MAAP #141: Protected Areas & Indigenous Territories Effective Against Deforestation in the Western Amazon

Base Map. Primary forest loss across the western Amazon, with magnified visualization of the data. Click to enlarge. See Methodology for data sources.

As deforestation continues to threaten primary forest across the Amazon, key land use designations are one of the best hopes for the long-term conservation of critical remaining intact forests.

Here, we evaluate the impact of two of the most important land use designations: protected areas and indigenous territories.

Our study area focused on the four mega-diverse countries of the western Amazon (Bolivia, Colombia, Ecuador, & Peru), covering a vast area of over 229 million hectares (see Base Map).

We calculated primary forest loss over the past four years (2017-2020) across the western Amazon and analyzed the results across three major land use categories:

1) Protected Areas (national and state/department levels), which covered 43 million hectares as of 2020.

2) Indigenous Territories (official), which covered over 58 million hectares as of 2020.

3) Other (that is, all remaining areas outside protected areas and indigenous territories), which covered the remaining 127 million hectares as of 2020.

In addition, we took a deeper look at the Peruvian Amazon and also included long-term forestry lands.

In summary, we found that, averaged across all four years, protected areas had the lowest primary forest loss rate, closely followed by indigenous territories (see Figure 1). Outside of these critical areas, the primary forest loss rate was more than double.

Below, we describe the key results in greater detail, including a detailed look at each country.

 

Key Findings – Western Amazon

Figure 1. Primary forest loss rates in the western Amazon.

Overall, we documented the loss of over 2 million hectares of primary forests across the four countries of the western Amazon between 2017 and 2020. Of the four years, 2020 had the most forest loss (588,191 ha).

Of this total, 9% occurred in protected areas (179,000 ha) and 15% occurred in indigenous territories (320,000 ha), while the vast majority (76%) occurred outside key these land use designations (1.6 million ha).

To standardize these results for the varying area coverages, we calculated primary forest loss rates (loss/total area of each category). Figure 1 displays the combined results for these rates across all four countries.

From 2017-19, protected areas (green) had the lowest primary forest loss rates across the western Amazon (less than 0.10%).

Indigenous territories (brown) also had low primary forest loss rates from 2017-18 (less than 0.11%), but this rose in 2019 (0.18%) due to fires in Bolivia.

In the intense COVID pandemic year of 2020, this overall pattern flipped, with elevated primary forest loss in protected areas, again largely due to major fires in Bolivia. Thus, indigenous territories had the lowest primary forest loss rate followed by protected areas (0.15% and 0.19%, respectively) in 2020.

Averaged across all four years, protected areas had the lowest primary forest loss rate (0.11%), closely followed by indigenous territories (0.14%). Outside of these critical areas (red), the primary forest loss rate was more than double (0.30%). The lowest primary forest loss rates (less than 0.10%) occurred in the protected areas of Ecuador and Peru (0.01% and 0.03%, respectively), and indigenous territories of Colombia (0.07%).

Country Results

Figure 2. Primary forest loss rates in the Colombian Amazon.

Colombian Amazon

Colombia had, by far, the highest primary forest loss rates outside protected areas and indigenous territories (averaging 0.67% across all four years).

By contrast, Colombian indigenous territories had one of the lowest primary forest loss rates across the western Amazon (averaging 0.07% across all four years).

The primary forest loss rates for protected areas were on average nearly double that of indigenous territories (mostly due to the high deforestation in Tinigua National Park), but still much lower than non-protected areas.

 

 

 

 

 

Figure 3. Primary forest loss rates in the Ecuadorian Amazon.

Ecuadorian Amazon

Overall, Ecuador had the lowest primary forest loss rates across all three categories.

Protected areas had the lowest primary forest loss rate of any category across the western Amazon (averaging 0.01% across all four years).

Indigenous territories also had relatively low primary forest loss rates, averaging half that of outside protected areas and indigenous territories (0.10% vs 0.21%, respectively).

 

 

 

 

 

 

Figure 4. Primary forest loss rates in the Bolivian Amazon.

Bolivian Amazon

Bolivia had the most dynamic results, largely due to intense fire seasons in 2019 and 2020. Indigenous territories had the lowest primary forest loss rates, with 2019 being the only exception, due to large fires in the Santa Cruz department that affected the Monte Verde indigenous territory.

Protected areas had the lowest primary forest loss rate in 2019, but in extreme contrast, the highest the following year in 2020, also due to large fires in the Santa Cruz department that affected Noel Kempff Mercado National Park.

Overall, primary forest loss was highest outside protected areas and indigenous territories (averaging 0.33% across all four years).

 

 

 

Figure 5a. Primary forest loss rates in the Peruvian Amazon. Data: UMD.

Peruvian Amazon

Following Ecuador, Peru also had relatively low primary forest loss rates, particularly in protected areas (averaging 0.03% across all four years).

Primary forest loss in indigenous territories (that is, combined data for native communities and Territorial/Indigenous Reserves for groups in voluntary isolation) was surprisingly high, similar to that of areas outside protected areas across all four years. For example, in 2020, elevated primary forest loss was concentrated in several titled native communities in the regions of Amazonas, Ucayali, Huánuco, and Junín.

 

 

 

 

 

Figure 5b. Deforestation rates in the Peruvian Amazon. Data: MINAM/Geobosques.

As noted above, we conducted a deeper analysis for the Peruvian Amazon, using deforestation data produced by the Peruvian government and adding the additional category of long-term forestry lands (known as Permanent Production Forests, or BPP in Spanish) (see Annex map).

We also separated the data for indigenous territories into native communities and Territorial/Indigenous Reserves for groups in voluntary isolation, respectively.

These data also show that deforestation was lowest in the remote Territorial/Indigenous Reserves, closely followed by protected areas (0.01% vs 0.02% across all four years, respectively). Deforestation in titled native communities was 0.21% across all four years. Surprisingly, deforestation was higher in the forestry lands than areas outside protected areas and indigenous territories (0.30% vs 0.27% across all four years).

 

 

 

 

Annex – Peruvian Amazon

The following map shows added detail for Peru, most notably the inclusion of long-term forestry lands (known as Permanent Production Forests, or BPP in Spanish).

