MAAP #182: Gold Mining Deforestation in the Ecuadorian Amazon

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.
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  • Yutzupino, located in Napo province, has experienced mining deforestation of 125 hectares since 2021. Surrounding sites in Napo have added 490 hectares since 2017.
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  • Shuar Arutam Indigenous Territory, located in Morona Santiago province, has experienced 257 hectares of mining deforestation since 2021.
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  • Podocarpus National Park, located in Zamora Chinchipe province, has experienced 25 hectares of mining deforestation within the park since 2019.
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  • 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.maapprogram.org/2023/mineria-ecuador-punino/

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

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

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

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

MAAP #151: Minería Ilegal en la Amazonía Ecuatoriana
https://www.maapprogram.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 #164: Amazon Tipping Point – Where Are We?

Base Map. Total Amazon forest loss. Data: ACA/MAAP.

It is increasingly reported that the largest rainforest in the world, the Amazon, is rapidly approaching a tipping point.

As repeatedly highlighted by the late Tom Lovejoy (see Acknowledgements), this tipping point is where parts of the rainforest will convert into drier ecosystems due to disrupted precipitation patterns and more intense dry seasons, both exacerbated by deforestation.

The Amazon generates much of its own rainfall by recycling water as air passes from its major source in the Atlantic Ocean. Thus, high deforestation in the eastern Amazon may lead to downwind impacts in the central and western Amazon (see Background section below).

The scientific literature indicates this tipping point could be triggered at 25% Amazon forest loss, in conjunction with climate change impacts.

The literature, however, is less clear on the critical first part of the tipping point equation: how much of the Amazon has already been lost?

There are numerous estimates, including 14% forest loss cited in the recent Science Panel for the Amazon report, but we did not find any actual definitive studies specifically addressing this question.

Here, we directly tackle this key question of how much of the original Amazon has been lost to date.

First, we present the first known rigorous estimate of original Amazon biome forest prior to European colonization: over 647 million hectares (1.6 billion acres; see Image 1 below).

Second, we estimate the accumulated total Amazon forest loss, from the original estimate to the present: over 85 million hectares (211 million acres; see Base Map).

Combining these two results, we estimate that 13% of the original Amazon biome forest has been lost.

More importantly, however, focusing on just the eastern third of the Amazon biome (see Image 2 below), we estimate that 31% of the original forest has been lost, above the speculated tipping point threshold. This finding is critical because the tipping point will likely be triggered in the eastern Amazon, as it is closest to the oceanic source of the water that then flows to the central and western Amazon.

Original Amazon Forest

Image 1 shows the first known estimate of original Amazon forest prior to European colonization. Note that we use a broader biogeographical definition of the Amazon that covers nine countries (Amazon biome) rather than the strict Amazon watershed (see Methodology).

Image 1. Original Amazon biome forest. Data: ACA/MAAP.

This represents the most rigorous effort to date to recreate the original Amazon. For example, we attempted to recreate original forest lost to historic dam reservoirs.

The map has just three classes: Original Amazon forest, Original non-forest (such as natural savannah), and Water.

We found that the original Amazon forest covered over 647 million hectares (647,607,020 ha). This is equivalent to 1.6 billion acres.

Of this total, 61.4% occurred in Brazil, followed by Peru (12%), Colombia (7%), Venezuela (6%), and Bolivia (5%). The remaining four countries (Ecuador, Guyana, Suriname, and French Guiana) make up the final 8%.

Amazon Forest Loss

Image 2 shows the accumulated total Amazon forest loss, from the original estimate to the present (2022).

Image 2. Total Amazon forest loss. Vertical lines indicate the Amazon broken down into thirds. Data: ACA/MAAP.

Of the original forest noted above, we documented the historic loss of over 85 million hectares (85,499,157 ha). This is equivalent to 211 million acres.

The largest loss occurred in Brazil (69.5 million ha), followed by Peru (4.7 million ha), Colombia (4 million ha), Bolivia (3.8 million ha), and Venezuela (1.4 million ha). The remaining four countries (Ecuador, Guyana, Suriname, and French Guiana) make up the final 1.9 million ha.

By comparing the original Amazon biome, we calculated the historic loss of 13.2% of the original Amazon forest due to deforestation and other causes.

More importantly, however, we find that 30.8% of the original Amazon has been lost in the eastern third of the Amazon biome (see vertical dashed lines Image 2), above the speculated tipping point threshold. This finding is critical because as noted above, the tipping point will likely be triggered in the east as it is the source of the water flowing to the central and western Amazon.

In contrast, we find that 10.8% of the original Amazon has been lost in the central third of the Amazon biome and 6.3% has been lost in the western third, both of which are below the speculated tipping point threshold.

Background

The Amazon generates around half of its own rainfall by recycling moisture up to 6 times as air masses move from the Atlantic Ocean in the east across the basin to the west. Thus, the rainforest plays a major part in keeping itself alive, by recycling water through its trees to generate rainfall from east to west.

This unique hydrological cycle has historically supported rainforest ecosystems for vast areas far from the main ocean source.

But it also raises the question of how much deforestation would be required to cause the cycle to degrade to the point of being unable to support these forests, thus the Amazon tipping point hypothesis.

In this scenario, rainforests would transform into drier ecosystems, such as open canopy scrubland and savannah.

The tipping point concept originally referred to an abrupt ecosystem change, but it is now believed that the shift could happen gradually (30-50 years).

It is worth noting that the western Amazon near the Andes mountains would likely maintain its rainforests, as air currents flowing over the mountains would continue causing water vapor to condense and fall as rain.

Methodology

At the core of this work, we generated two major estimates: original Amazon forest and total historical Amazon forest loss.

For both of these estimates, we used the biogeographical boundary of the Amazon (as determined by RAISG 2020), which encompasses nine countries. Thus, we used a broader definition of the Amazon (Amazon biome) rather than the strict Amazon watershed, which omits part of the northeastern Amazon biome.

For original Amazon forest, we defined three major classes: Forest, Non-Forest, and Water. This analysis was based on data from MapBiomas Brazil (collection 2 from 1990) with some additional modifications. Original Forest was made up of these MapBiomas categories: Forest Formation, Mangrove, Flooded Forest, Mosaic of Agriculture and Pasture. Non-Forest was made up of these MapBiomas categories: Savanna Formation, Natural Non-Forest Flood Formation, Grassland, and Other non-Forest Formations. Water was made up of these MapBiomas categories: River, Lake, Ocean and Glacier.

