MAAP #132: Amazon Deforestation Hotspots 2020

We present a first look at the major hotspots of primary forest loss across the Amazon in 2020 (see Base Map).*

Base Map. Forest loss hotspots across the Amazon in 2020. Data: UMD/GLAD, RAISG, MAAP. The letters A-G correspond to the zoom examples below.
Base Map. Forest loss hotspots across the Amazon in 2020. Data: UMD/GLAD, RAISG, MAAP. The letters A-G correspond to the zoom examples below.

There are several major headlines:

  • We estimate over 2 million hectares (5 million acres) of primary forest loss across the nine countries of the Amazon in 2020.*
  • The countries with the highest 2020 primary forest loss are 1) Brazil, 2) Bolivia, 3) Peru, 4) Colombia, 5) Venezuela, and 6) Ecuador.
  • The majority of the hotspots occurred in the Brazilian Amazon, where massive deforestation stretched across nearly the entire southern region. Many of these areas were cleared in the first half of the year and then burned in July and August. In September, there was a shift to actual forest fires (see MAAP #129).
  • Several of the most intense hotspots were in the Bolivian Amazon, where fires raged through the dry forests (known as the Chiquitano) in the southeast region.
  • There continues to be an arc of deforestation in the northwestern Colombian Amazon, impacting numerous protected areas.
  • In the Peruvian Amazon, deforestation continues to impact 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).

Below, we show a striking series of high-resolution satellite images that illustrate some of the major deforestation events across the Amazon in 2020 (indicated A-G on the Base Map).

 

 

Widespread Deforestation in the Brazilian Amazon

Zooms A-C show examples of a troublingly common phenomenon in the Brazilian Amazon: large-scale deforestation events in the first half of the year that are later burned in July and August, causing major fires due to the abundant recently-cut biomass. Much of the deforestation in these areas appears to associated with clearing rainforests for cattle pastures. The three examples below show the striking loss of over 21,000 hectares of primary forest in 2020.

Zoom A. Deforestation in the Brazilian Amazon (Amazonas state) of 3,400 hectares between April (left panel) and November (right panel) 2020. Data: ESA, Planet.
Zoom A. Deforestation in the Brazilian Amazon (Amazonas state) of 3,400 hectares between April (left panel) and November (right panel) 2020. Data: ESA, Planet.

 

Zoom B. Deforestation in Brazilian Amazon (Amazonas state) of 2,540 hectares between January (left panel) and November (right panel) 2020. Data: Planet.
Zoom B. Deforestation in Brazilian Amazon (Amazonas state) of 2,540 hectares between January (left panel) and November (right panel) 2020. Data: Planet.

 

Zoom C. Deforestation in Brazilian Amazon (Para state) of 15,250 hectares between January (left panel) and October (right panel) 2020. Data: Planet.
Zoom C. Deforestation in Brazilian Amazon (Para state) of 15,250 hectares between January (left panel) and October (right panel) 2020. Data: Planet.

 

 

Forest Fires in the Brazilian Amazon

In September, there was a shift to actual forest fires in the Brazilian Amazon (see MAAP #129). Zoom D and E show examples of these major forest fires, which burned over 50,000 hectares in the states of Pará and Mato Grosso. Note both fires impacted indigenous territories (Kayapo and Xingu, respectively).

Zoom D. Forest fire in Brazilian Amazon (Para state) that burned 9,000 hectares between March (left panel) and October (right panel) 2020. Data: Planet.
Zoom D. Forest fire in Brazilian Amazon (Para state) that burned 9,000 hectares between March (left panel) and October (right panel) 2020. Data: Planet.
Zoom E. Forest fire in Brazilian Amazon (Mato Grosso state) that burned over 44,000 hectares between May (left panel) and October (right panel) 2020. Data: Planet.
Zoom E. Forest fire in Brazilian Amazon (Mato Grosso state) that burned over 44,000 hectares between May (left panel) and October (right panel) 2020. Data: Planet.

Forest Fires in the Bolivian Amazon

The Bolivian Amazon also experienced another intense fire season in 2020. Zoom F shows the burning of a massive area (over 260,000 hectares) in the Chiquitano dry forests (Santa Cruz department).

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

Arc of Deforestation in the Colombian Amazon

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, Zoom G 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.

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

Deforestation in the central Peruvian Amazon

Finally, Zoom H 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.

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

*Notes and Methodology

The analysis was based on early warning forest loss alerts known as GLAD alerts (30-meter resolution) produced by the University of Maryland and also presented by Global Forest Watch. It is critical to highlight that this data represents a preliminary estimate and more definitive data will come later in the year. For example, our estimate does include some forest loss caused by natural forces. Note that this data detects and classifies burned areas as forest loss. Our estimate includes both confirmed (1,355,671 million hectares) and unconfirmed (751,533 ha) alerts.

Our geographic range is the biogeographic boundary of the Amazon as defined by RAISG (see Base Map above). This range includes nine countries.

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%.

Acknowledgements

We thank E. Ortiz (AAF), M.E. Gutierrez (ACCA), and S. Novoa for their helpful comments on this report.

Citation

Finer M, Mamani N (2020) Amazon Deforestation Hotspots 2020. MAAP: 132.

 

MAAP #131: Power Of Free High-resolution Satellite Imagery From Norway Agreement

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.

Image 1. Monthly Planet basemap for October 2020 across the Amazon, as seen on Global Forest Watch.
Image 1. Monthly Planet basemap for October 2020 across the Amazon, as seen on Global Forest Watch.
Moreover, we show the power of this imagery visualized on Global Forest Watch, where it can be combined with early warning forest loss alerts.
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 2. Forest loss alerts in Chiribiquete National Park

 

Image 3. Monthly Planet basemap for October 2020 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 4. Monthly Planet basemap for November 2020 in Chiribiquete National Park.

