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MAAP #128: United Cacao Case – 7 Years After Massive Deforestation in the Peruvian Amazon

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Image 1. The first sign of large-scale deforestation, near the town of Tamshiyacu, in June 2013. Data: Planet (RapidEye). First time published. Click to enlarge.

Here, we confirm the massive deforestation of primary forest (more than 2,000 hectares) in the Peruvian Amazon by the company United Cacao between 2013 and 2016.

We present a series of recently obtained (and never before published) satellite images to emphasize the reality and importance of a deforestation case that is still being debated at the highest levels in the Peruvian government, seven years later.

In June 2013, a high-resolution satellite, through scattered clouds, revealed the start of massive deforestation of primary forest near the town of Tamshiyacu, in the Loreto region (Image 1).

In August of that same year, the clouds cleared a bit more, giving a better view. Image 2 (see below) shows the rapid deforestation of primary forest in 2013.

By September 2015, the deforestation had reached 2,380 hectares, or 5,880 acres (Image 3).

Most recently, in October 2020, a new very high-resolution image shows cacao crops in areas that, seven years ago, were primary forest (Image 4).

Below, we show, for the first time, these high and very-high resolution images (5 and 0.5 meters, respectively) recently obtained from the satellite company Planet, clearly showing the situation from 2012 -2020. Additionally, we show the historical context with Landsat images dating back to 1985, and briefly describe the current political situation regarding the case.

Deforestation 2013

Image 2 shows the first stage of large-scale deforestation (1,100 hectares) by the company United Cacao, between August 2012 (left panel) and August 2013 (right panel).

Image 2. Large-scale deforestation by United Cacao between August 2012 (left panel) and August 2013 (right panel). Data: Planet (RapidEye). First time published. Click to enlarge.

Deforestation 2015

Image 3 shows the total large-scale deforestation (2,380 hectares, or 5,880 acres) by United Cacao between August 2012 (left panel) and September 2015 (right panel). Insets A-C indicate the locations of the zooms below.

Image 3. Large-scale deforestation by United Cacao between August 2012 (left panel) and September 2015 (right panel). Data: Planet (RapidEye). First time published. Click to enlarge.

2020 – Cacao Crops in Deforested Areas

Images 4-6 show current cacao crops (right panel) in areas that, seven years ago, were primary forest (left panel).

Image 4. Current cacao crops (right panel) in areas that, seven years ago, were primary forest (left panel). Data: Planet, Airbus. First time published. Click to enlarge.
Image 5. Current cacao crops (right panel) in areas that, seven years ago, were primary forest (left panel). Data: Planet, Airbus. First time published. Click to enlarge.
Image 6. Current cacao crops (right panel) in areas that, seven years ago, were primary forest (left panel). Data: Planet, Airbus. First time published. Click to enlarge.

Current Policy Situation

In 2014, the Ministry of Agriculture (MINAGRI) ordered United Cacao (Cacao del Perú Norte SAC) to halt its development and production activities, but the company did not comply.

In 2019, MINAGRI rejection the Program for  Adequacy and Environmental Management (PAMA) presented by the company that took over the operation, Tamshi S.A.C. The PAMA is a type of environmental impact evaluation for projects already in operation.

Also in 2019, environmental enforcement of the case was transferred from MINAGRI to the Agency for Environmental Assessment and Enforcement (OEFA).

Most recently, OEFA issued a major fine, equivalent to around $35 million, to the company Tamshi S.A.C. for carrying out activities without having an approved environmental management plan. OEFA also issued 17 corrective measures, one of which was the immediate stoppage of activities.

Acknowledgments

We thank C. Ipenza, A. Felix, C. Noriega, S. Novoa, and G. Palacios for their helpful comments on this report.

This report was conducted with technical assistance from USAID, via the Prevent project. Prevent is an initiative that, over the next 5 years, will work with the Government of Peru, civil society, and the private sector to prevent and combat environmental crimes in Loreto, Ucayali and Madre de Dios, in order to conserve the Peruvian Amazon.

This publication is made possible with the support of the American people through USAID. Its content is the sole responsibility of the authors and does not necessarily reflect the views of USAID or the US government.

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

Citation

Finer M, Mamani N (2020) United Cacao Case – 7 Years After Massive Deforestation in the Peruvian Amazon. MAAP: 128.

MAAP #127: Mennonite Colonies Continue Major Deforestation in Peruvian Amazon

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Recent deforestation associated with the Mennonite colony Tierra Blanca 1, in Loreto, Peru. Data: Planet

The Mennonites, a religious group often associated with organized agricultural activity, have started three new colonies in the Peruvian Amazon.

We have documented the deforestation of 8,500 acres (3,440 hectares) in these three colonies over the past four years (updated October 2020).

The deforestation started in 2017, but continues to be active in 2020 (with 1,900 acres lost, 25% of the total).

Notably, this combined Mennonite deforestation now exceeds the total loss from the infamous United Cacao case (2,400 hectares), one of the last major controversial large-scale deforestation cases in the Peruvian Amazon (MAAP #27).

Moreover, there are strong indications that the deforestation associated with these three Mennonite colonies is illegal (see Legality Statement below).

Below, we present the following:

  • A Base Map showing the location of the three new Mennonite colonies in the Peruvian Amazon.
  • A series of satellite images showing the recent deforestation in the most active colony (Tierra Blanca 1), including a very high resolution (0.5 meter) Skysat image.
  • a Legality Statement.
  • A graphic showing that the deforested area was not previously cleared (that is, it was intact forest).