 

 

 

 

 

 

 

 

 

 

 

 

*Methodology

To estimate deforestation across all three categories, we used annual forest loss data (2017-20) from the University of Maryland (Global Land Analysis and Discovery GLAD laboratory) to have a consistent source across all four countries (Hansen et al 2013).

We obtained this data, which has a 30-meter spatial resolution, from the “Global Forest Change 2000–2020” data download page. It is also possible to visualize and interact with the data on the main Global Forest Change portal.

It is important to note that these data include both human-caused deforestation and forest loss caused by natural forces (landslides, wind storms, etc…).

We also filtered this data for only primary forest loss, following the established methodology of Global Forest Watch. Primary forest is generally defined as intact forest that has not been previously cleared (as opposed to previously cleared secondary forest, for example). We applied this filter by intersecting the forest cover loss data with the additional dataset “primary humid tropical forests” as of 2001 (Turubanova et al 2018). For more details on this part of the methodology, see the Technical Blog from Global Forest Watch (Goldman and Weisse 2019).

Thus, we often use the term “primary forest loss” to describe the data.

Data presented as primary forest loss or deforestation rate is standardized per the total area covered of each respective category. For example, to properly compare raw forest loss data in areas that are 100 hectares vs 1,000 hectares total size respectively, we divide by the area to standardize the result.

Our geographic range included four countries of the western Amazon and consists of a combination of the Amazon watershed limit (most notably in Bolivia) and Amazon biogeographic limit (most notably in Colombia) as defined by RAISG. See Base Map above for delineation of this hybrid Amazon limit, designed for maximum inclusion.

Additional data sources include: National and state/deprartment level protected areas: RUNAP 2020 (Colombia), SNAP 2017 & RAISG 2020 (Ecuador), SERNAP & ACEAA 2020 (Bolivia), and SERNANP 2020 (Peru).

Indigenous Territories: RAISG 2020 (Colombia, Ecuador, and Bolivia), and MINCU & ACCA 2020 (Peru). For Peru, this includes titled native communities and Indigenous/Territorial Reserves for indigenous groups in voluntary isolation.

For the additional analysis in Peru, we used deforestation data from MINAM/Geobosques (note this is actual deforestation and not primary forest loss) and BPP data from SERFOR. We also separated data from titled native communities and Territorial/Indigenous Reserves for groups in voluntary isolation.

Acknowledgements

We thank M. MacDowell (AAF) A. Folhadella (ACA), J. Beavers (ACA), S. Novoa (ACCA), and D. Larrea (ACEAA) for their helpful comments on this report.

This work was supported by the Andes Amazon Fund (AAF), Norwegian Agency for Development Cooperation (NORAD), and International Conservation Fund of Canada (ICFC).

 

Citation

Finer M, Mamani N, Silman M (2021) Protected Areas & Indigenous Territories Effective Against Deforestation in the Western Amazon. MAAP: 141.

MAAP #136: Amazon Deforestation 2020 (Final)

Base Map. Forest loss hotspots across the Amazon in 2020. Data: Hansen/UMD/Google/USGS/NASA, RAISG, MAAP. The letters A-E correspond to the zoom examples below.

*To download the report, click “Print” instead of “Download PDF” at the top of the page.

In January, we presented the first look at 2020 Amazon deforestation based on early warning alert data (MAAP #132).

Here, we update this analysis based on the newly released, and more definitive, annual data.*

The Base Map illustrates the final results and indicates the major hotspots of primary forest loss across the Amazon in 2020.

We highlight several key findings:

  • The Amazon lost nearly 2.3 million hectares (5.6 million acres) of primary forest loss in 2020 across the nine countries it spans.
    g
  • This represents a 17% increase in Amazon primary forest loss from the previous year (2019), and the third-highest annual total on record since 2000 (see graph below).
    j
  • The countries with the highest 2020 Amazon primary forest loss are 1) Brazil, 2) Bolivia, 3) Peru, 4) Colombia, 5) Venezuela, and 6) Ecuador.
    h
  • 65% occurred in Brazil (which surpassed 1.5 million hectares lost), followed by 10% in Bolivia, 8% in Peru, and 6% in Colombia (remaining countries all under 2%).
    k
  • For Bolivia, Ecuador, and Peru, 2020 recorded historical high Amazon primary forest loss. For Colombia, it was the second highest on record.

In all of the data graphs, orange indicates the 2020 primary forest loss and red indicates all years with higher totals than 2020.

For example, the Amazon lost nearly 2.3 million hectares in 2020 (orange), the third highest on record behind only 2016 and 2017 (red).

Note that the three highest years (2016, 2017, and 2020) had one major thing in common: uncontrolled forest fires in the Brazilian Amazon.

See below for country-specific graphs, key findings, and satellite images for the top four 2020 Amazon deforestation countries (Brazil, Bolivia, Peru, and Colombia).

 

 

 

Brazilian Amazon

2020 had the sixth-highest primary forest loss on record (1.5 million hectares) and a 13% increase from 2019.

Many of the 2020 hotspots occurred in the Brazilian Amazon, where massive deforestation stretched across nearly the entire southern region.

A common phenomenon observed in the satellite imagery through August was that rainforest areas were first deforested and then later burned, causing major fires due to the abundant recently-cut biomass (Image A). This was also the pattern observed in the high-profile 2019 Amazon fire season. Much of the deforestation in these areas appears to associated with expanding cattle pasture areas.

In September 2020 (and unlike 2019), there was a shift to actual Amazon forest fires (Image B). See MAAP #129 for more information on the link between deforestation and fire in 2020.

Note that the three highest years (2016, 2017, and 2020) had one major thing in common: uncontrolled forest fires in the Brazilian Amazon.

Image A. Deforestation in Brazilian Amazon (Amazonas state) of 2,540 hectares between January (left panel) and November (right panel) 2020. Data: Planet.
Image B. Forest fire in Brazilian Amazon (Para state) that burned 9,000 hectares between March (left panel) and October (right panel) 2020. Data: Planet.

