MAAP #189: Amazon Fire Season Heats Up

Image 1. Example of 2023 (June 29) major fire in Brazilian Amazon.

The Amazon fire season is well under way: to date, we have detected over 260 major fires thus far in 2023 (see Base Map below).

This year is of special concern because scientists indicate we have entered a new El Niño episode. The most intense Amazon fire seasons on record, 2016 and 2017, immediately followed the last major El Niño event.

Most of the fires (54%) this year have occurred in the Brazilian Amazon.

Of these, the vast majority (73%) have burned r­­­­ecently deforested areas. This high number is consistent with previous years (see MAAP #168) and once again highlights the critical link between deforestation and fires in the Brazilian Amazon. That is, most major fires are burning the remnants of a recent deforestation event.

It is also worth noting that many of the fires in the Brazilian Amazon (42%) were burning areas recently deforested specifically for new soy plantations.

We have thus far detected 40 major fires in the Bolivian Amazon. The vast majority (88%) have been burning areas recently deforested specifically for new soy plantations.

We have detected an additional 30 major fires in the Peruvian Amazon, mostly burning high elevation grasslands.

Earlier in the year, between January and March, we detected 50 major fires in the Colombian Amazon. Notably, 100% of them were in burning recently deforested areas.

These findings are based on the unique data from the real-time Amazon Fires Monitoring app developed by our partner organization in Peru, Conservación Amazónica ACCA. In a novel approach, the app combines data from the atmosphere (aerosol emissions in smoke) and the ground (heat anomaly alerts) to quickly and precisely detect major fires, defined as fires burning abundant biomass. In short, the app filters out smaller fires (such as routine burning an old field) and highlights major fires (such as burning recently deforested areas, standing forest, or natural grasslands).

2023 Major Amazon Fires Base Map

Base Map. 2023 major Amazon fires (through July 2023). Data: ACCA, ACA/MAAP.

Amazon Fires Dashboard

We also present our new Amazon fires dashboard, which currently shows results for the 2022 fire season. The dashboard highlights a number of the key findings from last year:

  • We detected 983 major fires.
  • The vast majority (72%) were in Brazil, followed by Bolivia, Peru, and Colombia.
  • Importantly, 73% of the major fires burned recently deforested areas, followed by grasslands, forest fires, and pasture.

The dashboard was developed by the SAS Institute’s Data for Good Program.

Methodology

The reported results are based on an analysis of data generated by a unique real-time Amazon Fires Monitoring app during the year 2023, through July 13.

The app, hosted by Google Earth Engine, was developed and updated daily by the Peru-based organization Conservación Amazónica (ACCA). The resulting data was analyzed and recorded daily by the US-based organization Amazon Conservation. The app was created in 2019 and upgraded in 2020, with the current version launching in May 2021.

When fires burn, they emit gases and aerosols (aerosol definition: Suspension of fine solid particles or liquid droplets in air or another gas) as part of the outgoing smoke. A relatively new satellite (Sentinel-5P from the European Space Agency) detects these aerosol emissions.

The aerosol data, which has a spatial resolution of 7.5 sq km, is not impacted by cloud cover, thus enabling near real-time monitoring during all weather conditions. The app is typically updated each day in the late afternoon/early evening with data for that same day. Thus, there is a high potential for authorities and civil society to also use this app to respond to major fires in the field.

Importantly, the app distinguishes small fires (such as from clearing old fields and thus burning little biomass) from larger fires (such as burning recently deforested areas or standing forests and thus burning high amounts of biomass).

We define a “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 (AI) of >1 (or cyan-green to red on the app).

In a novel approach, the app combines this aerosol data from the atmosphere with heat anomaly data from the ground.

For all detected major fires, we cross-referenced the aerosol emissions pattern with the ground heat-based data to pinpoint the exact location of the fire source. Typically for major fires, there is a large cluster of heat-anomaly alerts aiding the process.

In a final step, the detected major fires are then analyzed with high-resolution optical satellite imagery from Planet Explorer. With this imagery, we can confirm the major fire (by observing smoke on the day of the fire or a burned area scar in the days following the fire) and estimate its size.

Moreover, with Planet’s extensive satellite imagery archive, we can determine the fire type. That is, by comparing imagery from the fire date to previous dates, we can determine whether the fire was burning a) a recently deforested area (defined as fires in areas recently deforested during the past three years), b) an older deforested area (typically long-standing pasture areas), c) standing forest (that is, a forest fire), or natural savannah.

In the app, we can also cross-reference if a major fire has occurred within a protected area or titled indigenous territory.

Note that the high values in the aerosol indices may also be due to other reasons such as emissions of volcanic ash or desert dust so it is important to cross-reference elevated emissions with heat data and optical imagery.

Acknowledgements

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

Citation

Finer M, Costa H, Villa L (2023) Amazon Fire Season Heats Up. MAAP: 189.

MAAP #187: Amazon Deforestation & Fire Hotspots 2022

2022 Amazon Forest Loss Base Map. Deforestation and fire hotspots across the full Amazon biome. Data: UMD/GLAD, ACA/MAAP.

We present a detailed look at the major 2022 Amazon forest loss hotspots, based on the final annual data recently released by the University of Maryland (and featured on Global Forest Watch).

This dataset is unique in that it is consistent across all nine countries of the Amazon, and distinguishes forest loss from fire, leaving the rest as a proxy for deforestation (but also includes natural loss).

Thus, we are able to present both deforestation and fire hotspots across the Amazon.

The Base Map (see right) and Results Graph (see below) reveal several key findings:

  • In 2022, we estimate the deforestation of 1.98 million hectares (4.89 million acres). This represents a major 21% increase from 2021, and is the second highest on record, behind only the peak in 2004.
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  • Deforestation hotspots were especially concentrated along roads in the Brazilian Amazon, the soy frontier in the southeast Bolivian Amazon, and near protected areas in northwest Colombian Amazon.
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  • The vast majority of the deforestation occurred in Brazil (72.8%), followed by Bolivia (12.4%)Peru (7.3%), and Colombia (4.9%). Note that deforestation in Bolivia was the highest on record, and in Brazil the highest since the early 2000s.
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  • Fires impacted an additional 491,223 hectares (1.2 million acres) of primary forest. This total represents a 1.6% increase from 2021, and the 4th highest on record (behind only intense fire seasons of 2016, 2017, and 2020). Moreover, each of the seven most intense fire seasons has occurred in the past seven years. Nearly 93% of the fire impact occurred in just two countries: Brazil and Bolivia.
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  • In total, 2.47 million hectares (6.1 million acres) of primary forest were impacted by deforestation and fire. This total represents the third highest on record, only behind the post-El Niño years of 2016 and 2017.
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  • Since 2002, we estimate the deforestation of 30.7 million hectares (75.9 million acres) of primary forest, greater than the size of Italy or the U.S. state of Arizona.