 

 

 

 

Base Map. Location of the three new Mennonite Colonies in the Peruvian Amazon. Data: MAAP.

Base Map

The Base Map shows the location of the three new Mennonite colonies in the Peruvian Amazon.

Two colonies are located near the town of Tierra Blanca in the northern Peruvian Amazon (Loreto region).

The other colony is located near the town of Masisea in the central Peruvian Amazon (Ucayali region).

Of the total deforestation (8,500 acres):

  • 63% (5,370 acres) is from the colony Tierra Blanca 1;
  • 25% (2,145 acres) is from the colony Masisea;
  • 12% (990 acres) is from the colony Tierra Blanca 2.

 

 

 

 

 

 

Deforestation 2017-20

The following image shows the total deforestation of 5,370 acres (2,174 hectares) between November 2016 (left panel) and October 2020 (right panel), associated with the Mennonite colony Tierra Blanca 1. The red dot serves as a reference point between the two panels. Click to enlarge.

Deforestation between September 2016 (left panel) and October 2020 (right panel), associated with the Mennonite colony Tierra Blanca 1. Data: Planet, MAAP. Click to enlarge.

Deforestation 2020

The following image shows the most recent deforestation of 1,540 acres (625 hectares) between January 2020 (left panel) and October 2020 (right panel), associated with the Tierra Blanca 1 Mennonite colony. The red lines indicate new 2020 deforestation. Also see the Annex below for a map of the 2020 deforestation in relation to previous 2017-19 deforestation. Click to enlarge.

Deforestation between January 2020 (left panel) and October 2020 (right panel), associated with the Mennonite colony Tierra Blanca 1. Data: Planet, MAAP. Click to enlarge.

Very High Resolution Satellite Image (Skysat)

We recently obtained a very high resolution (0.5 meter) satellite image of the Tierra Blanca 1 colony, thanks to the company Planet and their Skysat fleet. The image allows enhanced visualization of some details of the deforested area, such as roads, buildings, and cleared land for likely agricultural activities. Click to enlarge.

Very high resolution satellite image (0.5 meters) over the Tierra Blanca 1 colony. Data: Planet (Skysat). Click to enlarge.

Legality Statement

Regarding the findings in Loreto (Tierra Blanca), we consulted with the Regional Government of Loreto who, in a document dated October 15, 2020, indicated that the Mennonite colonies do not have any approvals for the large-scale forest clearing in the area. The documented also indicated that they were coordinating with the environmental prosecutor’s office (known as FEMA) to investigate the case and its environmental impact.

Regarding the findings in Ucayali (Massisea), our investigations revealed that there is an investigation in progress by the environmental prosecutor’s office (FEMA). In addition, the regional government has initiated a sanctioning procedure for the alleged unauthorized land use change (deforestation) associated with Mennonite colony near Masisea.

Annex

We present a time series of satellite images ranging from 1985 to 2020 that shows that the major deforestation in the area began with the Mennonite intervention.

Annex. Deforestation in 2020 in relation to 2017-19, associated with Mennonite colony Tierra Blanca 1. Data: MAAP.

Acknowledgements

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

This work was supported by the following major funders: Erol Foundation, Norwegian Agency for Development Cooperation (NORAD), and International Conservation Fund of Canada (ICFC).

Citation

Finer M, Mamani N, Suarez D (2020) MAAP: Mennonite Colonies Continue Major Deforestation in Peruvian Amazon Peruana. MAAP: 27.

MAAP #126: Drones and Legal Action in the Peruvian Amazon

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ACOMAT member flying a drone for monitoring their forestry concession. Source: ACCA.

The southern Peruvian Amazon (Madre de Dios region), is threatened by illegal mining, logging, and illegal deforestation.

In response, an association of forest concessionaires (known as ACOMAT) is implementing a comprehensive monitoring system that links the use of technology (satellites and drones) with legal action.

ACOMAT was formed in 2012 and now comprises 15 forestry concessions, covering 440,000 acres (178,000 hectares) in the southern Peruvian Amazon (see Base Map). Most of the concessions are alternatives to logging, such as Brazil nuts, Conservation, and Ecotourism.

This comprehensive system has three main elements:

1) Real-time, satellite-based forest loss monitoring (such as GLAD alerts) to quickly detect any possible new threats, even across vast and remote areas.

2) Field patrols with drone flights to verify forest alerts (or monitor threatened areas) with very high resolution images.

3) If suspected illegality is documented, initiate a criminal or administrative complaint, utilizing both the satellite and drone-based evidence.

In the case of ACOMAT, during 2019 they conducted 26 drone patrols and filed 15 legal complaints with the regional Environmental Prosecutor’s Office, known as FEMA. Below, we describe several of these cases.

Note that there is high potential to replicate this comprehensive monitoring model at the level of forest custodians (for example, concessionaires and indigenous communities) in the Amazon and other tropical forests.

Key ACOMAT Cases

Next, we describe four cases where comprehensive monitoring was performed (see Insets A-D on the Base Map).

Base Map. ACOMAT concessions. Data: ACCA, MINAM/PNCBMCC, SERNANP.

