MAAP #172: Minería ilegal de oro en el Parque Nacional Podocarpus, Ecuador
https://www.maaproject.org/2023/mineria-podocarpus-ecuador/

MAAP #170: Actividad Minera en Territorio Shuar Arutam (Amazonia Ecuatoriana)
https://www.maaproject.org/2022/mineria-shuar-arutam-ecuador/

MAAP #167: Actividad Minera en el Bosque Protector Cuenca Alta del Río Nangaritza (Ecuador)
https://www.maaproject.org/2022/minera-nangaritza-ecuador/

MAAP #162: Dinámica de la actividad minera en la  provincia de Napo (Ecuador)
https://www.maaproject.org/2022/mineria-napo-ecuador/

MAAP #151: Minería Ilegal en la Amazonía Ecuatoriana
https://www.maaproject.org/2022/mineria-ecuador/

Acknowledgments

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

MAAP #155: Deforestation Hotspots in the Venezuelan Amazon

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Amazon Base Map. Forest Carbon Flux across the Amazon, 2001-2020. Data: Harris et al 2021. Analysis: Amazon Conservation/MAAP.

We present here the first report of a series focused on the Venezuelan Amazon, which covers over 47 million hectares of the northern section of the Amazon biome (above western Brazil).

As the Amazon Base Map indicates, Venezuela is a key part to the remaining core Amazon that is still functioning as a critical carbon sink, making it an important piece to long-term conservation strategies.

However, deforestation has been increasing in recent years (see graph in Base Map), indicating escalating threats.

Specifically, there is a clear trend of increasing primary forest loss since 2015, including a recent spike in 2019.

We estimate the loss of over 140,000 hectares (345,000 acres) over the past four years, accounting for 1.6% of the total loss across the Amazon during that time period.

Below, we investigate the major hotspots and drivers of deforestation currently in the Venezuelan Amazon.

 

 

Venezuela Base Map. Hotspots of primary forest loss across the Venezuelan Amazon (2017-2020). UMD/GLAD, MAAP.

The Venezuela base map shows the major hotspots of primary forest loss across the Venezuelan Amazon over the past four years (2017-2020).

Note that most hotspots are within the Orinoco Mining Arc, a large area over 11 million hectares created by a controversial presidential decree in 2016 designed to promote mining (SOSOrinoco 2021), as well as within and around the extensive network of protected areas.

These protected areas cover 43% (20 million hectares) of the Venezuelan Amazon and accounted for around 30% of total forest loss. The most impacted areas in recent years are Caura, Canaima, and Yapacana National Parks (over 22,000 hectares combined).

We zoomed in on these hotspots and found that mining, fires, and agriculture (including cattle pasture) are the three primary deforestation drivers across the Venezuelan Amazon. There may be complex interactions between these drivers, such as mining centers leading to fires and agricultural expansion to support the new mining population.

It is worth noting that Venezuela joins Peru, Brazil, and Suriname as countries where mining is now documented to be actively driving major deforestation of primary forest.

We also note that, as in the rest of the Amazon, virtually all fires are caused by humans (that is, not natural events) and most are likely linked to preparing land for agricultural activities. During drier periods, these fires may escape, causing larger forest fires.

Below, we illustrate these drivers in a series of high-resolution (3 meters) and very high-resolution (0.5 meters) images.

High-resolution Zooms

Mining

Zoom A. Yapacana National Park

Yapacana National Park, which is a unique mosaic of natural savannas and forest, is currently experiencing deforestation impacts from active mining operations. We show two examples of recent mining in the Cerro Yapacana mining sector, featuring very-high resolution imagery from late 2021 (see Zooms A1 and A2). These two areas have lost over 550 hectares since the early 2000s.

Zoom A1. Mining deforestation in Yapacana National Park. Data: Planet/Skysat.
Zoom A2. Mining deforestation in Yapacana National Park. Data: Planet/Skysat.

 

Zoom B. Caura National Park

Caura National Park is also experiencing active mining activity. Below are two examples of recent mining activity, featuring very-high resolution imagery from early 2022 (see Zooms B1 and B2).

 

Zoom B1. Mining deforestation in Caura National Park. Data: Planet/Skysat.

 

Zoom B2. Mining deforestation in Caura National Park. Data: Planet/Skysat.

