MAAP #19: Gold Mining Deforestation Advancing Along Upper Malinowski River (Madre De Dios, Peru)

In MAAP #5, we described the intensifying deforestation along the Upper Malinowski River in the department of Madre de Dios, Peru. Here in MAAP #19, we update this information and confirm that the deforestation continues at a rapid pace. This finding is based on analysis of three high-resolution images between September 2014 and November 2015. As described below, we document the deforestation of 392 hectares (969 acres) between September 2014 and November 2015 due to gold mining along the Upper Malinowki River.

Image 19a. Gold mining deforestation between September 2014 and 2015 along Upper Malinowski. Data: SERNANP, WorldView-2 from Digital Globe (NextView).
Image 19a. Gold mining deforestation between September 2014 and 2015 along Upper Malinowski. Data: SERNANP, WorldView-2 from Digital Globe (NextView).

Image 19a shows a comparison of two high resolution (0.5 m) images taken one year apart over the same area along the Upper Malinowski River (left panel is from September 2014, while the right panel is from September 2015). Comparison analysis of these images reveals two primary findings. First, deforestation is rapidly spreading upstream along the Upper Malinowski and its tributaries.

Second, this deforestation is nearing the border of the Bahuaja Sonene National Park boundary (see Image 19b).

Image 19c. Deforestation analysis between September and November 2015 along the Upper Malinowski. Data: CLASlite, SERNANP, WorldView-2 from Digital Globe (NextView).
Image 19c. Deforestation analysis between September and November 2015 along the Upper Malinowski. Data: CLASlite, SERNANP, WorldView-2 from Digital Globe (NextView).

Deforestation Analysis

Image 19c is a detailed deforestation analysis between the two images. We documented the deforestation of 352 hectares (870 acres) due to gold mining activities between September 2014 and September 2015 along the Upper Malinowski (note: this calculation covers the area displayed in Image 19a).

Image 19c. Deforestation analysis between September and November 2015 along the Upper Malinowski. Data: CLASlite, SERNANP, WorldView-2 from Digital Globe (NextView).
Image 19b. Zoom of gold mining deforestation near the Bahuaja Sonene National Park. Data: SERNANP, WorldView-2 from Digital Globe (NextView).

During preparation of this article, a new high resolution image over the same area from November 2015 became available. As an indication of how rapidly the gold mining is advancing, we documented an additional deforestation of 40 hectares (99 acres) between September and November 2015.

Thus, we documented a total deforestation of 392 hectares (969 acres) between September 2014 and November 2015 along the Upper Malinowki.


Two Gold Mining Deforestation Fronts

The Upper Malinowki is just west (and upstream) of the mining zone known as La Pampa featured in MAAP articles #1, #12, and #17. These currently appear to be the two major gold mining deforestation fronts in Madre de Dios. Image 19b illustrates the general location of these two areas (“C” indicates La Pampa and “D” indicates the Upper Malinowski). Note that La Pampa is within the buffer zone of the Tambopata National Reserve and the Upper Malinowski is within the buffer zone of the Bahuaja Sonene National Park.

Imagen 19d. General location of the Alto Malinowski (“D”) and La Pampa (“C”). Data: CLASlite, MINAM, SERNANP, ACCA, Hansen/UMD/Google/USGS/NASA, USGS.
Imagen 19d. General location of the Alto Malinowski (“D”) and La Pampa (“C”). Data: CLASlite, MINAM, SERNANP, ACCA, Hansen/UMD/Google/USGS/NASA, USGS.

 


Citation

Finer M, Snelgrove C (2015) Gold Mining Deforestation Rapidly Advancing along Upper Malinowski River (Madre de Dios, Peru). MAAP: 19.

MAAP #18: Proliferation of Logging Roads in The Peruvian Amazon

MAAP articles #3 and #15 detailed the construction of several new logging roads in the central Peruvian Amazon. Here in MAAP 18, we provide a more comprehensive analysis of the proliferation of logging roads in this section of the Amazon. In Image 18a, we show a high resolution example of a new logging road in this area with active construction during 2015 (see Inset A1 in Image 18c for more context).

Image 18a. New logging road in the Peruvian Amazon. Data: WorldView-2 of Digital Globe (NextView).
Image 18a. New logging road in the Peruvian Amazon. Data: WorldView-2 of Digital Globe (NextView).

Image 18b illustrates the location of all identified logging roads in the central Peruvian Amazon (southern Loreto and northern Ucayali). Most of these roads are located along the Ucayali River and its headwater tributaries. The left panel highlights just the logging roads, while the right panel also includes protected areas, native communities, and logging concessions.

Image 18b. Logging roads in the central Peruvian Amazon. Data: SERNANP, IBC, USGS, MINAGRI.
Image 18b. Logging roads in the central Peruvian Amazon. Data: SERNANP, IBC, USGS, MINAGRI.

In Image 18b, we documented the construction of 1,134 km of logging roads between 2013 and 2015 in the central Peruvian Amazon. Of this total, 538 km is in the matrix of logging concessions and native communities in southern Ucayali, 226.1 km is in undesignated areas in southern Loreto, 210 km is in the buffer zone of Cordillera Azul National Park, and 159 km is around the new Sierra del Divisor National Park.

Note that the buffer zone of Cordillera Azul National Park and surroundings of Sierra del Divisor National Park contain logging concessions and native communities, thus the responsibility of forest authority is the regional government.

Determining the legality of these roads is complex. As the right panel highlights, many of these roads are near logging concessions and native communities, whom may have obtained the rights for logging from the relevant forestry authority (in many cases, the regional government).

Below, we focus on the logging roads in the northern section of Image 18b (see Inset A).

Zoom A: Logging Roads in Southern Loreto/Northern Ucayali

 

Image 18c. Logging roads in southern Loreto/northern Ucayali. Data: SERNANP, IBC, USGS, MINAGRI.
Image 18c. Logging roads in southern Loreto/northern Ucayali. Data: SERNANP, IBC, USGS, MINAGRI.