A. Illegal logging in the Los Amigos Conservation Concession

In October 2019, a patrol was carried out to investigate a threatened area within the Los Amigos Conservation Concession (the world’s first Conservation Consession). During the patrol, which included five drone flights, illegal logging was documented, including stumps with sawn trees , paths for the transfer of wood to a nearby river, and abandoned camps. The drone images were added as evidence in support of the previously filed criminal complaint to the FEMA in Madre de Dios. Below we present two striking images from the drone flights, clearly showing the illegal logging. Status of the Complaint: In Preliminary Investigation.

Case A. Illegal logging in the Los Amigos Conservation Concession, identified with drone overflight. Source: ACCA.
Case A. Illegal logging in the Los Amigos Conservation Concession, identified with drone overflight. Source: ACCA.

B. Ilegal Logging in the MADEFOL Forestry Concession

In May 2019, a field patrol was carried out to investigate a threatened area within the MADEFOL forestry concession. During the patrol, which included two drone flights, illegal logging was documented, including stumps with sawn trees, a recently abandoned camp, and an access road. With the drone images as evidence, a new criminal complaint was filed with the FEMA in Madre de Dios. Below is an image from the drone flights, clearly showing the evidence of illegal logging. Status of the complaint: In qualification.

Case B. Illegal logging in the “MADEFOL” forestry concession identified with drone overflight. Source: ACCA.

C. Illegal Gold Mining in a Conservation Concession

In May 2019, a field patrol was carried out in the “Inversiones Manu SAC” Conservation Concession to investigate an area that had previously been affected by illegal gold miners. During the patrol, which included two drone flights, illegal gold mining was documented in the Malinowski River. With the drone images as evidence, a new criminal complaint was filed with the FEMA in Madre de Dios. Below is a drone image clearly showing the evidence of illegal gold mining. Status of the complaint: Preliminary Investigation.

Caso C. Minería ilegal en la Concesión de Conservación “Inversiones Manu SAC,” identificada con sobrevuelo de dron. Fuente: ACCA.

D. Deforestation in a Brazil Nut Concession

In October 2019, a patrol was carried out to investigate an early warning deforestation alert within the “Sara Hurtado Orozco B” Brazil nut concession.

During the patrol, which included one drone flight, the recent deforestation of five acres (two hectares) was documented. With the drone images, a new criminal complaint was filed with the FEMA of Madre de Dios. It should be noted that this concession was being investigated for a separate illegal deforestation event. Below is one of the images of the drone flight, clearly showing the illegal deforestation. Status of the complaint: In preliminary proceedings.

Caso D. Deforestación en la Concesión Forestal de Castaña “Sara Hurtado Orozco B”. Fuente: ACCA.

Importance of the “ACOMAT Model”

We have started using the term “Acomat model” to refer to the innovative use of the three elements described above (real-time monitoring, drone flights, and criminal complaints) by the ACOMAT concessionaires.

ACOMAT was created in 2012, and since 2017 has received crucial support from the organization Conservation Amazónica-ACCA, supported by funds from Norway’s International Climate and Forest Initiative (NICFI), led by the Norwegian Agency for Development Cooperation (NORAD).

This project has provided training on all three major aspects, satellite-based monitoring alerts, drones, and the legal process. Concessionaires now receive deforestation alerts to their phones, have the ability to organize and conduct field patrols, and some are trained to perform their own drone flights.

Acknowledgments

We thank R. Segura (DAI), M.E. Gutierrez (ACCA), D. Suarez (ACCA), H. Balbuena (ACCA), M. Silman (WFU), and G. Palacios for their helpful comments on this report.

This report was conducted with technical assistance from USAID, via the Prevent project. Prevent is an initiative that, over the next 5 years, will work with the Government of Peru, civil society, and the private sector to prevent and combat environmental crimes in Loreto, Ucayali and Madre de Dios, in order to conserve the Peruvian Amazon.

This publication is made possible with the support of the American people through USAID. Its content is the sole responsibility of the authors and does not necessarily reflect the views of USAID or the US government.

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

Citation

Finer M, Castañeda C, Novoa S, Paz L (2020) Drones and Legal Action in the Peruvian Amazon. MAAP 126.

 

MAAP #125: Detecting Illegal Logging with Very High Resolution Satellites

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Very high resolution satellite image showing illegal logging in the southern Peruvian Amazon. Data: Maxar. Analysis: MAAP/ACCA.

Illegal logging in the Peruvian Amazon is mainly selective and, until now, difficult to detect through satellite information.

In this report, we present the enormous potential of very high resolution satellite imagery (<70 cm) to identify illegal logging.

The leading entities that offer this type of data are Planet (Skysat) and Maxar (Worldview).

We emphasize that this technique has the potential to detect the illegal activity in real time, when preventive action is still possible.

This is an important advance because when an intervention normally occurs, such as detaining a boat or truck with illegal timber, the damage is done.

Below, we show a specific case of using very high resolution satellite imagery to detect and confirm probable illegal logging in the southern Peruvian Amazon (Madre de Dios region).

 

 

 

 

Case: Turbina SAC

The Base Map below shows the intensity of probable illegal logging activity* in the Turbina SAC forestry concession, from 2016 to the present. Specifically, it shows the exact points of illegal logging events (felled trees) and logging camps, as identified through our analysis of very high-resolution satellite images. Note that this forestry concession is adjacent to the Los Amigos Conservation Concession, an important long-term (20 years) biodiversity conservation area.