We then made a number of modifications with manual edits based on data from the University of Maryland, INPE (Terrabrasilis), ArcGis satellite images, Planet mosaics, Google Earth Engine Landsat images from 1984-1990, and official government data for several countries (Ministry of the Environment of Ecuador (MAE) and Peru (GeoBosques/MINAM), Forest and Carbon Monitoring System/IDEAM of Colombia, National Institute for Space Research of Brazil (INPE/Terrabrasilis), General Directorate of Forest Management and Development of Bolivia (DGGDF), and the National Service of Protected Areas of Bolivia (SERNAP). As an example of a major modification, deforested areas and historic dam reservoirs were changed to Original Forest based on an analysis of the oldest available satellite image for the area (1984-1990). We also corrected some misclassifications, such as forest patches in clearly non-forest areas were changed to Non-Forest (and vice versa) and mountain forest areas found as water were changed to Forest. Also, agriculture and urban areas in likely savannah areas were changed to Non-Forest. Additional Water data from MapBiomas based on 1985 was incorporated. Overall, our focus was defining Original Forest as best as possible; data confusions between Non-Forest and Water categories were not worked on as thoroughly.

For total historical Amazon forest loss, we used data from the University of Maryland. Specifically, we first used their data layer ‘Tree Cover 2000″ (>30% canopy density) to estimate historical (pre-2000) forest loss. We then added annual forest loss data from 2001 to 2021.

Finally, we divided the original Amazon forest by the total historical loss to estimate how much of the original Amazon has been lost. In addition, we delimited the Amazon in thirds according to distance east to west at the widest point. We then estimated how much of the original Amazon has been lost in each of these three sections.

References

(in chronological order)

Sampaio, G., Nobre, C., Costa, M. H., Satyamurty, P., Soares‐Filho, B. S., & Cardoso, M. (2007). Regional climate change over eastern Amazonia caused by pasture and soybean cropland expansion. Geophysical Research Letters, 34(17).

Hansen, M. C. et. al. (2013) High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342.

Nobre et al. (2016) Land-use and climate change risks in the Amazon and the need of a novel sustainable development paradigm. PNAS, 113 (39).

Turubanova S., Potapov P., Tyukavina, A., and Hansen M. (2018) Ongoing primary forest loss in Brazil, Democratic Republic of the Congo, and Indonesia. Environmental Research Letters.

Lovejoy, T. E., & Nobre, C. (2018). Amazon Tipping Point. Science Advances, 4(2).

Lovejoy, T. E., & Nobre, C. (2019). Amazon tipping point: Last chance for action. Science Advances, 5 (12).

Bullock et. al. (2019) Satellite-based estimates reveal widespread forest degradation in the Amazon. Glob Change Biol., 26.

Amigo, I. (2020) The Amazon’s fragile future. Nature, 578.

MapBiomas. 2020. MapBiomas Amazonia v2.0. https://amazonia.mapbiomas.org/.

Killeen (2021) A Perfect Storm in the Amazon Wilderness

Berenguer E. et. al. (2021) Ch 19. Drivers and ecological impacts of deforestation and forest degradation. In: Nobre C, Encalada et al. (Eds). Amazon Assessment Report 2021. United Nations Sustainable Development Solutions Network, New York, USA. Available from https://www.theamazonwewant.org/spa-reports

Hirota M et. al (2021) Science Panel for the Amazon, Ch 24. Resilience of the Amazon Forest to Global Changes: Assessing the Risk of Tipping Points. In: Nobre C, Encalada et al. (Eds). Amazon Assessment Report 2021. United Nations Sustainable Development Solutions Network, New York, USA. Available from https://www.theamazonwewant.org/spa-reports/

Wunderling et al (2022) Recurrent droughts increase risk of cascading tipping events by outpacing adaptive capacities in the Amazon rainforest. PNAS 119 (32) e2120777119.

Acknowledgements

This report is in memory of Tom Lovejoy, who helped launch the critical concept of an Amazon tipping point. Starting in 2019, we collaborated with Tom on the need assessment and background research behind this report.

We thank Carmen Thorndike for helping with the initial literature review, and Carlos Nobre for review of the final report. We also thank J. Beavers (ACA), A. Folhadella (ACA), M.E. Gutierrez (ACCA), and C. Josse (EcoCiencia) for additional comments.

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

Citation

Finer M, Mamani N (2022) Amazon Tipping Point – Where Are We?. MAAP: 164.

MAAP #160: Lasers Estimate Carbon in the Amazon – NASA’s GEDI Mission

Simulation of GEDI lasers collecting data. Source: UMD.

NASA’s GEDI mission uses lasers to provide cutting-edge estimates of aboveground biomass and related carbon on a global scale.

Launched in late 2018 and installed on the International Space Station, GEDI’s lasers return an estimate of aboveground biomass density at greater accuracy and resolution than previously available.

Here, we zoom in on the Amazon and take a first look at the recently available Level 4B data: Gridded Aboveground Biomass Density measured in megagrams per hectare (Mg/ha) at a 1-kilometer resolution.

See the GEDI homepage for more background information on the mission, which extends until January 2023. Be sure to check out this illustrative video.

 

 

 

 

Base Map – Aboveground Biomass in the Amazon

The Base Map displays the GEDI data for the nine countries of the Amazon biome, displaying aboveground biomass for the time period April 2019 to August 2021.

Base Map. Aboveground Biomass Density in the Amazon. Data: NASA/UMD GEDI L4B. Click twice to enlarge.

 

We highlight the following initial major findings:

  • The data is not yet comprehensive as there are some areas the lasers have not yet recorded data (indicated in white).
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  • The areas with the highest aboveground biomass and related carbon (indicated in dark green and purple) include:
    • Northeast Amazon: Corner of Brazil, Suriname, & French Guiana.
    • Southwest Amazon: Southwest Brazil and adjacent Peru (see zoom below).
    • Northwest Amazon: Northern Peru, Ecuador, and southeast Colombia.

Zoom In – Southwest Amazon

To better visualize the GEDI laser data, we also present a zoom of the Southwest Amazon. Although deforested areas (and natural savannahs) are illustrated in yellow and orange, note the surrounding presence of high carbon forest (green and purple).

Zoom In – Southwest Amazon. Aboveground Biomass Density. Data: NASA/UMD GEDI L4B. Click twice to enlarge.

Zoom Out – Global Scale

Note that tropical forests, including the Amazon, have the highest levels of aboveground biomass globally.

Zoom Out – Glocal scale. Aboveground Biomass Density. Data: NASA/UMD GEDI L4B. Click twice to enlarge.