Bolivian Amazon

2020 had the highest primary forest loss on record in the Bolivian Amazon, surpassing 240,000 hectares.

Indeed, the most intense hotspots across the entire Amazon ocurred in southeast Bolivia, where fires raged through the drier Amazon forests (known as the Chiquitano and Chaco ecosystems).

Image C shows the burning of a massive area (over 260,000 hectares) in the Chiquitano dry forests (Santa Cruz department).

 

 

 

 

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

Peruvian Amazon

2020 also had the highest primary forest loss on record in the Peruvian Amazon, surpassing 190,000 hectares.

This deforestation is concentrated in the central region. On the positive, the illegal gold mining that plagued the southern region has decreased thanks to effective government action (see MAAP #130).

Image D shows expanding deforestation (over 110 hectares), and logging road construction (3.6 km), in an indigenous territory south of Sierra del Divisor National Park in the central Peruvian Amazon (Ucayali region). The deforestation appears to be associated with an expanding small-scale agriculture or cattle pasture frontier.

 

 

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

Colombian Amazon

2020 had the second-highest primary forest loss on record in the Colombian Amazon, nearly 140,000 hectares.

As described in previous reports (see MAAP #120), there is an “arc of deforestation” concentrated in the northwest Colombian Amazon. This arc impacts numerous protected areas (including national parks) and Indigenous Reserves.

For example, Image E shows the recent deforestation of over 500 hectares in Chiribiquete National Park. Similar deforestation in that sector of the park appears to be conversion to cattle pasture.

 

 

 

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

*Notes and Methodology

To download the report, click “Print” instead of “Download PDF” at the top of the page.

The analysis was based on 30-meter resolution annual data produced by the University of Maryland (Hansen et al 2013), obtained from the “Global Forest Change 2000–2020” data download page. It is also possible to visualize and interact with the data on the main Global Forest Change portal.

Importantly, this data detects and classifies burned areas as forest loss. Nearly all Amazon fires are human-caused. Also, this data does include some forest loss caused by natural forces (landslides, wind storms, etc…).

Note that when comparing 2020 to early years, there are several methodological differences from the University of Maryland introduced to data after 2011. For more details, see “User Notes for Version 1.8 Update.”

It is worth noting that we found the early warning (GLAD) alerts to be a good (and often conservative) indicator of the final annual data.

Our geographic range includes nine countries and consists of a combintion of the Amazon watershed limit (most notably in Bolivia) and Amazon biogeographic limit (most notably in Colombia) as defined by RAISG. See Base Map above for delineation of this hybrid Amazon limit, designed for maximum inclusion. Inclusion of the watershed limit in Bolivia is a recent change incorporated to better include impact to the Amazon dry forests of the Chaco.

We applied a filter to calculate only primary forest loss. For our estimate of primary forest loss, we intersected the forest cover loss data with the additional dataset “primary humid tropical forests” as of 2001 (Turubanova et al 2018). For more details on this part of the methodology, see the Technical Blog from Global Forest Watch (Goldman and Weisse 2019).

To identify the deforestation hotspots, we conducted a kernel density estimate. This type of analysis calculates the magnitude per unit area of a particular phenomenon, in this case forest cover loss. We conducted this analysis using the Kernel Density tool from Spatial Analyst Tool Box of ArcGIS. We used the following parameters:

Search Radius: 15000 layer units (meters)
Kernel Density Function: Quartic kernel function
Cell Size in the map: 200 x 200 meters (4 hectares)
Everything else was left to the default setting.

For the Base Map, we used the following concentration percentages: Medium: 7-10%; High: 11-20%; Very High: >20%.

 

Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (15 November): 850–53.

Acknowledgements

We thank E. Ortiz (AAF), M. Silman (WFU), M. Weisse (WRI/GFW) for their helpful comments on this report.

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

Citation

Finer M, Mamani N (2020) Amazon Deforestation Hotspots 2020 (Final). MAAP: 136.

MAAP #132: Amazon Deforestation Hotspots 2020

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

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

There are several major headlines:

  • We estimate over 2 million hectares (5 million acres) of primary forest loss across the nine countries of the Amazon in 2020.*
    p
  • The countries with the highest 2020 primary forest loss are 1) Brazil, 2) Bolivia, 3) Peru, 4) Colombia, 5) Venezuela, and 6) Ecuador.
    p
  • The majority of the hotspots occurred in the Brazilian Amazon, where massive deforestation stretched across nearly the entire southern region. Many of these areas were cleared in the first half of the year and then burned in July and August. In September, there was a shift to actual forest fires (see MAAP #129).
    p
  • Several of the most intense hotspots were in the Bolivian Amazon, where fires raged through the dry forests (known as the Chiquitano) in the southeast region.
    p
  • There continues to be an arc of deforestation in the northwestern Colombian Amazon, impacting numerous protected areas.
    p
  • In the Peruvian Amazon, deforestation continues to impact the central region. On the positive, the illegal gold mining that plagued the southern region has decreased thanks to effective government action (see MAAP #130).

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

Widespread Deforestation in the Brazilian Amazon

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

Zoom A. Deforestation in the Brazilian Amazon (Amazonas state) of 3,400 hectares between April (left panel) and November (right panel) 2020. Data: ESA, Planet.
Zoom B. Deforestation in Brazilian Amazon (Amazonas state) of 2,540 hectares between January (left panel) and November (right panel) 2020. Data: Planet.
Zoom C. Deforestation in Brazilian Amazon (Para state) of 15,250 hectares between January (left panel) and October (right panel) 2020. Data: Planet.

Forest Fires in the Brazilian Amazon

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

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

Forest Fires in the Bolivian Amazon

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

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

Arc of Deforestation in the Colombian Amazon

As described in previous reports (see MAAP #120), there is an “arc of deforestation” concentrated in the northwest Colombian Amazon. This arc impacts numerous protected areas (including national parks) and Indigenous Reserves. For example, Zoom G shows the recent deforestation of over 500 hectares in Chiribiquete National Park. Similar deforestation in that sector of the park appears to be conversion to cattle pasture.