Zoom C. Canaima National Park

The following image shows the recent expansion of mining deforestation in Canaima National Park between 2017 (left panel) and 2020 (right panel).

Zoom C. Mining deforestation in Canaima National Park. Data: Planet/Skysat.

Zoom D: Orinoco Mining Arc

To the north of these protected areas, there is both industrial and river-based mining deforestation in the Orinoco Mining Arc. Zoom D shows an example of major river-based mining deforestation (over 1,800 hectares) between 2017 and 2020, plus a very-high resolution imagery from late 2021.

Zoom D. Mining deforestation in the Orinoco Mining Arc. Data: Planet.

Agriculture

Zoom E shown an example of agricultural expansion (likely cattle ranching) in the northeastern section of the Orinoco Mining Arc. We estimate the forest loss shown in the panels between 2017 and 2020 is over 400 hectares.

Zoom E. Agricultuire deforestation in the Orinoco Mining Arc. Data: Planet.

Fire

Finally, Zooms F and G show recent examples of major fires impacts. Zoom F is an area that experienced major fires in 2019 within and around Canaima National Park. We estimate the forest loss shown in the panels between 2017 and 2020 is 1,175 hectares.

Zoom F. Major fires in 2019 within and around Canaima National Park. Data: Planet.

Zoom G is an area that experienced major fires in 2020 in the near mining sites in the western section of the Orinoco Mining Arc. We estimate the forest loss shown in the panels between 2017 and 2020 is 1,128 hectares.

Zoom G. Major fires in 2020 in the Orinoco Mining Arc. Data: Planet.

Methodology

For a study area with maximum inclusion, for the Venezuelan Amazon we used the wider biogeographic boundary (as defined by RAISG) rather than the strict Amazon watershed boundary (which actually only includes a small portion of Venezuela).

We obtained data for the Orinoco Mining Arc (Arco Minero del Orinoco) and protected areas from the organization SOSOrinoco. The latter dataset contains Areas Under Special Administration Regime (Áreas Bajo Régimen de Administración Especial – ABRAE), which meet the IUCN international definition of protected areas: national parks, natural monuments, wildlife refuges, reserves and sanctuaries.

We used “primary forest loss” data as our proxy for 2002-2020 annual deforestation. This 30-meter resolution (based on Landsat) data is produced by the University of Maryland and presented by Global Forest Watch. Note that it includes forest loss from fires and natural causes. 2021 early warning alert data is also from University of Maryland.

To identify primary forest loss 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 Spatial Analyst Tool Box of ArcGIS.

Finally, we investigated the major hotspots with both high resolution (3 meters) and very high resolution (0.5 meters) satellite imagery from the company Planet to identify causes (drivers).

References

SOSOrinoco. 2021. Deforestation & Changes in Vegetation &  Land Use Cover within the so-called Orinoco Mining Arc between 2000-2020.

Acknowledgements

We thank the organization SOSOrinoco for important information and comments related to this report.

Citation

Finer M, Mamani N (2022) Deforestation Hotspots in the Venezuelan Amazon. MAAP: 155.

MAAP #156: Intense Mining Activity in Yapacana National Park (Venezuelan Amazon)

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Base Map: Mining areas in Yapacana National Park. Data: SOS Orinoco, ACA/MAAP, Planet.

We present the second report in our series focused on the Venezuelan Amazon.

The first (MAAP #155) documented the loss of over 140,000 hectares (345,000 acres) of primary forest over the past four years. We also zoomed in on the major hotspots, showing that mining is one of the primary deforestation drivers, including in protected areas.

Here we focus on a key protected area, Yapacana National Park.

The park, created in 1978, is a key biogeographical site, with diverse ecosystems (including white sand savannahs), high endemism and biodiversity, and unique Guiana Shield outcrops. Illegal mining started in the park in the 1980s and started to surge in the 2000s (see SOS Orinoco 2020 for details on the complex socio-political issues).

We show Yapacana National Park is currently experiencing intense illegal mining activity.

Specifically, we carried out a detailed estimate of current mining camps and machinery, based on recent and very high-resolution Skysat satellite imagery from Planet (0.5 meters).

We found over 8,000 mining data points (over 4,100 camps and 3,800 pieces of machinery), indicating that Yapacana National Park may currently be the most impacted site in the Amazon (replacing the case La Pampa in the buffer zone of Tambopata National Reserve, in the southern Peruvian Amazon), based on density of mining-related activity.