Base Map. Illegal logging activities in the Turbina SAC forestry concession. The size of the points is for reference only. Data: MAAP/Amazon Conservation.

Very High Resolution Satellite Imagery

Below, we show a series of very high-resolution satellite images, courtesy of the innovative satellite companies Planet and Maxar.

The first image shows the identification of probable illegal logging between June 2019 (left panel) and August 2020 (right panel). The red circle indicates the exact area (canopy) of the illegally logged tree.

The identification of illegal logging between June 2019 (left panel) and August 2020 (right panel). Click to enlarge. Data: Maxar, Planet, MAAP.

The following image shows the identification of illegal logging in March 2020. The red circle indicates the exact area of the illegally logged trees.

Identification of illegal logging. Data: Maxar, MAAP.

The following image shows the identification of a logging camp in March 2o20. The red circle indicates the area of the camp.

Satellite image of an illegal logging camp. Data: Maxar, MAAP.

*Statement on Legality

We determined that this logging activity is illegal from a detailed analysis of official information from the Peruvian Government (specifically, the Peruvian Forestry Service, SERFOR, and forestry oversight agency, OSINFOR). This information indicates that, although the concession is in force (Vigente), its status is classified as Inactive (Inactiva). In addition, 2013 was the last year that this concession had an approved logging plan (Plan Operativo de Aprovechamiento, or POA), and it was for a different sector of the concession from the newly detected logging activity.

To confirm our assumption of illegal activity, we requested the technical opinion from the corresponding regional forestry and wildlife authority, however, as of the date of publication of this report, we have not yet received a response.

Thus, with the information we had at the time of publication, we concluded the logging was illegal as it was not conducted within a current management plan.

Methodology

We carried out the analysis in two main steps:

The first step was the visual interpretation and digitization of new logging events and associated logging camps within the Turbina forestry concession. This analysis was based on the evaluation of submetric images obtained from the satellite companies Planet and Maxar, for the period 2019-20. It is worth noting that for Planet, we had the new ability to “task” new images for a specific area, rather than waiting for an image to appear by other means. Logging in the Peruvian Amazon is usually highly selective for high-value species, thus its detection requires a comparative analysis of images (before and after), in such a way that the trees cut during the study period (2019-20 in this case) can be identified.

The second step focused on an analysis of the legality of the identified logging events. The locations of the logged trees and camps were cross-referenced with spatial information on the state and status of forestry concessions provided by the GeoSERFOR (SERFOR) portal, as well as the areas delimited in the annual operational plans of the concessions, verified by OSINFOR and distributed through the SISFOR portal (WMS). We considered both spatial and temporal aspects to the forestry concession data.

Citation

Novoa S, Villa L, Finer M (2020) Detecting Illegal Logging with Very High Resolution Satellites. MAAP: 125.

Acknowledgments

We thank A. Felix (USAID Prevent), M.E. Gutierrez (ACCA), and G. Palacios for their helpful comments on this report.

This report was conducted with technical assistance from USAID, via the Prevent project. Prevent is an initiative that, over the next 5 years, will work with the Government of Peru, civil society, and the private sector to prevent and combat environmental crimes in Loreto, Ucayali and Madre de Dios, in order to conserve the Peruvian Amazon.

This publication is made possible with the support of the American people through USAID. Its content is the sole responsibility of the authors and does not necessarily reflect the views of USAID or the US government.

MAAP #124: Deforestation Hotspots 2020 in the Peruvian Amazon.

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Base Map. 2020 Forest Loss Hotspots in the Peruvian Amazon. Data: UMD/GLAD, MAAP, SERNANP.

We have entered the peak deforestation season in the Peruvian Amazon, so it is also a critical time for real-time monitoring (MAAP’s specialty).

Here, we highlight the major deforestation events documented so far in 2020 (through August 23).

The Base Map shows the current forest loss hotspots, indicated by the colors yellow, orange and red.

Below, we present the most urgent deforestation cases, caused by gold mining and agriculture (both large and small scale), the current leading deforestation drivers in Peru.

The Letters A-I on the Base Map correspond to the location of the cases described below.

One of the key cases is the new illegal gold mining hotspot along the Pariamanu river (Letter A in the southern Peruvian Amazon).

Another important case is the expanding large-scale agriculture by a Mennonite colony that continues causing an alarming deforestation.

The other cases deal with small-scale agriculture, which cumulatively represent the main deforestation driver in Peru.

Urgent Deforestation Cases 2020

1. Gold Mining

In MAAP #121, we reported that, in general, gold mining deforestation has decreased in the southern Peruvian Amazon following the government’s Operation Mercury, but it does continue in several critical areas. The images below show two of these areas (Pariamanu and Araza) with alarming new deforestation in 2020.

A. Pariamanu

The following image shows the gold mining deforestation of 52 acres (21 hectares) of primary forest along the Pariamanu River in the southern Peruvian Amazon (Madre de Dios region) between January (left panel) and August (right panel) of 2020. We highlight that the Peruvian government has just carried out an operation against the illegal mining activity in this area.

Pariamanu case (illegal gold mining). Data: Planet, MAAP.

B. Araza

The following image shows the gold mining deforestation of 114 acres (46 hectares) along the Chaspa River in the Puno region, between January (left panel) and August (right panel) of 2020.

Araza case. Data: Planet, MAAP.