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

Deforestation in the central Peruvian Amazon

Finally, Zoom H shows expanding deforestation (over 110 hectares), and logging road construction (3.6 km), in an indigenous territory south of Sierra del Divisor National Park in the central Peruvian Amazon (Ucayali region). The deforestation appears to be associated with an expanding small-scale agriculture or cattle pasture frontier.

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

*Notes and Methodology

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

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

We applied a filter to calculate only primary forest loss. For our estimate of primary forest loss, we intersected the forest cover loss data with the additional dataset “primary humid tropical forests” as of 2001 (Turubanova et al 2018). For more details on this part of the methodology, see the Technical Blog from Global Forest Watch (Goldman and Weisse 2019).

To identify the deforestation hotspots, we conducted a kernel density estimate. This type of analysis calculates the magnitude per unit area of a particular phenomenon, in this case forest cover loss. We conducted this analysis using the Kernel Density tool from Spatial Analyst Tool Box of ArcGIS. We used the following parameters:

Search Radius: 15000 layer units (meters)
Kernel Density Function: Quartic kernel function
Cell Size in the map: 200 x 200 meters (4 hectares)
Everything else was left to the default setting.

For the Base Map, we used the following concentration percentages: Medium: 7-10%; High: 11-20%; Very High: >20%.

Acknowledgements

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

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

Citation

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

Amazon Fire Tracker 2020: Images of the Brazilian Amazon Fires

Our innovative new app for Real-time Amazon Fire Monitoring has now detected over 350 major fires in the Brazilian Amazon this season.*

Specifically, we have detected 365 major fires as of August 17, since the first major fire detected on May 28.

The fire season is accelerating, as 79% of the major fires have occured in August.

Below, we present a series of satellite images showing key examples from August 2020.

We highlight our key finding that the vast majority of major fires (88%burned recently deforested areas covering 557,000 acres (226,000 hectares). Thus, the fires are actually a striking indicator of the rampant deforestation currently threatening the the Brazilian Amazon.

We have detected 4 Forest fires (1% of the major fires) covering 2,790 acres (1,130 hectares) and 3 savanna fires covering 38,000 acres (15,000 hectares). The rest of the major fires are burning older agricultural areas.

Other key findings include:

  • The vast majority of the fires (96%) are illegal, occuring past the 120 day moratorium established in July.
  • At least 18 of the major fires have been in protected areas or indigenous territories.
  • Most of the fires (70%) have occurred in two departments: Amazonas and Para. Mato Grosso and Rondonia each account for 15%.

We have detected an additional 10 major fires in the Bolivian Amazon, and that will be the feature of a future report.

Images of the 2020 Brazilian Amazon Fires

1) Fires burning recently deforested areas

Brazilian Amazon Fire #338 (August 16, 2020)

Brazilian Amazon Fire #335 (August 16, 2020)

Brazilian Amazon Fire #233 (August 11, 2020)

 

Brazilian Amazon Fire #230 (August 11, 2020)

Brazilian Amazon Fire #221 (August 11, 2020)

Brazilian Amazon Fire #202 (August 10, 2020)

Brazilian Amazon Fire #188 (August 9, 2020)

Brazilian Amazon Fire #124 (August 6, 2020)

Brazilian Amazon Fire #110 (August 4, 2020)

Brazilian Amazon Fire #109 (August 4, 2020)

Brazilian Amazon Fire #76 (August 1, 2020)

2) Forest Fires 

Brazilian Amazon Fire #218, August 2020

Brazilian Amazon Fire #195, August 2020

3) Grassland (Savanna) Fires 

Brazilian Amazon Fire #219, August 2020

*Notes and Methodology

The app specializes in filtering out thousands of the traditional heat-based fire alerts to prioritize only those burning large amounts of biomass (defined here as a major fire).

In a novel approach, the app combines data from the atmosphere (aerosol emissions in smoke) and the ground (heat anomaly alerts) to effectively detect and visualize major Amazon fires.

When fires burn, they emit gases and aerosols. A new satellite (Sentinel-5P from the European Space Agency) detects these aerosol emissions. Thus, the major feature of the app is detecting elevated aerosol emissions which in turn indicate the burning of large amounts of biomass. For example, the app distinguishes small fires clearing old fields (and burning little biomass) from larger fires burning recently deforested areas or standing forest (and burning lots of biomass).

We define “major fire” as one showing elevated aerosol emission levels on the app, thus indicating the burning of elevated levels of biomass. This typically translates to an aerosol index of >1 (or cyan-green to red on the app). To identify the exact source of the elevated emissions, we reduce the intensity of aerosol data in order to see the underlying terrestrial heat-based fire alerts. Typically for major fires, there is a large cluster of alerts. The major fires are then confirmed, and burn areas estimated, using high-resolution satellite imagery from Planet Explorer.

See MAAP #118 for additional details.

No fires permitted in the Brazilian state of Mato Grosso after July 1, 2020. No fires permitted in all of Brazilian Amazon after July 15, 2020. Thus, we defined “illegal” as any major fires detected after these respective dates.

There was no available Sentinel-5 aerosol data on July 4, 15, and 26.

Acknowledgements

This analysis was done by Amazon Conservation in collaboration with SERVIR Amazonia.

Citation

Finer M, Nicolau A, Vale H, Villa L, Mamani N (2020) Amazon Fire Tracker 2020: Images of the Brazilian Amazon Fires. MAAP.

MAAP #122: Amazon Deforestation 2019

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

Newly released data for 2019 reveals the loss of over 1.7 million hectares (4.3 million acres) of primary Amazon forest in our 5 country study area (Bolivia, Brazil, Colombia, Ecuador, and Peru).* That is twice the size of Yellowstone National Park.

Table 1 shows 2019 deforestation (red) in relation to 2018 (orange).

Primary forest loss in the Brazilian Amazon (1.29 million hectares) was over 3.5 times higher than the other four countries combined, with a slight increase in 2019 relative to 2018. Many of these areas were cleared in the first half of the year and then burned in August, generating international attention.

Primary forest loss rose sharply in the Bolivian Amazon (222,834 hectares), largely due to uncontrolled fires escaping into the dry forests of the southern Amazon.