 

Image 5. Monthly Planet basemap for December 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 6. Forest loss alerts in illegal gold mining zone (Pariamanu).

 

Image 7. Monthly Planet basemap for October 2020 in Pariamanu.
Image 7. Monthly Planet basemap for October 2020 in Pariamanu.

 

Image 8. 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 9. Forest loss alerts in the Ecuadorian Amazon.
Image 10. Monthly Planet basemap for September 2020 in Ecuadorian Amazon.
Image 10. Monthly Planet basemap for September 2020 in Ecuadorian Amazon.

 

Image 11. Monthly Planet basemap for December 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.

Citation

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

MAAP #122: Amazon Deforestation 2019

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).

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

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.
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

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

MAAP #117: New Oil Road Deeper Into Yasuni National Park (Ecuador), Toward Uncontacted Indigenous Reserves

Yasuní National Park, located in the heart of the Ecuadorian Amazon, is one of the most biodiverse spots in the world and overlaps ancestral Waorani territory. In the recent MAAP #114, we showed the construction of four new oil drilling platforms (and access road) in the controversial ITT oil block, located in the heart of Yasuní.

Here, we show that beginning in mid-March 2020, we detected the construction of a new access road heading further south from the last platform (Image 1). As of early May, this road construction was 4.7 km through primary forest.

Updated: June 30 (4.7 km); June 14 (3.7 km); May 17 (2.2 km).

Image 1. Construction of a new 4.7 km oil access road deeper into Yasuni National Park between March (left panel) and June (right panel) 2020.

MAAP Synthesis: 2019 Amazon Deforestation Trends and Hotspots

MAAP, an initiative of Amazon Conservation, specializes in satellite-based, real-time deforestation monitoring of the Amazon. Our geographic focus covers five countries: Bolivia, Brazil, Colombia, Ecuador, and Peru (see Base Map).

We found that, since 2001, this vast area lost 65.8 million acres (26.6 million hectares) of primary forest, an area equivalent to the size of the United Kingdom (or the U.S. state of Colorado).

Base Map. Amazon Deforestation, 2001-2019. Data: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, MAAP
Base Map. Amazon Deforestation, 2001-2019. Data: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, MAAP. Click to see image in high resolution.

In 2019, we published 18 high-impact reports on the most urgent cases of deforestation. 2019 highlights include:

  • Fires in the Brazilian Amazon actually burned freshly deforested areas (MAAP #113);
  • Effective illegal gold mining crackdown in the Peruvian Amazon as a result of the government’s Operation Mercury (MAAP #104);
  • Illegal invasion of protected areas in the Colombian Amazon (MAAP #106);
  • Construction of oil-drilling platforms in the mega-diverse Yasuni National Park of the Ecuadorian Amazon (MAAP #114).

Here, in our annual Synthesis Report, we go beyond these emblematic cases and look at the bigger picture for 2019, describing the most important deforestation trends and hotspots across the Amazon.

*Note: to download a PDF, click the “Print” button below the title.


Synthesis Key Findings

Trends: We present a GIF comparing deforestation trends for each country since 2001. The preliminary 2019 estimates have several important headlines:
  • Possible major deforestation decrease in the Colombian Amazon following a dramatic increase over the previous three years;
  • Likely major deforestation increase in the Bolivian Amazon due to forest fires;
  • Downward deforestation trend continues in the Peruvian Amazon, but still historically high;
  • Deforestation of 2.4 million acres in the Brazilian Amazon, but the trend depends on the data source.
Hotspots: We present a Base Map highlighting the major deforestation hotspots in 2019. Results emphasize the deforestation and fires in the Brazilian Amazon, along with several key areas in Colombia, Peru, and Bolivia.

Deforestation Trends 2001-2019

The following GIF shows deforestation trends for each country between 2001 and 2019 (see descriptive notes below). Click here for static versions of each graph.

Three important points about the data: First, as a baseline, we use annual forest loss from the University of Maryland to have a consistent source across all five countries (thus it may differ from official national data). Second, we applied a filter to only include loss of primary forest (see Methodology). Third, the 2019 data represents a preliminary estimate based on early warning alerts.

maaproject.org-maap-synthesis-2019-amazon-deforestation-trends-and-hotspots

  1. Deforestation in the Ecuadorian Amazon is relatively low, reaching a maximum of 18,800 hectares (46,500 acres) in 2017. The estimate for 2019 is 11,400 hectares (28,000 acres).
    .
  2. In the Bolivian Amazon, deforestation decreased in 2018 to 58,000 hectares (143,000 acres) after a peak in 2016 of 122,000 hectares (302,000 acres). However, with the recent widespread forest fires, deforestation increased again in 2019, to 135,400 hectares (334,465 acres).
    .
  3. The Colombian Amazon experienced a deforestation boom starting in 2016 (coinciding with the FARC peace accords), reaching an historical high of 153,800 hectares (380,000 acres) in 2018. However, the deforestation estimate for 2019 is back to pre-boom levels at 53,800 hectares (133,000 acres).
    .
  4. Deforestation in the Peruvian Amazon declined in 2018 (compared to 2017) to 140,000 hectares (346,325 acres), but remained relatively high compared to historical data. The official deforestation data from the Peruvian government for 2018 is slightly higher at 154,700 hectares (382,272 acres), but also represents an important reduction compared to 2017. The deforestation estimate for 2019 indicates the continued downward trend to 134,600 hectares (332,670 acres).
    .
  5. Deforestation in the Brazilian Amazon is on another level compared to the other four countries. The 2019 deforestation estimate of 985,000 hectares (2.4 million acres) is consistent with the official data of the Brazilian government. The trend, however, is quite different; we show a decrease in deforestation compared to the previous three years, but the official data indicates an increase. To better understand the differences between data sources (including spatial resolution, inclusion of burned areas, and timeframe), consult this blog by Global Forest Watch.