Image 18c is a zoom of the logging roads shown in the northern section of Image 18a (Inset A), located in southern Loreto and northern Ucayali. It shows five primary areas of interest. Both Insets A1 and A2 correspond to new roads within the southeast buffer zone of the Cordillera Azul National Park with active construction in 2015 (see below for more details).

Insets A3, A4, and A5 correspond to roads with active construction between 2013 and 2015 that have already been featured on MAAP. Inset 3 includes a logging road in the northeast sector of the buffer zone of Cordillera Azul National Park (see MAAP #3 for more details). Insets 3 and 5 show logging roads around the new Sierra del Divisor National Park (see MAAP #15 and MAAP #7 for more details).

Zoom A1: Logging Roads in Nuevo Irazola

Image 18d provides more details about a new logging road with very recent construction within the southeast buffer zone of Cordillera Azul National Park (See Inset A1 in Image 18C for context). This road has grown 68 km between 2013 and 2015, with more than half of this construction occurring over the past year. According to information obtained from the forestry department within the Regional Government of Ucayali (PRMRFFS), the native community of Nuevo Irazola made a logging permission request for industrial and/or commercial use and prepared an Annual Operating Plan. However, a high-resolution (0.5 m) image shows a recent stretch of the road exceeds the area requested for forestry activities (see Image 18d).

Image 18d. High-resolution image of a new forest road in the southeast buffer zone of Cordillera Azul National Park. Data: WorldView-2 of Digital Globe (NextView).
Image 18d. High-resolution image of a new forest road in the southeast buffer zone of Cordillera Azul National Park. Data: WorldView-2 of Digital Globe (NextView).

Zoom A2: Rapid Expansion of a Logging Road

 

Image 18e. Time series of a forest road in the southeast buffer zone of Cordillera Azul National Park. Data: USGS.
Image 18e. Time series of a forest road in the southeast buffer zone of Cordillera Azul National Park. Data: USGS.

Image 18e illustrates the rapid expansion of another forest road located in the southeast section of the Cordillera Azul National Park buffer zone (See Inset A2 in Image 18C for context). We documented the construction of 29.1 km during the six weeks between September 10 (left panel) and October 20 (right panel), a rate of nearly five kilometers per week. The legality of this road is currently unknown, but note that it is extending in the direction of a forestry concession.

Citation

Novoa S, Fuentes MT, Finer M, Pena N, Julca J (2015) Proliferation of Logging Roads in the Peruvian Amazon. MAAP #18.

Note: MAAP #18 is a collaborative effort between Amazon Conservation Association (ACA), Conservación Amazónica (ACCA), and the Centro de Conservación Investigación y Manejo de Áreas Naturales (CIMA).

MAAP #17: Birth of A New Illegal Gold Mining Zone in The Peruvian Amazon [High Resolution View]

In MAAP #12, we featured a high resolution image from July 29, 2015 of the area known as “La Pampa,” a hotspot of illegal mining in the buffer zone of the Tambopata National Reserve (Madre de Dios region, Peru).

Just seven weeks later, we obtained a new high resolution image of La Pampa for September 16, 2015. Image 17a shows the birth of a new gold mining zone between the July image (left panel) and September image (right panel) (see the letter “A” in Image 17b for context). The current extent of this new clearing is 1.5 hectares. This mining activity is illegal since it is located within the buffer zone of the Tambopata National Reserve.


Reference Map

Image 17b is the reference map, showing the forest cover change between July (left panel) and September (right panel) 2015. In the right panel, the letter “A” corresponds to Image 17a, while the letter “B” corresponds to Image 17c.

Image 17b. Reference map. Data: WorldView Digital Globe (NextView).
Image 17b. Reference map. Data: WorldView Digital Globe (NextView).

Expanding Deforestation

Image 17c shows the deforestation expanding to the west between July (left panel) and September (right panel) 2015.

Image 17c. Deforestation expanding to the west between July and September 2015. Data: WorldView Digital Globe (NextView).
Image 17c. Deforestation expanding to the west between July and September 2015. Data: WorldView Digital Globe (NextView).

Citation

Finer M, Olexy T (2015) High Resolution View: Birth of a New Illegal Mining Zone. MAAP #17.

MAAP #16: Oil Palm-Driven Deforestation in The Peruvian Amazon (Part 2: Shanusi)

In MAAP #4 we described the major deforestation caused by two new large-scale oil palm projects in the central Peruvian Amazon (Nueva Requena, Ucayali region).

Here in MAAP #16, we describe the major deforestation related to two other oil palm projects, Palmas del Shanusi and Palmas del Oriente, in the northern Peruvian Amazon (regions Loreto and San Martin). These projects (operated by Grupo Palmas, an agriculture company owned by Grupo Romero) cover 10,029 hectares.

Image 16a. Deforestation within and around the two large-scale oil palm projects Palmas del Shanusi and Oriente. Data: PNCB, USGS, Grupo Palmas.
Image 16a. Deforestation within and around the two large-scale oil palm projects Palmas del Shanusi and Oriente. Data: PNCB, USGS, Grupo Palmas.

Image 16a shows the extensive forest clearing within and around Palmas del Shanusi and Oriente. The 2000-2014 forest loss data comes from the Peruvian government (PNCB-MINAM/SERFOR-MINAGRI) and the 2015 data comes from our analysis of Landsat imagery using CLASlite forest monitoring software.

Within the two projects, we documented that Grupo Palmas cleared 6,974 hectares of primary forest between 2006 and 2011 (see Images 16a and 16b). This represents 70% of the projects’ area (Peruvian law requires the conservation of 30% of an agricultural project area’s forest cover). Thus, a key issue is that the Peruvian legal framework, under certain conditions, allows the clearing of thousands of hectares of primary forest for large-scale agriculuture projects (see the report Deforestation by Definition by the Environmental Investigation Agency for more details).

We defined primary forest as an area characterized by dense, closed-canopy coverage from the earliest available Landsat image (in this case 1994) until immediately prior to plantation installation.