Primary forest loss rose slightly in the Peruvian Amazon (161,625 hectares) despite a relatively successful crackdown on illegal gold mining, pointing to small-scale agriculture (and cattle) as the main driver.

On the positive side, primary forest loss decreased in the Colombian Amazon (91,400 hectares) following a major spike following the 2016 peace accords (between the government and FARC). It is worth noting, however, that we have now documented the loss of 444,000 hectares (over a million acres) of primary forest in the Colombian Amazon in the past four years since the peace agreement (see Annex).

*Two important points about the data. First, we use annual forest loss from the University of Maryland to have a consistent source across all five countries. Second, we applied a filter to only include loss of primary forest (see Methodology).

2019 Deforestation Hotspots Map

The Base Map below shows the major 2019 deforestation hotspots across the Amazon.

2019 deforestation hotspots across the Amazon. Data: Hansen/UMD/Google/USGS/NASA, MAAP.

Many of the major deforestation hotspots were in Brazil. Early in the year, in March, there were uncontrolled fires up north in the state of Roraima. Further south, along the Trans-Amazonian Highway, much of the deforestation occurred in the first half of the year, followed by the high profile fires starting in late July. Note that many of these fires were burning recently deforested areas, and were not uncontrolled forest fires (MAAP #113).

The Brazilian Amazon also experienced escalating gold mining deforestation in indigenous territories (MAAP #116).

Bolivia also had an intense 2019 fire season. Unlike Brazil, many were uncontrolled fires, particularly in the Beni grasslands and Chiquitano dry forests of the southern Bolivian Amazon (MAAP #108).

In Peru, although illegal gold mining deforestation decreased (MAAP #121), small-scale agriculture (including cattle) continues to be a major driver in the central Amazon (MAAP #112) and an emerging driver in the south.

In Colombia, there is an “arc of deforestation” in the northwestern Amazon. This arc includes four protected areas (Tinigua, Chiribiquete and Macarena National Parks, and Nukak National Reserve) and two Indigenous Reserves (Resguardos Indígenas Nukak-Maku and Llanos del Yari-Yaguara II) experiencing substantial deforestation (MAAP #120). One of the main deforestation drivers in the region is conversion to pasture for land grabbing or cattle ranching.

Annex – Colombia peace accord trend

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

Methodology

The baseline forest loss data presented in this report were generated by the Global Land Analysis and Discovery (GLAD) laboratory at the University of Maryland (Hansen et al 2013) and presented by Global Forest Watch. Our study area is strictly what is highlighted in the Base Map.

For our estimate of primary forest loss, we used the annual “forest cover loss” data with density >30% of the “tree cover” from the year 2001. Then we intersected the forest cover loss data with the additional dataset “primary humid tropical forests” as of 2001 (Turubanova et al 2018). For more details on this part of the methodology, see the Technical Blog from Global Forest Watch (Goldman and Weisse 2019).

For boundaries, we used the biogeographical limit (as defined by RAISG) for all countries except Bolivia, where we used the Amazon watershed limit (see Base Map).

All data were processed under the geographical coordinate system WGS 1984. To calculate the areas in metric units, the projection was: Peru and Ecuador UTM 18 South, Bolivia UTM 20 South, Colombia MAGNA-Bogotá, and Brazil Eckert IV.

Lastly, to identify the deforestation hotspots, we conducted a kernel density estimate. This type of analysis calculates the magnitude per unit area of a particular phenomenon, in this case forest cover loss. We conducted this analysis using the Kernel Density tool from Spatial Analyst Tool Box of ArcGIS. We used the following parameters:

Search Radius: 15000 layer units (meters)
Kernel Density Function: Quartic kernel function
Cell Size in the map: 200 x 200 meters (4 hectares)
Everything else was left to the default setting.

For the Base Map, we used the following concentration percentages: Medium: 7%-10%; High: 11%-20%; Very High: >20%.

References

Goldman L, Weisse M (2019) Explicación de la Actualización de Datos de 2018 de Global Forest Watch. https://blog.globalforestwatch.org/data-and-research/blog-tecnico-explicacion-de-la-actualizacion-de-datos-de-2018-de-global-forest-watch

Hansen, M. C., P. V. Potapov, R. Moore, M. Hancher, S. A. Turubanova, A. Tyukavina, D. Thau, S. V. Stehman, S. J. Goetz, T. R. Loveland, A. Kommareddy, A. Egorov, L. Chini, C. O. Justice, and J. R. G. Townshend. 2013. “High-Resolution Global Maps of 21st-Century Forest Cover Change.” Science 342 (15 November): 850–53. Data available on-line from: http://earthenginepartners.appspot.com/science-2013-global-forest.

Turubanova S., Potapov P., Tyukavina, A., and Hansen M. (2018) Ongoing primary forest loss in Brazil, Democratic Republic of the Congo, and Indonesia. Environmental Research Letters  https://doi.org/10.1088/1748-9326/aacd1c 

Acknowledgements

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

This work was supported by the following major funders: Norwegian Agency for Development Cooperation (NORAD), Gordon and Betty Moore Foundation, International Conservation Fund of Canada (ICFC), Metabolic Studio, Erol Foundation, MacArthur Foundation, and Global Forest Watch Small Grants Fund (WRI).

Citation

Finer M, Mamani N (2020) 2019 Amazon Deforestation. MAAP: 122.

MAAP #116: Amazon Gold Mining, Part 2: Brazil

Base Map. Major gold mining deforestation zones across the Amazon. Data: MAAP.

We present the second part of our series on Amazon gold mining, with a focus on the Brazil*

Specifically, we focus on mining in indigenous territories in the Brazilian Amazon.

Extractive activities, such as gold mining, are constitutionally not permitted on indigenous lands, but the Bolsonaro administration is advancing a bill (PL 191) that would reverse this.

The Base Map indicates three Brazilian indigenous territories where we identified recent major gold mining deforestation:

  1. Munduruku (Pará)
  2. Kayapó (Pará)
  3. Yanomami (Roraima)

We documented the gold mining deforestation of 10,245 hectares (25,315 acres) across all three indigenous territories over the past three years (2017 – 2019). That is the equivalent of 14,000 soccer fields.