The goal of this report is to precisely inform the international community about the magnitude of the crisis in Yapacana National Park in hopes of an eventual solution.

Intense Mining in Yapacana National Park

The Base Map (see above) shows the major mining sectors in Yapacana National Park and our Skysat coverage over the recent time period of December 2021 to March 2022 (vertical dark green polygons). In this area, we recorded an astounding 8,214 mining data points (4,167 camps and 3,884 pieces of machinery). This finding is consistent with previous estimates that there are over 2,000 illegal miners operating in the park (and even indicates that this is an underestimate).

The Letters A-C correspond to the zoom images below.


Zoom A: Cerro Yapacana (north)

Zoom A centers on a major mining area in the Cerro Yapacana sector that experienced the deforestation of 360 hectares since the early 2000s, including a spike starting in 2016. It shows a very high-resolution Skysat image from early December 2021, with and without the mining data (left and right panel, respectively). Note how the second image brings out previously “invisible” elements within the overall mining area: 945 mining data points (413 camps and 532 equipment).  Further below, Zooms A1 and A2 further illustrate this point.

Zoom A. Mining activity in the Cerro Yapacana northern sector without (left panel) and with (right panel) the mining data. Data: ACA/MAAP, Planet (Skysat).
Zoom A1. Mining activity in the Cerro Yapacana sector without (left panel) and with (right panel) the mining data. Data: ACA/MAAP, Planet (Skysat).
Zoom A2. Mining activity in the Cerro Yapacana sector without (left panel) and with (right panel) the mining data. Data: ACA/MAAP, Planet (Skysat).

Zoom B: Cerro Yapacana (south)

Zoom B centers on a major mining area in the Cerro Yapacana sector that experienced the deforestation of 175 hectares since the early 2000s, including a spike starting in 2014. It shows a very high-resolution Skysat image from early December 2021, with and without the mining data (left and right panel, respectively). Note how the second image brings out previously “invisible” elements within the overall mining area: 1,175 mining data points (667 camps and 508 equipment). Again, note how the second image brings out previously “invisible” elements within the overall mining area. Zooms B1 and B2 further illustrate this point.

Zoom B. Mining activity in the Cerro Yapacana southern sector without (left panel) and with (right panel) the mining data. Data: ACA/MAAP, Planet (Skysat).
Zoom B1. Mining activity in the Cerro Yapacana southern sector without (left panel) and with (right panel) the mining data. Data: ACA/MAAP, Planet (Skysat).
Zoom B2. Mining activity in the Cerro Yapacana southern sector without (left panel) and with (right panel) the mining data. Data: ACA/MAAP, Planet (Skysat).

Zoom C: Cerro Moyo

Lastly, Zoom C centers on a major mining area in the Cerro Moyo sector that experienced the deforestation of 240 hectares since the early 2000s, including a spike starting in 2011. It shows a very high-resolution Skysat image from March 2022, with and without the mining data (left and right panel, respectively). Again, note how the second image brings out previously “invisible” elements within the overall mining area: 579 data points (55 camps and 524 equipment). Zoom C1 further illustrates this point.

Zoom C. Mining activity in the Cerro Moyo sector without (left panel) and with (right panel) the mining data. Data: ACA/MAAP, Planet (Skysat).
Zoom C1. Mining activity in the Cerro Moyo sector without (left panel) and with (right panel) the mining data. Data: ACA/MAAP, Planet (Skysat).

Methodology

We tasked very high-resolution Skysat satellite imagery (0.5 meters), using the host company Planet’s tasking dashboard, of known mining locations in Yapacana National Park. We then closely and manually analyzed these images, documenting both mining camps and equipment. We researched aerial examples of mining areas in other countries to improve our identification abilities.

As a guide to locate key mining zones in these areas, we used mining area data produced by the organization SOS Orinoco, which used manual visual interpretation methods to identify these areas.

References

BirdLife International. Yapacana National Park (Parque Nacional Yapacana IBA). http://datazone.birdlife.org/site/factsheet/14941

Castillo R. y V. Salas. 2007. Estado de Conservación del Parque Nacional Yapacana. Reporte Especial. En: BioParques: Programa Observadores de Parques

SOS Orinoco. 2019. La Minería Aurífera en el Parque Nacional Yapacana Amazonas Venezolano: Un caso de extrema urgencia ambiental y geopolítica, nacional e internacional.