Acknowledgements

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

Citation

Finer M, Ariñez A (2022) Lasers Estimate Carbon in the Amazon – NASA’s GEDI Mission. MAAP: 160.

MAAP #157: New and Proposed Roads Across the Western Amazon

Amazon Roads Base Map 1.

Extensive deforestation, especially along the major road networks, has shockingly turned the eastern Brazilian Amazon into a net carbon source (see MAAP #144).

Fortunately, the greater Amazon across all nine countries is still a net carbon sink, largely thanks to the still intact core of the western Amazon.

The biggest long-term threat to this core Amazon is likely new roads, as they are a leading cause of opening up vast and previously remote areas to deforestation and degradation (Vilela et al 2020).

Here, we present an initial analysis of new and proposed roads across the western Amazon.

Although it’s difficult to predict what proposed projects are actually likely to eventually move forward, we do find the potential of a major road expansion across the core western Amazon (see Base Map 1).

Moreover, even by just focusing on the most advanced or actively discussed projects, we find the risk of major negative impact.

Below, we discuss our initial Amazon Roads Base Map and present a series of zooms showing the primary forest at risk if select road projects move forward.

 

 

Amazon Roads Base Map

Base Map 2 highlights new, proposed, and existing roads (red, yellow, and black lines, respectively), in relation to protected areas and indigenous territories for context. We focus on the still largely intact core of the western Amazon (Bolivia, Colombia, Ecuador, Peru, and western Brazil).

Most of the new roads were constructed in the past five years and were digitized from satellite imagery. Note that for some of these new roads, just initial construction of a rough road started and there is still potential for future impacts from road improvement and paving.

Most of the proposed roads were obtained from official government data sets. As noted above, it’s difficult to predict what proposed road projects are actually likely to eventually move forward. Nonetheless, it is clear to see there is the potential to greatly divide the remaining core western Amazon with the portfolio of proposed roads.

Amazon Roads Base Map 2. Data: ACA/MAAP, MTC, MINAM, MI, ABT, GAD Napo, FCDS, EcoCiencia, Diálogo Chino, CSF, RAISG, ACCA, ACEAA.

Zooms of High-Impact New & Proposed Roads

In this section, we focus on the currently most advanced or actively discussed projects (see Letters A-F on Amazon Roads Base Map). We highlight their potential impacts to vast sections of the core western Amazon protected areas and indigenous terrritories.

A. Boca Manu Road (Peru)

The new/proposed road that we refer to here as the Boca Manu road would serve as a new connection between Cusco and Madre de Dios regions. It is notable due its sensitive route between Manu National Park and Amarakaeri Communal Reserve to Boca Manu, and from there between Los Amigos Conservation Concession and Amarakaeri Communal Reserve to Boca Colorado. In addition to likely impacting these protected areas and the concession, the road also has the potential to impact the nearby territory of  indigenous groups in voluntary isolation. See this recent report from Diálogo Chino for more information about this road and its status and impacts.

Zoom A. Boca Manu Road. Data: MTC, MINAM, ACA, ACCA, RAISG.

B. Pucallpa – Cruzeiro do Sul Road (Peru – Brazil)

This proposed road would connect the Peruvian city of Pucallpa with the edge of the existing road network in western Brazil, near the town of Cruzeiro do Sul. Although the potential route has several options, it would sure cut through or near Sierra del Divisor National Park in Peru and the adjacent Serra do Divisor National Park in Brazil. This area is characterized by vast primary forests, thus creating a new binational route connecting the deforestation fronts in each country could obviously trigger significant impacts. See this recent report from Diálogo Chino for more information about this road and its status and impacts.

Zoom B. Pucallpa – Cruzeiro do Sul Road. Data: MTC, MINAM, ACA, CSF, Diálogo Chino, RAISG.

C. Yurua Road (Peru)

The new/proposed road that we refer to here as the Yurua road would connect the Peruvian towns of Nueva Italia on the Ucayali River and Breu on the Yurua River. This 200 km route was originally built as a logging road in the late 1980s to access remote timber areas in the central Peruvian Amazon, but had fallen into disrepair by the early 2000s. A recent MAAP analysis (see MAAP #146) found that between 2010 and 2021 much of the route had been rehabilitated, triggering elevated deforestation along the way. If this road were ever to be paved then impacts would likely continue to rise, including with native communities along the route. See MAAP #146 for more information about this road and its status and impacts.

Zoom C. Yurua Road. Data: MTC, MINAM, ACA, ACCA, RAISG.

D. Genaro Herrera – Angamos Road (Peru)

This new/proposed road would build off an old track through the vast forests connecting the northern Peruvian towns of Genaro Herrera and Angamos, in the region of Loreto. In 2021, clearing began along this route, advancing over 100 kilometers from both ends. If completed and paved, the final road project would impact protected areas on both sides (including the Matsés National Reserve to the south) and pose a major threat to indigenous people in voluntary isolation reportedly living to the north. See this recent report for more information about this road and its status and impacts.

Zoom D. Genaro Herrera – Angamos Road. Data: MTC, ACA, RAISG.

E. Cachicamo – Tunia Road (Chiribiquete National Park, Colombia)

Chiribiquete National Park, located in the heart of the Colombian Amazon, has been experiencing increasing deforestation pressures, partly due to expanding road networks around and even within the park. For example, the Cachicamo-Tunia Road, constructed in 2020, has triggered a new deforestation front in the northwest section of the park. Note this road is also impacting an adjacent Indigenous Reserve.

Zoom E. Cachicamo – Tunia Road. Data: FCDS, RAISG, ACA.

F.  Manaus – Porto Velho Road (BR-319, Brazil)

Arguably the most controversial project on the list: paving the middle section of BR-319 in the heart of the Brazilian Amazon. This nearly 900 km road connects the remote city of Manaus (otherwise only reachable by air or water) with the rest of Brazilian road network in Humaitá and Porto Velho to the south. It was built in the early 1970s but abandoned and impassable by the late 1980s, isolating Manaus once again. Since 2015, a basic maintenance program has made the road generally passable, but the main project remains: paving the 400 km middle section that passes through the core western Amazon. This paving would effectively connect Manaus with the existing highways in the south, and most likely trigger massive forest loss by extending the arc of deforestation northwards, including within and around the protected areas that surround the road. This road project has been the subject of numerous recent press reports, including investigative pieces by the Washington Post and El Pais.

Zoom F. Manaus – Porto Velho Road. Data: Ministério da Infraestrutura, ACA, RAISG.

