MAAP #48: Oil Palm Deforestation in the central Peruvian Amazon

Image 48a. Data: UMD/GLAD
Image 48a. Data: UMD/GLAD

In MAAP #26, we presented a 2015 Deforestation Hotspots map for the Peruvian Amazon, which showed that the highest concentration of deforestation is located in the central Amazon region.

Here, we zoom in on one of these hotspots, located in the northern Huanuco region along its border with San Martin (see Inset E of Image 48a).*

We found that the main deforestation driver in this hotspot was the establishment of small- and medium-scale oil palm plantations.**

*Note that we analyzed the hotspots in Insets A-D in MAAP #26 and MAAP #37.

** We defined small-scale as less than 5 hectares, medium-scale as 5-50 hectares, and large-scale as greater than 50 hectares

 

 

 

 

Image 48b. Data: ACA, Hansen/UMD/Google/USGS/NASA
Image 48b. Data: ACA, Hansen/UMD/Google/USGS/NASA

Oil Palm Causing Deforestation

Image 48b shows our area of interest.

The San Martin side is characterized by large- and medium-scale plantations (yellow), while the Huanuco side is characterized by small- and medium-scale plantations.

Red indicates areas deforested and converted to oil palm plantations between 2010 and 2014, according to our analysis of high-resolution satellite imagery.

We estimate the deforestation of 558 hectares (1,370 acres) for establishment of oil palm plantations between 2010-2014 in northern Huanuco. Two-thirds of the plantations are medium scale (5-50 hectares) and the remaining third are small-scale (<5 hectares).***

Historical forest loss data indicates that most of the deforestation occurred in secondary forests, with a smaller percentage in primary forests.

***See MAAP #32 for more information on the importance of knowing the size of the deforestation events.

 

 

Image 48c. Data: ACA, Hansen/UMD/Google/USGS/NASA
Image 48c. Data: ACA, Hansen/UMD/Google/USGS/NASA

High-Resolution Zooms

Image 48c shows a zoom of our area of interest.

The insets indicate the areas shown below with satellite imagery from August 2009 (left panel) and October 2015 (right panel).

Each image shows the existence of forest in 2009 replaced by oil palm in 2015 (the red dot is a point of reference indicating the same spot across time).

huanucooilpalm_zoome2_engver3

Image 48d. Data: Digital Globe (Nextview)
Image 48d. Data: Digital Globe (Nextview)
huanucooilpalm_zoome4_eng
Image 48e. Data: Digital Globe (Nextview)

Citation

Finer M, Olexy T (2016) Oil Palm Deforestation in the central Peruvian Amazon. MAAP: 48.

MAAP #42: Papaya – New Deforestation Driver in Peruvian Amazon

In the previous MAAP #26, we published a preliminary map of Deforestation Hotspots in the Peruvian Amazon for 2015. Subsequently in 2016, we have been compiling information to improve understanding on the potential causes (drivers) of deforestation in the identified hotspots. In this article, we focus on a medium-intensity hotspot located along the newly paved Interoceanic Highway in the eastern part of the Madre de Dios region (see Inset A in Image 42a).

Image 42a. Data. UMD/GLAD, MTC, MAAP
Image 42a. Data. UMD/GLAD, MTC, MAAP

The analysis in this article is based on field work carried out by the Peruvian Ministry of Environment, in collaboration with Terra-i. This team has verified the presence of papaya plantations in the area indicated by Inset A and shared their photos and coordinates with MAAP to allow us to search for and analyze relevant satellite imagery.

Synthesizing all of the available information, we found that the establishment of papaya plantations was an important deforestation driver in the area in 2015. Within the focal area (Inset A), we estimate the deforestation of 204 hectares (504 acres) for papaya plantations in 2015, a major increase relative to 2014 (see bar graph in Image 42a).

All of the papaya deforestation is small (< 5 hectares) or medium (5-50 hectares) scale. According to the analysis presented in MAAP #32, these two scales represented 99% of the deforestation events in Peru in 2015. Approximately 90% of the observed deforestation is within areas zoned for agricultural activity. Therefore, the legality of the deforestation in not known (i.e. if all the required permits were obtained).

Below, we show satellite images and field photos of 5 examples of the recent deforestation caused by papaya cultivation.

Example #1

Image 42b shows the deforestation of 12 hectares between September 2013 (left panel) and January 2016 (right panel). The red point indicates the same place in both images. Image 42c is a photo of the new papaya plantation in this area.

Image 42b. Data: Digital Globe (Nextview), Planet Labs
Image 42b. Data: Digital Globe (Nextview), Planet Labs
c. point-37-source-minam---dgot-detection-by-terra-i-8132014-driver-papaya_25582479922_o
Image 42c. Photo: MINAM/DGOT, Terra-i

Example #2

Image 42d shows the deforestation of 5 hectares between September 2013 (left panel) and January 2016 (right panel). The red point indicates the same place in both images. Image 42e is a photo of the new papaya plantation in this area.