Importantly, we also documented the clearing of an additional 9,840 hectares of primary forest immediately surrounding the projects (see Images 16a and 16b). There was clearing of more than a thousand hectares each year between 2010 and 2013, followed by another thousand hectares between 2014 and 2015. Analysis of high-resolution imagery confirms that much of this additional clearing resulted in large-scale model oil palm plantations.

In total, we documented the clearing of over 16,800 hectares of primary forest for large-scale oil palm plantations within and around Palmas del Shanusi and Oriente. It is important to note that there has now been more forest clearing outside than inside the original projects, an important lesson for other new agricultural areas such as Tamshiyacu.

Image 16b. Primary forest cleared within and around Grupo Palmas projects.
Image 16b. Primary forest cleared within and around Grupo Palmas projects.

High Resolution Zooms

Following is a series of high resolution zooms showing examples of forest clearing within and around Palmas del Shanusi and Oriente. Image 16c is the reference map indicating the location of the various zooms (Images 16d – 16g). Zooms 16d and 16e show the same area before (left panel) and after (right panel) forest clearing. Zooms 16f and 16g show areas of recent forest clearing.

Image 16c. Reference Map. Data: USGS.
Image 16c. Reference Map. Data: USGS.
Image 16d. High-resolution zoom A; deforestation outside the Grupo Palmas project. Data: Google Earth, WorldView-2 from Digital Globe (NextView).
Image 16d. High-resolution zoom A; deforestation outside the Grupo Palmas project. Data: Google Earth, WorldView-2 from Digital Globe (NextView).
Image 16e. High-resolution zoom B; forest clearing within the Grupo Palmas project. Data: Google Earth, WorldView-2 from Digital Globe (NextView).
Image 16e. High-resolution zoom B; forest clearing within the Grupo Palmas project. Data: Google Earth, WorldView-2 from Digital Globe (NextView).
Image 16f. High-resolution zoom C. Data: Google Earth, WorldView-2 from Digital Globe (NextView).
Image 16f. High-resolution zoom C. Data: Google Earth, WorldView-2 from Digital Globe (NextView).
Image 16g. High-resolution zoom D. Data: Google Earth, WorldView-2 from Digital Globe (NextView).
Image 16g. High-resolution zoom D. Data: Google Earth, WorldView-2 from Digital Globe (NextView).

References

This work builds off of information presented in the following publication: Environmental Investigation Agency. Deforestation by Definition. 2015. Washington, DC. Link: http://eia-global.org/news-media/deforestation-by-definition


Citation

Finer M, Novoa S (2015) Oil Palm-driven Deforestation in the Peruvian Amazon (Part 2: Shanusi) MAAP: Image #16. Link: https://maaproject.org/2015/10/image16-shanusi/

Image #15: Sierra Del Divisor – New Logging Road Threatens Northern Section of Proposed National Park

In MAAP #7, we emphasized the need to promote the Sierra del Divisor Reserved Zone to the category of National Park due to the growing threats within and around the area. Here in MAAP #15, we show how the construction of a new logging road threatens the northwest section of the current Reserved Zone. New high-resolution images reveal that the construction of this logging road has continued to expand in 2015, and now even crosses a corner of the Reserve.

In addition, in anticipation of the upcoming visit of Peruvian President Ollanta Humala to the United Nations in New York to discuss climate change, we present data on the levels of carbon stored in the proposed Sierra del Divisor National Park.

Image 15a. Landsat (30 m res) images of the new logging road crossing the Sierra del Divisor Reserved Zone. Data: USGS, SERNANP
Image 15a. Landsat (30 m res) images of the new logging road crossing the Sierra del Divisor Reserved Zone. Data: USGS, SERNANP

Image 15a shows the most recent expansion of the logging road between June (left panel) and September (right panel) 2015. For more context, note that the area displayed in Image 15a corresponds to the dashed box marked with the letter “A” in Image 15c.

Image 15b displays a high-resolution (1.5 m) image from August 7 of the section of road crossing the northern section of the Sierra del Divisor Reserved Zone.

Image 15b. High-resolution image of logging road crossing northern tip of Reserved Zone. Data: SPOT 7 Airbus.
Image 15b. High-resolution image of logging road crossing northern tip of Reserved Zone. Data: SPOT 7 Airbus.

Expansion 2012 – 2015

In Figure 15c, we show the expansion of this logging road from 2012 to 2015, totaling approximately 75 km of new road construction during these three years.

Image 15c. Expansion of the logging road in the northeast sector of the Reserve Zone. Data: MINAM-PNCB/MINAGRI-SERFOR, SERNANP, USGS.
Image 15c. Expansion of the logging road in the northeast sector of the Reserve Zone. Data: MINAM-PNCB/MINAGRI-SERFOR, SERNANP, USGS.

Carbon Data

 

Imagen 15d. High-resolution carbon geography of Sierra del Divisor area. Data: Asner et al. 2014 a,b.
Imagen 15d. High-resolution carbon geography of Sierra del Divisor area. Data: Asner et al. 2014 a,b.

Dr. Greg Asner (from the Carnegie Institution for Science) and colleagues recently produced a high-resolution carbon map of Peru (Asner et al. 2014 a,b).

According to this data, the Sierra del Divisor Reserved Zone has the second largest carbon stock among all Peruvian protected areas (behind only Alto Purus National Park).

As seen in Image 15d, much of the proposed national park area contains high to very high carbon levels. Using this data, we calculated that the proposed Sierra del Divisor National Park contains approximately 165 million metric tons of above-ground carbon.

 

SERNANP Response

In response to this article, SERNANP (the Peruvian protected areas agency) issued this statement:

The deforestation alert in the northwest sector parallel to the Sierra del Divisor Reserved Zone is caused by the improvement of an alleged older road that runs along the natural protected area, which is being operateded by a neighboring forest concessionaire. We denounced this before the Special Prosecutor for Environmental Matters in Loreto in 2012, as we considered it irregular and a threat to the protected area.