G. Ixiamas – Chivé Road (Bolivia)

In recent years, Bolivia has been seeking financing for a 250 km road linking the current frontier town Ixiamas with the isolated town Chivé, located near the Peruvian border on the Madre de Dios river. This road would cross extensive tracts of primary Amazon forest and savannah in the north of the La Paz department, including the newly created Bajo Madidi Municipal Conservation Area and the Tacana II indigenous territory.

Zoom G. Ixiamas – Chivé Road. Data: ABT, ACEAA, ACA, RAISG.

Methodology

Our analysis and maps focus on the western Amazon (Bolivia, Colombia, Ecuador, Peru, and western Brazil).

Most of the new roads were constructed in the past five years and were digitized from satellite imagery. Note that for some of these new roads, just initial rehabilitation/improvement of a rough road started and there is still potential for future impacts from paving.

Most of the proposed roads were obtained from official government data sets (and complemented by civil society reports).

We credit the following data sources: Ministerio de Transportes y Comunicaciones (Peru), Geobosques/MINAM (Peru), Ministério da Infraestrutura (Brazil),  Autoridad de Fiscalización y Control Social de Bosques y Tierra – ABT (Bolivia), Gobierno Autonomo Descentralizado Provincial de Napo (Ecuador), Fundación para la Conservación y el Desarrollo Sostenible – FCDS (Colombia), Fundación EcoCiencia (Ecuador), Diálogo Chino, Conservation Strategy Fund, RAISG, Conservación Amazónica – ACCA (Peru), Conservación Amazónica – ACEAA (Bolivia), and Amazon Conservation (digitalization of some new and proposed roads).

Reference:
Vilela et al (2020) A better Amazon road network for people and the environment. PNAS 17 (13) 7095-7102.

Acknowledgments

We especially thank Diálogo Chino for their support of this report. We also thank E. Ortiz, S. Novoa, S. Villacis, D. Larrea, M. Terán, and D. Larrea for helpful comments on earlier drafts of the text and images.

Citation

Finer M, Mamani N (2022) New and Proposed Roads Across the Western Amazon. MAAP: 157.

MAAP #151: Illegal Mining in the Ecuadorian Amazon

Base Map. The two case studies of illegal mining in the Ecuadorian Amazon: Yutzupino and Punino. Data: EcoCiencia.

In this report, we report on illegal gold mining activity in the Ecuadorian Amazon, building off our previous reports on Peru (MAAP #130) and Brazil (MAAP #116).

The Base Map shows the two new cases presented below: Yutzupino (Napo province) and Punino (border of Napo and Orellana provinces).

Both cases showed alarming expansion in 2021 and require continued action by authorities to minimize the impact in 2022.

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).

 

 

 

 

 

Yutzupino

We have documented the rapid mining expansion of 70 hectares (173 acres) between October 2021 and January 2022, on the banks of the Jatunyacu River in the Napo province (see Image Yutzupino 1). Most of this activity occurred in December, highlighting the recent activity at the site.

Image Yutzupino 1. Data: Planet.

The gold mining concession Confluencia is located in this area. However, the operating company TerraEarth Resources has stated that it is not responsible for this sudden mining expansion, indicating that the detected activity is illegal because it does not have the proper licenses.

On January 8 of this year (2022), the Ecuadorian government carried out a field intervention, confirming the illegal activity (see national news report). Despite this action, the illegal mining activity has continued to advance in January 2022, increasing by at least 6 hectares (15 acres).

To analyze this most recent activity, we obtained a very high-resolution satellite image (Skysat, 0.50 meters) from January 17 (2022). We identified the presence of at least 70 mining-related machines that still remained on site after the government’s field operation was carried out (see Image Yutzupino 2 and Zooms A-B).

Image Yutzupino 2. Data: Planet, EcoCiencia.
Skysat Zoom A. Data: Planet, EcoCiencia.
Skysat Zoom B. Data: Planet, EcoCiencia.

Punino

We have also documented the mining deforestation of 32 hectares (79 acres) between November 2019 and November 2021, on the banks of the Río Punino on the border between the provinces of Napo and Orellana (see Image Punino 1).

Image Punino 1. Data: Planet.

Two active gold mining concessions, Punino I and Punino II, are located in this area. However, nearly half (46%) of the detected mining deforestation (15 ha) is located outside these concessions, indicating that it is illegal activity (see Image Punino 2).

Image Punino 2. Data: EcoCiencia, Planet.

Para contextualizar dicha deforestación ilegal, hemos utilizado una imagen de muy alta resolución (Skysat, 0.50 metros) para mostrar en detalle la expansión minera fuera de las concesiones mineras, incluso con dragados, máquinas, y campamentos (ver Imagen Punino 3).

To analyze this most recent illegal mining deforestation, we obtained a very high-resolution satellite image (Skysat, 0.50 meters) from December 2021. We identified the details of the mining expansion outside the concessions, including machines and camps (see Image Punino 3).

Image Punino 3. Data: EcoCiencia, Planet.

Acknowledgments

We thank C. Rivadeneyra (F. EcoCiencia), E. Ortiz (AAF), and A. Folhadella (ACA) for their contributions to this report.

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).

Cita

Villacís S, Ochoa J, Borja MO, Josse C, Finer M, Mamani N (2022) Illegal Mining in the Ecuadorian Amazon. MAAP: #151.

MAAP #150: New Oil Platforms Deeper into Yasuni National Park (Ecuador), towards Uncontacted Indigenous Zone

Base Map. Location of Yasuni National Park, ITT Block, and Zona Intangible in the Ecuadorian Amazon.

Yasuni National Park, located in the heart of the Ecuadorian Amazon, is one of the most biodiverse places in the world thanks to its unique location at the intersection of the Amazon, Andes Mountains, and the equator (see Base Map).

In addition, it is part of the ancestral territory of the Waorani indigenous peoples. The entire southern portion of Yasuni National Park has been declared an Untouchable Zone (Zona Intangible) to protect the territory of the relatives of the Waorani who live in voluntary isolation (Tagaeri-Taromenane).

In a series of previous reports, we have shown the construction of oil drilling platforms (and associated access road) in the ITT Block. This controversial block, run by the state oil company Petroecuador, is located in the remote and largely intact northeast sector of Yasuni National Park.

In this report, based on the latest satellite images, we show the most recent construction within the ITT Block: an oil drilling platform known as Ishpingo B. This platform is located just 300 meters from the buffer zone of the Zona Intangible.

We also issue a warning about the future construction of additional oil drilling platforms that would enter the buffer zone and reach the limit of the Zona Intangible itself.

Image 1. Data: Planet, MAAP/ACA.