2. Large-scale Agriculture

C. Mennonite Colony (near Tierra Blanca)

We reported last year that a new colony of Mennonites caused the deforestation of 4,200 acres (1,700 hectares) between 2017 and 2019 in the Loreto region (MAAP #112). The following image shows the additional deforestation of 820 acres (332 hectares) in 2020 between January (left panel) and August (right panel).

Mennonite case (near Tierra Blanca). Data: Planet, MAAP.

3. Small-scale Agriculture

D. Jeberos

In 2018, we reported on the construction of a new road (65 km) cutting through primary forest in the Loreto region, between the city of Yurimaguas and the town of Jeberos (MAAP #84). The following image shows the deforestation of 40 acres (16 hectares) along the new road in 2020, between January (left panel) and August (right panel).

Jeberos case (near Tierra Blanca). Data: Planet, MAAP.

E. Las Piedras

The following image shows the deforestation of 64 acres (26 hectares) of primary forest in a Brazil-nut concession along the Las Piedras River in the Madre de Dios region, between November 2019 (left panel) and August 2020 (right panel) .

Las Piedras case. Data: Planet, MAAP.

F. Bolognesi

The following image shows an example of deforestation (580 acres or 235 hectares) in one of the areas with the highest concentration of forest loss, located in the Ucayali region.

Bolognesi case. Data: Planet, MAAP.

G. Santa Maria de Nieva

The following image shows an example of deforestation(346 acres or 140 hectares) in another one of the areas with the highest concentration of forest loss, located in the Amazonas region.

Santa Maria de Nieva case. Data: Planet, MAAP.

H. Mishahua River

The following image shows the recent deforestation of 168 acres (68 hectares) along the Mishahua River, in the Ucayali region. Just to the north, we documented extensive deforestation along the Sepahua River in 2019, where it also appears to be starting up again in 2020.

Mishahua case. Data: Planet, MAAP.

I. South of Sierra del Divisor National Park

The following image shows an example of deforestation (166 acres or 67 hectares) in another one of the areas with the highest concentration of forest loss, located south of the Sierra del Divisor National Park in the Ucayali region.

Mishahua case. Data: Planet, MAAP.

 

Metodology

The analysis was based on early warning GLAD alerts from the Universidad de Maryland and Global Forest Watch.

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 S. Novoa and G. Palacios for helpful comments to earlier versions of this report.

This work was supported by the following major funders: Erol Foundation, Norwegian Agency for Development Cooperation (NORAD), and International Conservation Fund of Canada (ICFC).

Citation

Finer M, Mamani N (2020) Deforestation Hotspots 2020 in the Peruvian Amazon. MAAP: 124.

MAAP #124: Deforestation Hotspots 2020 in the Peruvian Amazon

Posted on by dcadmin
Base Map. 2020 Forest Loss Hotspots in the Peruvian Amazon. Data: UMD/GLAD, MAAP, SERNANP.

We have entered the peak deforestation season in the Peruvian Amazon, so it is also a critical time for real-time monitoring (MAAP’s specialty).

Here, we highlight the major deforestation events documented so far in 2020 (through August 23).

The Base Map shows the current forest loss hotspots, indicated by the colors yellow, orange and red.

Below, we present the most urgent deforestation cases, caused by gold mining and agriculture (both large and small scale), the current leading deforestation drivers in Peru.

The Letters A-I on the Base Map correspond to the location of the cases described below.

One of the key cases is the new illegal gold mining hotspot along the Pariamanu river (Letter A in the southern Peruvian Amazon).

Another important case is the expanding large-scale agriculture by a Mennonite colony that continues causing an alarming deforestation.

The other cases deal with small-scale agriculture, which cumulatively represent the main deforestation driver in Peru.

 

 

 

 

 

Urgent Deforestation Cases 2020

1. Gold Mining

In MAAP #121, we reported that, in general, gold mining deforestation has decreased in the southern Peruvian Amazon following the government’s Operation Mercury, but it does continue in several critical areas. The images below show two of these areas (Pariamanu and Araza) with alarming new deforestation in 2020.

A. Pariamanu

The following image shows the gold mining deforestation of 52 acres (21 hectares) of primary forest along the Pariamanu River in the southern Peruvian Amazon (Madre de Dios region) between January (left panel) and August (right panel) of 2020. We highlight that the Peruvian government has just carried out an operation against the illegal mining activity in this area.

Pariamanu case (illegal gold mining). Data: Planet, MAAP.

B. Araza

The following image shows the gold mining deforestation of 114 acres (46 hectares) along the Chaspa River in the Puno region, between January (left panel) and August (right panel) of 2020.

Araza case. Data: Planet, MAAP.

2. Large-scale Agriculture

C. Mennonite Colony (near Tierra Blanca)

We reported last year that a new colony of Mennonites caused the deforestation of 4,200 acres (1,700 hectares) between 2017 and 2019 in the Loreto region (MAAP #112). The following image shows the additional deforestation of 820 acres (332 hectares) in 2020 between January (left panel) and August (right panel).

Mennonite case (near Tierra Blanca). Data: Planet, MAAP.

3. Small-scale Agriculture

D. Jeberos

In 2018, we reported on the construction of a new road (65 km) cutting through primary forest in the Loreto region, between the city of Yurimaguas and the town of Jeberos (MAAP #84). The following image shows the deforestation of 40 acres (16 hectares) along the new road in 2020, between January (left panel) and August (right panel).

