Country: Peru

MAAP #93: Shrinking Primary Forests of the Peruvian Amazon

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Base Map. Data: SERNANP, IBC, Hansen/UMD/Google/USGS/NASA, PNCB/MINAM, GLCF/UMD, ANA.

The primary forests of the Peruvian Amazon, the second largest stretch of the Amazon after Brazil, are steadily shrinking due to deforestation.

Here, we analyze both historic and current data to identify the patterns.

The good news: As the Base Map shows, the Peruvian Amazon is still home to extensive primary forest.* We estimate the current extent of Peruvian Amazon primary forest to be 67 million hectares (165 million acres), greater than the total area of France.

Importantly, we found that 48% of the current primary forests (32.2 million hectares) are located in officially recognized protected areas and indigenous territories (see Annex).**

The bad news: The Peruvian Amazon primary forests are steadily shrinking.

We estimate the original extent of primary forests to be 73.1 million hectares (180.6 million acres). Thus, there has been a historic loss of 6.1 million hectares (15 million acres), or 8% of the original. A third of the historic loss (2 million hectares) has occurred since 2001.

Below, we show three zooms (in GIF format) of the expanding deforestation, and shrinking primary forests, in the southern, central, and northern Peruvian Amazon.

 

 

 

GIF of deforestation in the southern Peruvian Amazon. Data: see Base Map

Southern Peruvian Amazon

Note these three important trends in the GIF (click to enlarge):

  • Increasing deforestation all along the route of the Interoceanic Highway;
  • Increasing gold mining deforestation across several different fronts near the southwestern section of the highway;
  • Increasing agricultural deforestation around Iberia, along the northern section of the highway near the border with Brazil.

 

 

 

 

 

 

 

 

GIF of deforestation in the central Peruvian Amazon. Data: see Base Map

Central Peruvian Amazon

Note these three important trends in the GIF (click to enlarge):

  • The substantial historic (pre 1990) deforestation around the cities Pucallpa and Tarapoto;
  • Increasing deforestation along the road leading west from Pucallpa;
  • Large-scale deforestation for oil palm plantations outside of Pucallpa and Yurimaguas.

 

 

 

 

 

 

 

 

 

 

Base Map plus protected areas and indigenous communities.

Northern Peruvian Amazon

Note these three important trends in the GIF (click to enlarge):

  • The historic (pre 1990) deforestation around Iquitos;
  • Increasing deforestation along the Iquitos-Nauta road;
  • Large-scale deforestation for United Cacao plantation near the town of Tamshiyacu.

 

 

 

 

 

 

 

 

 

 

Base Map plus protected areas and indigenous communities. Data: SERNANP, IBC, Hansen/UMD/Google/USGS/NASA, PNCB/MINAM, GLCF/UMD, RAISG, Ministerio de Cultura.

Annex

The Base Map with three additional categories: Protected Areas, titled Native Communities, and Indigenous Reserves.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Notes

*Defining primary forest: According to the Supreme Decree (No. 018-2015-MINAGRI) approving the Regulations for Forest Management under the framework of the new 2011 Forestry Act (No. 29763), the official definition of primary forest in Peru is: “Forest with original vegetation characterized by an abundance of mature trees with species of superior or dominant canopy, which has evolved naturally.” Using methods of remote sensing, our interpretation of that definition are areas that from the earliest available image are characterized by dense closed-canopy coverage and experienced no major clearing events.

It should be emphasized that our definition of primary forest does not mean that the area is pristine. These primary forests may have been degraded by selective logging and hunting.

**Historical Peruvian Amazon primary forests: 73,188,344 hectares. Current Peruvian Amazon primary forests: 67,043,378 hectares. Of this total, 27.6% are located in designated protected areas (18.5 million hectares), 18% in titled Native Communities (12 million hectares), and 4% in Indigenous Reserves/ Territories designated for indigenous peoples in voluntary isolation (2.9 million hectares). There is some overlap between these three categories, and the final combined percentage (48%) takes this into account.