Image 42d. Digital Globe (Nextview), Planet Labs
Image 42d. Digital Globe (Nextview), Planet Labs
e. point-11-source-minam-detection-by-terra-i-112015-driver-papaya_25051222004_o
Image 42e. Photo: MINAM/DGOT, Terra-i

Example #3

Image 42f shows the deforestation of 5 hectares between September 2013 (left panel) and January 2016 (right panel). The red point indicates the same place in both images. Image 42g is a photo of the new papaya plantation in this area.

Image 42f. Digital Globe (Nextview), Planet Labs
Image 42f. Digital Globe (Nextview), Planet Labs
Imagen G. MINAM/DGOT, Terra-i
Image 42g. MINAM/DGOT, Terra-i

Example #4

Image 42h shows the deforestation of 12 hectares between September 2013 (left panel) and May 2016 (right panel). The red point indicates the same place in both images. Image 42i is a photo of the new papaya plantation in this area.

Image 42h. MINAM/DGOT, Terra-i
Image 42h. MINAM/DGOT, Terra-i
Imagen I. MINAM/DGOT, Terra-i
Image 42i. Photo: MINAM/DGOT, Terra-i

Example #5

Image 42j shows the deforestation of 9 hectares between April 2015 (left panel) and May 2016 (right panel). The yellow boxes indicate the same place in both images. Image 42k is a photo of the new papaya plantation in this area.

Image 42j. MINAM/DGOT, Terra-i
Image 42j. MINAM/DGOT, Terra-i
Imagen J. MINAM/DGOT, Terra-
Image 42k. Photo: Farah Carrasco

Citation

Finer M, Novoa S, Carrasco F (2016) Papaya – Potential New Driver of Deforestation in Madre de Dios. MAAP: 42.

MAAP #37: Deforestation Hotspot in the central Peruvian Amazon driven by Cattle Pasture

Image 36a. Data: UMD/GLAD
Image 37a. Data: UMD/GLAD

In the previous MAAP #26, we presented a map of Deforestation Hotspots in the Peruvian Amazon during 2015*. This analysis showed that the highest concentration of deforestation is in the central Peruvian Amazon.

Here in MAAP #37, we focus on this region, as indicated by Image 37a. Specifically, we analyze the hotspots shown in Insets C and D, located in the eastern section of the department of Huanuco.

(Note that we previously described the hotspots indicated by Insets A and B, located in northwest Ucayali department, in MAAP #26).

For 2015, we calculated a total deforestation of 7,930 hectares (19,595 acres) in the area indicated by these two insets. The main deforestation driver is likely cattle pasture (see below). It is worth noting that the vast majority of the deforested area (87%) is outside of areas zoned for agriculture use.

We calculated an additional deforestation of 16,590 hectares (41,000 acres) in 2013 and 2014. Again, the vast majority of the forest loss appears to be outside areas zoned for agriculture use.

 

 

 

 

Deforestation Driver: Cattle Pasture

The predominant land use in the area is cattle pasture, so that is likely the leading driver of the documented deforestation.

We took a sample (1,500 hectares) of areas that were deforested in 2014, and found that 76% (1,140 hectares) were converted to cattle pasture in 2015. All sample areas were greater than 5 hectares and had available high-resolution imagery from September 2015. Based on an analysis of the imagery, we estimate that a similar amount of area was being cleared for pasture in 2015.

Below, we show a series of high-resolution images of this deforestation (click each image to enlarge).

Inset C Hotspot

Huanuco_zoomC_v5
Image 37b. Data: PNCB/MINAM, UMD/GLAD, MTC

Image 37b shows a detailed view of the deforestation inside the area indicated by Inset C.

In this area, we documented deforestation of 5,050 hectares in 2015. Of this total, 46% of the deforestation events were small-scale (<5 ha), 43% were medium-scale (5-50 ha), and 12% were large-scale (>50 ha).

We calculated an additional deforestation 0f 9,940 hectares in 2013 and 2014.

In Image 37c we show, in high resolution, an example of the recent deforestation in this area between August 2014 (left panel) and September 2015 (right panel). See Inset C1 for context.

Huanuco_C1_v5_DG
Image 37c. Data: WorldView of Digital Globe (NextView).

Inset D Hotspot

Huanuco_zoomD_v5
Image 37d. Data: PNCB/MINAM, UMD/GLAD, MTC

Image 37d shows a detailed view of the deforestation inside the area indicated by Inset D.

In this area, we documented deforestation of 2,883 hectares in 2015. Of this total, 44% of the deforestation events were small-scale (<5 ha), 51% were medium-scale (5-50 ha), and 6% were large-scale (>50 ha).

We calculated an additional deforestation of 6,650 hectares in 2013 and 2014.

In Images 37e – 37f, we show, in high resolution, two examples of the recent deforestation in this area between June (left panel) and September (right panel) of 2015. See Insets D1 and D2 for context.

Huanuco_D1_v3_DG
Image 37e. Data: WorldView of Digital Globe (NextView).
Huanuco_D2_v2_DG
Image 37f. Data: WorldView of Digital Globe (NextView).