[La deforestación que se advierte en el sector noroeste paralelo a la Zona Reservada Sierra del Divisor se origina por el mejoramiento de una supuesta carretera antigua que viene ejecutando un concesionario forestal colindante con el área natural protegida, la cual denunciamos ante la Fiscalía Especializada de Materia Ambiental – Loreto en el año 2012, por considerarla irregular y constituirse en una amenaza a este espacio protegido.] This past August, the Special Prosecutor scheduled an inspection, which was conducted jointly with the Public Prosecutor of the Ministry of the Environment. We have been making every effort to ensure that the Special Prosecutor performs the corresponding actions according to law, such as requiring OSINFOR to supervise the forest concessionaire due to the irregular events that we denounced.

[Recién en agosto último la Fiscalía programó la inspección fiscal, que se realizó conjuntamente con la Procuraduría Pública del Ministerio del Ambiente, en la cual venimos realizando todos los esfuerzos para que la Fiscalía Especializada realice las actuaciones que corresponde de acuerdo a Ley, así como requerir al OSINFOR supervise al concesionario forestal, por los hechos irregulares que denunciamos.] Lima, 17 de setiembre del 2015

References

Asner GP, Knapp DE, Martin RE, Tupayachi R, Anderson CB, et al. (2014 a) Targeted carbon conservation at national scales with high-resolution monitoring. Proceedings of the National Academy of Sciences, 111(47), E5016-E5022.

Asner GP, Knapp DE, Martin RE, Tupayachi R, Anderson CB, et al. (2014 b) The high-resolution carbon geography of Peru. Berkeley, CA: Minuteman Press.


Citation

Finer M, Novoa S (2015) Sierra del Divisor – New logging road crosses northern section of Reserve Zone MAAP: Image #15. Link: https://maaproject.org/2015/09/image15-sierra-divisor/

 

MAAP #14: Cusco – Increasing Deforestation Driven by Coca and Gold Mining

In MAAP #14 we take our first detailed look at the region of Cusco. The city of Cusco is of course well known as the former capital of the Inca empire and current gateway to Machu Picchu, but the greater Cusco region is a vast area including large tracts of Amazon forest. Here, we focus on the eastern Cusco region, an area that is experiencing increasing deforestation from gold mining and coca cultivation.

Image 14a. Recent deforestation patterns in northeast Cusco region. Data: PNCB, USGS, SERNANP, IBC.
Image 14a. Recent deforestation patterns in northeast Cusco region. Data: PNCB, USGS, SERNANP, IBC.

Key Results

We highlight two major expanding deforestation zones in the eastern Cusco region. Both zones are along major tributaries of the Araza River, which itself is a tributary of the Inambari River.

1) Nuciniscato River (see Zoom A). We documented a major deforestation spike since 2010 along this river and its major tributaries. Since 2010, there has been deforestation of 764 ha, much of which appears to be related to gold mining.

2) Nojonunta River (see Zoom B). We document a recent (2014) deforestation surge in this area, much of which appears to be related to coca cultivation.

Data Description

In the following maps:

Any variation of green in the satellite imagery indicates areas of forest cover.

Yellow (2000-2004), orange (2005-2008), red (2009-2012), and purple (2013) indicate areas that were deforested between 2000 and 2013 according to data from the National Program of Forest Conservation for the Mitigation of Climate Change (PNCB) of the Ministry of the Environment of Peru.

The colors pink (2014) and turquoise (2015) indicate areas that were deforested in the last two years based on our analysis of Landsat imagery using CLASlite forest monitoring software.

Zoom A: Nuciniscato River

 

Image 14b. Zoom A (see Image 12a for context). Data: PNCB, USGS, SERNANP, IBC.
Image 14b. Zoom A (see Image 12a for context). Data: PNCB, USGS, SERNANP, IBC.

We documented the deforestation of 967 ha along the Nuciniscato River and its major tributaries since 2000. Image 14b shows that the vast majority (79% or 764 ha) of this deforestation has occurred since 2010. Peak deforestation occurred in 2012 (219 ha) and dipped slightly in 2014 (115 ha).

As noted in MAAP #6, part of this deforestation (along the upper Nuciniscato River) is entering the buffer zone of the Amarakaeri Communal Reserve.

Zooms A1 and A2: Examples of Deforestation in 2015

To better understand the principal deforestation drivers along the Nuciniscato River, we acquired high resolution satellite imagery. Much of the recent deforestation since 2010 is characteristic of gold mining: along river courses with forest clearing, earth removal, and waste-water lagoons. Images 14c and 14d both show very recent deforestation (between February and August 2015) with these characteristics.

Image 14c. Zoom A1 (see Image 14b for context). Data: SPOT 7 from Airbus, GeoEye from Digital Globe (NextView).
Image 14c. Zoom A1 (see Image 14b for context). Data: SPOT 7 from Airbus, GeoEye from Digital Globe (NextView).
Image 14d. Zoom A2 (see Image 14b for context). Data: SPOT 7 from Airbus, GeoEye from Digital Globe (NextView).
Image 14d. Zoom A2 (see Image 14b for context). Data: SPOT 7 from Airbus, GeoEye from Digital Globe (NextView).

Zoom B: Nojonunta River

 

Image 14e. Zoom B (see Image 21a for context). Data: PNCB, USGS.
Image 14e. Zoom B (see Image 21a for context). Data: PNCB, USGS.

We documented the deforestation of 477 ha along the Nojonunta River since 2000. Image 14e shows that the vast majority (85% or 403 ha) of this deforestation has occurred since 2010. Peak deforestation occurred in 2014 (207 ha), particularly in the upper Nojonunta.

Zoom B1: Deforestation Driven by Coca Cultivation

 

Image 14f. Zoom B1. Data: SPOT 7 from Airbus, UNODC 2014.
Image 14f. Zoom B1. Data: SPOT 7 from Airbus, UNODC 2014.

In the recent UNODC (United Nations Office on Drugs and Crime) report “Monitoreo de Cultivos de Coca 2014” [Coca Crop Monitoring 2014], it was reported that the area around the Nojonunta River (coca zone San Gabán) has a medium to high density of coca cultivation.

Image 14f displays the UNODC coca density data (left panel) in relation to a recent high resolution satellite image of the area (right panel). Thus, the data indicates that coca cultivation is a major driver of the deforestation detected in this case.