Metodology

To generate the estimate of original (historical) expanse of primary forests in the Peruvian Amazon, we combined two satellite-based data sources. First, we used data from the Global Land Cover Facility (GLCF 2014), which established a forest cover baseline as of 1990 (The GLCF products are based on the Landsat Global Land Survey collection, which were compiled for years circa 1975, 1990, 2000 and 2005). Areas with no data due to shadows and clouds were filled in with GLCF data covering 2000-2005 time frame. The historical primary forest layer was created by combining the following three GLCF data layers: “Persistent Forest,” “Forest Gain,” and “Forest Loss.” Next, we incorporated the “Hydrography” data layer generated by the Peruvian Environment Ministry (Programa Nacional de Conservación de Bosques) to avoid including water bodies. We defined the limit of the analysis as the hydrographical basin of the Amazon. We generally define “historical Peruvian Amazon primary forest” as the expanse of primary forests before the European colonization of Peru (around 1750).

To generate the estimate of current primary forests, we subtracted areas determined to experience deforestation or forest loss from 1990 to 2017. For data covering 1990-2000, we incorporated two datasets: GLCF forest loss 1990-2000 and “No Forest as of 2000” (“No Bosque al 2000”) generated by the Peruvian Environment Ministry. For data covering 2001-2016, we used annual data generated by the Peruvian Environment Ministry. Finally, for 2017, we used early warning alert data generated by the Peruvian Environment Ministry. As a result, we define current primary forests as an area of historical forest with no observable (30 meter resolution) forest loss from 1990 to 2017.

Global Land Cover Facility (GLCF) and Goddard Space Flight Center (GSFC). 2014. GLCF Forest Cover Change 2000 2005, Global Land Cover Facility,University of Maryland, College Park.

Citation:

Finer M, Mamani N (2018) Shrinking Primary Forests of the Peruvian Amazon. MAAP: 93.

MAAP #92: New Deforestation Threats in the Peruvian Amazon (Part 2: Agriculture Expansion)

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Base Map. Data: SERNANP, MAAP

In this ongoing series, we describe major new projects that may lead to the rapid deforestation of large areas of primary Amazon forest.

The first report (MAAP #84) described the deforestation associated with the construction of the Yurimaguas – Jeberos road (see Base Map), which crosses extensive primary forest and a priority site for conservation in the Loreto region.

The current report describes the deforestation associated with major agricultural expansion in three areas in the northern Peruvian Amazon, referred to here as the “Imiria,” “Orellana“, and “San Martin” cases.

These three cases are important because they present characteristics of large-scale, agro-industrial activities (linear plots organized around an extensive new access road network).

In all three cases, early warning alerts (GLAD/Global Forest Watch) initially detected the deforestation in 2017 (see MAAP #69) and their subsequent expansion in 2018. The total deforestation documented to date in these three cases is 3,600 acres.

Below, we show satellite images of the most recent deforestation due to agricultural expansion in these three areas. In these images, yellow circles indicate 2016-17 deforestation and red circles/arrows indicate the most recent 2018 deforestation.

 

 

 

 

 

 

Imiría case (Ucayali)

Just to the north of the Imiría Regional Conservation Area, we documented the deforestation of 872 acres between June 2017 (left panel) and July 2018 (right panel). In the following image, note the organized deforestation around a new access road network. The red circles indicate the most recent 2018 deforestation. Also, note that the access road just reached the boundary of the Imiría Regional Conservation Area. Regarding the cause of deforestation, a recent news article indicates that a nearby indigenous community (Ceylan en Masisea) has reported the expansion of industrial-scale rice plantations.

Imiría case. (ACR = Regional Conservation Area) Data: Planet, SERNANP, MAAP

Orellana case (Loreto)

In the Loreto region, near the town of Orellana, we documented the deforestation of 902 acres between December 2016 (left panel) and July 2018 (right panel). In the following image, again note the organized deforestation around a new access road network. The red arrows indicate the new access roads built in 2018.

Orellana case. Data: Planet, MAAP

San Martin Case

In northeastern San Martín region, we documented the recent deforestation of 1,828 acres between December 2016 (left panel) and August 2018 (right panel) related to a new oil palm plantation. The red circle highlights the most recent 2018 deforestation, which indicates a major expansion of the plantation.