Below, we zoom in on the six countries with the highest deforestation (Brazil, Bolivia, Peru, Colombia, Ecuador, and Venezuela) with additional maps and analysis.

Amazon Primary Forest Loss (Combined), 2002-2022

Amazon Forest Loss Results Graph, 2002-22. Data: UMD/GLAD, ACA/MAAP.

Amazon Primary Forest Loss (By Country), 2002-2022

Brazilian Amazon

Brazil Base Map, 2022. Deforestation and fire hotspots in the Brazilian Amazon in relation to major roads. Data: UMD/GLAD, ACA/MAAP.

In 2022, the Brazilian Amazon lost 1.4 million hectares (3.56 million acres) of primary forest to deforestation. Fires directly impacted an additional 348,824 hectares.

The deforestation rose 20.5% from 2021, and was the highest on record since the peak years of 2002 – 2005.

The fire impact was the 4th highest on record, only behind the intense fire years of 2016, 2017, and 2020.

The deforestation was concentrated along the major road networks, especially roads 230 (Trans-Amazonian Highway), 364, 319, and 163 in the states of Amazonas, Pará, Rondônia, and Acre (see Brazil Base Map).

The direct fire impacts were concentrated in the soy frontier, located in southeastern state of Mato Grosso

 

 

 

 

 

 

Bolivian Amazon

Bolivia Base Map, 2022. Deforestation and fire hotspots in Bolivian Amazon. Data: UMD/GLAD, ACA/MAAP.

In 2022, the Bolivian Amazon lost 245,177 hectares of primary forest to deforestation. Fires directly impacted an additional 106,922 hectares.

We highlight that this deforestation was 47% higher than 2021, and the highest on record (by far).

The fire impact was also up from last year, and the second-highest on record behind just the intense year of 2020.

Both the deforestation and fires were concentrated in the soy frontier located in southeastern department of Santa Cruz (see Bolivia Base Map).

 

 

 

 

 

 

 

 

 

 

Peruvian Amazon

Peru Base Map, 2022. Deforestation and fire hotspots in the Peruvian Amazon. Data: UMD/GLAD, ACA/MAAP.

In 2022, the Peruvian Amazon lost 144,682 hectares of primary forest to deforestation. Fires directly impacted an additional 16,408 hectares.

Deforestation increased 6.7% from 2021, and was the 5th highest on record. Fire impact decreased from last year, but was still relatively high.

The deforestation was concentrated in the central and southern Amazon (Ucayali and Madre de Dios regions, respectively) (see Peru Base Map).

In the central Amazon, we highlight the rapid deforestation for a new Mennonite colony (see MAAP #166).

In the southern Amazon, gold mining deforestation continues to be an issue in indigenous communities and within the official Mining Corridor.

 

 

 

 

 

 

 

Colombian Amazon

Colombia Base Map, 2022. Deforestation and fire hotspots in northwest Colombian Amazon. Data: UMD/GLAD, ACA/MAAP, FCDS.

In 2022, the Colombian Amazon lost 97,417 hectares of primary forest to deforestation. Fires directly impacted an additional 12,880 hectares.

Deforestation decreased 2% from 2021, but it was still relatively high (5th highest on record), continuing the trend of elevated forest loss since the FARC peace agreement in 2016.

Fire impact increased from last year and was actually the highest on record, edging out 2018 and 2019.

As described in previous reports (see MAAP #120), the Colombia Base Map shows there continues to be an “arc of deforestation” in the northwest Colombian Amazon (Caqueta, Meta, and Guaviare departments).

This arc impacts numerous Protected Areas (particularly Tinigua and Chiribiquete National Parks) and Indigenous Reserves (particularly Yari-Yaguara II and Nukak Maku).

 

 

 

 

Ecuadorian Amazon

Ecuador Base Map, 2022. Deforestation and fire hotspots in the Ecuadorian Amazon. Data: UMD/GLAD, ACA/MAAP.

Although accounting for just 1% of total loss across the Amazon, deforestation in the Ecuadorian Amazon was the highest on record in 2022 (18,902 hectares), up a striking 80% since 2021.

There are several deforestation hotspots caused by gold mining (see MAAP #182), oil palm plantation expansion, and small-scale agriculture.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Venezuelan Amazon

In the Venezuelan Amazon, deforestation was on par with last year (12,584 hectares).

There is a deforestation hotspot caused by gold mining in Yapacana National Park (see MAAP #173, MAAP #156, MAAP #169).

There are also hotspots in the Orinoco Mining Arc caused by mining and agriculture.

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Methodology

The analysis was based on 30-meter resolution annual forest loss data produced by the University of Maryland and also presented by Global Forest Watch.

This data was complemented with the Global Forest Loss due to fire dataset that is unique in terms of being consistent across the Amazon (in contrast to country specific estimates) and distinguishes forest loss caused directly by fire (note that virtually all Amazon fires are human-caused). The values included were ‘medium’ and ‘high’ confidence levels (code 3-4).

The remaining forest loss serves as a likely close proxy for deforestation, with the only remaining exception being natural events such as landslides, wind storms, and meandering rivers. The values used to estimate this category was ‘low’ certainty of forest loss due to fire (code 2), and forest loss due to other ‘non-fire’ drivers (code 1).

For the baseline, it was defined to establish areas with >30% tree canopy density in 2000. Importantly, we applied a filter to calculate only primary forest loss 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).

Our geographic range for the Amazon is a hybrid designed for maximum inclusion: biogeographic boundary (as defined by RAISG) for all countries, except for Bolivia and Peru, where we use the watershed boundary, and Brazil, where we use the Legal Amazon boundary.

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 the 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: High: 3-14%; Very High: >14%.

Acknowledgements

We thank colleagues at Global Forest Watch (GFW), an initiative of the World Resources Institute (WRI) for comments and access to data.

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

Citation

Finer M, Mamani N (2023) Amazon Deforestation & Fire Hotspots 2022. MAAP: 187

MAAP #183: Protected Areas & Indigenous Territories Effective Against Deforestation Across Amazon

Base Map. Primary forest loss (2017-21) across the Amazon, in relation to protected areas and indigenous territories.

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: protected areas & indigenous territories.

Our study looked across all nine countries of the Amazon biome, a vast area of 883.7 million hectares (see Base Map).