Citation

Finer M, Novoa S (2015) Increasing deforestation in Northeast Cusco region from coca and gold mining. MAAP: Image #14. Link: https://maaproject.org/2015/09/image-14-cusco/

MAAP #13: Clearing of Primary Forest for Cacao Resumes in Tamshiyacu (Loreto, Peru)

As confirmed in MAAP #9, the company United Cacao (through its subsidiary in Peru, Cacao Peru North) cleared 2,126 hectares of primary forest between May 2013 and August 2014 to establish a large-scale cacao plantation outside the town of Tamshiyacu, in northeastern Peru (Loreto region). New satellite imagery reveals that the forest clearing has recently resumed in 2015. We detected the cutting of 150 hectares in recent months, bringing the total area cleared as part of the United Cacao project to 2,276 hectares.

Image 13a shows a series of satellite images (NASA Landsat) taken between November 2014 and August 2015. In these images, a clearing of 24 hectares was detected in the period from November 2014 to June 2015. This reduction in forest clearing was possibly because of the Resolution issued by the Ministry of Agriculture, which temporarily paralyzed the agricultural activities of United Cacao.

However, more recent images have revealed a large increase in forest clearing – 126 hectares – between June and August 2015.

This brings to 2,276 ha the total forest clearing generated by the United Cacao project between May 2013 and August 2015.

In the Landsat images, the dark green color indicates forest cover, the light green secondary vegetation, the pink color indicates exposed ground (a key indicator of forest clearing), while scattered patches in black and white indicate clouds and their shadows.

Forest clearing between June and August 2015

 

Image 13b Base map indicating the location of a series of zooms. Data: USGS.
Image 13b Base map indicating the location of a series of zooms. Data: USGS.

Image 13b indicates the location of a number of zooms (see below) that clearly illustrate the forest clearing that occurred between June and August 2015. The images 13c – 13e are of each respective zoom and show each area before and after the forest clearing. Note that Worldview-3 imagery resolution is 33 cm and Worldview-2 imagery resolution is 50 cm.

Imagen 13c. Zoom A. Data: WorldView from Digital Globe (NextView).
Imagen 13c. Zoom A. Data: WorldView from Digital Globe (NextView).
Image 13d. Zoom B. Data: WorldView from Digital Globe (NextView).
Image 13d. Zoom B. Data: WorldView from Digital Globe (NextView).
Image 13e. Zoom C. Data: WorldView from Digital Globe (NextView).
Image 13e. Zoom C. Data: WorldView from Digital Globe (NextView).

Changing the Cacao Production Model in Peru

According to a recent interview with the President of United Cacao, the company is adopting the agro-industrial model. In other words, it is changing cacao production in Peru from the traditional small-scale model sited on long-deforested land for the agro-industrial model that requires large land parcels that are normally occupied by forests.

Image #12: High-Resolution View of Illegal Gold Mining Deforestation in La Pampa (Madre De Dios, Peru)

In MAAP #1, we described the expansion of deforestation through February 2015 in La Pampa, a gold mining hotspot located in the Madre de Dios region in the southern Peruvian Amazon. Since then, we have obtained a new high-resolution image showing the current situation (as of late July 2015) in great detail in La Pampa.

Here in MAAP #12, we present an analysis with the following three objectives: 1) Update data for the recent expansion of gold mining deforestation in La Pampa, 2) show a series of high-resolution images that illustrate the scale and magnitude of current gold mining operations, and 3) illustrate how the Tambopata National Reserve currently represents a good defense against deforestation expansion.

Image 12a. High-resolution images showing the expansion of deforestation by gold mining in La Pampa between August 2014 and July 29, 2015. Data: GeoEye and WorldView2 from Digital Globe (NextView).
Image 12a. High-resolution images showing the expansion of deforestation by gold mining in La Pampa between August 2014 and July 29, 2015. Data: GeoEye and WorldView2 from Digital Globe (NextView).

Image 12a shows, in high resolution, the expansion of gold mining deforestation in La Pampa during the last year (between August 2014 and July 2015). The red square indicates the main zone of deforestation.


Deforestation 2014-15

 

Image 12b. CLASlite Results 2014-15. Data: USGS, SERNANP.
Image 12b. CLASlite Results 2014-15. Data: USGS, SERNANP.

Image 12b shows the CLASlite results of the expansion of gold mining deforestation in La Pampa during the past year (between August 2014 and July 2015). We found deforestation of 725 hectares (Ha) in the last year, including 224 Ha since February (the date of the last image analyzed in the MAAP #1). This equates to nearly 1,000 soccer fields of deforestation throughout the year.

High Resolution View – July 2015

This series of maps illustrates the scale and magnitude of gold mining operations in La Pampa as of July 29, 2015, just two weeks after a major raid by the Peruvian government against illegal gold mining camps.

Image 12c. Zoom A (see Image 12a for context). Date of image: July 29, 2015. Data: WorldView2 from Digital Globe (NextView).
Image 12c. Zoom A (see Image 12a for context). Date of image: July 29, 2015. Data: WorldView2 from Digital Globe (NextView).

Image 12c displays, in high-resolution, the current center of the mining activity in La Pampa. Note that it is a zoom of zone A indicated in Image 12a. One can see the high density of gold mining operations and infrastructure in almost every area of the image. Also note in Image 12c that the location of four additional zooms described below are also shown.

Images 12d – g show a series of additional zooms from four different locations within the center of the current mining activity in this sector of La Pampa and highlights the scale and magnitude of operations.

Image 12d. Zoom B (see Image 12c for context). Data: WorldView2 from Digital Globe (NextView).
Image 12d. Zoom B (see Image 12c for context). Data: WorldView2 from Digital Globe (NextView).
Image 12e. Zoom C (see Image 12c for context). Data: WorldView2 from Digital Globe (NextView).
Image 12e. Zoom C (see Image 12c for context). Data: WorldView2 from Digital Globe (NextView).
Image 12f. Zoom D (see Image 12c for context). Data: WorldView2 from Digital Globe (NextView).
Image 12f. Zoom D (see Image 12c for context). Data: WorldView2 from Digital Globe (NextView).
Image 12g. Zoom E (see Image 12c for context). Data: WorldView2 from Digital Globe (NextView).
Image 12g. Zoom E (see Image 12c for context). Data: WorldView2 from Digital Globe (NextView).