Deforestation Hotspots 2019

Base Map shows the most intense deforestation hotspots during 2019.

maap-synthesis-2019-amazon-deforestation-trends-and-hotspots-BaseMap-Letters
Base Map. Amazon Deforestation, 2001-2019. Data: UMD/GLAD, Hansen/UMD/Google/USGS/NASA, MAAP. Click to see image in high resolution.

Many of the major deforestation hotspots were in Brazil. The letters A indicate areas deforested between March and July, and then burned starting in August, covering over 735,000 acres in the states of Rondônia, Amazonas, Mato Grosso, Acre, and Pará (MAAP #113). They also indicate areas where fire escaped into the surrounding primary forest, impacting an additional 395,000 acres. There is a concentration of these hotspots along the Trans-Amazonian Highway. The letter B indicates uncontrolled forest fires earlier in the year (March) in the state of Roraima (MAAP #109).

Bolivia also had an intense 2019 fire season. Letter C indicates the area where fires in Amazonian savanna ecosystems escaped to the surrounding forests.

In Colombia, the letter D indicates an area of high deforestation surrounding and within four protected areas: Tinigua, Chiribiquete, and Macarena National Parks, and the Nukak National Reserve (MAAP #106).

In Peru, there are several key areas to highlight. Letter E indicates a new Mennonite colony that has caused the deforestation of 2,500 acres in 2019, near the town of Tierra Blanca in the Loreto region (MAAP #112). Letter F indicates an area of high concentration of small-scale deforestation in the central Amazon (Ucayali and Huánuco regions), with cattle ranching as one of the main causes (MAAP #37). Letter G indicates an area of high concentration of deforestation along the Ene River (Junín and Ayacucho regions). In the south (Madre de Dios region), letter H indicates expanding agricultural activity around the town of Iberia (MAAP #98) and letter I indicates deforestation caused by a combination of gold mining and agricultural activity.


 

Methodology

As noted above, there are three important considerations about the data in our analysis: First, as a baseline, we use annual forest loss from the University of Maryland to have a consistent source across all five countries. Thus, the values may differ from official national data. Second, we applied a filter to only include loss of primary forest in order to better approximate the official methodology and data. Third, the 2019 data represents a preliminary estimate based on early warning alerts.

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.

Specifically, for our estimate of forest cover loss, we multiplied the annual “forest cover loss” data by the density percentage of the “tree cover” from the year 2001 (values >30%).

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).

All data were processed under the geographical coordinate system WGS 1984. To calculate the areas in metric units the UTM (Universal Transversal Mercator) projection was used: Peru and Ecuador 18 South, Colombia 18 North, Western Brazil 19 South and Bolivia 20 South.

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, 9.88 acres)
Everything else was left to the default setting.

For the Base Map, we used the following concentration percentages: Medium: 10%-20%; High: 21%-35%; Very High: >35%.


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.

Planet Team (2017). Planet Application Program Interface: In Space for Life on Earth. San Francisco, CA. https://api.planet.com

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

Agradecemos a S. Novoa (ACCA), R. Botero (FCDS), A. Condor (ACCA) y G. Palacios por sus útiles comentarios a este reporte.

Acknowledgements

We thank S. Novoa (ACCA), R. Botero (FCDS), A. Condor (ACCA), A. Folhadella (Amazon Conservation), M. Cohen, and G. Palacios for helpful comments to earlier versions of this report.

This work was supported by the following major funders: NASA/USAID (SERVIR), 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) MAAP Synthesis: 2019 Amazon Deforestation Trends and Hotspots. MAAP Synthesis #4.

MAAP #114: Oil Drilling Pushes Deeper into Yasuni National Park

Base Map. Oil Exploitation in Yasuni National Park.

Yasuni National Park, located in the heart of the Ecuadorian Amazon, is one of the most biodiverse places in the world and forms part of the ancestral territory of the Waorani (see Base Map).

Under the ground of this vast area, however, are large oil fields.

In July 2019, the Waorani won an important legal victory to prevent oil activity in the western part of their territory (Block 22).

However, here we show the construction of new oil drilling platforms in the controversial ITT Block, in the northeast part of Yasuni National Park.

We calculated the deforestation of 57.3 hectares (141.6 acres) for drilling platforms and access roads within ITT and the adjacent Block 31.

In addition, incorporating edge effects caused by the deforestation, we estimate the impacted area is actually 655 hectares (1,619 acres), exceeding the limit of 300 hectares (741 acres) established in the public referendum of 2018.*

MAAP #102: Saving The Ecuadorian Chocó

Chocó endemic, Long-wattled Umbrellabird. ©Stephen Davies
Chocó endemic, Long-wattled Umbrellabird. ©Stephen Davies

Chocó endemic, Long-wattled Umbrellabird. ©Stephen Davies

The Ecuadorian Chocó, located on the other (western) side of the Andes Mountains from its Amazonian neighbor, is renowned for its high levels of endemic species (those that live nowhere else on Earth).

It is part of the “Tumbes-Chocó-Magdalena” Biodiversity Hotspot, home to numerous endemic plants, mammals, and birds (1,2), such as the Long-wattled Umbrellabird.

It is also one of the most threatened tropical forests in the world (1).

Here, we conduct a deforestation analysis for the northern Ecuadorian Chocó (see Base Map below) to better understand the current conservation scenario. Importantly, we compare the original forest extent (left panel) to the actual forest cover (right panel).

We document the loss of over 60% (1.8 million hectares) of low, mid, and upper elevation forest (compare the three tones of green between panels).

See our other Key Results below.