We calculated primary forest loss over the past 5 years (2017-2021).

For the first time, we were able to distinguish fire vs non-fire forest loss. For non-fire, while this does include natural events (such as landslides and wind storms), we consider this our best proxy for human-caused deforestation.

We analyzed the results across three major land use categories:

1) Protected Areas (national and state/department levels), which cover 197 million hectares (23.6% of Amazon).

2) Indigenous Territories (official), which cover 163.8 million hectares (19.6% of Amazon).

3) Other (all remaining areas outside protected areas and indigenous territories), which cover 473 million hectares (56.7% of Amazon).

In summary, we found that deforestation was the primary driver of forest loss, with fire always being a smaller subset. Averaged across all 5 years, protected areas and indigenous territories had similar levels of effectiveness, reducing primary forest loss rate by 3x compared to areas outside of these designations.

Below, we show the key results across the Amazon in greater detail, including a breakdown for the western Amazon (Bolivia, Colombia, Ecuador, and Peru) and the Brazilian Amazon.

Key Findings

Amazon Biome

We documented the loss of 11 million hectares of primary forests across all nine countries of the Amazon biome between 2017 and 2021. Of this total, 71% was non-fire (deforestation and natural) and 29% was fire.

For the major land use categories, 11% of the forest loss occurred in both protected areas and indigenous territories, respectively, while the remaining 78% occurred outside these designations.

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

Figure 1. Primary forest loss rates across the Amazon, 2017-21.

Broken down by year, 2017 had the highest forest loss rates, with both a severe deforestation and fire season. In addition, 2021 had the second highest deforestation rate, while 2020 had the second highest fire loss rate.

Averaged across all five years, protected areas (green) had the lowest overall primary forest loss rate (0.12%), closely followed by indigenous territories (0.14%).

Interestingly, indigenous territories (orange) actually had a slightly lower deforestation rate compared to protected areas (0.7 vs 0.8%), but higher fire loss rate (o.7 vs .04%), resulting in the overall higher forest loss rate noted above.

Outside of these designations (red), the primary forest loss rate was triple (.36%), especially due to much higher deforestation.

Western Amazon

Breaking the results down specifically for the western Amazon (Bolivia, Colombia, Ecuador, and Peru), we documented the loss of 2.6 million hectares of primary forests between 2017 and 2021. Of this total, 80% was non-fire (deforestation and natural) and 20% was fire.

For the major land use categories, 9.6% occurred in protected areas, 15.6% in indigenous territories, and the remaining 74.8% occurred outside these designations.

Figure 2 displays the standardized primary forest loss rates across the western Amazon.

Figure 2. Primary forest loss rates across the Western Amazon, 2017-21.

Broken down by year, 2017 had the highest deforestation rate and overall forest loss rates. But 2020 had the highest fire loss rate, mainly due to extensive fires in Bolivia. 2021 also had a relatively high deforestation rate. Also, note the high level of fires in protected areas in 2020 and 2021, and indigenous territories in 2019.

Averaged across all five years, protected areas had the lowest overall primary forest loss rate (0.11%), followed by indigenous territories (0.16%).

Outside of these designations, the primary forest loss rate was .30%. That is, triple the protected areas rate and double the indigenous territories rate.

Brazilian Amazon

Breaking the results down specifically for the Brazilian Amazon, we documented the loss of 8.1 million hectares of primary forests between 2017 and 2021. Of this total, 68% was non-fire (deforestation and natural) and 32% was fire.

For the major land use categories, 9.4% occurred in indigenous territories, 11.2% occurred in protected areas, and the remaining 79.4% occurred outside these designations.

Figure 3 displays the standardized primary forest loss rates across the Brazilian Amazon.

Figure 3. Primary forest loss rates in the Brazilian Amazon, 2017-21.

Broken down by year, 2017 had the highest forest loss rate recorded in the entire study (.58%), due to both elevated deforestation and fire. Note that indigenous territories were particularly impacted by fire in 2017.

2020 had the next highest forest loss rate, also driven by an intense fire season. Fires were not as severe the following year in 2021, but deforestation increased.

Averaged across all five years, indigenous territories had the lowest overall primary forest loss rate (0.14%), closely followed by protected areas (0.15%).

Interestingly, indigenous territories had a lower deforestation rate compared to protected areas (0.5 vs 0.11%), but higher fire impact (0.09 vs 0.04%).

Outside of these designations (red), the primary forest loss rate was triple (.45%).

Methodology

To estimate deforestation across all three categories (protected areas, indigenous territories, and other), we used annual forest loss data (2017-21) from the University of Maryland (Global Land Analysis and Discovery GLAD laboratory) to have a consistent source across all countries (Hansen et al 2013).

We obtained this data, which has a 30-meter spatial resolution, from the “Global Forest Loss due to Fires 2000–2021” data download page. It is also possible to visualize and interact with the data on the main Global Forest Change portal.

The annual data is disaggregated into forest loss due to fire vs. non-fire (other disturbance drivers). It is important to note that the non-fire drivers 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). Thus, we often use the term “primary forest loss” to describe this filtered data.

Data presented as primary forest loss rate is standardized per the total area covered of each respective category per year (annual). 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 extends from the Andes to the Amazon plain and reaching the transitions with the Cerrado and the Pantanal. This range includes nine countries of the Amazon (or Pan-Amazon region as defined by RAISG) and consists of a combination of the Amazon watershed limit, the Amazon biogeographic limit and the Legal Amazon limit in Brazil. See Base Map above for delineation of this hybrid Amazon limit, designed for maximum inclusion.

Additional data sources include:

  • National and state/department level protected areas: RUNAP 2020 (Colombia), SNAP 2022 (Ecuador), SERNAP & ACEAA 2020 (Bolivia), SERNANP 2022 (Peru), INPE/Terrabrasilis 2022 (Brazil), SOS Orinoco 2021 (Venezuela), and RAISG 2020 (Guyana, Suriname, and French Guiana.)
  • Indigenous Territories: RAISG & Ecociencia 2022 (Ecuador), INPE/Terrabrasilis 2022 (Brazil), RAISG 2020 (Colombia, Bolivia, Venezuela, Guyana, Suriname, and French Guiana), and MINCU & ACCA 2021 (Peru). For Peru, this includes titled native communities and Indigenous/Territorial Reserves for indigenous groups in voluntary isolation.

For analysis, we categorized Protected Areas first, then Indigenous Territories to avoid overlapping areas. Each category was disaggregated by year created/recognized to match the annual report of forest loss, for example. If a Protected area was created in December 2018, it would be considered within the analysis for the year 2019.