San Martin case. Data: Planet, MAAP

Coordinates

Imiria case: -8.733077,-74.369202
Orellana case: -6.569118,-75.357971
San Martín case: -6.26539,-75.800171

Citation

Finer M, Villa L (2018) New Deforestation Threats in the Peruvian Amazon (Part 2: Agriculture Expansion). MAAP: 92.

MAAP #91: Introducing PeruSAT-1, Peru’s new High-resolution Satellite

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PeruSat-1. Credit: Airbus DS

In September 2016, Peru’s first satellite, PeruSAT-1, launched. It is Latin America’s most powerful Earth observation satellite, capturing images at a resolution of 0.70 meters.

The cutting-edge satellite was constructed by Airbus (France) and is now operated by the Peruvian Space Agency, CONIDA.

The organization Amazon Conservation was granted early access to the imagery to boost efforts related to near real-time deforestation monitoring.

Below, we present a series of PeruSAT images that demonstrate their powerful utility in terms of detecting and understanding deforestation in the Peruvian Amazon.

 

 

 

 

Gold Mining

We have reported extensively on the continuing gold mining deforestation in the southern Peruvian Amazon (see MAAP #87). We are now using PeruSAT to identify active and emerging mining deforestation fronts. For example, in the following images of an active mining zone, it is possible to clearly observe the environmental impact, and identify mining camps and wastewater pools.

PeruSAT-1 image of active gold mining. Data: ®CONIDA (2018), Distribution CONIDA, Peru; All rights reserved.
PeruSAT-1 image (zoom) of active gold mining. Data: ®CONIDA (2018), Distribution CONIDA, Peru; All rights reserved.

Agricultural Expansion

The following image shows a papaya plantation that appeared after a recent deforestation event near the Interoceanic highway in the southern Peruvian Amazon (Mavila, Madre de Dios). See MAAP #42 for more details on papaya emerging as new deforestation driver in this area.

PeruSAT-1 image of papaya plantation. Data: ®CONIDA (2018), Distribution CONIDA, Peru; All rights reserved.

Logging Roads

The following image shows, in high-resolution, a new logging road crossing primary forest in the southern Peruvian Amazon (district of Iñapari, Madre de Dios).

PeruSAT-1 image of logging road. Data: ®CONIDA (2018), Distribution CONIDA, Peru; All rights reserved.

Citation

Villa L, Finer M (2018) Introducing PeruSAT-1, Peru’s new High-resolution Satellite. MAAP: 91.

MAAP #90: Using Drones to monitor Deforestation and Illegal Logging

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Drone types: helipcopter and fixed-wing (plane)

For the past three years, the organization Amazon Conservation has been working to establish a sustainable, local-based drones program for environmental monitoring in the southern Peruvian Amazon (Madre de Dios region).

This program is based on two types of drones, multi-rotor (helicopter style) and fixed-wing (airplane style).

One of the main objectives is to improve the near real-time monitoring of deforestation and illegal logging.

The monitoring is currently focused on three priority areas: 1) Brazil nut concessions, 2) forestry concessions of the local association ACOMAT, and 3) along the Interoceanic Highway (see Base Map).

Below, we show a series of drone images that we have used to identify the drivers of recent deforestation events. These drivers include gold mining, agriculture, illegal logging, cattle pasture, and natural forest loss.

Base Map. Priority areas of the Amazon Conservation drones initiative.

Interoceanic Highway

In March 2018, in collaboration with the organization ProPurús, we realized drone flights along the Interoceanic Highway in an effort to demonstrate the possible threats of building a new road along the border with Brazil (see MAAP #76). The following images show the two main threats to the area: gold mining and small/medium-scale agriculture (<50 hectares).

A. Drone image: gold mining.
B. Drone image: Deforestation from agriculture (corn)

Brazil Nut Concessions

In 2018, Amazon Conservation launched a new project, funded by Google Challenge, to develop a monitoring program for Brazil nut concessions covering a million hectares (2.47 million acres) in southern Peru. For example, the following image shows the invasion of a papaya plantation that caused the recent deforestation of five acres inside a concession.