Below, see more detailed data, including a series of satellite GIFs of the recent gold mining deforestation in each territory.

*Part 1 looked at the Peruvian Amazon (see MAAP #115). For information on Suriname, see this report from Amazon Conservation Team. For all other countries see this resource from RAISG.

 

Graph 1. Gold mining deforestation in three indigenous territories in the Brazilian Amazon.

Mining Deforestation Increasing

In 2019, all three territories experienced an increase in gold mining deforestation.

In Munduruku Territory, we documented the loss of 3,456 hectares due to mining activity between 2017 and 2019. Note the major spike in 2019, where mining deforestation reached 2,000 hectares.

In Kayapó Territory, we documented the loss of 5,614 hectares between 2017 and 2019. Note that mining deforestation also reached 2,000 hectares in 2019.

In Yanomami Territory, we documented the loss of 1,174 hectares between 2017 and 2019. Note that mining deforestation reached 500 hectares in 2019.

Overall,  44% (4,500 hectares) of the gold mining deforestation occurred in 2019, indicating an increasing trend.

A. Munduruku (Pará)

The GIF below shows an example of gold mining deforestation in Munduruku Territory between 2017 and 2019.

Gold mining deforestation in Munduruku Territory between 2017 and 2019. Data: Planet, MAAP.

B. Kayapó (Pará)

The GIF below shows an example of gold mining deforestation in Kayapó Territory between 2017 and 2019.

Gold mining deforestation in Kayapó Territory between 2017 and 2019. Data: Planet, MAAP.

C. Yanomami (Roraima)

The GIF below shows an example of gold mining deforestation in Yanomami Territory between 2017 and 2019.

Gold mining deforestation in Yanomami Territory between 2017 and 2019. Data: Planet, MAAP.

Annex: Detailed Territory Maps

Below see detailed gold mining deforestation maps for all three Brazilian indigenous territories detailed in this report. Click each image to enlarge.

Gold mining deforestation in Munduruku Territory between 2017 and 2019. Data: MAAP. Click to enlarge.
Gold mining deforestation in Kayapó Territory between 2017 and 2019. Data: MAAP. Click to enlarge.
Gold mining deforestation in Yanomami Territory between 2017 and 2019. Data: MAAP. Click to enlarge.

Acknowledgements

We thank S. Novoa (ACCA), V. Guidotti de Faria (Imaflora), and G. Palacios for helpful comments to earlier versions of this report.

This work was supported by the following major funders: Global Forest Watch Small Grants Fund (WRI), Norwegian Agency for Development Cooperation (NORAD),  International Conservation Fund of Canada (ICFC), Metabolic Studio, and Erol Foundation.

Citation

Finer M, Mamani N (2020) Amazon Gold Mining, part 2: Brazil. MAAP: 116.

MAAP #115: Illegal Gold Mining in the Amazon, part 1: Peru

Base Map. The main illegal gold mining areas in the Peruvian Amazon. Data: MAAP.

In a new series, we highlight the main illegal gold mining frontiers in the Amazon.

Here, in part 1, we focus on Peru. In the upcoming part 2, we will look at Brazil.

The Base Map indicates our focus areas in Peru*:

  • Southern Peru (A. La Pampa, B. Alto Malinowski, C. Camanti, D. Pariamanu);
  • Central Peru (E. El Sira).

Notably, we found an important reduction in gold mining deforestation in La Pampa (Peru’s worst gold mining area) following the government’s launch of Operation Mercury in February 2019.

Illegal gold mining continues, however, in three other major areas of the southern Peruvian Amazon (Alto Malinowski, Camanti, and Pariamanu), where we estimate the mining deforestation of 5,300 acres (2,150 hectares) since 2017.

Of that total, 22% (1,162 acres) occurred in 2019, indicating that displaced miners from Operation Mercury have NOT caused a surge in these three areas.

Below, we show a series of satellite videos of the recent gold mining deforestation (2017-19) in each area.

*Recent press reports indicate the increase in illegal gold mining activity in northern Peru (Loreto region), along the Nanay and Napo Rivers, but we have not yet detected associated deforestation.

A. La Pampa (Southern Peru)

In MAAP #104, we reported a major reduction (92%) of gold mining deforestation in La Pampa during the first four months of Operation Mercury, a governmental mega-operation to confront the illegal mining crisis in this area.

The following video shows how gold mining deforestation has declined considerably since February 2019, the beginning of the operation. Note the rapid deforestation during the years 2016-18, followed by a sudden stop in 2019.

B. Alto Malinowski (Southern Peru)

The following video shows gold mining deforestation in a section of the upper Malinowski River (Madre de Dios region). We estimate the mining deforestation of 4,120 acres (1,668 hectares) throughout the Alto Malinowski area during the 2017 – 2019 period.

Of that total, 20% (865 acres) occurred in 2019, indicating that displaced miners from Operation Mercury have not caused a surge in this area adjacent to La Pampa.

According to our analysis of governmental information (see Annex 2), the recent mining activity is likely illegal because: a) much of it occurs outside of titled mining concessions, b) and all of it occurs outside of the mining corridor established for legal mining activity (see Annex 1).

Note that the mining deforestation is within the Kotsimba Indigenous Community territory. However, it has not penetrated Bahuaja Sonene National Park, in part due to the actions of the Peruvian Protected Areas Service (SERNANP).

C. Camanti (Southern Peru)

The following video shows the gold mining deforestation of 944 acres (382 hectares) in the Camanti district (Cusco region), during the 2017 – 2019 period.

Of that total, 21% (198 acres) occurred in 2019, indicating that there has been no increase in mining activity in this area since the beginning of Operation Mercury in February (in contrast to press reports that have suggested that many displaced miners have moved to this area).

According to governmental information (see Annex 2), this mining activity is likely illegal because: a) much of it occurs outside of titled mining concessions, b) all occurs outside of the mining corridor, and c) all occurs inside both a protected forest (Bosque Protector) and buffer zone of the Amarakaeri Communal Reserve.