References

* Based on the data from the GLAD alerts, produced by the University of Maryland, Google, and Global Forest Watch. http://www.globalforestwatch.org/map/5/-9.31/-75.01/PER/grayscale/umd_as_it_happens

*Hansen, M.C., A. Krylov, A. Tyukavina, P.V. Potapov, S. Turubanova, B. Zutta, S. Ifo, B. Margono, F. Stolle, and R. Moore. Humid tropical forest disturbance alerts using Landsat data. Environ. Res. Lett. 11: 034008.


Citation

Finer M, Novoa S, Cruz C, Peña N (2016) Deforestation Hotspot in the central Peruvian Amazon. MAAP: 37.

MAAP #32: Large-scale vs. Small-scale Deforestation in the Peruvian Amazon

Graph 32a. Data: PNCB/MINAM, UMD/GLAD
Graph 32a. Data: PNCB/MINAM, UMD/GLAD

In the previous MAAP #25 and MAAP #26, we illustrated deforestation hotspots in the Peruvian Amazon for the periods 2012-2014 and 2015*, respectively. Here in MAAP #32, we present a complementary analysis based on the size of deforestation events.

Graph 32a shows the comparative results of deforestation patterns between 2013 and 2015, indicating that:
Small-scale (< 5 hectares) accounted for the vast majority of deforestation events (70-80%) each year.
Medium-scale (5-50 hectares) accounted for approximately 20% of the deforestation events each year.
Large-scale (> 50 hectares) deforestation was variable. In 2013, the year with the most activity of new cacao and oil palm plantations, it accounted for 8% of the deforestation events. In 2015 it was only 1%.

In summary, small- and medium-scale deforestation events represent more than 90% of the total and a constant threat, while large-scale deforestation events represents a latent threat. As described below, large-scale projects can quickly cause massive deforestation events, and should therefore remain a high priority.

*We have increased our deforestation estimate for 2015 to 163,238 hectares (403,370 acres), the second highest on record (behind only 2014). This estimate is based on GLAD alerts, produced by University of Maryland, Google, and Global Forest Watch.

Base Map

Image 32a shows, in graphic form, the deforestation patterns described above for 2013 (left panel) and 2015 (right panel). Further below, we show zooms for three key zones in the north, central, and south, respectively.

Categ_13_15_v1_en
Image 32a. Data: PNCB/MINAM, UMD/GLAD

Northern Peruvian Amazon

Image 32b shows a zoom of the northern Peruvian Amazon for 2013 (left panel) and 2015 (right panel). In general, there is a pattern of small-scale deforestation along the rivers of Loreto. Additionally, in 2013, there were large-scale deforestation events for a cacao project located to the southeast of the city of Iquitos (see MAAP #27 for more details) and for oil palm plantations along the border of Loreto and San Martin regions (see MAAP #16 for more details). In 2015, the expansion of deforestation continued in these areas, but at a medium-scale.

Categ_13_15_n_v1_en
Image 32b. Data: PNCB/MINAM, UMD/GLAD

Central Peruvian Amazon

Image 32c shows a zoom of the central Peruvian Amazon for 2013 (left panel) and 2015 (right panel). In general, there is a concentration of small- and medium-scale deforestation between northwest Ucayali and southeast Huánuco. Additionally, in 2013, there is large-scale deforestation for two new oil palm plantations located northeast of the city of Pucallpa (see MAAP #4 for more details).

Categ_13_15_c_v1_en
Image 32c. Data: PNCB/MINAM, UMD/GLAD

Southern Peruvian Amazon

Image 32d shows a zoom of the southern Peruvian Amazon for 2013 (left panel) and 2015 (right panel). In general, there is a pattern of small- and medium-scale deforestation along the Interoceanic highway in Madre de Dios. Additionally, there is the persistence of large-scale deforestation in southern Madre de Dios related to illegal gold mining (see MAAP #12 for more details).

Categ_13_15_s_v1_en
Image 32d. Data: PNCB/MINAM, UMD/GLAD

Citation

Finer M, Novoa S (2016) Large-scale vs. Small-scale Deforestation in the Peruvian Amazon. MAAP: 32.

MAAP #26: Deforestation Hotspots in the Peruvian Amazon, 2015

Thanks to the newly launched GLAD alerts (developed by the University of Maryland and Google1, and presented by Global Forest Watch), we now have weekly access to high-resolution forest loss data across Peru. Here in MAAP #26, we analyze the first batch of this data to better understand deforestation patterns in the Peruvian Amazon in 2015. In the coming weeks and months, we will use this map as a base for investigating major hotspots of forest loss in the country.

Kernell_2015a_v1_en
Image 26a. Kernel density map for forest loss in the Peruvian Amazon in 2015. Data: Hansen et al 2016 (ERL).

According to the GLAD alert data, total estimated forest loss in Peru in 2015 was 158,658 hectares (392,050 acres). If confirmed, that represents the second highest total on record, behind only 2014 (177,500 hectares).