C. Drone image: Invasión of papaya in Brazil nut concession.

ACOMAT Forestry Concessions

Since 2017, Amazon Conservation has been working on a project, financed by the Norwegian Agency for Development Cooperation (NORAD), to improve the monitoring of forest concessions of the local association ACOMAT (Association of Timber and Non-Timber Forest Concessionaires of the Provinces from Manu and Tambopata). The following images show examples of forest loss and degradation due to illegal logging, cattle grazing, natural loss (windstorm), and gold mining.

D. Drone image: illegal logging.
E. Drone image: cattle pasture.
F. Drone image: natural forest loss from windstorm.
G. Drone image: gold mining.

Citation

Garcia R, Novoa S, Castañeda C, Rengifo P, Jimenez M, Finer M (2018) Using Drones to monitor Deforestation and Illegal Logging. MAAP: 90.

MAAP #87: Gold Mining deforestation continues in the Peruvian Amazon

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Expansión hacia el este de mineria aurífera en La Pampa. Fuente: Planet.

We have reported extensively on the ongoing gold mining deforestation crisis in the southern Peruvian Amazon (see Archive), estimating the loss of over 17,500 acres in the five years between 2013 and 2017.

Here, we present new analysis showing that the destruction continues in 2018: we estimate an additional 4,265 acres during the first six months (January – June). This most recent deforestation is concentrated in two critical areas: La Pampa and Alto Malinowski. Most, if not all, of the mining appears to be illegal (see Annex).

This brings the total gold mining deforestation since 2013 to over 21,750 acres.

Next, we show a series of satellite images of the recent deforestation in La Pampa and Alto Malinowski.

 

 

Base Map

The Base Map highlights the most recent (2018) gold mining deforestation in red. We estimate this deforestation to be around 4,265 acres in the two most critical zones: La Pampa and Alto Malinowski. The yellow boxes indicate the location of the zooms described below. At the end of the article, in the Annex, we present the same base map but with all the overlapping land designations as well to illustrate the complexity of the situation.

Base Map. 2018 gold mining deforestation in southern Peruvian Amazon. Data: Planet, UMD/GLAD, MINAM/PNCB

La Pampa

The following images show the gold mining deforestation in the area known as “La Pampa” between January (left panel) and May (right panel) 2018. Note that the second image is in slider format.

Zoom de La Pampa. Datos: Planet, MAAP

[twenty20 img1=”7415″ img2=”7416″ width=”80%” offset=”0.5″]

Alto Malinowski

The following images show the gold mining deforestation in the area known as “Alto Malinowski” between January (left panel) and May (right panel) 2018. Note that the second image is in slider format.

[twenty20 img1=”7417″ img2=”7418″ width=”80%” offset=”0.5″]

Annex

We present the same base map as above, but also with relevant land designations.  Note that much of the deforestation is concentrated in forestry concessions (ironically, in “reforestation” concessions) and in the Kotsimba Native Community, both of which are outside the legal mining corridor and within the buffer zones of Tambopata National Reserve and Bahuaja Sonene National Park. Thus, most, if not all, of the mining activity appears to be illegal.

Citation

Finer M, Villa L, Mamani N (2018) Gold Mining continues to ravage the Peruvian Amazon. MAAP: 87.

Science Magazine_Combating Deforestation: From Satellite to Intervention

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Science Magazine: Combating deforestation: From satellite to intervention
Full text
Reprint (PDF):

*Note: The article can only be viewed for free via this author page.

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A new policy article entitled “Combating deforestation: From satellite to intervention” was just published in Science, one of the leading journals in the world.

The authors include members of Amazon Conservation, World Resources Institute (Global Forest Watch), and Planet.

We first describe how rapidly improving satellite technology has created an unprecedented moment for near real-time monitoring.

We then outline a five-step protocol for near real-time tropical deforestation monitoring, with the goal of bridging the gap between technology and policy.

Satellite image of expanding gold mining deforestation in Peru. Image: Planet.