Tambopata National Reserve: Defense Against Deforestation

Image 12h illustrates how the Tambopata National Reserve remains a good defense against deforestation.

Image 12h. Tambopata National Reserve. Date of Image: July 29, 2015. Data: WorldView2 from Digital Globe (NextView).
Image 12h. Tambopata National Reserve. Date of Image: July 29, 2015. Data: WorldView2 from Digital Globe (NextView).

SERNANP Response

In response to this article, SERNANP (the Peruvian protected areas agency) issued this statement:

The area known as La Pampa is located in the buffer zone of the Tambopata National Reserve (RNTAMB) in the Madre de Dios region.

“El sector denominado La Pampa se encuentra ubicado en la zona de amortiguamiento de la Reserva Nacional Tambopata (RNTAMB) en la región Madre de Dios.”

In its capacity as lead agency of natural protected areas of Peru, SERNANP has been making great efforts to deal with illegal mining and other activities that threaten the Reserve. As part of these actions, we carried out monitoring in this region through images from LANDSAT 8). This monitoring system has confirmed the excellent state of conservation of the Reserve. Information has also been collected by park guards on patrols conducted along the Malinowski River and on monitoring trails located within the protected area.

“En su calidad de ente rector de las áreas naturales protegidas del Perú, el SERNANP viene realizando grandes esfuerzos para hacer frente a la minería ilegal y otras actividades que amenacen a la Reserva. Como parte de estas acciones se realiza un monitoreo mediante imágenes (LANSAT 8), sistema que ha corroborado el óptimo estado de conservación de la Reserva, información que ha sido recopilada también por los guardaparques en los patrullajes realizados a lo largo del río Malinowski y en las trochas de monitoreo ubicadas al interior del área protegida.”

Similarly, this system has allowed SERNANP to collect information on threats in the buffer zone, data that has been shared promptly with leading authorities on illegal mining. This information is centered on points of access to the buffer zone, trails, gas stations, distances, among others; this has contributed to the development and implementation of the strategy against illegal mining in the Tambopata Natural Reserve.

“Asimismo, este sistema ha permitido recopilar información sobre las amenazas en la zona de amortiguamiento, datos que han sido compartidos oportunamente con las principales autoridades competentes en materia de minería ilegal. Esta información está centrada en puntos de acceso a la zona de amortiguamiento, trochas, grifos, distancias, entre otros; lo que ha contribuido en la elaboración y aplicación de la estrategia de la RN Tambopata contra la minería ilegal.”

This strategy also includes the continued involvement and support of the Chief of the Tambopata National Reserve on issues related to the promotion of economic activities and the exploitation of natural resources by local populations, promoting tourism as a strategy for conservation of the protected area, lectures on environmental education, and others.

“Esta estrategia comprende también la permanente participación y apoyo de la Jefatura de la Reserva Nacional Tambopata en temas relacionados con el impulso de actividades económicas como el aprovechamiento de recursos naturales por parte de las poblaciones locales, la promoción del turismo como estrategia de conservación del área protegida, charlas de educación ambiental, entre otros.”


Citation

Finer M, Olexy T (2015) High Resolution View of Illegal Gold Mining in La Pampa (Madre de Dios, Peru). MAAP #12. Link: https://maaproject.org/2015/08/image12-lapampa/

Image #11: Importance of Protected Areas in The Peruvian Amazon

The Peruvian national protected areas system, known as SINANPE, is critically important to Amazon conservation efforts in the country.

There are currently 46 protected areas in the Peruvian Amazon under national or regional administration*. In total, these areas cover 19.5 million hectares and include a wide variety of designations, including areas of indirect use (those with strict protection, such as National Parks) and direct use (those that allow the exploitation of natural resources, such as National Reserves) under national administration and Regional Conservation Areas under regional administration.

Here, MAAP #11 presents a deforestation analysis that demonstrates the effectiveness of protected areas in relation to the surrounding landscape in the Peruvian Amazon.

Image 11a. Recent forest loss in relation to protected areas in the Peruvian Amazon. Data: SERNANP, PNCB-MINAM/SERFOR-MINAGRI, NatureServe.
Image 11a. Recent forest loss in relation to protected areas in the Peruvian Amazon. Data: SERNANP,

Key Results

Image 11a shows recent (2000 – 2013) forest loss patterns in relation to the current national protected area system in the Peruvian Amazon (Image 11b shows the same, but with zooms of the northern, central, and southern regions, respectively). Note that some of the documented forest loss surely comes from natural causes, such as landslides or meandering rivers.

Across all protected areas administered nationally (such as National Parks and National Reserves), we found that deforestation was significantly lower starting at 2 km within their boundaries compared to outside them (see Images 11b and 11c).

The rate of deforestation outside of protected areas is more than twice of that within them (within the 5 km buffer zone study area, see below).

Image 11b. Regional zooms (north, central, south) of recent forest loss in relation to protected areas. Data: SERNANP, PNCB-MINAM/SERFOR-MINAGRI, NatureServe.
Image 11b. Regional zooms (north, central, south) of recent forest loss in relation to protected areas. Data: SERNANP, PNCB-MINAM/SERFOR-MINAGRI, NatureServe.

Deforestation Analysis – Methods

We conducted a basic analysis of all protected areas administered nationally (National Park, National Sanctuary, Historic Sanctuary, National Reserve, Protection Forest, Communal Reserve, and Reserved Zone) to estimate their relative effectiveness in controlling deforestation in relation to the surrounding landscape. The forest loss data comes from the National Program of Forest Conservation for the Mitigation of Climate Change (PNCB) of the Ministry of the Environment of Peru. This deforestation analysis had two key components.

Image 11c. Illustration of spatial intervals for deforestation analysis.
Image 11c. Illustration of spatial intervals for deforestation analysis.