 

Base Map

Base Map. Ecuadorian Chocó, original forest extent (left panel) vs. actual forest cover (right panel). Data- MAE, Hansen:UMD:Google:USGS:NASA
Base Map. Ecuadorian Chocó, original forest extent (left panel) vs. actual forest cover (right panel). Data- MAE, Hansen:UMD:Google:USGS:NASA

 

Key Results

Our key results include:*

 

Key Results, Ecuadorian Chocó. Data- MAAP, MAE, Hansen:UMD:Google:USGS:NASA
Key Results, Ecuadorian Chocó. Data- MAAP, MAE, Hansen:UMD:Google:USGS:NASA
  • 61% forest loss (1.8 million hectares) across all three elevations.
    • 68% loss (1.2 million ha) of lowland rainforest,
    • 50% loss (611,200 ha) of mid and upper elevation forests.
      .
  • 20% of the forest loss (365,000 ha) occurred after 2000.
    • 4,650 ha lost during most recent 2017-18 period (mostly in lowlands).
  • 39% total forest remaining (1.17 million ha) across all three elevations.
    • Just 32% (569,000 ha) lowland rainforest remaining.
  • 99% of Cotacachi-Cayapas Ecological Reserve remaining.
  • 61% of Mache-Chindul Ecological Reserve remaining.

*Forest loss data corresponds to the study area indicated in the Base Map. Data sources: pre-2017 from Ecuadorian Environment Ministry; 2017-18 from University of Maryland (Hansen 2013). Elevation definitions: Lowland forest <400 meters (dark green), mid-elevation forest 400-1000 m (olive green), and upper elevation forest >1000 m (bright green).

 

High Resolution Zooms

In the Base Map, we indicate two areas (insets A and B) where we zoom in with high-resolution satellite imagery to see what recent deforestation looks like in the region.

Zoom A shows the deforestation of 380 hectares directly to the north of an oil palm plantation, possibly for an expansion.

Zoom B shows the deforestation of 50 hectares with the Chachi Indigenous Reserve.

Zoom A. Data- Planet, ESA, MAAP
Zoom A. Data- Planet, ESA, MAAP
Zoom B. Data- Planet, MAAP
Zoom B. Data- Planet, MAAP

 

Conservation Opportunity

Efforts are underway to protect a critical stretch of low to mid elevation Chocó forest to the west of Cotacachi-Cayapas Ecological Reserve.

Chocó Conservation Opportunity. Data- Jocotoco Foundation, MAE, Hansen:UMD:Google:USGS:NASA.
Chocó Conservation Opportunity. Data- Jocotoco Foundation, MAE, Hansen:UMD:Google:USGS:NASA.

It involves the unique opportunity to acquire over 22,000 hectares of forest that would help safeguard connectivity between public and private conservation and indigenous areas. Connecting these areas provides the only opportunity to protect the entire altitudinal gradient from 100-4900 m on the western slope of the tropical Andes. It will also establish an effective buffer zone for governmental reserves and reduce the socio-economic vulnerability of local communities.

To support this effort, please contact the Jocotoco Foundation (Martin.Schaefer@jocotoco.org) or the International Conservation Fund of Canada (carlos@ICFCanada.org).

 

References

1) Critical Ecosystem Partnership Fund (2005) Ecosystem Profile: Tumbes-Chocó-Magdalena. Link: https://www.cepf.net/our-work/biodiversity-hotspots/tumbes-choco-magdalena

2) Mittermeier RA et al (2011) Global Biodiversity Conservation: The Critical Role of Hotspots. Biodiversity Hotspots, 3-22.

 

Acknowledgements

We thank M. Schaefer (Jocotoco), C. Garcia (ICFC), D. Pogliani (ACCA), S. Novoa (ACCA), R. Catpo (ACCA), H. Balbuena (ACCA) y T. Souto (ACA) for helpful comments on earlier versions of this report.

 

Citation

Finer M, Mamani N (2019) Saving the Ecuadorian Chocó. MAAP: 102.

MAAP #100: Western Amazon – Deforestation Hotspots 2018 (A Regional Perspective)

For the 100th MAAP report, we present our first large-scale western Amazon analysis: Colombia, Peru, Ecuador, Bolivia, and western Brazil (see Base Map).

We use the new 2018 data for forest cover loss, generated by the  University of Maryland (Hansen et al 2013) and presented by Global Forest Watch.

These data indicate 2.5 million acres of forest cover loss in the western Amazon in 2018.*

We conducted an additional analysis that indicates, of this total, 1.9 million acres were primary forest.*

Base Map. Deforestation Hotspots in the western Amazon. Data: Hansen/UMD/Google/USGS/NASA, GFW, SERNANP, SNAP, SINAP, SERNAP, RAISG
Base Map. Deforestation Hotspots in the western Amazon. Data: Hansen/UMD/Google/USGS/NASA, GFW, SERNANP, SNAP, SINAP, SERNAP, RAISG

To identify deforestation hotspots consistently across this vast landscape, we conducted a kernel density analysis (see Methodology).

The Base Map shows the hotspots in yellow, orange and red, indicating areas with medium, high, and very high forest loss concentrations, respectively.

Next, we focus on five zones of interest (Zooms A-E) in Colombia, Brazil, Bolivia, and Peru. For all images, please click to enlarge.

*Forest Cover Loss: 5 acres per minute. Almost half (49%) occurred in Brazil, followed by Peru (20%), Colombia (20%), Bolivia (8%), and Ecuador (3%). see Annex.

**Primary Forest Loss: 3.5 acres per minute. Over half (53%) occurred in Brazil, followed by Peru (20%), Colombia (18%), Bolivia (7%), and Ecuador (2%). see Annex.

 


Colombia

The largest concentration of 2018 forest loss is in the northeast Colombian Amazon (494,000 acres). Out of this total, 11% (56,800 acres) occurred in national parks. National experts indicate that land grabbing has emerged as a leading direct driver of deforestation (Arenas 2018). See MAAP #97 for more information.

Zoom A shows the forest loss expanding towards western Chiribiquete National Park, including distinct deforestation in this protected area during 2018.