To better understand where the GLAD alert data was concentrated in 2015, we conducted kernel density estimation, a type of analysis that calculates the magnitude per unit area of a particular phenomenon (in this case, forest loss). Image 26a shows the kernel density map for forest loss in the Peruvian Amazon in 2015. It reveals that recent deforestation was concentrated in a number of hotspots in the departments of Huánuco, Madre de Dios, and Ucayali.

Note that in MAAP #25, we conducted this same type of analysis for 2012 – 2014 forest loss data. Thus, with this latest analysis we can see how deforestation trends shifted in 2015.

Insets A and B highlight an area in central Peru (department of Ucayali) where deforestation intensified in 2015. See below for high-resolution images showing the deforestation in these areas. In the coming weeks and months, we will be publishing additional articles highlighting other key 2015 deforestation hotspots.

 

 

 

 

 

 

 

 

Inset A

MAAP_Coronel_Portillo_29a_v1_en
Image 26b. 2000-15 deforestation for area in Inset A. Data: Hansen et al 2016 (ERL), PNCB/MINAM, Hansen/UMD/Google/USGS/NASA, USGS (Landsat 8)

Image 26b shows detailed deforestation information for the area indicated in Inset A (from Image 26a). Note the extensive 2015 deforestation just to the west of two large-scale oil palm plantations (201 hectares, see pink areas).

Further below, Image 26c shows a high-resolution satellite image of the area in Inset A1 before (left panel) and after (right panel) the recent deforestation events.

 

MAAP_Coronel_Portillo_29b_v1_m_en
Image 26c. High-resolution view of area in Inset A1 before (left panel) and after (right panel) recent deforestation events. Data: WorldView-2 de Digital Globe (NextView).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Inset B

MAAP_Coronel_Portillo_29d_v1_en
Image 26d. 2000-15 deforestation for area in Inset B from Image Xa. Data: Hansen et al 2016 (ERL), PNCB/MINAM, Hansen/UMD/Google/USGS/NASA, USGS (Landsat 8)

Image 26d shows detailed deforestation information for the area indicated in Inset B (from Image 26a). Note the extensive 2015 deforestation along the Aguaytia River (164 hectares, see pink areas). Recent deforestation (2012-14) appears to be associated with agricultural and logging activities.

Further below, Image 26e shows a high-resolution satellite image of the area in Inset B1 before (left panel) and after (right panel) the recent deforestation events.

MAAP_Coronel_Portillo_29c_v1_m_en
Image 26e. High-resolution view of area in Inset B1 before (left panel) and after (right panel) recent deforestation events. Data: WorldView-2 de Digital Globe (NextView).

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Methodology

We conducted this analysis using the Kernel Density  tool from Spatial Analyst Tool Box of ArcGis 10.1 software. Our goal was to emphasize local concentrations of deforestation in the raw data while still representing overarching patterns of deforestation between 2012 and 2014. We accomplished this using 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.

Reference

1 Hansen, M.C., A. Krylov, A. Tyukavina, P.V. Potapov, S. Turubanova, B. Zutta, S. Ifo, B. Margono, F. Stolle, and R. Moore. Humid tropical forest disturbance alerts using Landsat data. Environmental Research Letters, in press. Accessed through Global Forest Watch on March 2, 2016. www.globalforestwatch.org

Citation

Finer M, Novoa S, Snelgrove C (2015) 2015 Deforestation Hotspots in the Peruvian Amazon. MAAP: 26.

MAAP #25: Deforestation Hotspots in the Peruvian Amazon, 2012-2014

Deforestation continues to increase in the Peruvian Amazon. According to the latest information from the Peruvian Environment Ministry1, 2014 had the highest annual forest loss on record since 2000 (177,500 hectares, or 438,600 acres per year). 2013 and 2012 had the third and fourth-highest annual forest loss totals, respectively (behind only 2009).

Source: PNCB/MINAM
Source: PNCB/MINAM

To better understand where this deforestation is concentrated, we conducted kernel density estimation. This type of analysis calculates the magnitude per unit area of a particular phenomenon (in this case, forest loss).

Image 25a shows the kernel density map for forest loss in the Peruvian Amazon between 2012 and 2014 and reveals that recent deforestation is concentrated in a number of “hotspots” in the departments of Loreto, San Martin, Ucyali, Huanuco, and Madre de Dios.

Insets A-D highlight four areas with high densities of forest loss described in previous MAAP articles. We are currently studying the other high density deforestation areas not included in the insets.