Acknowledgements

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

We thank M. MacDowell and M. Cohen for helpful comments on this report.

Citation

Finer M, Mamani N (2023) Protected Areas & Indigenous Territories Effective Against Deforestation Across Amazon. MAAP: 176.

MAAP #178: Gold Mining Deforestation Across the Amazon

Base Map. Mining deforestation hotspots across the Amazon. Letters A-J indicate locations of case studies below. Click image to enlarge.

Gold Mining is one of the major deforestation drivers across the Amazon.

Although not typically at the scale of agricultural deforestation, gold mining has the potential to severely impact critical areas such as protected areas & indigenous territories.

Relatedly, gold mining often targets remote areas, thus impacting largely intact and carbon-rich primary forests.

Here, for the first time, we present a large-scale overview of the major gold mining deforestation hotspots across the entire Amazon biome.

We found that gold mining is actively causing deforestation in nearly all nine countries of the Amazon (see Base Map).

In  this report, we focus on five countries: Peru, Brazil, Venezuela, Ecuador, and Bolivia, featuring case studies of the most severe active gold mining fronts.

In most cases, this mining is likely illegal given that it is occurring in protected areas and indigenous territories.

Note that we focus on mining activity that is causing deforestation of primary forests. There are additional critical gold mining areas that are occurring in rivers, such as in northern Peru and southern Colombia, that are not included in this report.

Below, we show a series high-resolution satellite images of the Amazon case studies. Each example highlights recent gold mining deforestation; that is comparing 2020 (left panel) with 2022 (right panel).

Case Studies, in High-resolution

Peruvian Amazon

Southern Peru (specifically, the region of Madre de Dios) is one of the most severe and emblematic examples of gold mining deforestation in the Amazon, clearing thousands of hectares of primary forest (see MAAP #154). The active mining fronts have evolved substantially over the past 20+ years. Most recently, gold mining has impacted areas such as Mangote and Pariamanu.

A. Mangote

B. Pariamanu

Brazilian Amazon

In the vast Brazilian Amazon, illegal gold mining deforestation is most severe across a number of indigenous territories, most notably: Munduruku (Pará state), Kayapó (Pará), and Yanomami (Roraima).

C. Munduruku Indigenous Territory


D. Kayapó Indigenous Territory


E. Yanomami Indigenous Territory

Venezuelan Amazon

Mining is one of the major deforestation drivers in the Venezuelan Amazon (MAAP #155). This mining impact is occurring in the designated Orinoco Mining Arc, but also key protected areas such as Caura, Canaima, and Yapacana National Parks.

F. Canaima National Park


G. Yapacana National Park

Ecuadorian Amazon

We have been documenting the numerous mining deforestation hotspots in the Ecuadorian Amazon that appear to be intensifying in recent years. Two key examples are along the Punino River (Napo and Orellana provinces) and further south in Podocarpus National Park.

H. Punino River

I. Podocarpus National Park

Bolivian Amazon

One of the newest gold mining deforestation hotspots is along the Tuichi River in Madidi National Park.

J. Madidi National Park

Methodology

Mining deforestation hotspots were identified based on MAAP’s ongoing monitoring efforts, and assisted by Amazon Mining Watch.

Acknowledgements

We thank A. Folhadella, S. Novoa, D. Larrea, C. De Ugarte, and M. Teran for helpful comments on this report, and Conservación Amazónica – ACCA for data on mining sites in northern Peru.

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

Citation

Finer M, Ariñez A, Mamani N (2023) Mining Deforestation Across the Amazon. MAAP: 178.

MAAP #181: Illegal Gold Mining in Yanomami Indigenous Territory (Brazil)

Base Map. Illegal mining deforestation alerts in Yanomami Indigenous Territory (northern Brazilian Amazon).

The Brazilian government recently launched a series of raids against illegal gold mining in Yanomami Indigenous Territory, located in the northern Brazilian Amazon (see inset of Base Map).

These raids highlight the severe consequences brought by illegal mining activity, particularly deforestation, contamination, malnutrition, and disease.

Here we present the results of a new machine learning algorithm that analyzes satellite imagery archives across large areas to quickly and precisely detect new gold mining deforestation fronts.

The resolution of these mining deforestation alerts is 10 meters, based on the European Space Agency’s freely available Sentinel-2 satellite imagery data.

These alerts reveal the extent of the gold mining deforestation in Yanomami Indigenous Territory is much greater than realized (see Base Map).

In the Base Map, the red dots indicate the most recent gold mining deforestation alerts, occurring in 2022.

Note that while the raids appear to be concentrated along the Uraricoera River, active gold mining deforestation is actually occurring all throughout the vast northern section of the territory, including the Parima and Mucajai Rivers as well.

We estimate the new gold mining deforestation of over 2,000 hectares since 2019. Much of this deforestation (67%, or 1,350 hectares) occurred most recently in 2022.

Below, we show five examples of this recent gold mining deforestation with high-resolution satellite imagery (3 meters) that confirm the alert detections.

Zooms of Illegal Gold Mining Deforestation, 2020 – 2022

Below, we show five examples of this recent gold mining deforestation with high-resolution (3 meter) satellite imagery that confirm the alert detections (see insets A-E in the Base Map). Note that two of the examples are on the the Uraricoera River, while the other three examples are from other parts of the territory.

Zoom A

Zoom B

Zoom C

Zoom D

Zoom E

Methodology

Gold mining deforestation alerts were generated by Amazon Mining Watch’s updated machine learning algorithim based on Sentinel-2 satellite imagery data.

The Amazon Mining Watch is a partnership between the Pulitzer Center´s Rainforest Investigations Network and Earthrise Media. These two nonprofit organizations have joined forces to bring together the power of machine learning and investigative journalism to shed light on large-scale environmental problems in the Amazon.

 

MAAP #164: Amazon Tipping Point – Where Are We?

Base Map. Total Amazon forest loss. Data: ACA/MAAP.

It is increasingly reported that the largest rainforest in the world, the Amazon, is rapidly approaching a tipping point.

As repeatedly highlighted by the late Tom Lovejoy (see Acknowledgements), this tipping point is where parts of the rainforest will convert into drier ecosystems due to disrupted precipitation patterns and more intense dry seasons, both exacerbated by deforestation.

The Amazon generates much of its own rainfall by recycling water as air passes from its major source in the Atlantic Ocean. Thus, high deforestation in the eastern Amazon may lead to downwind impacts in the central and western Amazon (see Background section below).

The scientific literature indicates this tipping point could be triggered at 25% Amazon forest loss, in conjunction with climate change impacts.