First, we compared recent forest loss within versus outside each protected area at four different spatial intervals: 1 km, 2 km, 3 km, and 5 km (see Image 11c). In other words, starting at the boundary line for each area, we created a 1 km buffer both inside and outside the area and compared the relative (forest loss/area *100) deforestation. We then repeated this analysis for the other intervals. The establishment of these intervals areas is based on the assumption that the closer to the limits of each protected area, deforestation could be more related to anthropogenic activities in surrounding areas, which is expected to reduce the effect of natural losses due to changes in the courses of rivers and landslides in unstable areas.

Second, we controlled for protected area creation date. If an area was created prior to 2000, such as Manu National Park created in 1973, we used the complete 2000-2013 PNCB forest loss dataset. If an area was created after 2000, such as Alto Purus National Park created in 2004, we used just the forest loss dataset for the years following its creation (in this case, 2005-2013).

This analysis was designed to show general patterns, not be a definitive evaluation of the effectiveness of protected areas. A more complete evaluation could control for additional variables (such as slope, elevation, climate, distance to population centers, etc…).

Deforestation Analysis – Results

 

Image 11d. Results of deforestation analysis.
Image 11d. Results of deforestation analysis.

Across all protected areas administered nationally, we found that deforestation was significantly lower starting at 2 km within their boundaries compared to outside them (p < 0.05) (see Image 11d). The significance level increased by an order of magnitude between 3 and 5 km. We didn’t detect a significant difference between 1 km within and outside the protected area boundaries.

On average, we found that 0.5% of the area within protected areas experienced forest loss between 2000-2013, while outside the protected areas was nearly 1.2%. In other words, the rate of deforestation outside of protected areas is more than twice of that within them. Furthermore, as mentioned earlier, some forest loss within the protected areas surely comes from natural causes, such as landslides or meandering rivers.

Related Studies

As noted above, this analysis was designed to show general patterns, not be a definitive evaluation of the effectiveness of protected areas. Several other recent studies have pointed out the importance of controlling for additional variables.

In a study focused on the Brazilian Amazon, Pfaff et al (PLOS ONE 2015) found that is important to control for the location of protected areas, which is often in more isolated areas with lower deforestation pressures.

Specifically regarding the Peruvian Amazon, a study by the research organization Resources for the Future (2014) found that “the average protected area reduces forest cover change”. This study rigorously controlled for a number of key variables (such as elevation, slope, climate, and distance to cities), but used older and more limited forest loss and protected areas data.

*This total of 46 protected areas includes: a) all the categories considered part of SINANPE (including Reserved Zones and Regional Conservation Areas) except for Private Conservation Areas, and b) all areas that are totally or partially located in the Amazon basin.

SERNANP Response

In response to this article, SERNANP (the Peruvian protected areas agency) issued this statement:

Actualmente el SERNANP viene realizando una verificación en campo por parte del personal guardaparque de las Áreas Naturales Protegidas durante sus acciones de patrullaje merced a la información de pérdida de bosque proporcionada por el Ministerio del Ambiente, periodo 2013-2014, a fin de determinar si el cambio de la cobertura se debe a causas naturales o antrópicas. Esto podrá complementar el análisis desarrollado por ACCA.

Es importante señalar, que el SERNANP viene aplicando el enfoque ecosistémico en la planificación y gestión de las Áreas Naturales Protegidas, en este sentido desarrolla acciones que permiten evitar la deforestación al interior de estos espacios protegidos, pero a su vez nos proponemos que en su entorno se desarrollen actividades compatibles con la conservación que eviten el fraccionamiento del hábitat y permitan la sostenibilidad de la conservación de las Áreas Naturales Protegidas a futuro.

En este sentido, considerando de vital importancia generar alianzas con las entidades que toman decisiones en el territorio fuera de estos espacios, hemos establecido a nivel nacional un trabajo conjunto con los Gobiernos Regionales a fin de integrar las Áreas Naturales Protegidas dentro de corredores de conservación con otras modalidades de conservación que se impulsan a través de sus sistemas regionales de conservación. Con ello, se esperaría detener el fraccionamiento de hábitat alrededor de las Áreas Naturales Protegidas, lo que podría conllevar a su insostenibilidad a futuro. Al respecto, es preciso mencionar que los Sistemas Regionales de Conservación cuentan con un espacio de coordinación donde se reúnen las principales instituciones que gestionan territorio y en la cual se discuten las iniciativas de desarrollo social y económico para que se realicen en armonía con la conservación de la biodiversidad del país, el SERNANP forma parte de estos espacios a nivel nacional.


Citation

Finer M, Novoa S (2015) Importance of Protected Areas in the Peruvian Amazon. MAAP: Image #11. Link: https://maaproject.org/2015/08/image-11-protected-areas

MAAP #9: Confirming Forest Clearing for Cacao in Tamshiyacu (Loreto, Peru) Came from Primary Forest

Recall that in Image #2 we documented the rapid clearing of 2,126 hectares of primary forest between May 2013 and August 2014 for a new cacao project outside of the town of Tamshiyacu in the northern Peruvian Amazon (Department of Loreto).

However, the company that carried out the forest clearing (United Cacao, through its wholly-owned subsidiary in Peru, Cacao del Peru Norte) has responded “that this area had been used for farming since the late 1990s, and thus it was not primary forest…There was no high-conservation-value forest on that land (Cannon JC, 2015, mongabay.com).” In addition, the company’s website states that “The site was heavily logged of all tropical hardwoods in the 1980s.”

Here, in Image #9, we 1) publish new high-resolution (33 cm) satellite imagery that shows how the cacao project is expanding into dense, closed-canopy forest and 2) detail exactly how we determined that the vast majority of the clearing indeed came from primary forest. These findings are critically important because the company has major expansion plans.

Image of the Week 9a. Mosaic of very high-resolution (33 cm) images of the United Cacao plantation near Tamshiyacu, Peru, in June 2015. Colors indicate insets. Data: WorldView-3 from Digital Globe (NextView).
Image of the Week 9a. Mosaic of very high-resolution (33 cm) images of the United Cacao plantation near Tamshiyacu, Peru, in June 2015. Colors indicate insets. Data: WorldView-3 from Digital Globe (NextView).