Jeberos case (near Tierra Blanca). Data: Planet, MAAP.

 

E. Las Piedras

The following image shows the deforestation of 64 acres (26 hectares) of primary forest in a Brazil-nut concession along the Las Piedras River in the Madre de Dios region, between November 2019 (left panel) and August 2020 (right panel) .

Las Piedras case. Data: Planet, MAAP.

F. Bolognesi

The following image shows an example of deforestation (580 acres or 235 hectares) in one of the areas with the highest concentration of forest loss, located in the Ucayali region.

Bolognesi case. Data: Planet, MAAP.

G. Santa Maria de Nieva

The following image shows an example of deforestation(346 acres or 140 hectares) in another one of the areas with the highest concentration of forest loss, located in the Amazonas region.

Santa Maria de Nieva case. Data: Planet, MAAP.

H. Mishahua River

The following image shows the recent deforestation of 168 acres (68 hectares) along the Mishahua River, in the Ucayali region. Just to the north, we documented extensive deforestation along the Sepahua River in 2019, where it also appears to be starting up again in 2020.

Mishahua case. Data: Planet, MAAP.

I. South of Sierra del Divisor National Park

The following image shows an example of deforestation (166 acres or 67 hectares) in another one of the areas with the highest concentration of forest loss, located south of the Sierra del Divisor National Park in the Ucayali region.

Mishahua case. Data: Planet, MAAP.

 

Metodology

The analysis was based on early warning GLAD alerts from the Universidad de Maryland and Global Forest Watch.

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 S. Novoa and G. Palacios for helpful comments to earlier versions of this report.

This work was supported by the following major funders: Erol Foundation, Norwegian Agency for Development Cooperation (NORAD), and International Conservation Fund of Canada (ICFC).

Citation

Finer M, Mamani N (2020) Deforestation Hotspots 2020 in the Peruvian Amazon. MAAP: 124.

MAAP #123: Detecting Illegal Logging in the Peruvian Amazon

Posted on by dcadmin
Image 1. Example of a 2019 logging road with signs of illegality. Data: Planet.

In the Peruvian Amazon, the widespread illegal logging is difficult to detect with satellites because it is selective for high-value species (not clearcutting).

It is possible, however, to detect the associated logging roads.

In this report, we present a novel technique to identify illegal logging: analyze new logging roads in relation to detailed land use data available from government agencies.

Thus, our new method detects the crime in real-time and preventive action is still possible. This is important because when an intervention against illegal logging normally occurs, stopping a boat or truck with illegal timber, the damage is done.

This analysis has two parts. First, we identified the new logging roads built in the Peruvian Amazon during 2019, updating our previous work for 2015-18 (see Base Map).

Second, we analyzed the new logging road data in relation to governmental land use information in order to identify possible illegality.

This data is from 2019, but we are now applying this technique in real time during 2020.

Base Map. 2019 Logging roads, in relation to 2015-18 logging roads. Data: MAAP.

Logging Roads 2019

The Base Map illustrates the location of logging roads built in the Peruvian Amazon during the last 5 years.

Previously (MAAP #99), we documented the construction of 3,300 kilometers of logging roads between 2015 and 2018.

Here, we estimate the construction of an additional 1,500 kilometers in 2019 (see red).

Note that forest roads are mainly concentrated in the Ucayali, Madre de Dios and Loreto regions.

Below, we show three types of possible illegality that detected in 2019:

  • Logging roads in areas without forestry concessions or permits (Cases 1-2).
    .
  • Logging roads in existing forest concessions, but whose current status is defined as “Non-Active or Undefined” (Cases 3-5).
    .
  • Logging roads in Native Communities (Case 6).

Cases of Possible Illegality

Logging roads in areas without forestry concessions or permits

Case 1. We detected the opening of a new logging road network (55 km) in an area without forestry concessions or permits, between the limits of the Loreto and San Martín regions. The image shows the digitized logging roads (red, left panel), and non-digitized satellite image (right panel). The arrows provide reference points between panels.

Case 1. Data: MAAP, Planet. Click to enlarge.

Case 2. We detected the construction of a new logging road network (5.8 km) in the buffer zone of Asháninka Communal Reserve, reaching only 300 meters from the protected area. The image shows the digitized logging roads (red, left panel), and non-digitized satellite image (right panel). The arrows provide reference points between panels.

Case 2. Data: MAAP, Planet, IBC, SERNANP. Click to enlarge.

Logging roads in existing forest concessions, but whose current state is labelled as “Non-Active or Undefined” 

Case 3. We detected the construction of a new logging road (45.3 km) that crosses a native community and reaches a forest concession whose status is defined as “Undefined,” in the Loreto region just north of Pacaya Samiria National Reserve. The image shows the digitized logging roads (red, left panel), and non-digitized satellite image (right panel). The arrows provide reference points between panels.

Case 3. Data: MAAP, ESA, IBC, SERFOR. Click to enlarge.

Case 4. We detected the construction of a new logging road network (53.2 km), of which nearly half (21.4 km) crosses a forest concession whose status is defined is “Non Active”, near the town of Sepahua in the Ucayali region. The image shows the digitized logging roads (red, left panel), and non-digitized satellite image (right panel). The arrows provide reference points between panels.