Zoom B shows the extensive 2018 deforestation (30,000 acres) within Tinigua National Park. A recent news report indicates that cattle ranching is one of the factors related to this deforestation.

Zoom A. Colombia-Chiribiquete. Data: Hansen/UMD/Google/USGS/NASA, SINAP, Planet, ESA
Zoom A. Colombia-Chiribiquete. Data: Hansen/UMD/Google/USGS/NASA, SINAP, Planet, ESA
Zoom B. Colombia – Tinigua. Data: Hansen/UMD/Google/USGS/NASA, SINAP, Planet, ESA
Zoom B. Colombia – Tinigua. Data: Hansen/UMD/Google/USGS/NASA, SINAP, Planet, ESA

 


Brazil (border with Bolivia)

Another important result is the contrast between northern Bolivia (Pando department) and adjacent side Brazil (states of Acre, Amazonas, and Rondônia). Zoom C shows several deforestation hotspots on the Brazilian side, while the Bolivian side is much more intact.

Zoom C. Brazil, Bolivia border. Data: Hansen/UMD/Google/USGS/NASA, ESA, RAISG
Zoom C. Brazil, Bolivia border. Data: Hansen/UMD/Google/USGS/NASA, ESA, RAISG

 


Bolivia

In Bolivia, the major forest loss hotspots are further south. Zoom D shows the recent deforestation (5,000 acres in 2018) due to agricultural activity associated with one of the first major Mennonite settlements in Beni department (Kopp 2015). The other Mennonite settlements are located further south.

Zoom D. Bolivia, Black River Mennonite settlement. Data: Hansen/UMD/Google/USGS/NASA, SERNAP, Planet
Zoom D. Bolivia, Black River Mennonite settlement. Data: Hansen/UMD/Google/USGS/NASA, SERNAP, Planet

Peru

The Hansen data indicates over 200,000 acres of forest loss during 2018 in the Peruvian Amazon. One of the most important deforestation drivers, especially in southern Peru, is gold mining. We estimate 23,000 acres of gold mining deforestation during 2018 in the southern Peruvian Amazon (see MAAP #96).

Zoom E shows the most emblematic case of gold mining deforestation: the area known as La Pampa.

It is important to emphasize, however, that in February 2019 the Peruvian government launched “Operation Mercury 2019” (Operación Mercurio 2019), a multi-sectoral and comprehensive mega-operation aimed at eradicating illegal mining and associated crime in La Pampa, as well as promote development in the region.

Zoom D. Peru – La Pampa. Data: Hansen/UMD/Google/USGS/NASA, SERNAP, Planet
Zoom D. Peru – La Pampa. Data: Hansen/UMD/Google/USGS/NASA, SERNAP, Planet

Annex

Annex. Forest cover and primary forest loss in the western Amazon.  Data: Hansen/UMD/Google/USGS/NASA, Global Forest Watch.
Annex. Forest cover and primary forest loss in the western Amazon.  Data: Hansen/UMD/Google/USGS/NASA, Global Forest Watch.

Methods

The 2018 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 presented in the Base Map: the areas within the Amazonian biogeographic boundary of the western Amazon.

Specifically, for our estimate of forest cover loss, we multiplied the annual “forest cover loss” data by the density percentage of the “tree cover” from the year 2000 (values >30%).

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).

All data were processed under the geographical coordinate system WGS 1984. To calculate the areas in metric units the UTM (Universal Transversal Mercator) projection was used: Peru and Ecuador 18 South, Colombia 18 North, Western Brazil 19 South and Bolivia 20 South.

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 / 9.88 acres)

Everything else was left to the default setting.

For the Base Map, we used the following concentration percentages: Medium: 10%-20%; High: 21%-35%; Very High: >35%.


References

Arenas M (2018) Acaparamiento de tierras: la herencia que recibe el nuevo gobierno de Colombia. Mongabay, 2 AGOSTO 2018. https://es.mongabay.com/2018/08/acaparamiento-de-tierras-colombia-estrategias-gobierno/

Goldman L, Weisse M (2019) Technical Blog: Global Forest Watch’s 2018 Data Update Explained. 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.

Kopp Ad (2015) Las colonias menonitas en Bolivia. Tierra. http://www.ftierra.org/index.php/publicacion/libro/147-las-colonias-menonitas-en-bolivia

Planet Team (2017). Planet Application Program Interface: In Space for Life on Earth. San Francisco, CA. https://api.planet.com

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 M. Terán (ACEAA), M. Weisse (GFW/WRI), A. Thieme (UMD), R. Catpo (ACCA) and A. Cóndor (ACCA) for helpful comments to this report.


Citation

Finer M, Mamani N (2019) Western Amazon – Deforestation Hotspots 2018 (a regional perspective). MAAP: 100.

MAAP Synthesis #3: Deforestation in the Andean Amazon (Trends, Hotspots, Drivers)

Download a PDF of this Article

Satellite image of the deforestation produced by United Cacao. Source: DigitalGlobe (Nextview)
Satellite image of the deforestation produced by United Cacao. Source: DigitalGlobe (Nextview)

MAAP, an initiative of the organization Amazon Conservation, uses cutting-edge satellite technology to monitor deforestation in near real-time in the megadiverse Andean Amazon (Peru, Colombia, Ecuador, and Bolivia).

The monitoring is based on 5 satellite systems: Landsat (NASA/USGS), Sentinel (European Space Agency), PeruSAT-1, and the companies Planet and DigitalGlobe. For more information about our innovative methodology, see this recent paper in Science Magazine.

Launched in 2015, MAAP has published nearly 100 high-impact reports on the major Amazonian deforestation issues of the day.

Here, we present our third annual synthesis report with the objective to concisely describe the bigger picture: Deforestation trends, patterns, hotspots and drivers across the Andean Amazon.