Key Results:

We obtained very high-resolution (33 cm) satellite imagery taken over the United Cacao plantation in June 2015 (see Image 9a). In this imagery, one can clearly see that the cacao project is embedded and expanding into dense, closed-canopy forest.

We analyzed a series of satellite (Landsat) images dating back to 1985 to determine that, prior to the arrival of United Cacao in 2013, the project area 1) had NOT been used for major farming activities, 2) was NOT heavily logged of all tropical hardwoods, and 3) was dominated (98%) by primary forest (see Image 9b). In fact, by analyzing spectral signatures in the Landsat images, we confirm that the area cleared by United Cacao in 2013 was dominated by primary forest (see Image 9c).

We show data from the Carnegie Airborne Observatory showing that the majority of the United Cacao project area had the highest possible value of carbon (over 150 tons per hectare) immediately prior to the forest clearing in 2013.

Finally, we present information indicating that the current documented forest clearing of 2,126 hectares may soon double or triple.

Landsat Time-series

 

Image 9b. Landsat time-series (1985-2012) of the future United Cacao plantation area (indicated by black box) prior to arrival of the company. Data: USGS
Image 9b. Landsat time-series (1985-2012) of the future United Cacao plantation area (indicated by black box) prior to arrival of the company. Data: USGS

Image 9b displays a series of Landsat images dating back to 1985 showing that, prior to the arrival of United Cacao, the area was dominated (nearly 98%) by primary forest and NOT used for major agriculture activities or heavily logged of all tropical hardwoods.

In these Landsat images, dark green indicates forest cover, light green indicates secondary vegetation, pink indicates exposed ground (and is therefore a key indicator of recent forest clearing), and the scattered white and black spots indicate clouds and their shade.

In 1985, the future cacao project area (indicated by black box) was completely covered by forest with no signs of clearing, major logging, or farming. By 1995, there were a few scattered areas of cleared forest in the center of the future project area. By 2005, there was a slight expansion of these cleared areas in the center of the future project area. By 2012, immediately before the start of forest clearing, the future project area appeared much the same: a few scattered areas of cleared forest in the center, but the vast majority of the area was primary forest.

We defined primary forest as an area that from the earliest available image (in this case, from 1985) was characterized by dense closed-canopy coverage and experienced no major clearing events.

NDVI Analysis

 

Image 9c. NDVI analysis of the United Cacao plantation area prior to arrival of the company. Letters indicate significance (i.e., “a” values are significantly different than “b” values). Data: USGS.
Image 9c. NDVI analysis of the United Cacao plantation area prior to arrival of the company. Letters indicate significance (i.e., “a” values are significantly different than “b” values). Data: USGS.

To further investigate the issue of primary forest, we used the Landsat imagery to conduct an NDVI (Normalized Difference Vegetation Index) analysis. NDVI is a common index of photosynthetic activity, or “greenness,” based on the fact that different surfaces (primary forest, secondary forest, water, bare ground, etc…) reflect light (visible and near-infrared) differently.

As seen in Image 9c, we obtained NDVI measurements across four different years (1985, 1995, 2005, and 2012) for 100 random points from each of three different areas: 1) area cleared by United Cacao in 2013 (orange dots), 2) nearby protected area that is proxy for primary forest (yellow dots), and 3) disturbed area along a major river that is proxy for secondary forest (purple dots).

For all four years, we found that the NDVI values for the area cleared by United Cacao in 2013 were similar to those of the nearby protected area (in fact, these values were nearly identical in 1985 and 1995), but significantly different than the disturbed area along the major river. In other words, the forest cleared by United Cacao was nearly identical to our proxy for primary forest and significantly different than our proxy for secondary forest. Thus, we conclude that United Cacao cleared over 2,000 hectares of primary forest in 2013.

Carbon Data Tells the Same Story

 

Image 9d. High-resolution carbon map of United Cacao plantation area (indicated by black box) prior to forest clearing. Data: Asner et al (2014) The high-resolution carbon geography of Peru. Berkeley, CA: Minuteman Press.
Image 9d. High-resolution carbon map of United Cacao plantation area (indicated by black box) prior to forest clearing. Data: Asner et al (2014) The high-resolution carbon geography of Peru. Berkeley, CA: Minuteman Press.

The Carnegie Airborne Observatory, led by Dr. Greg Asner, and the Peruvian Ministry of Environment, recently produced a high-resolution carbon geography of Peru. Interestingly, they mapped the carbon content of the United Cacao plantation area immediately prior to the forest clearing.

As seen in Image 9d, the vast majority of the United Cacao project area had the highest possible value of carbon (over 150 tons per hectare) immediately prior to the forest clearing in 2013. The only exceptions were the scattered previously cleared areas identified in Image 9b.

According to Asner, “The carbon levels were extremely high, indicating that they were large, intact forests that we normally picture when we think of primary Amazon forest.”

More Forest Clearing Coming…

 

Image 9e. Project area map from the United Cacao website.
Image 9e. Project area map from the United Cacao website.

According to its website, United Cacao owns around 3,250 hectares near Tamshiyacu, and this total may soon increase to 4,000 hectares. In addition, the company has started an initiative with local farmers that may include an additional 3,250 hectares.

Thus, the current documented forest clearing of 2,126 hectares may soon double or triple.

Finally, it is worth mentioning that we detected a sawmill within the project area. This discovery raises the question, Has the company obtained the necessary permits for this activity?

Image 9f. A sawmill detected within the cacao project area. Inset: The pink dot indicates location of sawmill within the project area. Data: WorldView-3 de Digital Globe (NextView).
Image 9f. A sawmill detected within the cacao project area. Inset: The pink dot indicates location of sawmill within the project area. Data: WorldView-3 de Digital Globe (NextView).

Citation

Finer M, Novoa S (2015) Demonstrating that Forest Clearing for Cacao in Tamshiyacu (Loreto, Peru) came from Primary Forest. MAAP: Image #8. Link: https://maaproject.org/2015/06/image-9-cacao-tamshiyacu/