Case 4. Data: MAAP, Planet, IBC, SERFOR. Click to enlarge.

Case 5. We detected the construction of a new logging road (17.7 km) in a forestry concession whose current status is defined as “Non Active,” in the Madre de Dios region. The image shows the digitized logging roads (red, left panel), and non-digitized satellite image (right panel). The arrows provide reference points between panels.

Case 5. Data: MAAP, ESA, IBC, SERFOR. Click to enlarge.

Logging roads in Native Communities

Case 6. We detected the construction of a logging road (23.4 km) within an indigenous community in the Ucayali region. We did not find evidence of a permit for this activity. The image shows the digitized logging roads (red, left panel), and non-digitized satellite image (right panel). The arrows provide reference points between panels.

Case 6. Data: MAAP, Planet, SERNANP, IBC, SERFOR. Click to enlarge.

Methodology

Our analysis included two main steps:

The first step consisted of evaluating linear patterns in the 2019 early warning and final forest loss data, available from Global Forest Watch (data from the University of Maryland) and Geobosques (data from the Peruvian Ministry of the Environment). From the linear patterns, we distinguished between logging access roads and other types of roads and highways. Logging roads tend to have linear patterns that branch into the interior of the forest where the commercial timber is found. Other types of roads have a more defined destination, such as towns or farms. Once logging roads were identified, we downloaded the associated high-resolution imagery (3 meters) from Planet Explorer and digitized the roads in ArcGIS. During this process, additional logging roads detected in the high resolution images were also digitized.

The second step focused on the legality analysis. The new logging road data were overlaid with other types of land use information, such as forestry concessions on the GeoSERFOR portal (SERFOR), permits and concessions on the SISFOR portal (OSINFOR), indigenous communities (IBC 2019), protected areas (SERNANP), population centers (INEI 2019), and official road networks (MTC 2018). For example, as shown above, this process identified logging roads near protected areas, within indigenous communities, and within non-active forest concessions.

We analyzed information on several websites now available from national and regional authorities, such as SISFOR (OSINFOR), GEOSERFOR (SERFOR), and IDERs (Spatial Data Infrastructure of Regional governments). These new resources provide valuable information, however may have limitations in ability to constantly update information on the status of concessions and forest permits, especially from regional governments.

Annex – Logging road data per region

REGION, Logging Roads (Km)

LORETO, 231.2
MADRE DE DIOS, 477.8
UCAYALI, 720.0
HUANUCO, 45.5
JUNÍN, 19.8
PASCO, 15.1
SAN MARTIN, 2.4

TOTAL, 1511.7

References

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

Acknowledgments

We thank R. Valle (OSINFOR), A. Felix (DAI), D. Suarez (ACCA), and G. Palacios for their helpful comments on this report.

This report was conducted with technical assistance from USAID, via the Prevent project. Prevent is an initiative that, over the next 5 years, will work with the Government of Peru, civil society, and the private sector to prevent and combat environmental crimes in Loreto, Ucayali and Madre de Dios, in order to conserve the Peruvian Amazon.

This publication is made possible with the support of the American people through USAID. Its content is the sole responsibility of the authors and does not necessarily reflect the views of USAID or the US government.

Citation

Finer M, Paz L, Novoa S, Villa L (2020) Detecting Illegal Logging in the Peruvian Amazon. MAAP: 123.

MAAP #122: Amazon Deforestation 2019

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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.

MAAP #121: Reduction of Illegal Gold Mining in the Peruvian Amazon

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Base Map. Illegal gold mining deforestacion in the protected area buffer zones of the southern Peruvian Amazon, 2017-2019. Data: MAAP. Click to enlarge image.

Thanks to the support of the USAID, via the Prevent Project, dedicated to the prevention and combat of environmental crimes in the Amazon, we conducted a detailed analysis of recent illegal gold mining deforestation in the southern Peruvian Amazon.

The objective is to understand the trends from early 2017 to June 2020 (which includes the first part of the mandatory quarantine issued by the Peruvian government as of March 16, 2020 due to the coronavirus pandemic).

We focus on the buffer zones of two protected areas in the Madre de Dios region: Tambopata National Reserve and Bahuaja Sonene National Park (see Base Map).*

This area includes La Pampa, the current highest intensity illegal mining zone in the country. In February 2019, the Peruvian government launched Operation Mercury  to confront the illegality in La Pampa and surrounding areas.

The Base Map shows that gold mining deforestation in La Pampa decreased over 90% following Operation Mercury.

However, illegal gold mining does continue after Operation Mercury (including during the coronavirus state of emergency), but at lower rates. Thus, current snapshots may be misleading and recent context is important.

On the Base Map, the red arrows indicate the areas with the most recent illegal activity (click the image to enlarge). See below for more details.

Main Results

Table 1. Illegal gold mining deforestation before (yellow) and after (red) Operation Mercury in the buffer zones of Madre de Dios. Data: MAAP.