The literature, however, is less clear on the critical first part of the tipping point equation: how much of the Amazon has already been lost?

There are numerous estimates, including 14% forest loss cited in the recent Science Panel for the Amazon report, but we did not find any actual definitive studies specifically addressing this question.

Here, we directly tackle this key question of how much of the original Amazon has been lost to date.

First, we present the first known rigorous estimate of original Amazon biome forest prior to European colonization: over 647 million hectares (1.6 billion acres; see Image 1 below).

Second, we estimate the accumulated total Amazon forest loss, from the original estimate to the present: over 85 million hectares (211 million acres; see Base Map).

Combining these two results, we estimate that 13% of the original Amazon biome forest has been lost.

More importantly, however, focusing on just the eastern third of the Amazon biome (see Image 2 below), we estimate that 31% of the original forest has been lost, above the speculated tipping point threshold. This finding is critical because the tipping point will likely be triggered in the eastern Amazon, as it is closest to the oceanic source of the water that then flows to the central and western Amazon.

Original Amazon Forest

Image 1 shows the first known estimate of original Amazon forest prior to European colonization. Note that we use a broader biogeographical definition of the Amazon that covers nine countries (Amazon biome) rather than the strict Amazon watershed (see Methodology).

Image 1. Original Amazon biome forest. Data: ACA/MAAP.

This represents the most rigorous effort to date to recreate the original Amazon. For example, we attempted to recreate original forest lost to historic dam reservoirs.

The map has just three classes: Original Amazon forest, Original non-forest (such as natural savannah), and Water.

We found that the original Amazon forest covered over 647 million hectares (647,607,020 ha). This is equivalent to 1.6 billion acres.

Of this total, 61.4% occurred in Brazil, followed by Peru (12%), Colombia (7%), Venezuela (6%), and Bolivia (5%). The remaining four countries (Ecuador, Guyana, Suriname, and French Guiana) make up the final 8%.

Amazon Forest Loss

Image 2 shows the accumulated total Amazon forest loss, from the original estimate to the present (2022).

Image 2. Total Amazon forest loss. Vertical lines indicate the Amazon broken down into thirds. Data: ACA/MAAP.

Of the original forest noted above, we documented the historic loss of over 85 million hectares (85,499,157 ha). This is equivalent to 211 million acres.

The largest loss occurred in Brazil (69.5 million ha), followed by Peru (4.7 million ha), Colombia (4 million ha), Bolivia (3.8 million ha), and Venezuela (1.4 million ha). The remaining four countries (Ecuador, Guyana, Suriname, and French Guiana) make up the final 1.9 million ha.

By comparing the original Amazon biome, we calculated the historic loss of 13.2% of the original Amazon forest due to deforestation and other causes.

More importantly, however, we find that 30.8% of the original Amazon has been lost in the eastern third of the Amazon biome (see vertical dashed lines Image 2), above the speculated tipping point threshold. This finding is critical because as noted above, the tipping point will likely be triggered in the east as it is the source of the water flowing to the central and western Amazon.

In contrast, we find that 10.8% of the original Amazon has been lost in the central third of the Amazon biome and 6.3% has been lost in the western third, both of which are below the speculated tipping point threshold.

Background

The Amazon generates around half of its own rainfall by recycling moisture up to 6 times as air masses move from the Atlantic Ocean in the east across the basin to the west. Thus, the rainforest plays a major part in keeping itself alive, by recycling water through its trees to generate rainfall from east to west.

This unique hydrological cycle has historically supported rainforest ecosystems for vast areas far from the main ocean source.

But it also raises the question of how much deforestation would be required to cause the cycle to degrade to the point of being unable to support these forests, thus the Amazon tipping point hypothesis.

In this scenario, rainforests would transform into drier ecosystems, such as open canopy scrubland and savannah.

The tipping point concept originally referred to an abrupt ecosystem change, but it is now believed that the shift could happen gradually (30-50 years).

It is worth noting that the western Amazon near the Andes mountains would likely maintain its rainforests, as air currents flowing over the mountains would continue causing water vapor to condense and fall as rain.

Methodology

At the core of this work, we generated two major estimates: original Amazon forest and total historical Amazon forest loss.

For both of these estimates, we used the biogeographical boundary of the Amazon (as determined by RAISG 2020), which encompasses nine countries. Thus, we used a broader definition of the Amazon (Amazon biome) rather than the strict Amazon watershed, which omits part of the northeastern Amazon biome.

For original Amazon forest, we defined three major classes: Forest, Non-Forest, and Water. This analysis was based on data from MapBiomas Brazil (collection 2 from 1990) with some additional modifications. Original Forest was made up of these MapBiomas categories: Forest Formation, Mangrove, Flooded Forest, Mosaic of Agriculture and Pasture. Non-Forest was made up of these MapBiomas categories: Savanna Formation, Natural Non-Forest Flood Formation, Grassland, and Other non-Forest Formations. Water was made up of these MapBiomas categories: River, Lake, Ocean and Glacier.

We then made a number of modifications with manual edits based on data from the University of Maryland, INPE (Terrabrasilis), ArcGis satellite images, Planet mosaics, Google Earth Engine Landsat images from 1984-1990, and official government data for several countries (Ministry of the Environment of Ecuador (MAE) and Peru (GeoBosques/MINAM), Forest and Carbon Monitoring System/IDEAM of Colombia, National Institute for Space Research of Brazil (INPE/Terrabrasilis), General Directorate of Forest Management and Development of Bolivia (DGGDF), and the National Service of Protected Areas of Bolivia (SERNAP). As an example of a major modification, deforested areas and historic dam reservoirs were changed to Original Forest based on an analysis of the oldest available satellite image for the area (1984-1990). We also corrected some misclassifications, such as forest patches in clearly non-forest areas were changed to Non-Forest (and vice versa) and mountain forest areas found as water were changed to Forest. Also, agriculture and urban areas in likely savannah areas were changed to Non-Forest. Additional Water data from MapBiomas based on 1985 was incorporated. Overall, our focus was defining Original Forest as best as possible; data confusions between Non-Forest and Water categories were not worked on as thoroughly.

For total historical Amazon forest loss, we used data from the University of Maryland. Specifically, we first used their data layer ‘Tree Cover 2000″ (>30% canopy density) to estimate historical (pre-2000) forest loss. We then added annual forest loss data from 2001 to 2021.

Finally, we divided the original Amazon forest by the total historical loss to estimate how much of the original Amazon has been lost. In addition, we delimited the Amazon in thirds according to distance east to west at the widest point. We then estimated how much of the original Amazon has been lost in each of these three sections.