Our principal findings include:

Trends: Deforestation across the Andean Amazon has reached 4.2 million hectares (10.4 million acres) since 2001. Annual deforestation has been increasing in recent years, with a peak in 2017 (426,000 hectares / 1,052,668 acres). Peru has had the highest annual deforestation, followed by surging Colombia (in fact, Colombia surpassed Peru in 2017). The vast majority of the deforestation events are small-scale (‹5 hectares / 12.35).

Hotspots: We present the first regional-scale deforestation hotspots map for the Andean Amazon, allowing for spatial comparisons between Peru, Colombia, and Ecuador.  We discuss six of the most important hotspots.

Drivers: We present MAAP Interactive, a dynamic map with detailed information on the major deforestation drivers: gold mining, agriculture (oil palm and cacao), cattle ranching, logging, and dams. Agriculture and ranching cause the most widespread impact across the region, while gold mining is most intense southern Peru.

Climate Change. We estimated the loss of 59 million metric tons of carbon in the Peruvian Amazon during the last five years (2013-17) due to forest loss. In contrast, we also show that protected areas and indigenous lands have safeguarded 3.17 billion metric tons of carbon.


I. Deforestation Trends

Image 1 shows forest loss trends in the Andean Amazon between 2001 and 2017.*  The left graph shows data by country, while the right graph shows data by forest loss event size.

Image 1. Annual forest loss by country and size. Data: Hansen/UMD/Google/USGS/NASA, UMD/GLAD, Global Forest Watch, MINAM/PNCB, RAISG.
Image 1. Annual forest loss by country and size. Data: Hansen/UMD/Google/USGS/NASA, UMD/GLAD, Global Forest Watch, MINAM/PNCB, RAISG.

Trends by Country

Over the past 17 years (2001-2017), deforestation has surpassed 4.2 million hectares (10.4 million acres) in the Andean Amazon (see green line). Of this total, 50% is Peru (2.1 million hectares/5.2 million acres), 41% Colombia (1.7 million hectares/4.27 million acres), and 9% Ecuador (887,000 acres/359,000 hectares). This analysis did not include Bolivia.

Since 2007, there has been an increasing deforestation trend, peaking during the past two years (2016-17). In fact, 2017 has the highest annual forest loss on record with 426,000 hectares (over one million acres), more than double the total forest loss in 2006.

Peru had the highest average annual Amazonian deforestation between 2009 and 2016. The past four years have the highest annual deforestation totals on record in the country, with peaks in 2014 (177,566 hectares/439,000 acres) and 2016 (164,662 hectares/406,888 acres). According to new data from the Peruvian Environment Ministry, there was an important decline in 2017 (155,914 hectares/385,272 acres), but it is still the fourth highest annual total on record.

There has been a surge of deforestation in Colombia during the past two years. Note that in 2017, Colombia surpassed Peru with a record high of 214,700 hectares (530,400 acres) deforested.

Deforestation is also increasing in Ecuador, with highs of 32,000 hectares (79,000 acres) in 2016 and 55,500 hectares (137,000) acres in 2017.

For context, Brazil has had an average deforestation loss rate of 639,403 hectares (1.58 million acres) over the past several years.

* Data: Colombia & Ecuador: Hansen/UMD/Google/USGS/NASA; Peru: MINAM/PNCB, UMD/GLAD. While this information includes natural forest loss events, it serves as our best estimate of deforestation resulting from anthropogenic causes.  It is estimated that the non-anthropic loss comprises approximately 3.5% of the total loss. Note that the analysis does not include Bolivia.


Trends by Size

The pattern related to the size of deforestation events in the Andean Amazon remained relatively consistent over the last 17 years. Most noteworthy: the vast majority (74%) of the deforestation events are small-scale (‹5 hectares). Only 2% of deforestation events are large-scale (>100 hectares). The remaining 24% are medium-scale (5-100 hectares).

These results are important for conservation efforts.  Addressing this complex situation – in which most of the deforestation events are small-scale – requires significantly more attention and resources.  In addition, while large-scale deforestation (usually associated with agro-industrial practices) is not that common, it nonetheless represents a serious latent threat, due to the fact that only a small number of agro-industrial projects (for example, oil palm) are able to rapidly destroy thousands of acres of primary forest.


II. Deforestation Hotspots

Image 2: Deforestation hotspots 2015-2017. Data: Hansen/UMD/Google/USGS/NASA.
Image 2: Deforestation hotspots 2015-2017. Data: Hansen/UMD/Google/USGS/NASA.

We present the first regional-scale deforestation hotspots map across the Andean Amazon (Colombia, Ecuador, Peru).  Image 2 shows the results for the past three, 2015 – 2017.

The most critical zones (“high” deforestation density) are indicated in red. They include:

A. Central Peruvian Amazon: Over the last 10 years, this zone, located in the Ucayali and Huánuco regions, has consistently had one of the largest concentrations of deforestation in Peru (Inset A).  Its principal drivers include oil palm and cattle grazing.

B. Southern Peruvian Amazon: This zone, located in the Madre de Dios region, is impacted by gold mining (Inset B1), and increasingly by small- and medium-scale agriculture along the Interoceanic Highway (Inset B2).

C. Central Peruvian Amazon: A new oil palm plantation located in the San Martín region has been identified as a recent large-scale deforestation event in this zone (Inset C).

D. Southwestern Colombian Amazon: Cattle grazing is the principal deforestation driver documented in this zone, located in the departments of Caquetá and Putumayo (Inset D).

E. Northern Colombian Amazon: There is expanding deforestation along a new road in this zone, located in the department of Guaviare (Inset E).

F. Northern Ecuadoran Amazon: This zone is located in the Orellana province, where small- and medium-scale agriculture, including oil palm, is the principal driver of deforestation (Inset F).