SOS Orinoco. 2020. La Minería Aurífera en el Parque Nacional Yapacana, Amazonas Venezolano | Un caso de extrema urgencia ambiental y geopolítica, nacional e internacional – Actualización al 2020.

Acknowledgements

We thank the organization SOSOrinoco for important information and comments related to this report.

Citation

Finer M, Mamani N (2022) Intense Mining Activity in Yapacana National Park (Venezuelan Amazon). MAAP: 156.

MAAP #153: Amazon Deforestation Hotspots 2021

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Amazon Base Map. Deforestation hotspots across the Amazon in 2021 (as of September 18). Data: UMD/GLAD, ACA/MAAP.

We present a first look at the major 2021 Amazon deforestation hotspots.*

The Amazon Base Map illustrates several key findings:p

  • We estimate the loss of over 1.9 million hectares (4.8 million acres) of primary forest loss across the nine countries of the Amazon biome in 2021.
    k
  • This matches the previous two years, bringing the total deforestation to 6 million hectares (15 million acres) since 2019, roughly the size of the state of West Virginia.
    p
  • In 2021, most of the deforestation occurred in Brazil (70%), followed by Bolivia (14%), Peru (7%), and Colombia (6%).
    p
  • In Brazil, hotspots are concentrated along the major road networks. Many of these areas were also burned following the deforestation.
    j
  • In Bolivia, fires once again impacted several important ecosystems, including the Chiquitano dry forests.
    p
  • In Peru, deforestation continues to impact the central region, most notably from large-scale clearing for a new Mennonite colony.
    p
  • In Colombia, there continues to be an arc of deforestation impacting numerous protected areas and indigenous territories.

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

Brazil Base Map. Deforestation hotspots in Brazilian Amazon. Data: UMD/GLAD, ACA/MAAP.

Brazilian Amazon

The Brazil Base Map shows the notable concentration of deforestation hotspots along the major roads (especially roads 163, 230, 319, and 364) in the states of Acre, Amazonas, Pará, and Rondônia.

 

 

 

 

 

 

 

 

 

 

 

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

Bolivian Amazon

The Bolivia Base Map shows the concentration of hotspots due to major fires in the Chiquitano dry forest biome, largely located in the department of Santa Cruz in the southeast section of the Amazon.

 

 

 

 

 

 

 

 

 

 

 

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

Peruvian Amazon

The Peru Base Map shows the concentration of deforestation in the central Amazon (Ucayali region).

We highlight the rapid deforestation (365 hectares) for a new Mennonite colony in 2021, near the town of Padre Marquez (see MAAP #149).

Also, note some additional hotspots in the south (Madre de Dios region), but these are largely from expanding agriculture instead of the historical driver of gold mining.

Indeed, gold mining deforestation has been greatly reduced due to government actions, but this illegal activity still threatens several key areas and indigenous territories (MAAP #130).

 

 

 

 

 

 

 

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

Colombian Amazon

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).

 

 

 

 

 

 

 

 

 

*Notes and Methodology

The analysis was based on 10-meter resolution primary forest loss alerts (GLAD+) produced by the University of Maryland and also presented by Global Forest Watch. These alerts are derived from the Sentinel-2 satellite operated by the European Space Agency.

We emphasize that this data represents a preliminary estimate and more definitive annual data will come later in the year.

We also note that this data does include forest loss caused by natural forces and burned areas.

Our geographic range for the Amazon is a hybrid between both the biogeographic boundary (as defined by RAISG) and watershed boundary, designed for maximum inclusion.

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: Medium: 5-7%; High: 7-14%; Very High: >14%.

Acknowledgements

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

Citation

Finer M, Mamani N, Spore J (2022) Amazon Deforestation Hotspots 2021. MAAP: 153.

MAAP #147: Amazon Deforestation Hotspots 2021 (1st Look)

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Base Map. Deforestation hotspots across the Amazon in 2021 (as of September 18). Data: UMD/GLAD, ACA/MAAP.