MAAP #85: Illegal Logging in the Peruvian Amazon, and how Satellites can help address it

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Example of new logging road in the Peruvian Amazon. Data: Planet

We propose a new tool to address illegal logging in the Peruvian Amazon: using cutting-edge satellites to monitor logging road construction in near real-time.

Illegal logging in the Amazon is difficult to detect because it is selective logging of individual valuable trees, not large clear-cuts.

However, a new generation of satellites can quickly detect new logging roads, which in turn may indicate the leading edge of illegal logging.

Here, we analyzed satellite imagery to identify all new logging roads built in the Peruvian Amazon over the past three years (2015-17).

We then show how it is possible to track logging road construction in near-real time, using three satellite-based systems: GLAD alerts, Sentinel-1 (radar satellites), and Planet (optical satellites).

 

 

 

 

 


The Technology

GLAD alerts. Source: GFW

GLAD alerts quickly detect areas of recent forest loss (based on 30 meter resolution Landsat imagery) and highlight those pixels. For example, the image on the right shows GLAD alerts for a recent logging road. The satellites described below can then zoom in on these highlighted areas and continue the monitoring in near real-time.

The European Space Agency’s Sentinel-1 satellites freely offer a new image every 12 days no matter the weather conditions, as radar technology allows it to penetrate clouds (see MAAP #79).

The company Planet has a fleet of 175+ mini satellites, lined up like pearls in a necklace, that are able to capture a high-resolution optical image almost daily, though clouds remain an issue (see MAAP #59).

 

 

 

 

Key Findings

Base Map. Logging roads in the Peruvian Amazon. Data: MAAP, SERNANP, IBC. Click to enlarge.

The Base Map illustrates the location of all logging roads built in the Peruvian Amazon since 2001.

We estimate the construction of 1,365 miles (2,200 km) of logging roads during the last three years (2015-17). We indicate these roads in red.

Note that the roads are concentrated in three zones:

  • Southern Loreto, between Cordillera Azul and Sierra del Divisor National Parks;
  • Southern Ucayali; and
  • Northeast Madre de Dios.

Another important finding is the potential rapid speed of logging road construction: up to 1.5 miles (2.5 km) per week.

Next, we focus on two emblematic logging roads (near Sierra del Divisor and Cordillera Azul National Parks, respectively) to demonstrate the feasibility of near real-time monitoring based on Sentinel-1 and Planet satellites.

 

 

 

 

 

A. Logging Road near Sierra del Divisor

Image A1 is a GIF that shows a series of radar images (Sentinel-1) of the construction of a logging road between 2015 and 2017 just north of Sierra del Divisor National Park. The length of the road is 43 miles (69 km). Image A2 is a Planet image showing the status of the road as of the end of 2017.

Image A1. Construction of logging road near Sierra del Divisor. Data: ESA
Image A2. Logging road near Sierra del Divisor. Data: Planet

B. Logging Road near Cordillera Azul

Image B1 is a GIF that shows a series of radar images (Sentinel-1) of the construction of a logging road between 2015 and 2017 east of Cordillera Azu National Park. The length of the road is 33 miles (53 km). Image B2 is a Planet image showing the status of the road as of the end of 2017.

Image B1. Construction of logging road near Cordillera Azul. Data: ESA
Image B2. Logging road near Cordillera Azul. Data: Planet

Notes

1 Not all illegal logging requires roads, but logging roads may indicate some of the most organized, financed, and large-scale operations.

Coordinates

Zona A: -6.966982,-74.6521
Zona B: -7.650428,-75.552979

Citation

Villa L, Finer M (2018) Illegal Logging in the Peruvian Amazon, and how Satellites can help. MAAP: 85.

MAAP #84: New Threats to the Peruvian Amazon (Part 1: Yurimaguas-Jeberos Road)

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Image A: New Yurimaguas-Jeberos road crossing primary forest. Data: Planet

The efforts and international commitments of the Peruvian Government to reduce deforestation may be compromised by new projects do not have adequate environmental assessment.

In this series, we address the most urgent of these projects, those that threaten large areas of primary Amazonian forest.