 

 

 

 

 


III. Drivers of Deforestation     

MAAP Interactive (screenshot)
MAAP Interactive (screenshot)

One of the main objectives of MAAP is to improve the availability of precise and up-to-date information regarding the current drivers (causes) of deforestation in the Andean Amazon.  Indeed, one of our most important advances has been the use of high-resolution imagery to identify current deforestation drivers.

In order to improve the analysis and understanding of the identified drivers, we have created an Interactive Map that displays the spatial location of each driver associated with every MAAP report.  An important characteristic of this map is the ability to filter the data by driver, by selecting the boxes of interest.

Image 3 shows a screenshot of the Interactive Map.  Note that it contains detailed information on these principal drivers: gold mining, oil palm, cacao, small-scale agriculture, cattle pasture, logging roads, and dams.  It also includes natural causes such as floods, forest fires, and blowdowns.  In addition, it highlights deforestation events in protected areas.

Below, we discuss the principal drivers of deforestation and degradation in greater detail.


Agriculture  oil palm, cacao, and other crops

Image 4: Interactive Map, agriculture. Data: MAAP.
Image 4: Interactive Map, agriculture. Data: MAAP.

Image 4 shows the results of the interactive map when applying the agriculture-related filters.

Legend:

Oil palm (bright green)

Cacao (brown)

Other crops (dark green)

Agricultural activity is one of the principal causes of deforestation in the Andean Amazon.

The majority of agriculture-related deforestation is caused by small- and medium-scale plantations (‹50 hectares).

Deforestation for large-scale, agro-industrial plantations is much less common, but represents a critical latent threat.

 

 


Large-scale Agriculture

We have documented five major deforestation events produced by large-scale plantations since 2007:  four of these occurred in Peru (three of which are related to oil palm and one to cacao) and one in Bolivia (resulting from sugar cane plantations).

First, between 2007 and 2011, two large-scale oil palm plantations caused the deforestation of 7,000 hectares on the border between Loreto and San Martín (MAAP #16).  Subsequent plantations in the surrounding area caused the additional deforestation of 9,800 hectares.

It is important to note that the Peruvian company Grupo Palmas is now working towards a zero deforestation value chain and has a new sustainability policy (see Case C of MAAP #64).

Next, between 2012 and 2015, two other large-scale oil palm plantations deforested 12,000 hectares in Ucayali  (MAAP #4, MAAP #41).

Between 2013 and 2015, the company United Cacao deforested 2,380 hectares for cacao plantations in Loreto (MAAP #9, MAAP #13, MAAP #27, MAAP #35).

Deforestation from large-scale agriculture decreased in Peru between 2016 and 2017, but there was one notable event: an oil palm plantation of 740 hectares in San Martín (MAAP #78).

Another notable case of deforestation related to large-scale agriculture has been occurring in Bolivia, where a new sugarcane plantation has caused the deforestation of more than 2,500 hectares in the department of La Paz.

Additionally, we found three new zones in Peru characterized by the deforestation pattern produced by the construction of organized access roads which have the potential of becoming large-scale agriculture areas (MAAP #69).


Small and Medium-scale Agriculture

Deforestation caused by small- and medium-scale agriculture is much more widespread, but it is often difficult to identify the driver from satellite imagery.

We have identified some specific cases of oil palm in Huánuco, Ucayali, Loreto, and San Martín (MAAP #48, MAAP #26, MAAP #16).

Cacao and papaya are emerging drivers in Madre de Dios.  We have documented cacao deforestation along the Las Piedras River (MAAP #23, MAAP #40) and papaya along the Interoceanic Highway (MAAP #42).

Corn and rice cultivation appear to be turning the area around the town of Iberia into a deforestation hotspot (MAAP #28).  In other cases, we have documented deforestation resulting from small- and medium-scale agriculture, though it has not been possible to identify the type of crop (MAAP #75, MAAP #78).

Additionally, small-scale agriculture is possibly a determining factor in the forest fires that degrade the Amazon during the dry season (MAAP #45, MAAP #47).

The cultivation of illicit coca is a cause of deforestation in some areas of Peru and Colombia.  For example, in southern Peru, the cultivation of coca is generating deforestation within the Bahuaja Sonene National Park and its surrounding areas.


Cattle Ranching

Image 5: Interactive Map, cattle ranching. Data: MAAP.
Image 5: Interactive Map, cattle ranching. Data: MAAP.

By analyzing high-resolution satellite imagery, we have developed a methodology for identifying areas deforested by cattle ranching.*

Image 5 shows the results of the Interactive Map when applying the “Cattle pasture” filter, indicating the documented examples in Peru and Colombia.

Legend:
Cattle ranching (orange)

Cattle ranching is the principal driver of deforestation in the central Peruvian Amazon (MAAP #26, MAAP #37, MAAP #45, MAAP #78). We also identified recent deforestation from cattle ranching in northeastern Peru (MAAP #78).

In the Colombian Amazon, cattle ranching is one the primary direct drivers in the country’s most intense deforestation hotspots (MAAP #63, MAAP #77).

* Immediately following a major deforestation event, the landscape of felled trees is similar for both agriculture and cattle pasture.  However, by studying an archive of images and going back in time to analyze older deforestation cases, it is possible to distinguish between the drivers.  For example, after one or two years, agriculture and cattle pasture appear very different in the images. The former tends to have organized rows of new plantings, while the latter is mostly grassland.


Gold Mining

Image 6: Interactive Map, gold mining. Data: MAAP.
Image 6: Interactive Map, gold mining. Data: MAAP.

Image 6 shows the results of the Interactive Map when applying the “Gold mining” filter.

Legend:
Gold Mining (yellow)

*With dot indicates within protected area

The area that has been most impacted by gold mining is clearly the southern Peruvian Amazon, where we estimate the total deforestation of more than 63,800 hectares. Of this, at least 7,000 hectares have been lost since 2013.  The two most critical zones are La Pampa and Alto Malinowski in Madre de Dios (MAAP #87, MAAP #75, MAAP #79).  Another critical area exists in Cusco in the buffer zone of the Amarakaeri Communal Reserve, where mining deforestation is now less than one kilometer from the boundary of the protected area (MAAP #71).