References

(in chronological order)

Sampaio, G., Nobre, C., Costa, M. H., Satyamurty, P., Soares‐Filho, B. S., & Cardoso, M. (2007). Regional climate change over eastern Amazonia caused by pasture and soybean cropland expansion. Geophysical Research Letters, 34(17).

Hansen, M. C. et. al. (2013) High-Resolution Global Maps of 21st-Century Forest Cover Change. Science 342.

Nobre et al. (2016) Land-use and climate change risks in the Amazon and the need of a novel sustainable development paradigm. PNAS, 113 (39).

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.

Lovejoy, T. E., & Nobre, C. (2018). Amazon Tipping Point. Science Advances, 4(2).

Lovejoy, T. E., & Nobre, C. (2019). Amazon tipping point: Last chance for action. Science Advances, 5 (12).

Bullock et. al. (2019) Satellite-based estimates reveal widespread forest degradation in the Amazon. Glob Change Biol., 26.

Amigo, I. (2020) The Amazon’s fragile future. Nature, 578.

MapBiomas. 2020. MapBiomas Amazonia v2.0. https://amazonia.mapbiomas.org/.

Killeen (2021) A Perfect Storm in the Amazon Wilderness

Berenguer E. et. al. (2021) Ch 19. Drivers and ecological impacts of deforestation and forest degradation. In: Nobre C, Encalada et al. (Eds). Amazon Assessment Report 2021. United Nations Sustainable Development Solutions Network, New York, USA. Available from https://www.theamazonwewant.org/spa-reports

Hirota M et. al (2021) Science Panel for the Amazon, Ch 24. Resilience of the Amazon Forest to Global Changes: Assessing the Risk of Tipping Points. In: Nobre C, Encalada et al. (Eds). Amazon Assessment Report 2021. United Nations Sustainable Development Solutions Network, New York, USA. Available from https://www.theamazonwewant.org/spa-reports/

Wunderling et al (2022) Recurrent droughts increase risk of cascading tipping events by outpacing adaptive capacities in the Amazon rainforest. PNAS 119 (32) e2120777119.

Acknowledgements

This report is in memory of Tom Lovejoy, who helped launch the critical concept of an Amazon tipping point. Starting in 2019, we collaborated with Tom on the need assessment and background research behind this report.

We thank Carmen Thorndike for helping with the initial literature review, and Carlos Nobre for review of the final report. We also thank J. Beavers (ACA), A. Folhadella (ACA), M.E. Gutierrez (ACCA), and C. Josse (EcoCiencia) for additional comments.

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

Citation

Finer M, Mamani N (2022) Amazon Tipping Point – Where Are We?. MAAP: 164.

MAAP #161: Soy Deforestation in the Brazilian Amazon

Example of fires burning an area recently deforested for a new soy plantation. Data: Planet.

The Amazon Soy Moratorium has often been credited with significantly reducing soy-related deforestation in the Amazon over the past 15 years.

The Moratorium is a voluntary zero-deforestation agreement in which traders agree not to purchase soy grown on land cleared after 2008.

However, increasing soybean prices may be driving a resurgence of the problem of direct soy deforestation. That is, direct conversion of primary deforestation to soy plantation without passing an initial period as cattle pasture.

A recent report by Global Forest Watch estimated the direct soy deforestation of 29,000 hectares in the Brazilian Amazon in 2019 (Schneider et al 2021).

Here, we report the additional direct soy deforestation of at least 42,000 hectares in the Brazilian Amazon since 2020. All of these areas occurred in the state of Mato Grosso, located on the southeast edge of the Amazon.

We detected all of these soy plantations based on recent major fire activity (84 major fires), in which the recently deforested area was burned in preparation for the upcoming planting season (see Methodology below for more details).

Below, we show a base map of these recently deforested and then burned areas in the Mato Grosso state of the Brazilian Amazon followed by a series of examples from the satellite imagery.

Base Map – Recent Soy Deforestation in Brazilian Amazon

The Base Map below shows the areas, indicated by red dots, of recent direct deforestation for new soy plantations that we detected by monitoring major fire activity in 2022.

Between May 2021 and June 2022, we detected 84 major fires that corresponded to burning areas recently deforested for new soy plantations. These 84 areas, all of which occurred in the state of Mato Grosso, cover an area of 42,000 hectares.

Our geographic focus was the Brazilian Amazon biome in the state of Mato Grosso, as covered by the Amazon Soy Moratorium. For example, we also documented extensive direct soy deforestation and fire in the Bolivian Amazon (Santa Cruz department), but we did not include that information here.

Base Map. Recent Soy Deforestation in Brazilian Amazon. Data: ACA/MAAP, NICFI.

Examples of Deforestation & Fire for New Soy Plantations

As noted above, we detected the direct deforestation for new soy plantations by monitoring major fire activity in 2022. It is assumed that fires are preparing the recently deforested area for upcoming soy planting.

Methodology

We first tracked major fires in 2021 and 2022 using our novel real-time fire monitoring app. See MAAP #118 for more background information about the app and general methodology for detecting major fires based on aerosol emissions. The first major fires were detected in May of each year (2021 and 2022) and we continued collecting data on a daily basis through early July of each year. We monitored fires across the entire Amazon, but this report focuses on Brazil.

For all major fires detected with the app, we confirmed them with high-resolution satellite imagery from Planet. This confirmation was accomplished by visualizing either smoke plumes the day of the fire or burned areas in subsequent days after the fire.

All confirmed fires were assigned a category based on likely direct fire type or driver. These categories include 1) burning area recently deforested for new soy plantation, burning area recently deforested for new cattle pasture, and burning grasslands embedded in the larger rainforest matrix. On rarer occasions, one of these fire types may escape into the surrounding forest, making it an actual forest fire.

Specifically, the soy-related fires were defined as those burning recently deforested areas (that is, areas cleared since 2020) that had a distinctive linear pattern seemingly designed for organized crop agriculture. Most of the newly identified soy areas were also adjacent to existing soy plantations. In other words, the soy deforestation and fire pattern were visually quite distinct from cattle-related and grassland fires. Local experts have informed us that the fires are likely prepping the recently deforested area for the upcoming soy planting season. For all determined direct soy-related fires, we estimated the burned area using the spatial measurement tools in Planet Explorer and entered it into a database. We noted that in July of both years, the fires shifted away from soy and more towards cattle areas.