We believe that these projects require urgent attention from both government and civil society to ensure an adequate response and avoid irreversible damage. For example, in the case below, it is not known whether there is an environmental impact study.

The first report of this series focuses on a new road (Jeberos – Yurimaguas) that threatens a large expanse of primary forest in the northern Peruvian Amazon (see Image A).

 

 

Yurimaguas-Jeberos Road

Image B. Data: GLAD/UMD, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA

Early warning forest loss alerts (GLAD alerts from the University of Maryland and Global Forest Watch) have detected the construction of a new road between the city of Yurimaguas and the town of Jeberos, in southern Loreto region (see Image B).

We estimate that the new road is 65 km (40 miles). In the image, the arrows indicate part of the route crossing primary forest (indicated in dark green).

Although the road improves the connectivity of an isolated town, the problem is that much of it crosses primary Amazon forest and may trigger massive deforestation. It is well documented that roads are one of the main drivers of deforestation in the Amazon (see MAAP #76).

In addition, most of the route crosses “Permanent Production Forest“, a legal land classification restricted to forestry activities, not agriculture or infrastructure (Image D). The route also crosses a regional conservation priority site (Image D).

It is important to note that the Regional Government of Loreto, which is promoting and financing the project, specifically said in a press statement that the road will “encourage the expansion of the agricultural and livestock frontier in this part of the region.” That phrase can be interpreted as frankly stating that the road will cause extensive deforestation. It is a particularly troubling scenario given that Yurimaguas is already a deforestation hotspot.

 

 

 

 

Image C shows the beginning of road construction between August 2017 (left panel) and April 2018 (right panel).

Image C. Road construction. Data: Planet.

Image D shows how the road crosses Permanent Production Forest and a regional conservation priority site.

Image D. Data: GOREL, MINAGRI, MAAP

Citation

Finer M, Mamani N (2018) New Threats to the Peruvian Amazon (Part 1: Yurimaguas-Jeberos Road). MAAP: 84.

MAAP #83: Climate Change Defense: Amazon Protected Areas and Indigenous Lands

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Base Map. Data: Asner et al 2014, MINAM/PNCB, SERNANP, IBC

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

Here, we show the importance of protected areas and indigenous lands to safeguard these carbon stocks.

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.1,2

In contrast, here we show that protected areas and indigenous lands have safeguarded 3.17 billion metric tons of carbon, as of 2017.3,4

The Base Map (on the right) shows, in shades of green, the current carbon densities in relation to these areas.

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.

The total safeguarded carbon (3.17 billion metric tons) is the equivalent to 2.5 years of carbon emissions from the United States.5

Below, we show several examples of how protected areas and indigenous lands are safeguarding carbon reservoirs in important areas, indicated by insets A-E.

A. Yaguas National Park

The following Image A shows how three protected areas, including the new Yaguas National Park, are effectively safeguarding 202 million metric tons of carbon in the northeastern Peruvian Amazon. This area is home to some of the highest carbon densities in the country.

Image 83a. Yaguas. Data: Asner et al 2014, MINAM/PNCB, SERNANP

B. Manu National Park, Amarakaeri Communal Reserve, CC Los Amigos

The following Image B shows how Los Amigos, the world’s first conservation concession, is effectively safeguarding 15 million metric tons of carbon in the southern Peruvian Amazon. Two surrounding protected areas, Manu National Park and Amarakaeri Communal Reserve, safeguard an additional 194 million metric tons. This area is home to some of the highest carbon densities in the country.

Image 83b. Los Amigos-Manu-Amarakaeri. Data: Asner et al 2014, MINAM/PNCB, SERNANP, ACCA

C. Tambopata National Reserve, Bahuaja Sonene National Park

The following Image C shows how two important natural protected areas, Tambopata National Reserve and Bahuaja Sonene National Park, are helping conserve carbon stocks in an area with intense illegal gold mining activity.

D. Sierra del Divisor National Park, National Reserve Matsés

Image 83d. Data: Asner et al 2014, MINAM/PNCB, SERNANP

The following Image D shows how four protected areas, including the new Sierra del Divisor National Park, and adjacent National Reserve Matsés are effectively safeguarding 270 million metric tons of carbon in the eastern Peruvian Amazon.