It is important to highlight two important cases in which the Peruvian government has taken effective actions to halt illegal mining within protected areas (MAAP #64).  In September 2015, illegal miners invaded Tambopata National Reserve and deforested 550 hectares over the course of a two-year period.  At the end of 2016, the government intensified its interventions and the invasion was halted in 2017. In regards to Amarakaeri Communal Reserve, in June 2015 we revealed the mining invasion deforestation of 11 hectares.  Over the course of the following weeks, SERNANP and ECA Amarakaeri implemented measures and rapidly halted the illegal activity.

Other small gold-mining fronts are emerging in the northern and central Peruvian Amazon (MAAP #45, MAAP #49).

In addition, we have also documented deforestation linked to illegal gold-mining activities in the Puinawai National Park in the Colombian Amazon.

 

 

 

 


Logging

Image 7: Interactive Map, logging roads. Data: MAAP.
Image 7: Interactive Map, logging roads. Data: MAAP.

In MAAP #85 we proposed a new tool to address illegal logging in the Peruvian Amazon: utilize satellite imagery to monitor construction of logging roads in near real-time.

Image 7 shows the results of the Interactive Map when applying the “Logging roads” filter.

Legend:
Logging Road (purple)

We estimate that 2,200 kilometers of forest roads have been constructed in the Peruvian Amazon during the last three years (2015-2017).  The roads are concentrated in southern Loreto, Ucayali, and northwestern Madre de Dios.

 

 

 

 

 

 

 

 

 


Roads

Image 8: Interactive map, roads. Data: MAAP.
Image 8: Interactive map, roads. Data: MAAP.

It has been well-documented that roads are one of the most important drivers of deforestation in the Amazon, particularly due to the fact that they facilitate human access and activities related to agriculture, cattle ranching, mining, and logging.

Image 8 shows the results of the Interactive Map when applying the “Roads” filter.

Legend:
Road (gray)

We have analyzed two controversial proposed roads in Madre de Dios, Peru.

The Nuevo Edén – Boca Manu – Boca Colorado road would traverse the buffer zone of two protected areas: Amarakaeri Communal Reserve and Manu National Park (MAAP #29).

The other, the Puerto Esperanza-Iñapari road, would traverse the Purús National Park and threaten the territory of the indigenous peoples in voluntary isolation who live in this remote area (MAAP #76).

 

 

 

 

 

 


Hydroelectric dams

Image 9 shows the results of the Interactive Map when applying the “Dams” filter.

Legend:
Hydroelectric Dam (light blue)

To date, we have analyzed three hydroelectric dams located in Brazil.  We have documented the loss of 36,100 hectares of forest associated with flooding produced by two dams (San Antonio and Jirau) on the Madeira River near the border with Bolivia (MAAP #34).  We also analyzed the controversial Belo Monte hydroelectrical complex located on the Xingú River, and estimate that 19,880 hectares of land have been flooded. According to the imagery, this land is a combination of forested areas and agricultural areas (MAAP #66).

Additionally, we show a very high-resolution image of the exact location of the proposed Chadín-2 hydroelectric dam on the Marañón River in Peru (MAAP #80).


Hydrocarbon (oil and gas)

Image 10: Interactive map, hidrocarbon. Data: MAAP.
Image 10: Interactive map, hidrocarbon. Data: MAAP.

Image 10 shows the results of the Interactive Map when applying the “Hydrocarbon filter.

Legend:
Hydrocarbon (black)

Our first report on this sector focused on Yasuní National Park in the Ecuadorian Amazon.  We documented the direct and indirect deforestation amounts of 417 hectares (MAAP #82).

We also show the location of recent deforestation in two hydrocarbon block in Peru: Block 67 in the north and Blocks 57 in the south.

 

 

 

 

 

 

 

 

 

 


Climate Change

Tropical forests, especially the Amazon, sequester huge amounts of carbon, one of the main greenhouse gases driving climate change.

In MAAP #81, we estimated the loss of 59 million metric tons of carbon in the Peruvian Amazon during the last five years (2013-17) due to forest loss, especially deforestation from mining and agricultural activities. This finding reveals that forest loss represents nearly half (47%) of Peru’s annual carbon emissions, including from burning fossil fuels.

In contrast, in MAAP #83 we show that protected areas and indigenous lands have safeguarded 3.17 billion metric tons of carbon, as of 2017. That is the equivalent to 2.5 years of carbon emissions from the United States.

The breakdown of results are:

1.85 billion tons safeguarded in the Peruvian national protected areas system;

1.15 billion tons safeguarded in titled native community lands; and

309.7 million tons safeguarded in Territorial Reserves for indigenous peoples in voluntary isolation.


Citation

Finer M, Mamani N (2018) Deforestation in the Andean Amazon (Trends, Hotspots, Drivers). MAAP Synthesis #3.

MAAP #89: Impacts Of Mining Project “Mirador” In The Ecuadorian Amazon

“Mirador” mining project in Ecuador.
“Mirador” mining project in Ecuador.

The Ecuadorian Amazon is experiencing a growing number of conflicts directly related to oil and mining extraction projects.

Here, we focus on the “Mirador” mining project, an open pit copper mine in the Cordillera del Cóndor, a mountain range along the Ecuador/Peru border that hosts a high level of endemism.

We show a series of satellite images that highlight both the environmental impacts, such as the deforestation of over 3,200 acres, and social impacts, such as the forced eviction of communities.

*The Ecuador series is a collaboration between Amazon Conservation, Amazon Conservation Team, and EcoCiencia, funded by the MacArthur Foundation.

https://maaproject.org/mirador-ecuador/