We present a first look at the major deforestation hotspots across all nine countries of the Amazon in 2021 (as of September 18).*

The Base Map illustrates several key findings thus far in 2021:p

  • We estimate the loss of over 860,000 hectares (2.1 million acres) of primary forest loss across the nine countries of the Amazon.
    p
  • Amazon deforestation has been concentrated in three countries: Brazil (79%), Peru (7%), Colombia (6%).
    p
  • The vast majority of deforestation (79%) occurred in the Brazilian Amazon, where massive hotspots stretched across the major road networks. Many of these areas were also burned following the deforestation.
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  • There continues to be an arc of deforestation in the northwestern Colombian Amazon, impacting numerous protected areas and indigenous territories.
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  • In the Peruvian Amazon, deforestation continues to impact the central region, most notably from a new Mennonite colony and large-scale rice plantation.
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  • In Bolivia, fires are once again impacting several important ecosystems, including the Beni grasslands and Chiquitano dry forests of the Amazon, and Chaco scrub forest outside the Amazon.

Below, we zoom in on the three countries with the highest deforestation (Brazil, Colombia, and Peru) and show a series of high-resolution satellite images that illustrate some of the major 2021 deforestation events.

Widespread Deforestation in the Brazilian Amazon

The Brazil Base Map shows the notable concentration of deforestation hotspots along the major roads (especially roads 163, 230, 319, and 364). Zooms A-C show high-resolution examples of this deforestation, which largely appears to be associated with clearing rainforests for pasture.

Brazil Base Map. Deforestation hotspots in Brazilian Amazon (as of September 18). Data: UMD/GLAD, ACA/MAAP.
Zoom A. Deforestation in the Brazilian Amazon near road 230 (TransAmazian Highway) between February (left panel) and September (right panel) of 2021. Data: Planet.
Zoom B. Deforestation in the Brazilian Amazon along road 319 in Amazonas state between May (left panel) and September (right panel) of 2021. Data: Planet, ESA.
Zoom C. Deforestation in the Brazilian Amazon along road 163 between November 2020 (left panel) and September 2021 (right panel). Data: Planet, ESA.
Colombia Base Map. Deforestation hotspots in northwest Colombian Amazon (as of September 18). Data: UMD/GLAD, ACA/MAAP.

Arc of Deforestation in the Colombian Amazon

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).

Zooms D & E show high-resolution examples of this deforestation, which largely appears to be associated with clearing rainforests for pasture.

Zoom D. Deforestation in the Colombian Amazon (Caqueta) between December 2020 (left panel) and September 2021 (right panel). Data: Planet.
Zoom E. Deforestation in the Colombian Amazon between January (left panel) and September (right panel) of 2021. Data: Planet, ESA.
Peru Base Map. Deforestation hotspots in the Peruvian Amazon (as of September 18). Data: UMD/GLAD, ACA/MAAP.

Deforestation in the central Peruvian Amazon

The Peru Base Map shows the concentration of deforestation in the central Peruvian Amazon (Ucayali, Huanuco, and southern Loreto regions).

Zooms F & G show two notable examples of this deforestation: the rapid deforestation in 2021 for a new Mennonite colony (299 hectares) and large-scale rice plantation (382 hectares), respectively.

Also note some additional hotspots in the south (Madre de Dios region) from gold mining and medium-scale agriculture.

The hotspot in the north (Loreto region) is natural forest loss from a windstorm.

Zoom F. Deforestation (299 hectares) in the Peruvian Amazon for a new Mennonite colony between January (left panel) and September (right panel) of 2021 in southern Loreto region. Data: Planet.
Zoom G. Deforestation (382 ha) in the Peruvian Amazon for a new large-scale rice plantation between January (left panel) and September (right panel) of 2021 in Ucayali region. Data: Planet.

*Notes and Methodology

The analysis was based on 10-meter resolution primary forest loss alerts (GLAD+) produced by the University of Maryland and also presented by Global Forest Watch. These alerts are derived from the Sentinel-2 satellite operated by the European Space Agency.

We emphasize that this data represents a preliminary estimate and more definitive annual data will come later next year.

We also note that this data does include forest loss caused by natural forces and burned areas.

Our geographic range for the Amazon is a hybrid between both the biogeographic boundary (as defined by RAISG) and watershed  boundary, designed for maximum inclusion.

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 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: Medium: 7-10%; High: 11-20%; Very High: >20%.

Acknowledgements

We thank E. Ortiz and A. Ariñez for their helpful comments on this report.

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

Citation

Finer M, Mamani N, Spore J (2020) Amazon Deforestation Hotspots 2021. MAAP: 147.