References

Martina Schneider, Liz Goldman, Mikaela Weisse, Luiz Amaral and Luiz Calado (2021) The Commodity Report: Soy Production’s Impact on Forests in South America. Link: https://www.globalforestwatch.org/blog/commodities/soy-production-forests-south-america/

X.-P. Song, M.C. Hansen, P. Potapov, et al (2021). Massive soybean expansion in South America since 2000 and implications for conservation. Nature Sustainability. Link: https://www.nature.com/articles/s41893-021-00729-z

Acknowledgements

We thank V. Silgueiro and R. Carvalho from the organization Instituto Centro de Vida (ICV) for helpful information and comments related to this report.

Citation

Finer M, Ariñez A (2022) Soy Deforestation in the Brazilian Amazon. MAAP: #161.

MAAP #160: Lasers Estimate Carbon in the Amazon – NASA’s GEDI Mission

Simulation of GEDI lasers collecting data. Source: UMD.

NASA’s GEDI mission uses lasers to provide cutting-edge estimates of aboveground biomass and related carbon on a global scale.

Launched in late 2018 and installed on the International Space Station, GEDI’s lasers return an estimate of aboveground biomass density at greater accuracy and resolution than previously available.

Here, we zoom in on the Amazon and take a first look at the recently available Level 4B data: Gridded Aboveground Biomass Density measured in megagrams per hectare (Mg/ha) at a 1-kilometer resolution.

See the GEDI homepage for more background information on the mission, which extends until January 2023. Be sure to check out this illustrative video.

 

 

 

 

Base Map – Aboveground Biomass in the Amazon

The Base Map displays the GEDI data for the nine countries of the Amazon biome, displaying aboveground biomass for the time period April 2019 to August 2021.

Base Map. Aboveground Biomass Density in the Amazon. Data: NASA/UMD GEDI L4B. Click twice to enlarge.

 

We highlight the following initial major findings:

  • The data is not yet comprehensive as there are some areas the lasers have not yet recorded data (indicated in white).
    h
  • The areas with the highest aboveground biomass and related carbon (indicated in dark green and purple) include:
    • Northeast Amazon: Corner of Brazil, Suriname, & French Guiana.
    • Southwest Amazon: Southwest Brazil and adjacent Peru (see zoom below).
    • Northwest Amazon: Northern Peru, Ecuador, and southeast Colombia.

Zoom In – Southwest Amazon

To better visualize the GEDI laser data, we also present a zoom of the Southwest Amazon. Although deforested areas (and natural savannahs) are illustrated in yellow and orange, note the surrounding presence of high carbon forest (green and purple).

Zoom In – Southwest Amazon. Aboveground Biomass Density. Data: NASA/UMD GEDI L4B. Click twice to enlarge.

Zoom Out – Global Scale

Note that tropical forests, including the Amazon, have the highest levels of aboveground biomass globally.

Zoom Out – Glocal scale. Aboveground Biomass Density. Data: NASA/UMD GEDI L4B. Click twice to enlarge.

Acknowledgements

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

Citation

Finer M, Ariñez A (2022) Lasers Estimate Carbon in the Amazon – NASA’s GEDI Mission. MAAP: 160.

MAAP #158: Amazon Deforestation & Fire Hotspots 2021

2021 Amazon Forest Loss Base Map. Deforestation and fire hotspots across the full Amazon biome. Data: UMD/GLAD, ACA/MAAP.

We present a detailed look at the major 2021 Amazon forest loss hotspots, based on the final annual data produced by the University of Maryland.

This dataset is unique in that distinguishes forest loss from fire, leaving the rest as a close proxy for deforestation.

Thus, for the first time, the results include both deforestation and fire hotspots across the Amazon.

The Base Map (see right) and Results Graph (see below) reveal several key findings:p

  • In 2021, we estimate the loss of 2 million hectares (4.9 million acres) of primary forest loss across the nine countries of the Amazon biome. This total represents a slight decrease from 2020, but the 6th highest on record.
    l
  • The vast majority of this loss was deforestation (78%), accounting for 1.57 million hectares. This total represents a slight increase from 2020, and the 5th highest on record. This deforestation impacted the entire stretch of the southern Amazon (southern Brazil, Bolivia, and Peru) plus further north in Colombia.
    l
  • This deforestation was concentrated in Brazil (73%), Bolivia (10%), Peru (8%), and Colombia (6%). In Brazil and Bolivia, deforestation was the highest since 2017. In Peru and Colombia, deforestation dropped from 2020 but was still historically high. See below for maps and graphs for each country. See Annex for 2020-21 details.
    k
  • Fires directly caused the remaining primary forest loss (22%), accounting for 436,000 hectares. This total represents a decrease from the severe fire season of 2020, but was the 4th highest on record. Moreover, each of the six most intense fire seasons has occurred in the past six years. Over 90% of the fire impact occurred in just two countries: Brazil and Bolivia. Note that fire impacts were concentrated in the southeast of each country (Mato Grosso and Santa Cruz states, respectively).
    k
  • Since 2002, we estimate the deforestation of over 27 million hectares (67 million acres) of primary forest, greater than the size of the United Kingdom or the U.S. state of Colorado. On top of this, we estimate an additional impact of 6.7 million hectares due to fires.

Below, we zoom in on the four countries with the highest deforestation (Brazil, Bolivia, Peru, and Colombia), with additional maps and analysis.

Amazon Forest Loss Results Graph, 2002-21. Data: UMD/GLAD, ACA/MAAP.

For deforestation, note that in 2021 there was a slight increase across the Amazon, continuing a gradual four-year trend. 2021 had the 5th highest deforestation on record (behind just 2002, 2004, 2005, and 2017).

For fire, in 2021 there was a decrease from the severe fire season of 2020, but was the 4th highest on record (behind just 2016, 2017, and 2020). Moreover, each of the last six years is in the top six worst fire seasons across the Amazon.

For total forest loss (deforestation and fire combined), in 2021 there was slight decrease from 2020, but the 6th highest on record.

Brazil Base Map, 2021. Deforestation and fire hotspots in the Brazilian Amazon. Data: UMD/GLAD, ACA/MAAP.

Brazilian Amazon

In 2021, the Brazilian Amazon lost 1.1 million hectares of primary forest to deforestation. Fires directly impacted an additional 293,000 hectares.

The deforestation was the highest since 2017 and also the peak of the early 2000s (6th highest on record). The fire impact was relatively high (5th highest on record), but less than the peak years of 2016, 2017, and 2020.

The deforestation was concentrated along the major road networks, especially roads 163, 230, 319, and 364 in the states of Acre, Amazonas, Pará, and Rondônia (see Brazil Base Map).