 

 

 

 

Inset A: Cacao in Loreto

Image 25a. Kernel density map for forest loss in the Peruvian Amazon between 2012 and 2014. Data: PNCB/MINAM, Hansen/UMD/Google/USGS/NASA.
Image 25a. Kernel density map for forest loss in the Peruvian Amazon between 2012 and 2014. Data: PNCB/MINAM, Hansen/UMD/Google/USGS/NASA.
Image Xb.
Image 25b. Deforestation for cacao in northern Peru between December 2012 (left panel) and September 2013 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA

Inset A (from Image 25a) indicates the deforestation of over 2,000 hectares (4,940 acres) on property owned by the company United Cacao (through its wholly owned Peruvian subsidiary, Cacao del Peru Norte) near the town of Tamshiyacu in the department of Loreto. MAAP #9 demonstrated that much of this deforestation took place at the expense of primary forest. Image 25b highlights this area, showing the forest loss between December 2012 (left panel) and September 2013 (center panel; the pinkish areas indicate recently cleared forests). The right panel shows the cumulative deforestation between 2012 and 2014. See MAAP #9 and MAAP #2 for more details.

 

Inset B: Oil Palm in Loreto/San Martin

Peru_KD_B_3panel_v1
Image 25c. Deforestation for oil palm in northern Peru between September 2011 (left panel) and September 2014 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA

Inset B (from Image 25a) indicates expanding deforestation within and around two large-scale oil palm plantations along the Loreto-San Martin border. Image 25c highlights this area, showing the forest loss between Setpember 2011 (left panel) and September 2014 (center panel). The right panel shows the cumulative deforestation between 2012 and 2014 (6,363 hectares, or 15,700 acres). See MAAP #16 for more details.

Inset C: Oil Palm in Ucayali

Image Xd.
Image 25d. Deforestation for oil palm in central Peru between September 2011 (left panel) and September 2013 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA

Inset C (from Image 25a) indicates the deforestation of 9,400 hectares (23,200 acres) of primary forest for two large-scale oil palm plantations in the department of Ucayali. Image 25d highlights this area, showing the forest loss between September 2011 (left panel) and September 2013 (center panel; the pinkish-black areas indicate recently cleared forests). The right panel shows the cumulative deforestation between 2012 and 2014. See MAAP #4 for more details.

Inset D: Gold Mining in Madre de Dios

Peru_KD_D_3panel_v1
Image 25e. Deforestation for gold mining in southern Peru between September 2011 (left panel) and September 2014 (center panel) and cumulative 2012-14 (right panel). Data: USGS, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA

Inset D (from Image 25a) indicates the extensive illegal gold mining deforestation in the buffer zone of Tambopata National Reserve in the department of Madre de Dios. Image 25e highlights this area, showing the forest loss between September 2011 (left panel) and September 2014 (center panel; the lighter areas indicate recently cleared forests). The right panel shows the cumulative deforestation between 2012 and 2014 (4,738 hectares, or 11,700 acres). See MAAP #1 for more details.

It is important to emphasize that in this case, extensive deforestation continued in 2015. See MAAP #12 and MAAP #24 for more details.

Methodology

We conducted this analysis using the Kernel Density  tool from Spatial Analyst Tool Box of ArcGis 10.1 software. Our goal was to emphasize local concentrations of deforestation in the raw data while still representing overarching patterns of deforestation between 2012 and 2014. We accomplished this using the following parameters:

Search Radius: 15000 layer units (meters)

Kernel Density Function: Quadratic

Cell Size in the map: 200 x 200 meters (4 hectares)

Everything else was left to the default setting.

References

1MINAGRI-SERFOR/MINAM-PNCB (2015) Compartiendo una visión para la prevención, control y sanción de la deforestación y tala ilegal.

Citation

Finer M, Snelgrove C, Novoa S (2015) Deforestation Hotspots in the Peruvian Amazon, 2012-2014. MAAP: 25.

MAAP #23: Increasing Deforestation along lower Las Piedras River (Madre de Dios, Peru)

The Las Piedras River in the southern Peruvian Amazon (department of Madre de Dios) is increasingly recognized for its outstanding wildlife (for example, see this video by naturalist and explorer Paul Rosolie, and this trailer for the upcoming film Uncharted Amazon). As seen in Image 23a, its headwaters are born in the Alto Purus National Park, but the lower Las Piedras is surrounded by a mix of different types of forestry concessions (logging, Brazil nut harvesting, ecotourism, and reforestation).

Here in MAAP #23, we document the growing deforestation on the lower Las Piedras River in the area surrounding the community of Lucerna (see red box in Image 23a for context).

Image Xa. Las Piedras River and surrounding designations. Data: MINAGRI, IBC, SERNANP.
Image 23a. Las Piedras River and surrounding designations. Data: MINAGRI, IBC, SERNANP.

Deforestation Analysis

Image 23b shows our deforestation analysis for an area along the lower Las Piedras River near the community of Lucerna (see red box in Image 23a for context). We found a sharp increase in deforestation starting in 2012. In the 11 years between 2000 and 2011, we detected the deforestation of 88 hectares (218 acres). In contrast, in the 4 years between 2012 and 2015, we detected the deforestation of 472 hectares (1,166 acres). 2015 had the highest deforestation total with 155 hectares (383 acres).

Image Xb. Lower Las Piedras River deforestation analysis. Data: MINAGRI, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA.
Image 23b. Lower Las Piedras River deforestation analysis. Data: MINAGRI, CLASlite, PNCB/MINAM, Hansen/UMD/Google/USGS/NASA.