This area is home to some of the highest carbon densities in the country.

E. Murunahua Indigenous Reserve

The following Image E shows the carbon protected in the Murunahua Indigenous Reserve (for indigenous peoples in voluntary isolation) and the surrounding titled native communities.

Imagen 83e. Datos: Asner et al 2014, MINAM/PNCB, SERNANP

References

1  UNFCCC. Emissions Summary for Peru. http://di.unfccc.int/ghg_profile_non_annex1

2  No incluye las emisiones por la degradación de bosques

3 Asner GP et al (2014). The High-Resolution Carbon Geography of Perú. Carnegie Institution for Science. ftp://dge.stanford.edu/pub/asner/carbonreport/CarnegiePeruCarbonReport-English.pdf

4 Sistema de Áreas Naturales Protegidas del Perú, que incluye áreas de administración nacional, regional, y privado. Datos de las tierras indígenas son de Instituto de Bien Común. Datos de pérdida forestal son de la Programa Nacional de Conservación de Bosques para la Mitigación del Cambio Climático (MINAM/PNCB).

5 UNFCCC. Emissions Summary for United States. http://di.unfccc.int/ghg_profile_annex1

Citation

Finer M, Mamani N (2017). Climate Change Defense: Amazon Protected Areas and Indigenous Lands. MAAP: 83.

Acknowledgments

This report was made possible by the generous support of the Norwegian Agency for Development Cooperation (NORAD).

MAAP #81: Carbon loss from deforestation in the Peruvian Amazon

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Base Map. Data: MINAM/PNCB, Asner et al 2014

When tropical forests are cleared, the enormous amount of carbon stored in the trees is released to the atmosphere, making it a major source of global greenhouse gas emissions (CO2) that drive climate change.

In fact, a recent study revealed that deforestation and degradation are turning tropical forests into a new net carbon source for the atmosphere, exacerbating climate change.1

The Amazon is the world’s largest tropical forest, and Peru is a key piece of that. Researchers (led by Greg Asner at the Carnegie Institution for Science) recently published the first high-resolution estimate of aboveground carbon in the Peruvian Amazon, documenting 6.83 billion metric tons.2

Here, we analyze this same dataset to estimate the total carbon emissions from deforestation in the Peruvian Amazon between 2013 and 2017. We estimate the loss of 59 million metric tons of carbon during these last five years, the equivalent of around 4% of annual United States fossil fuel emissions.3

We present a series of zoom images to show how carbon loss happened in several key areas impacted by the major deforestation drivers: gold mining, large-scale oil palm and cacao plantations, and smaller-scale agriculture. The labels A-G correspond to the zooms below.

We also show how protected areas are protecting hundreds of millions of metric tons of carbon in some of the most important areas in the country.

On the positive side, having this detailed information may provide added incentives to slow deforestation and degradation as part of critical climate change strategies.

 

 

Major Findings

Data: Asner et al 2014

The base map (see above) shows, in shades of green, carbon densities across Peru. It also shows, in red, the forest loss layer from 2013 to 2017.

We calculated the estimated amount of carbon emissions from forest loss during these five years: 59.029 teragrams, or 59 million metric tons.

The regions with the most carbon loss are 1) Loreto (13.4 million metric tons), 2) Ucayali (13.2 million), 3) Huánuco (7.3 million), 4) Madre de Dios (7 million), and 5) San Martin (6.9 million).

These values include some natural forest loss. Overall, however, they should be considered underestimates because they do not include forest degradation (for example, selective logging).

A recent study revealed that degradation may account for 70% of emissions, thus total carbon emissions from forests in the Peruvian Amazon may be closer to 200 million metric tons.

Next, we show a series of zoom images to show how carbon loss happened in several key areas. We also show how protected areas and conservation concessions are protecting the most important carbon reserves.

 

 

 

 

Zoom A: Central Peruvian Amazon

Image A shows the loss of 2.8 million metric tons of carbon in a section of the central Peruvian Amazon (Ucayali region). On the east side of image, note the loss due to two large-scale oil palm plantations (649,000 metric tons); on the west side, note small-scale agriculture penetrating deeper into high carbon density forest.