Ishpingo Platforms A & B

The following images show the construction of the two new oil drilling platforms (Ishpingo A and B) in the heart of the Yasuni National Park (ITT Block).

Image 1 (on the right) shows that the newest and southernmost platform (Ishpingo B) is located just 300 meters from the buffer zone of the Zona Intangible.

Image 2 (below) shows the construction of the two new platforms and associated access road between June 2020 (left panel) and January 2022 (right panel).

It is worth mentioning that the construction of these platforms has a corresponding environmental license in accordance with the “Environmental Impact Study and Environmental Management Plan of the Ishpingo North Development and Production Project.”

Image 2. Data ESA, Planet, MAAP/ACA.
Image 3. Data: MAAP/ACA, Energy and Environmental Consulting.

Towards the Zona Intangible

Image 3 shows (in red) the location of the two new platforms (Ishpingo A and B) in relation to Yasuni National Park and the Zona Intangible.

Once again, note that the newest and southernmost platform (Ishpingo B) is located just 300 meters from the buffer zone of the Zona Intangible.

Alert: It is critical to emphasize that a previous version of the Environmental Impact Study includes plans for the construction of eight additional platforms (Ishpingo C-J), all located within the buffer zone towards the limit of the Zona Intangible Zone.

In fact, in early 2022, the head of Petroecuador has begun to publicly state the importance of moving forward with these extremely controversial plans.

Acknowledgments

We thank M. Bayón and P. Bermeo for useful information about the Environmental Impact Studies.

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) and the International Conservation Fund of Canada (ICFC).

Citation

Finer M, Mamani N, Josse C, Villacis S (2022) New Oil Platforms Deeper into Yasuni National Park (Ecuador), towards Uncontacted Indigenous Zone. MAAP: 150.

MAAP #141: Protected Areas & Indigenous Territories Effective Against Deforestation in the Western Amazon

Base Map. Primary forest loss across the western Amazon, with magnified visualization of the data. Click to enlarge. See Methodology for data sources.

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 land use designations: protected areas and indigenous territories.

Our study area focused on the four mega-diverse countries of the western Amazon (Bolivia, Colombia, Ecuador, & Peru), covering a vast area of over 229 million hectares (see Base Map).

We calculated primary forest loss over the past four years (2017-2020) across the western Amazon and analyzed the results across three major land use categories:

1) Protected Areas (national and state/department levels), which covered 43 million hectares as of 2020.

2) Indigenous Territories (official), which covered over 58 million hectares as of 2020.

3) Other (that is, all remaining areas outside protected areas and indigenous territories), which covered the remaining 127 million hectares as of 2020.

In addition, we took a deeper look at the Peruvian Amazon and also included long-term forestry lands.

In summary, we found that, averaged across all four years, protected areas had the lowest primary forest loss rate, closely followed by indigenous territories (see Figure 1). Outside of these critical areas, the primary forest loss rate was more than double.

Below, we describe the key results in greater detail, including a detailed look at each country.

 

Key Findings – Western Amazon

Figure 1. Primary forest loss rates in the western Amazon.

Overall, we documented the loss of over 2 million hectares of primary forests across the four countries of the western Amazon between 2017 and 2020. Of the four years, 2020 had the most forest loss (588,191 ha).

Of this total, 9% occurred in protected areas (179,000 ha) and 15% occurred in indigenous territories (320,000 ha), while the vast majority (76%) occurred outside key these land use designations (1.6 million ha).

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

From 2017-19, protected areas (green) had the lowest primary forest loss rates across the western Amazon (less than 0.10%).

Indigenous territories (brown) also had low primary forest loss rates from 2017-18 (less than 0.11%), but this rose in 2019 (0.18%) due to fires in Bolivia.

In the intense COVID pandemic year of 2020, this overall pattern flipped, with elevated primary forest loss in protected areas, again largely due to major fires in Bolivia. Thus, indigenous territories had the lowest primary forest loss rate followed by protected areas (0.15% and 0.19%, respectively) in 2020.

Averaged across all four years, protected areas had the lowest primary forest loss rate (0.11%), closely followed by indigenous territories (0.14%). Outside of these critical areas (red), the primary forest loss rate was more than double (0.30%). The lowest primary forest loss rates (less than 0.10%) occurred in the protected areas of Ecuador and Peru (0.01% and 0.03%, respectively), and indigenous territories of Colombia (0.07%).

Country Results

Figure 2. Primary forest loss rates in the Colombian Amazon.

Colombian Amazon

Colombia had, by far, the highest primary forest loss rates outside protected areas and indigenous territories (averaging 0.67% across all four years).

By contrast, Colombian indigenous territories had one of the lowest primary forest loss rates across the western Amazon (averaging 0.07% across all four years).

The primary forest loss rates for protected areas were on average nearly double that of indigenous territories (mostly due to the high deforestation in Tinigua National Park), but still much lower than non-protected areas.

 

 

 

 

 

Figure 3. Primary forest loss rates in the Ecuadorian Amazon.

Ecuadorian Amazon

Overall, Ecuador had the lowest primary forest loss rates across all three categories.

Protected areas had the lowest primary forest loss rate of any category across the western Amazon (averaging 0.01% across all four years).

Indigenous territories also had relatively low primary forest loss rates, averaging half that of outside protected areas and indigenous territories (0.10% vs 0.21%, respectively).

 

 

 

 

 

 

Figure 4. Primary forest loss rates in the Bolivian Amazon.

Bolivian Amazon

Bolivia had the most dynamic results, largely due to intense fire seasons in 2019 and 2020. Indigenous territories had the lowest primary forest loss rates, with 2019 being the only exception, due to large fires in the Santa Cruz department that affected the Monte Verde indigenous territory.

Protected areas had the lowest primary forest loss rate in 2019, but in extreme contrast, the highest the following year in 2020, also due to large fires in the Santa Cruz department that affected Noel Kempff Mercado National Park.

Overall, primary forest loss was highest outside protected areas and indigenous territories (averaging 0.33% across all four years).

 

 

 

Figure 5a. Primary forest loss rates in the Peruvian Amazon. Data: UMD.

Peruvian Amazon

Following Ecuador, Peru also had relatively low primary forest loss rates, particularly in protected areas (averaging 0.03% across all four years).

Primary forest loss in indigenous territories (that is, combined data for native communities and Territorial/Indigenous Reserves for groups in voluntary isolation) was surprisingly high, similar to that of areas outside protected areas across all four years. For example, in 2020, elevated primary forest loss was concentrated in several titled native communities in the regions of Amazonas, Ucayali, Huánuco, and Junín.