Note that the Las Piedras Amazon Center (LPAC) Ecotourism Concession represents an effective barrier to deforestation. However, note that two other, less active, ecotourism concessions are experiencing extensive deforestation. The 4,460 hectare LPAC concession (which was created in 2007 and transferred to ARCAmazon in March 2015) hosts an active tourist lodge, research center,  and Forest Ranger Protection Program, which employs local people to patrol the area while monitoring wildlife and human impacts.

Image Xc. Recent Landsat image showing deforestation along lower Las Piedras. Data: USGS,MINAGRI.
Image 23c. Recent Landsat image showing deforestation along lower Las Piedras. Data: USGS,MINAGRI.

Image 23c shows a very recent (December 2015) Landsat image of the deforestation highlighted in Image 23b. The pinkish-red areas indicate the most recently cleared forests. We have received information indicating that much of this new deforestation is associated with cacao plantations. Cacao is of course used to produce chocolate.

Citation

Finer M, Pena N (2015) Increasing Deforestation along lower Las Piedras River (Madre de Dios, Peru). MAAP #23

MAAP Synthesis #1: Patterns and Drivers of Deforestation in the Peruvian Amazon

We present a preliminary analysis of current patterns and drivers of deforestation in the Peruvian Amazon. This analysis is largely based on the first 15 articles published on MAAP between April and September 2015, but also incorporates information from other relevant sources. We describe this analysis as preliminary because as MAAP research continues, we will be able to improve and refine our synthesis in subsequent editions.

MAAP_Synthe_Sa_v4_en
Image S1a. Recent patterns and drivers of deforestation in the Peruvian Amazon. Numbers indicate relevant MAAP article. Data: SERNANP, IBC, MINAM-PNCB/MINAGRI-SERFOR, MAAP.

Introduction & Summary of Key Results

Image S1a illustrates recent (2000 – 2013) patterns of deforestation in the Peruvian Amazon based on data from the Peruvian Ministries of Environment[i] and Agriculture[ii]. These two Ministries have documented a total forest loss of around 1.65 million hectares (ha) in the Peruvian Amazon between 2001 and 2014, with an increasing trend in recent years (2014 had the highest forest loss on record with 177,571 ha)[iii],[iv]. Another recent report by the Peruvian government stated that the majority (75%) of the Amazonian deforestation is due to small-scale clearings related to agriculture and livestock activities, usually near roads or rivers[v].

Building off of that historical and annual information, our goal at MAAP is to monitor deforestation in near real-time. Since April 2015, we have published numerous articles analyzing areas in the northern, central, and southern Peruvian Amazon. In this initial analysis, we have found that three of the most important drivers of deforestation are large-scale oil palm (and cacao) plantations, gold mining, and coca cultivation. We also found a growing network of logging roads that contribute to forest degradation. Image S1a displays the general geographic distribution of these drivers of deforestation and degradation.

We estimate that around 30,000 hectares of primary forest was cleared since 2000 for large-scale oil palm and cacao plantations. Cacao has recently joined oil palm as a deforestation driver due to the arrival of the company United Cacao and their implementation of the large-scale agro-industrial model in place of traditional small-scale plantations on previously degraded lands.

Gold mining has directly caused the deforestation of over 43,000 ha since 2000, mostly in the region of Madre de Dios. In recent years, this deforestation has been concentrated in the Tambopata National Reserve buffer zone.

Although coca cultivation is reportedly declining in Peru, we found that it remains a major driver of deforestation, particularly within and around remote protected areas. For example, we documented 143 ha of coca related deforestation within the Sierra del Divisor Reserved Zone, and an additional 2,638 ha related to shifting agricultural cultivation, which includes coca, within and around Bahuaja Sonene National Park.

We also documented a recent expansion of logging roads in the central Peruvian Amazon. This finding is significant because it is difficult to detect selective logging in satellite imagery, but now we can at least detect the roads that indicate that selective logging is taking place in a given area.

We identified some important geographic patterns related to the four drivers described above. For example, large-scale oil palm (and cacao) are concentrated in the northern Peruvian Amazon, while gold mining deforestation has largely been in the south. Coca-driven deforestation appears to be particularly problematic in the southern Peruvian Amazon, but also exists in the north. The construction of new logging roads is currently most active in the central Peruvian Amazon.

The documented deforestation is caused by both illegal and legal means. For the former, there is extensive deforestation from illegal gold mining and coca cultivation. Regarding the latter, oil palm and cacao companies are exploiting loopholes in the Peruvian legal framework that facilitate large-scale deforestation for agricultural projects.

Large-scale Agriculture (Oil Palm and Cacao)

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Image S1b. Large-scale agriculture deforestation in the northern Peruvian Amazon. Numbers indicate relevant MAAP article. Data: SERNANP, IBC, MINAM-PNCB/MINAGRI-SERFOR, MAAP.

Image S1b illustrates that large-scale agriculture (namely oil palm and cacao) is an important cause of deforestation in northern Peru.