The Base Map and Table 1 illustrate the following key results:

  • In La Pampa, we documented mining deforestation of 173 hectares (428 acres) per month before Operation Mercury (January 2018 – February 2019). After the intervention, deforestation was reduced to 14 hectares (36 acres) per month (March 2019 – May 2020), a decrease of 92%.
    .
  • Upstream, in the Alto Malinowski, we documented the mining deforestation of 61 hectares (150 acres) per month before Operation Mercury. After the intervention, deforestation was reduced to 28 hectares (69 acres) per month, a decrease of 53%.
    .
  • Downstream, in the Apaylon area, we documented the mining deforestation of 2.9 hectares (7 acres) per month, before Operation Mercury. After the intervention, deforestation increased to 4 hectares (10 acres) per month, an increase of 41%. Apaylon is main area in the buffer zone where deforestation has increased.
    .
  • Within Tambopata National Reserve, we documented the mining deforestation of 6.5 hectares (16 acres) per month, before Operation Mercury. After the intervention, deforestation was reduced to 0.5 hectares (1.2 acres) per month, a decrease of 93%.
    .
  • Overall, illegal gold mining does continue in the buffer zones of Madre de Dios, but at lower rates than the previous two years. We documented the gold mining deforestation of 797 hectares (1,670 acres) after Operation Mercury.
    .
  • Regarding the speculation that illegal activity would increase during the coronavirus pandemic, we have not documented any major increase or surge in the buffer zones of Madre de Dios.* Illegal mining does continue, however, we documented the deforestation of 80 hectares (198 acres) during the quarantine.
    .

Reduction of 90% in La Pampa

The following images show the major decrease in gold mining deforestation in La Pampa after Operation Mercury. Image 1 shows the rapid deforestation before Operation Mercury, between January 2017 (left panel) and February 2019 (right panel). Image 2 shows how the deforestation decreased after Operation Mercury, between February 2019 (left panel) and May 2020 (right panel). The red dot represents a reference point between the images.

Image 1. Rapid gold mining deforestation in La Pampa before Operation Mercury, between January 2017 (left panel) and February 2019 (right panel). Data: Planet.
Image 2. Mining deforestation decreased in La Pampa after Operation Mercury, between February 2019 (left panel) and May 2020 (right panel). Data: Planet.

Displaced Miners?

Table 2. Deforestation by illegal gold mining before (yellow) and after (red) Operation Mercury in two other threatened areas. Data: MAAP.

There has also been speculation that the focus of Operation Mercury in La Pampa would lead to illegal miners moving to other areas.* Base Map 2 shows two of the most threatened areas: Camanti and Pariamanu.

These are the main results for these two areas:

  • In Camanti (located in the buffer zone of Amarakaeri Communal Reserve), we documented the gold mining deforestation of 13.3 hectares (33 acres) per month before Operation Mercury. After the intervention, deforestation was reduced to 6.1 hectares (15 acres) per month, a decrease of 54%.
    .
  • In Pariamanu, we documented  the mining deforestation of 2.5 hectares (6 acres) per month before Operation Mercury. After the intervention, it increased to 4.2 hectares (10 acres) per month, an increase of 70%.
    .
  • In summary, illegal gold mining continues in these two areas outside La Pampa. We documented the mining deforestation of 175 hectares (432 acres) after Operation Mercury (including 22 hectares during the pandemic). There is some evidence that miners are being displaced to Pariamanu, but there has not been a surge in Camanti.
Base Map 2. Main mining areas in the south of the Peruvian Amazon. Click to enlarge image.

Statement of the Peruvian Protected Area Agency (SERNANP)

El Servicio Nacional de Áreas Naturales Protegidas por el Estado (SERNANP) nos ha comunicado lo siguiente:

  • La actividad de control y vigilancia en la Reserva Nacional Tambopata es permanente y las autoridades (SERNANP, Policía Nacional del Perú, Fiscalías Especializadas en Materia Ambiental, y Marina de Guerra del Perú) continúan interviniendo a todas las actividades de minería ilegal, manteniendo el 100%.
  • Las zonas de amortiguamiento son espacios que están sujetos a la intervención de las autoridades de la Operación Mercurio (no del SERNANP). Se han realizado intervenciones continuas e interdicciones tanto en  las zonas indicadas en el reporte, como en Apaylon y Camanti.
    ,
  • Cabe mencionar que la Operación Mercurio, durante el 2019 y sobre todo en el 2020 (Incluyendo el período de cuarentena) ha ampliado sus operativos mas allá de la Pampa, lo cual explica porque en Camanti las cifras también se ha reducido.  En el segundo semestre de 2020 y en el 2021, se espera que los operativos es amplíen a otras zonas de Madre de Dios.

*Notes

Acknowledgments

We thank R. Segura, M. Castro, E. Ortiz, M. Silman, M. E. Gutierrez, S. Novoa, H. Balbuena, M. Allemant, and G. Palacios for their helpful comments on this report.

This report was conducted with technical assistance from USAID, via the Prevent project. Prevent is an initiative that, over the next 5 years, will work with the Government of Peru, civil society, and the private sector to prevent and combat environmental crimes in Loreto, Ucayali and Madre de Dios, in order to conserve the Peruvian Amazon.

This publication is made possible with the support of the American people through USAID. Its content is the sole responsibility of the authors and does not necessarily reflect the views of USAID or the US government.

Citation

Finer M, Mamani N (2020) Reduction of Illegal Gold Mining in the Peruvian Amazon. MAAP:

MAAP Synthesis: 2019 Amazon Deforestation Trends and Hotspots

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

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).

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.

  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. Deforestation Hotspots 2019. Data: MAAP, UMD/GLAD, Hansen/UMD/Google/USGS/NASA. Click to see image in high resolution.

The Base Map shows the most intense deforestation hotspots during 2019.

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)
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.