 

 

 

 

 

Figure 5b. Deforestation rates in the Peruvian Amazon. Data: MINAM/Geobosques.

As noted above, we conducted a deeper analysis for the Peruvian Amazon, using deforestation data produced by the Peruvian government and adding the additional category of long-term forestry lands (known as Permanent Production Forests, or BPP in Spanish) (see Annex map).

We also separated the data for indigenous territories into native communities and Territorial/Indigenous Reserves for groups in voluntary isolation, respectively.

These data also show that deforestation was lowest in the remote Territorial/Indigenous Reserves, closely followed by protected areas (0.01% vs 0.02% across all four years, respectively). Deforestation in titled native communities was 0.21% across all four years. Surprisingly, deforestation was higher in the forestry lands than areas outside protected areas and indigenous territories (0.30% vs 0.27% across all four years).

 

 

 

 

Annex – Peruvian Amazon

The following map shows added detail for Peru, most notably the inclusion of long-term forestry lands (known as Permanent Production Forests, or BPP in Spanish).

 

 

 

 

 

 

 

 

 

 

 

 

*Methodology

To estimate deforestation across all three categories, we used annual forest loss data (2017-20) from the University of Maryland (Global Land Analysis and Discovery GLAD laboratory) to have a consistent source across all four countries (Hansen et al 2013).

We obtained this data, which has a 30-meter spatial resolution, from the “Global Forest Change 2000–2020” data download page. It is also possible to visualize and interact with the data on the main Global Forest Change portal.

It is important to note that these data 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). For more details on this part of the methodology, see the Technical Blog from Global Forest Watch (Goldman and Weisse 2019).

Thus, we often use the term “primary forest loss” to describe the data.

Data presented as primary forest loss or deforestation rate is standardized per the total area covered of each respective category. 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 included four countries of the western Amazon and consists of a combination of the Amazon watershed limit (most notably in Bolivia) and Amazon biogeographic limit (most notably in Colombia) as defined by RAISG. See Base Map above for delineation of this hybrid Amazon limit, designed for maximum inclusion.

Additional data sources include: National and state/deprartment level protected areas: RUNAP 2020 (Colombia), SNAP 2017 & RAISG 2020 (Ecuador), SERNAP & ACEAA 2020 (Bolivia), and SERNANP 2020 (Peru).

Indigenous Territories: RAISG 2020 (Colombia, Ecuador, and Bolivia), and MINCU & ACCA 2020 (Peru). For Peru, this includes titled native communities and Indigenous/Territorial Reserves for indigenous groups in voluntary isolation.

For the additional analysis in Peru, we used deforestation data from MINAM/Geobosques (note this is actual deforestation and not primary forest loss) and BPP data from SERFOR. We also separated data from titled native communities and Territorial/Indigenous Reserves for groups in voluntary isolation.

Acknowledgements

We thank M. MacDowell (AAF) A. Folhadella (ACA), J. Beavers (ACA), S. Novoa (ACCA), and D. Larrea (ACEAA) for their helpful comments on this report.

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

 

Citation

Finer M, Mamani N, Silman M (2021) Protected Areas & Indigenous Territories Effective Against Deforestation in the Western Amazon. MAAP: 141.

MAAP #136: Amazon Deforestation 2020 (Final)

Base Map. Forest loss hotspots across the Amazon in 2020. Data: Hansen/UMD/Google/USGS/NASA, RAISG, MAAP. The letters A-E correspond to the zoom examples below.

*To download the report, click “Print” instead of “Download PDF” at the top of the page.

In January, we presented the first look at 2020 Amazon deforestation based on early warning alert data (MAAP #132).

Here, we update this analysis based on the newly released, and more definitive, annual data.*

The Base Map illustrates the final results and indicates the major hotspots of primary forest loss across the Amazon in 2020.

We highlight several key findings:

  • The Amazon lost nearly 2.3 million hectares (5.6 million acres) of primary forest loss in 2020 across the nine countries it spans.
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  • This represents a 17% increase in Amazon primary forest loss from the previous year (2019), and the third-highest annual total on record since 2000 (see graph below).
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  • The countries with the highest 2020 Amazon primary forest loss are 1) Brazil, 2) Bolivia, 3) Peru, 4) Colombia, 5) Venezuela, and 6) Ecuador.
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  • 65% occurred in Brazil (which surpassed 1.5 million hectares lost), followed by 10% in Bolivia, 8% in Peru, and 6% in Colombia (remaining countries all under 2%).
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  • For Bolivia, Ecuador, and Peru, 2020 recorded historical high Amazon primary forest loss. For Colombia, it was the second highest on record.

In all of the data graphs, orange indicates the 2020 primary forest loss and red indicates all years with higher totals than 2020.

For example, the Amazon lost nearly 2.3 million hectares in 2020 (orange), the third highest on record behind only 2016 and 2017 (red).

Note that the three highest years (2016, 2017, and 2020) had one major thing in common: uncontrolled forest fires in the Brazilian Amazon.

See below for country-specific graphs, key findings, and satellite images for the top four 2020 Amazon deforestation countries (Brazil, Bolivia, Peru, and Colombia).

 

 

 

Brazilian Amazon

2020 had the sixth-highest primary forest loss on record (1.5 million hectares) and a 13% increase from 2019.

Many of the 2020 hotspots occurred in the Brazilian Amazon, where massive deforestation stretched across nearly the entire southern region.

A common phenomenon observed in the satellite imagery through August was that rainforest areas were first deforested and then later burned, causing major fires due to the abundant recently-cut biomass (Image A). This was also the pattern observed in the high-profile 2019 Amazon fire season. Much of the deforestation in these areas appears to associated with expanding cattle pasture areas.

In September 2020 (and unlike 2019), there was a shift to actual Amazon forest fires (Image B). See MAAP #129 for more information on the link between deforestation and fire in 2020.

Note that the three highest years (2016, 2017, and 2020) had one major thing in common: uncontrolled forest fires in the Brazilian Amazon.

Image A. Deforestation in Brazilian Amazon (Amazonas state) of 2,540 hectares between January (left panel) and November (right panel) 2020. Data: Planet.
Image B. Forest fire in Brazilian Amazon (Para state) that burned 9,000 hectares between March (left panel) and October (right panel) 2020. Data: Planet.

Bolivian Amazon

2020 had the highest primary forest loss on record in the Bolivian Amazon, surpassing 240,000 hectares.

Indeed, the most intense hotspots across the entire Amazon ocurred in southeast Bolivia, where fires raged through the drier Amazon forests (known as the Chiquitano and Chaco ecosystems).