Importantly, several oil palm and cacao companies are changing the production model in Peru from small-scale to large-scale agro-industrial. For example, in a recent interview, United Cacao CEO Dennis Melka stated that his company is trying to replicate the agro-industrial model used by oil palm companies in Southeast Asia[vi].

This shift is noteworthy because large-scale plantations usually come at the expense of forests, while small-scale plantations are better able to take advantage of previously cleared lands[vii]. We estimate that over 30,000 hectares of primary forest was cleared since 2000 for large-scale oil palm and cacao plantations (see below). Much less primary forest, around 575 ha, was cleared for small-scale oil palm (we have yet to evaluate small-scale cacao).

Note that we emphasize the clearing of primary forest. We conducted an additional analysis to determine whether oil palm (both small and large-scale) and cacao (just large-scale) plantations were originally sited on lands with primary forest, secondary forest, or already deforested. We defined primary forest as an area that from the earliest available Landsat, in this case 1990, was characterized by dense closed canopy forest cover.

The following is a concise breakdown of how we calculated the 30,000 ha of primary forest loss from large-scale plantations.

MAAP articles #2, #9, and #13 demonstrated that 2,276 ha of primary forest was cleared by United Cacao between May 2013 and September 2015 outside of the town of Tamshiyacu in the northern Peruvian Amazon (Loreto region).

MAAP article #4 detailed the deforestation of 9,400 ha of primary forest (plus an additional 2,350 ha of secondary forest) between 2011 and 2015 for two large-scale oil palm projects near the town of Nueva Requena in the central Peruvian Amazon (Department of Ucayali).

In addition, yet unpublished MAAP analysis shows that in Palmas de Shanusi/Oriente (oil palm projects operated by the company Grupo Palmas), 6,974 ha of primary forest were cleared between 2006 and 2011, although the legally mandated 30% forest cover reserves were maintained. An additional 8,225 ha of primary forest was cleared in areas immediately surrounding the concessions.

Finally, although not yet published on MAAP, we also documented nearly 3,500 ha of primary forest loss in other large-scale oil palm projects in San Martin and Ucayali regions.

It is important to emphasize that several oil palm and cacao companies are exploiting various loopholes in the Peruvian legal framework that facilitate large-scale deforestation for agricultural projects[viii]. In fact, these companies argue that according to Peruvian law, they are engaged in legal “forest clearing”, not illegal “deforestation”[ix].

Gold Mining

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Image S1c. Gold mining deforestation in the Peruvian Amazon. Numbers indicate relevant MAAP article. Data: SERNANP, IBC, MINAM-PNCB/MINAGRI-SERFOR, MAAP.

Image S1c illustrates that gold mining-driven deforestation is largely concentrated in the southern Peruvian Amazon, particularly in the region of Madre de Dios and adjacent Cusco.

According to the scientific literature, gold mining deforestation in Madre de Dios increased from 10,000 ha in 2000 to 50,000 ha in 2012[x]. MAAP articles #1, #5, and #12 documented the deforestation of an additional 2,774 ha between 2013 and 2015 in two gold mining hotspots (La Pampa and Upper Malinowski), both of which are located within the buffer zone of the Tambopata National Reserve. In addition, MAAP #6 showed gold mining deforestation expanding from another Madre de Dios gold mining hotspot (Huepetuhe) into the tip of Amarakaeri Communal Reserve (11 ha).

Much of the Madre de Dios gold mining deforestation described above is illegal because it is occurring within and around protected areas where mining is not permitted under the government-led formalization process.

MAAP articles #6 and #14 detailed recent gold mining deforestation in the region of Cusco. Specifically, we documented the deforestation of 967 ha along the Nuciniscato River and its major tributaries since 2000 (with the vast majority occurring since 2010). Much of this deforestation appears to be linked to gold mining.

Thus, the total documented gold mining deforestation in Madre de Dios and adjacent Cusco is at least 53,750 ha[xi], over 80% of which has occurred since 2000. This total is an underestimate since we have not yet done detailed studies for 2013 – 2015 deforestation in all of the known gold mining zones in these two regions.

In addition, MAAP #7 showed two gold mining zones in the region of Ucayali (along the Sheshea and Abujao Rivers, respectively). Much of this deforestation occurred between 2000 and 2012.

Finally, there are also reports of extensive gold mining in northern Peru (the regions of Amazonas and Loreto) but we do not yet have data showing that it is causing deforestation.

Coca

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Image S1d. Coca cultivation areas in the Peruvian Amazon. Numbers indicate relevant MAAP article. Data: UNODC 2014, MINAM-PNCB/MINAGRI-SERFOR, SERNANP, NatureServe.

Although the most recent report from the United Nations Office on Drugs and Crime (UNODC) indicates that overall coca cultivation is declining in Peru[xii], our research finds that it remains a major driver of deforestation in certain areas, particularly within and around several remote protected areas.

Image S1d displays the distribution of current coca-cultivation areas (in relation to protected areas) based on the data from the latest United Nations report. Of these areas, we have thus far focused on the three detailed below.