SERNANP (Peruvian Protected Areas Service) informed us that in December 2019, as part of Operation Mercury, the Public Ministry (Ministerio Público) led an interdiction with the support of law enforcement. Machinery, mining camps, and mercury were destroyed or removed during the raid. In 2020, as part of an extension of Operation Mercury, the Environmental Prosecutor’s Office (FEMA) of the Public Ministry announced that the buffer zone of the Amarakaeri Communal Reserve will be constantly monitored.

D. Pariamanu (Southern Peru)

The following video shows gold mining activity along a section of the Pariamanu River (Madre de Dios region). We estimate the gold mining deforestation of 245 acres (99 hectares) in the Pariamanu area, during the 2017 – 2019 period.

Of that total, 40% (99 acres) occurred in 2019, indicating that there has been a slight increase in mining activity since the beginning of Operation Mercury in February. This finding suggests that displaced miners may be moving to this area.

According to governmental information (see Annex 2), this mining activity is likely illegal because it is not within active mining concessions and outside the mining corridor. Morevoer,  the mining deforestation is within Brazil nut forestry concessions.

E. El Sira (Central Peru)

The following video shows the gold mining deforestation of 52 acres (21 hectares) in the buffer zone of El Sira Communal Reserve (Huánuco region), during the 2017 – 2019 period.

 

Although the mining activity occurs in an active mining concession, a recent report indicates that it is illegal because it does not have the deforestation authorization.

Annex 1: Mining Corridor

The mining corridor is the area that the Peruvian Government has defined as potentially legal for mining activity in the Madre de Dios region via a formalization process. As of 2019, over 100 miners have been formalized in Madre de Dios.

In general, mining activity in the corridor is considered legal, either formaly (the formalization process is completed with environmental and operational permits approved) or informaly (in the process of formalization). Thus, mining activity within the corridor is not considered illegal since it is not a prohibited area.

The following two videos show examples of gold mining deforestation in the mining corridor during 2019.

Annex 2: Land Use Map

For greater context, we present a map of qualifying titles directly related to the mining sector, in southern Peru. Layers include the mining corridor (see above), mining concession status (titled, pending, revoked), indigenous territories, and protected areas.

Land use map for southern Peruvian Amazon mining areas. Data: GEOCATMIN/INGEMMET. Click to enlarge.

Acknowledgements

We thank E. Ortiz (AAF), A. Flórez (SERNANP), P. Rengifo (ACCA), A. Condor (ACCA), A. Folhadella (Amazon Conservation), and G. Palacios for helpful comments to earlier versions of this report.

This work was supported by the following major funders: NASA/USAID (SERVIR), Norwegian Agency for Development Cooperation (NORAD), Gordon and Betty Moore Foundation, International Conservation Fund of Canada (ICFC), Metabolic Studio, Erol Foundation, MacArthur Foundation, and Global Forest Watch Small Grants Fund (WRI).

Citation

Finer M, Mamani N (2020) Illegal Gold Mining Frontiers, part 1: Peru. MAAP: 115.

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

Base Map. Oil Exploitation in Yasuni National Park. Click to enlarge.

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

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

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

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

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

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


ITT Block

The ITT Block covers one of the most remote and intact parts of Yasuni National Park. In 2007, the Ecuadorian government launched a unique initiative to keep ITT’s oil underground in exchange for economic compensation from the international community (Yasuni-ITT Initiative).

In 2013, however, the Initiative failed and was abandoned. Indeed, the government is now actively advancing it’s ITT oil extraction plans.

Next, we present a video of satellite images showing the recent oil-related activity inside the ITT Block, within Yasuni National Park. It involves the construction of 4 drilling platforms (Tambococha A,B,D, E) and an access road, between 2017 and 2019. The associated deforestation is 28.5 hectares (70 acres).

Zona Intangible (Untouchable Zone)

There are plans for at least 3 more drilling platforms deeper into Yasuni National Park (see yellow circle in map below). These platforms would bring oil activity close to the buffer zone of an area known as the Zona Intangible, or Untouchable Zone.

The government established the Zona Intangible in 2007 as an area where extractive activities, including oil, are prohibited to protect the territory of the Waorani relatives in voluntary isolation (Tagaeri and Taromenane).

Planned oil platforms (yellow circle) near the buffer zone of the Zona Intangible. Click to enlarge.

*Notes

Edge effects are the impacts that extend into the surrounding forest from the edge of deforestation. These impacts include changes in forest structure and microclimate, higher tree mortality, and increased susceptibility to fire. Based on Broadbent et al (2008), we incorporated an edge effect of 100 meters, which represents the median distance of edge effects recorded in 62 scientific studies. This is a conservative estimate given that an edge effect of 300-2000 meters could be also be justified according to the data.

In MAAP #82, we documented the oil-related deforestation of more than 400 hectares (990 acres) throughout all of Yasuni National Park.

Referenes

Bass M, Finer M, Jenkins C et al (2010) Global Conservation Significance of Ecuador’s Yasuní National Park. PLOS ONE. Link: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0008767

Finer M et al (2009) Ecuador’s Yasuní Biosphere Reserve: a brief modern history and conservation challenges. ERL. Link: https://iopscience.iop.org/article/10.1088/1748-9326/4/3/034005/fulltext/

Broadbent EB, Asner GP et al (2008) Forest fragmentation and edge effects from deforestation
and selective logging in the Brazilian Amazon. Bio Cons 141:1745–1757.

Acknowledgements

We thank A. Puyol (EcoCiencia), M. Bayon (Colectivo de Geografía Crítica del Ecuador), E. Martínez,  and G. Palacios for helpful comments to earlier versions of this report.

This work was supported by the following major funders: Norwegian Agency for Development Cooperation (NORAD), MacArthur Foundation, International Conservation Fund of Canada (ICFC), Metabolic Studio, and Global Forest Watch Small Grants Fund (WRI).

Citation

Finer M, Thieme A, Hettler B (2019) Oil Drilling Pushes Deeper into Yasuni National Park (Ecuador). MAAP: 114.