Image C shows the burning of a massive area (over 260,000 hectares) in the Chiquitano dry forests (Santa Cruz department).

 

 

 

 

Image C. Forest fire in Bolivian Amazon (Santa Cruz) that burned over 260,000 hectares between April (left panel) and November (right panel) 2020. Data: ESA.

Peruvian Amazon

2020 also had the highest primary forest loss on record in the Peruvian Amazon, surpassing 190,000 hectares.

This deforestation is concentrated in the central region. On the positive, the illegal gold mining that plagued the southern region has decreased thanks to effective government action (see MAAP #130).

Image D shows expanding deforestation (over 110 hectares), and logging road construction (3.6 km), in an indigenous territory south of Sierra del Divisor National Park in the central Peruvian Amazon (Ucayali region). The deforestation appears to be associated with an expanding small-scale agriculture or cattle pasture frontier.

 

 

Image D. Deforestation and logging road construction in Peruvian Amazon (Ucayali region) between March (left panel) and November (right panel) 2020. Data: Planet.

Colombian Amazon

2020 had the second-highest primary forest loss on record in the Colombian Amazon, nearly 140,000 hectares.

As described in previous reports (see MAAP #120), there is an “arc of deforestation” concentrated in the northwest Colombian Amazon. This arc impacts numerous protected areas (including national parks) and Indigenous Reserves.

For example, Image E shows the recent deforestation of over 500 hectares in Chiribiquete National Park. Similar deforestation in that sector of the park appears to be conversion to cattle pasture.

 

 

 

Image E. Deforestation in Colombian Amazon of over 500 hectares in Chiribiqete National Park between January (left panel) and December (right panel) 2020. Data: ESA, Planet.

*Notes and Methodology

To download the report, click “Print” instead of “Download PDF” at the top of the page.

The analysis was based on 30-meter resolution annual data produced by the University of Maryland (Hansen et al 2013), obtained from the “Global Forest Change 2000–2020” data download page. It is also possible to visualize and interact with the data on the main Global Forest Change portal.

Importantly, this data detects and classifies burned areas as forest loss. Nearly all Amazon fires are human-caused. Also, this data does include some forest loss caused by natural forces (landslides, wind storms, etc…).

Note that when comparing 2020 to early years, there are several methodological differences from the University of Maryland introduced to data after 2011. For more details, see “User Notes for Version 1.8 Update.”

It is worth noting that we found the early warning (GLAD) alerts to be a good (and often conservative) indicator of the final annual data.

Our geographic range includes nine countries and consists of a combintion of the Amazon watershed limit (most notably in Bolivia) and Amazon biogeographic limit (most notably in Colombia) as defined by RAISG. See Base Map above for delineation of this hybrid Amazon limit, designed for maximum inclusion. Inclusion of the watershed limit in Bolivia is a recent change incorporated to better include impact to the Amazon dry forests of the Chaco.

We applied a filter to calculate only primary forest loss. For our estimate of primary forest loss, we intersected 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).

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%.

 

Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (15 November): 850–53.

Acknowledgements

We thank E. Ortiz (AAF), M. Silman (WFU), M. Weisse (WRI/GFW) 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 (2020) Amazon Deforestation Hotspots 2020 (Final). MAAP: 136.

MAAP #131: Power of Free High-resolution Satellite Imagery from Norway Agreement

Image 1. Monthly Planet basemap for October 2020 across the Amazon, as seen on Global Forest Watch.

This report demonstrates the powerful application of freely available, high-resolution satellite imagery recently made possible thanks to an agreement between the Government of Norway and several satellite companies.*

This unprecedented agreement will bring commercial satellite technology, previously out of reach to many, to all working in tropical forest conservation around the world.

Here we show how MAAP (an initiative of Amazon Conservation) will use this information to enhance our real-time monitoring program and quickly share timely findings to partners in the field.

Specifically, we highlight the importance of the monthly basemaps (4.7-meter Planet imagery) available under the Norway agreement.* For example, Image 1 shows the stunning, nearly cloud-free October 2020 basemap across the Amazon.

l
Moreover, we show the power of this imagery visualized on Global Forest Watch, where it can be combined with early warning forest loss alerts.
p
Below, we highlight three examples where we combined this data to quickly detect and confirm deforestation in the Colombian, Ecuadorian, and Peruvian Amazon, respectively.

Colombian Amazon

First, we detected recent forest loss alerts (known as GLAD alerts), in the northwestern sector of Chiribiquete National Park. Image 2 is a screen shot of our monitoring search in Global Forest Watch (link here).

Second, we investigated the alerts with the freely available monthly Planet basemaps. Images 3-5 show the basemaps from October to December 2020. These images confirm that the area was covered in intact (likely primary) Amazon rainforest in October, and then experienced a major deforestation event (225 hectares) in November and December. Similar deforestation in the area appears to be conversion to cattle pasture. Note the crosshairs (+) represent the same point in all four images.

Image 2. Forest loss alerts in Chiribiquete National Park
Image 3. Monthly Planet basemap for October 2020 in Chiribiquete National Park.
Image 4. Monthly Planet basemap for November 2020 in Chiribiquete National Park.
Image 5. Monthly Planet basemap for December 2020 in Chiribiquete National Park.

Peruvian Amazon

Similarly, we detected recent forest loss alerts in an illegal gold mining area in the southern Peruvian Amazon known as Pariamanu (Image 6). Images 7 & 8 show the monthly basemaps confirming the expansion of illegal mining deforestation between October and December (see yellow arrows). Global Forest Watch link here.

Image 6. Forest loss alerts in illegal gold mining zone (Pariamanu).
Image 7. Monthly Planet basemap for October 2020 in Pariamanu.
Image 8. Monthly Planet basemap for October 2020 in Pariamanu.

Ecuadorian Amazon

Finally, we detected recent forest loss alerts of 100 hectares in an indigenous territory (Kichwa) surrounding an oil palm plantation in the Ecuadorian Amazon (Image 9). Images 10 & 11 show the monthly basemaps confirming large-scale deforestation between September and December, likely for the expansion of the plantation. Note the crosshairs (+) represents the same point in all three images. Global Forest Watch link here.
Image 9. Forest loss alerts in the Ecuadorian Amazon.
Image 10. Monthly Planet basemap for September 2020 in Ecuadorian Amazon.
Image 11. Monthly Planet basemap for December 2020 in Ecuadorian Amazon.