Image A. Central Peruvian Amazon. Data: Asner et al 2014, MINAM/PNCB

Zoom B: Southern Peruvian Amazon (gold mining) 

Image B shows the loss of 756 thousand metric tons of carbon due to gold mining in the southern Peruvian Amazon (Madre de Dios region). On the east side of image is the sector known as La Pampa; west side is Upper Malinowski.

Image B. Gold mining. Data: Asner et al 2014, MINAM/PNCB

Zoom C: Southern Peruvian Amazon (agriculture)

Image C shows the loss of 876 thousand metric tons of carbon in the southern Peruvian Amazon around the town of Iberia (Madre de Dios region). Note the expanding carbon loss along both sides of the Interoceanic Highway that crosses the image.

Image C. Iberia. Data: Asner et al 2014, MINAM/PNCB

Zoom D: United Cacao

Image D shows the loss of 291 thousand metric tons of carbon for a large-scale cacao project (United Cacao) in the northern Peruvian Amazon (Loreto region). Note that nearly all the forest clearing occurred in high carbon density forest. This is another line of evidence that the company cleared primary forest, contrary to their claims that the area was already degraded.

Image D. United Cacao. Data: Asner et al 2014, MINAM/PNCB

Zoom E: Yaguas National Park

Image E shows how three protected areas, including the new Yaguas National Park, are effectively safeguarding 202 million metric tons of carbon in the northeastern Peruvian Amazon. This area is home to some of the highest carbon densities in the country.

Image E. Yaguas. Data: Asner et al 2014, MINAM/PNCB

Zoom F: Los Amigos Conservation Concession

Image F shows how Los Amigos, the world’s first conservation concession, is effectively safeguarding 15 million metric tons of carbon in the southern Peruvian Amazon. Two surrounding protected areas, Manu National Park and Amarakaeri Communal Reserve, safeguard an additional 194 million metric tons. This area is home to some of the highest carbon densities in the country.

Image F. Los Amigos. Data: Asner et al 2014, MINAM/PNCB

Zoom G: Sierra del Divisor National Park

Image G. Data: Asner et al 2014, MINAM/PNCB

Image G shows how three protected areas, including the new Sierra del Divisor National Park, are effectively safeguarding 270 million metric tons of carbon in the eastern Peruvian Amazon.

This area is home to some of the highest carbon densities in the country.

 

 

 

 

 

 

 

 

 

 

 

 

Methodology

Para el análisis se utilizó los datos de carbono sobre el suelo  generados por Asner et al 2014, y los datos de pérdida de bosques identificados por el Programa Nacional de Conservación de Bosques (PNBC-MINAM) de los años 2013 al 2016 así como las alertas tempranas del año 2017. Primero uniformizamos los datos de pérdida de bosque 2013-2016 con las alertas tempranas del año 2017 para evitar superposición y tener un solo dato 2013-2017. Posteriormente, extraemos los datos de carbono de las áreas de pérdida de bosque del 2013-2017, este proceso permitió obtener la densidad de carbono (por hectárea) en relación al área de la pérdida de bosque para finalmente estimar el total de stocks de carbono perdido entre el año 2013 al 2017.

References

1 Baccini A, Walker W, Carvalho L, Farina M, Sulla-Menashe D, Houghton RA (2017) Tropical forests are a net carbon source based on aboveground measurements of gain and loss. Science. 13;358(6360):230-4.

2 Asner GP et al (2014). The High-Resolution Carbon Geography of Perú. Carnegie Institution for Science.

3 Boden TA, Andres RJ, Marland G (2017) National CO2 Emissions from Fossil-Fuel Burning, Cement Manufacture, and Gas Flaring: 1751-2014. DOI 10.3334/CDIAC/00001_V2017

Citation

Finer M, Mamani N (2017). Carbon loss from deforestation in the Peruvian Amazon. MAAP: 81.

Acknowledgments

This report was made possible by the generous support of the Norwegian Agency for Development Cooperation (NORAD).