MAAP articles #7 and #8 show recent coca-related deforestation within the southern section of the Sierra del Divisor Reserved Zone. This area is particularly important because it is soon slated to be upgraded to a national park. Specifically, we documented coca-related deforestation of 130 ha between 2013 and 2014 within the southwestern section of the reserve, and, most recently, a new plantation of 13 ha during June 2015 within the southeast section.

MAAP article #10 revealed that shifting agricultural cultivation, that includes coca, is also a major issue within and around Bahuaja Sonene National Park, located in the southern Peruvian Amazon. Specifically, we found the recent deforestation of 538 hectares within the southern section of the Park, and an additional 2,100 hectares in the surrounding buffer zone. Much of this deforestation is likely linked to coca cultivation since the latest United Nations report indicates these areas contain high coca plantation densities.

MAAP article #14 documents the deforestation of 477 ha along the Nojonunta River in Cusco since 2000 (with a major peak since 2010). Much of this deforestation is likely linked to coca cultivation since the latest United Nations report indicates these areas contain medium to high coca plantation densities. 

Logging Roads

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Image S1e. Logging roads in the Peruvian Amazon. Numbers indicate relevant MAAP article. Data: SERNANP, IBC, MINAM-PNCB/MINAGRI-SERFOR, MINAGRI, MAAP.

One of the major advances discovered in this work is the ability to identify the expansion of new logging roads. This advance is important because it is extremely difficult to detect illegal logging in satellite imagery because loggers in the Amazon often selectively cut high value species and do not produce large clearings. But now, although it remains difficult to detect the actual selective logging, we can detect the roads that indicate that selective logging is taking place in that area.

Image S1e illustrates the likely logging roads that we have recently detected. Of these areas, we have thus far focused on the two detailed below.

MAAP article #3 shows the rapid proliferation of two new road networks in the northern Peruvian Amazon (Loreto region). Most notably, it highlights the construction of 148 km of new roads, possibly illegal logging roads, through mostly primary forest between 2013 and 2014. One of the roads is within the buffer zone of the Cordillera Azul National Park.

In addition, MAAP article #7 shows the expansion of new logging roads near both the southern and northwestern sections of the Sierra del Divisor Reserved Zone. In both cases, the expansion is very recent (between 2013 and 2015).

 

[i] National Program of Forest Conservation for the Mitigation of Climate Change – PNCB.

[ii] Servicio Nacional Forestal y de Fauna Silvestre – SERFOR

[iii] MINAGRI-SERFOR/MINAM-PNCB (2015) Compartiendo una visión para la prevención, control y sanción de la deforestación y tala ilegal.

[iv] Note that some of the documented forest loss may come from natural causes, such as landslides or meandering rivers.

[v] MINAM (2013) Fondo Cooperativo Para El Carbono de los Bosques (FCPF) Plantilla de Propuesta para la Fase de Preparación para REDD+ (Readiness Plan Proposal – RPP). Link: http://www.minam.gob.pe/cambioclimatico/wp-content/uploads/sites/11/2014/03/R-PP-Per%C3%BA-Final-Dec-2013-RESALTADO_FINAL_PUBLICADA-FCPF_24-febrero.pdf

[vi] NF Joan (2015) United Cacao replicates Southeast Asia’s plantation model in Peru, says CEO Melka. The Edge Singapore.Link: http://www.unitedcacao.com/images/media-articles/20150713-the-edge-united-cacao.pdf

[vii] Gutiérrez-Vélez VH, DeFries R, Pinedo-Vásquez M, et al. (2011) High-yield oil palm expansion spares land at the expense of forests in the Peruvian Amazon. Environ. Res. Lett., 6, 044029. Link: http://iopscience.iop.org/article/10.1088/1748-9326/6/4/044029/pdf

[viii] Environmental Investigation Agency (2015) Deforestation by Definition. Washington, DC. Link: http://eia-global.org/news-media/deforestation-by-definition

[ix] Tello Pereyra R (2015) Situacion legal, judicial, y administrativa de  Cacao del Peru Norte SAC. Link: https://www.youtube.com/watch?v=p_YIe70u1oA

[x] Asner GP, Llactayo W, Tupayachia R, Ráez Luna E (2013) PNAS 110 (46) 18454-18459. Link: http://www.pnas.org/content/110/46/18454.abstract

[xi] That is, 50,000 ha from the literature and 3,750 ha from MAAP analysis.

[xii] UNODC (2015) Monitoreo de cultivos ilícitos Perú 2014. Link: https://www.unodc.org/documents/crop-monitoring/Peru/Peru_Informe_monitoreo_coca_2014_web.pdf

Citation

Finer M, Novoa S (2015) Patterns and Drivers of Deforestation in the Peruvian Amazon. MAAP Synthesis #1. Link: https://www.maapprogram.org/2015/09/maap-synthesis1/

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.

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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

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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.

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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.

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

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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://www.maapprogram.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.

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

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).

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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.

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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

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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 mentionned 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://www.maapprogram.org/2015/08/image-11-protected-areas