Summary

In summary, we show a major advance for free and real-time deforestation monitoring thanks to an agreement between the Government of Norway and satellite companies.* A key aspect of this agreement is making publically available (such as on Global Forest Watch) monthly basemaps created by the innovative satellite company Planet. Thus, users can now freely visualize recent forest loss alerts and then investigate them with high-resolution monthly basemaps on On Global Forest Watch. MAAP illustrated this process with three examples in the Colombian, Peruvian, Ecuadorian Amazon, respectively.

*Notes 

In September 2020, Norway’s Ministry of Climate and Environment entered into a contract with Kongsberg Satellite Services (KSAT) and its partners Planet and Airbus, to provide universal access to high-resolution satellite monitoring of the tropics in order to support efforts to stop the destruction of the world’s rainforests. This effort is led by Norway’s International Climate and Forest Initiative (NICFI). The basemaps are mosaics of the best cloud-free pixels each month. In addition to viewing the monthly basemaps on Global Forest Watch, users can sign up with Planet directly at this link: https://www.planet.com/nicfi/

Acknowledgements

We thank M. Cohen (ACA), M. Weisse (WRI/GFW), E. Ortiz (AAF) and G. Palacios for their helpful comments on this report.

This work was supported by NORAD (Norwegian Agency for Development Cooperation).

Citation

Finer M, Mamani N (2020) Power of Freely Available, High-resolution Satellite Imagery from Norway Agreement. MAAP: 131.

MAAP #122: Amazon Deforestation 2019

Table 1. Amazon 2019 primary forest loss for 2019 (red) compared to 2018 (orange). Data: Hansen/UMD/Google/USGS/NASA, MAAP.

Newly released data for 2019 reveals the loss of over 1.7 million hectares (4.3 million acres) of primary Amazon forest in our 5 country study area (Bolivia, Brazil, Colombia, Ecuador, and Peru).* That is twice the size of Yellowstone National Park.

Table 1 shows 2019 deforestation (red) in relation to 2018 (orange).

Primary forest loss in the Brazilian Amazon (1.29 million hectares) was over 3.5 times higher than the other four countries combined, with a slight increase in 2019 relative to 2018. Many of these areas were cleared in the first half of the year and then burned in August, generating international attention.

Primary forest loss rose sharply in the Bolivian Amazon (222,834 hectares), largely due to uncontrolled fires escaping into the dry forests of the southern Amazon.

Primary forest loss rose slightly in the Peruvian Amazon (161,625 hectares) despite a relatively successful crackdown on illegal gold mining, pointing to small-scale agriculture (and cattle) as the main driver.

On the positive side, primary forest loss decreased in the Colombian Amazon (91,400 hectares) following a major spike following the 2016 peace accords (between the government and FARC). It is worth noting, however, that we have now documented the loss of 444,000 hectares (over a million acres) of primary forest in the Colombian Amazon in the past four years since the peace agreement (see Annex).

*Two important points about the data. First, we use annual forest loss from the University of Maryland to have a consistent source across all five countries. Second, we applied a filter to only include loss of primary forest (see Methodology).

2019 Deforestation Hotspots Map

The Base Map below shows the major 2019 deforestation hotspots across the Amazon.

2019 deforestation hotspots across the Amazon. Data: Hansen/UMD/Google/USGS/NASA, MAAP.

Many of the major deforestation hotspots were in Brazil. Early in the year, in March, there were uncontrolled fires up north in the state of Roraima. Further south, along the Trans-Amazonian Highway, much of the deforestation occurred in the first half of the year, followed by the high profile fires starting in late July. Note that many of these fires were burning recently deforested areas, and were not uncontrolled forest fires (MAAP #113).

The Brazilian Amazon also experienced escalating gold mining deforestation in indigenous territories (MAAP #116).

Bolivia also had an intense 2019 fire season. Unlike Brazil, many were uncontrolled fires, particularly in the Beni grasslands and Chiquitano dry forests of the southern Bolivian Amazon (MAAP #108).

In Peru, although illegal gold mining deforestation decreased (MAAP #121), small-scale agriculture (including cattle) continues to be a major driver in the central Amazon (MAAP #112) and an emerging driver in the south.

In Colombia, there is an “arc of deforestation” in the northwestern Amazon. This arc includes four protected areas (Tinigua, Chiribiquete and Macarena National Parks, and Nukak National Reserve) and two Indigenous Reserves (Resguardos Indígenas Nukak-Maku and Llanos del Yari-Yaguara II) experiencing substantial deforestation (MAAP #120). One of the main deforestation drivers in the region is conversion to pasture for land grabbing or cattle ranching.

Annex – Colombia peace accord trend

Annex 1. Deforestation of primary forest in the Colombian Amazon, 2015-20. Data: Hansen/UMD/Google/USGS/NASA, UMD/GLAD. *Until May 2020

Methodology

The baseline forest loss data presented in this report were generated by the Global Land Analysis and Discovery (GLAD) laboratory at the University of Maryland (Hansen et al 2013) and presented by Global Forest Watch. Our study area is strictly what is highlighted in the Base Map.

For our estimate of primary forest loss, we used the annual “forest cover loss” data with density >30% of the “tree cover” from the year 2001. Then we intersected 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).

For boundaries, we used the biogeographical limit (as defined by RAISG) for all countries except Bolivia, where we used the Amazon watershed limit (see Base Map).

All data were processed under the geographical coordinate system WGS 1984. To calculate the areas in metric units, the projection was: Peru and Ecuador UTM 18 South, Bolivia UTM 20 South, Colombia MAGNA-Bogotá, and Brazil Eckert IV.

Lastly, 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%.

References

Goldman L, Weisse M (2019) Explicación de la Actualización de Datos de 2018 de Global Forest Watch. https://blog.globalforestwatch.org/data-and-research/blog-tecnico-explicacion-de-la-actualizacion-de-datos-de-2018-de-global-forest-watch

Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (15 November): 850–53. Data available on-line from: http://earthenginepartners.appspot.com/science-2013-global-forest.

Turubanova S., Potapov P., Tyukavina, A., and Hansen M. (2018) Ongoing primary forest loss in Brazil, Democratic Republic of the Congo, and Indonesia. Environmental Research Letters  https://doi.org/10.1088/1748-9326/aacd1c 

Acknowledgements

We thank G. Palacios for helpful comments to earlier versions of this report.

This work was supported by the following major funders: Norwegian Agency for Development Cooperation (NORAD), Gordon and Betty Moore Foundation, International Conservation Fund of Canada (ICFC), Metabolic Studio, Erol Foundation, MacArthur Foundation, and Global Forest Watch Small Grants Fund (WRI).

Citation

Finer M, Mamani N (2020) 2019 Amazon Deforestation. MAAP: 122.