MAAP #108: Understanding the Amazon Fires with Satellites, part 2

Base Map. Updated Amazon fire hotspots map, August 20-26, 2019. Red, Orange, and Yellow indicate the highest concentrations of fire, as detected by NASA satellites that detect fires at 375 meter resolution. Data. VIIRS/NASA, MAAP.

Here we present an updated analysis on the Amazon fires, as part of our ongoing coverage and building off what we reported in MAAP #107.

First, we show an updated Base Map of the “fire hotspots” across the Amazon, based on very recent fire alerts (August 20-26). Hotspots (shown in red, orange, and yellow) indicate the highest concentrations of fire as detected by NASA satellites.

Our key findings include:

– The major fires do NOT appear to be in the northern and central Brazilian Amazon characterized by tall moist forest (Rondônia, Acre, Amazonas, Pará states),* but in the drier southern Amazon of Brazil and Bolivia characterized by dry forest and shrubland (Mato Grosso and Santa Cruz).

– The most intense fires are actually to the south of the Amazon, along the border of Bolivia and Paraguay, in areas characterized by drier ecosystems.

– Most of the fires in the Brazilian Amazon appear to be associated with agricultural lands. Fires at the agriculture-forest boundary may be expanding plantations or escaping into forest, including indigenous territories and protected areas.

– The large number of agriculture-related fires in Brazil highlights a critical point: much of the eastern Amazon has been transformed into a massive agricultural landscape over the past several decades. The fires are a lagging indicator of massive previous deforestation.

– We continue to warn against using satellite-based fire detection data alone as a measure of impact to Amazonian forests. Many of the detected fires are in agricultural areas that were once forest, but don’t currently represent forest fires.

In conclusion, the classic image of wildfires scorching everything in their path are currently more accurate for the unique and biodiverse dry forests of the southern Amazon then the moist forests to the north. However, the numerous fires at the agriculture-moist forest boundary are both a threat and stark reminder of how much forest has been, and continues to be, lost by deforestation.

Next, we show a series of 11 satellite images that show what the fires look like in major hotspots and how they are impacting Amazonian forests. The location of each image corresponds to the letters (A-K) on the Base Map.

*If anyone has detailed information to the contrary, please send spatial coordinates to maap@amazonconservation.org

Zooms A, B: Chiquitano Dry Forest (Bolivia)

Some of the most intense fires are concentrated in the dry Chiquitano of southern Bolivia. The Chiquitano is part of the largest tropical dry forest in the world and is a unique, high biodiversity, and poorly explored Amazonian ecosystem. Zooms A-C illustrate fires in the Chiquitano between August 18-21 of this year, likely burning a mixture of dry forest, scrubland, and grassland.

Zoom A. Recent fires in the dry Chiquitano of southern Bolivia. Data: Planet.
Zoom B. Recent fires in the dry Chiquitano of southern Bolivia. Data: Planet.

Zoom D: Beni Grasslands (Bolivia)

Zoom D shows recent fires and burned areas in Bolivia’s Beni grasslands.

Zoom D. Recent fires and burned areas in Bolivia’s Beni grasslands. Data: ESA.

Zooms E,F,G,H: Brazilian Amazon (Amazonas, Rondônia, Pará, Mato Grosso)

Zoom E-H take us to moist forest forests of the Brazilian Amazon, where much of the media and social media attention has been focused. All fires we have seen in this area are in agricultural fields or at the agriculture-forest boundary. Note Zoom E is just outside a national park in Amazonas state; Zoom F shows fires at the agriculture-forest boundary in Rondônia state; Zoom G shows fires at the agriculture-forest boundary within a protected area in Pará state; and Zoom H shows fires at the agriculture-forest boundary in Mato Grosso state.

Zoom E. Fires at the agriculture-forest boundary outside a national park in Amazonas state. Data: Planet.
Zoom F. Fires at the agriculture-forest boundary in Rondônia state. Data: ESA.
Zoom G. Fires at the agriculture-forest boundary within a protected area in Pará state.
Zoom H. Fires at the agriculture-forest boundary in Mato Grosso. Data: ESA.

Zooms I, J: Southern Mato Grosso (Brazil)

Zooms I and J shows fires in grassland/scrubland at the drier southern edge of the Amazon Basin. Note both of these fires are within Indigenous Territories.

Zoom I. Fires within an Indigenous Territory at the drier southern edge of the Amazon Basin. Data: Planet.
Zoom J. Fires within an Indigenous Territory at the drier southern edge of the Amazon Basin. Data: Planet.

Zooms C, K: Bolivia/Brazil/Paraguay Border

Zooms C and K show large fires burning in the drier ecosytems at the Bolivia-Brazil-Paraguay border. This area is outside the Amazon Basin, but we include it due it’s magnitude.

Zoom C. Recent fires in the dry Chiquitano of southern Bolivia. Data: Planet.
Zoom K. Large fires burning around the Gran Chaco Biosphere Reserve. Data: NASA/USGS.

Acknowledgements

We thank  J. Beavers (ACA), A. Folhadella (ACA), M. Silman (WFU), S. Novoa (ACCA), M. Terán (ACEAA), and D. Larrea (ACEAA) for helpful comments to earlier versions of this report.

This work was supported by the following major funders: MacArthur Foundation, International Conservation Fund of Canada (ICFC), Metabolic Studio, and Global Forest Watch Small Grants Fund (WRI).

Citation

Finer M, Mamani N (2019) Seeing the Amazon Fires with Satellites. MAAP: 108.

MAAP #102: Saving the Ecuadorian Chocó

Chocó endemic, Long-wattled Umbrellabird. ©Stephen Davies

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

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

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

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

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

See our other Key Results below.

 

 

Base Map

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

Key Results

Our key results include:*

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

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

 

 

 

High Resolution Zooms

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

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

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

Zoom A. Data: Planet, ESA, MAAP.
Zoom B. Data: Planet, MAAP.
Chocó Conservation Opportunity. Data: Jocotoco Foundation, MAE, Hansen/UMD/Google/USGS/NASA.

Conservation Opportunity

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

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

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

 

 

 

 

 

 

References

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

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

Acknowledgements

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

Citation

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