The direct fire impacts were concentrated in the southeastern state of Mato Grosso.

It is also important to note that many areas experienced the one-two combination of initial deforestation followed by fire to prepare the area for agriculture or cattle.

 

 

 

Bolivia Base Map. Deforestation hotspots in Bolivian Amazon. Data: UMD/GLAD, ACA/MAAP.

Bolivian Amazon

In 2021, the Bolivian Amazon lost 161,000 hectares of primary forest to deforestation. Fires directly impacted an additional 106,000 hectares.

Deforestation was the third-highest on record, just behind the peak in 2016 and 2017. The fire impact was the second-highest on record, behind just the intense year of 2020 (thus, the last two years are the two highest on record).

Both the deforestation and fires were concentrated in the southeastern department of Santa Cruz (see Bolivia Base Map).

Much of the deforestation was associated with large-scale agriculture, while the fires once again impacted important natural ecosystems, most notably the Chiquitano dry forests.

 

 

 

 

 

 

 

Peru Base Map. Deforestation hotspots in the Peruvian Amazon. Data: UMD/GLAD, ACA/MAAP.

Peruvian Amazon

In 2021, the Peruvian Amazon lost 132,400 hectares of primary forest to deforestation. Fires directly impacted an additional 21,800 hectares.

Deforestation dropped from a record high in 2020, but was 6th highest on record. Thre fire impact was the second-highest on record (behind just 2017).

The deforestation was concentrated in the central and southern Amazon (Ucayali and Madre de Dios regions, respectively) (see Peru Base Map).

We highlight the rapid deforestation (365 hectares) for a new Mennonite colony in 2021, near the town of Padre Marquez (see MAAP #149).

Also, note some additional hotspots in the south (Madre de Dios region), but these are largely from expanding agriculture instead of the historical driver of gold mining.

Indeed, gold mining deforestation has been greatly reduced due to government actions, but this illegal activity still threatens several key areas and indigenous territories (MAAP #154).

 

 

 

 

Rapid deforestation (365 hectares) for a new Mennonite colony in 2021, near the town of Padre Marquez. Data: Planet.

Colombia Base Map. Deforestation hotspots in northwest Colombian Amazon. Data: UMD/GLAD, ACA/MAAP, FCDS.

Colombian Amazon

In 2021, the Colombian Amazon lost 98,000 hectares of primary forest to deforestation. Fires directly impacted an additional 9,000 hectares.

Deforestation and fire dropped from last year, but both were the fourth highest on record, following the trend of elevated forest loss and associated fires since the peace agreement in 2016.

As described in previous reports (see MAAP #120), the Colombia Base Map shows there continues to be an “arc of deforestation” in the northwest Colombian Amazon (Caqueta, Meta, and Guaviare departments).

This arc impacts numerous Protected Areas (particularly Tinigua and Chiribiquete National Parks) and Indigenous Reserves (particularly Yari-Yaguara II and Nukak Maku).

The main drivers of deforestation in the Colombian Amazon are land grabbing, expansion of road networks, and cattle ranching.

 

 

 

Annex

Notes and Methodology

The analysis was based on 30-meter resolution annual forest loss data produced by the University of Maryland and also presented by Global Forest Watch. For the first time, this data set distinguished forest loss caused directly by fire (note that virtually all Amazon fires are human-caused). The remaining forest loss serves as a likely close proxy for deforestation, with the only remaining exception being natural events such as landslides, wind storms, and meandering rivers.

Importantly, we applied a filter to calculate only primary forest loss 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).

Our geographic range for the Amazon is a hybrid designed for maximum inclusion: biogeographic boundary (as defined by RAISG) for all countries, except for Bolivia where we use the watershed boundary.

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 the 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: >5%; High: >7%; Very High: >14%.

Acknowledgements

We thank A. Gómez (FCDS), R. Botero (FCDS)… for helpful comments on earlier drafts of the text and images.

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

Citation

Finer M, Mamani N (2022) Amazon Deforestation Hotspots 2021. MAAP: 153.

MAAP #157: New and Proposed Roads Across the Western Amazon

Amazon Roads Base Map 1.

Extensive deforestation, especially along the major road networks, has shockingly turned the eastern Brazilian Amazon into a net carbon source (see MAAP #144).

Fortunately, the greater Amazon across all nine countries is still a net carbon sink, largely thanks to the still intact core of the western Amazon.

The biggest long-term threat to this core Amazon is likely new roads, as they are a leading cause of opening up vast and previously remote areas to deforestation and degradation (Vilela et al 2020).

Here, we present an initial analysis of new and proposed roads across the western Amazon.

Although it’s difficult to predict what proposed projects are actually likely to eventually move forward, we do find the potential of a major road expansion across the core western Amazon (see Base Map 1).

Moreover, even by just focusing on the most advanced or actively discussed projects, we find the risk of major negative impact.

Below, we discuss our initial Amazon Roads Base Map and present a series of zooms showing the primary forest at risk if select road projects move forward.

 

 

Amazon Roads Base Map

Base Map 2 highlights new, proposed, and existing roads (red, yellow, and black lines, respectively), in relation to protected areas and indigenous territories for context. We focus on the still largely intact core of the western Amazon (Bolivia, Colombia, Ecuador, Peru, and western Brazil).

Most of the new roads were constructed in the past five years and were digitized from satellite imagery. Note that for some of these new roads, just initial construction of a rough road started and there is still potential for future impacts from road improvement and paving.

Most of the proposed roads were obtained from official government data sets. As noted above, it’s difficult to predict what proposed road projects are actually likely to eventually move forward. Nonetheless, it is clear to see there is the potential to greatly divide the remaining core western Amazon with the portfolio of proposed roads.

Amazon Roads Base Map 2. Data: ACA/MAAP, MTC, MINAM, MI, ABT, GAD Napo, FCDS, EcoCiencia, Diálogo Chino, CSF, RAISG, ACCA, ACEAA.

Zooms of High-Impact New & Proposed Roads

In this section, we focus on the currently most advanced or actively discussed projects (see Letters A-F on Amazon Roads Base Map). We highlight their potential impacts to vast sections of the core western Amazon protected areas and indigenous terrritories.

A. Boca Manu Road (Peru)

The new/proposed road that we refer to here as the Boca Manu road would serve as a new connection between Cusco and Madre de Dios regions. It is notable due its sensitive route between Manu National Park and Amarakaeri Communal Reserve to Boca Manu, and from there between Los Amigos Conservation Concession and Amarakaeri Communal Reserve to Boca Colorado. In addition to likely impacting these protected areas and the concession, the road also has the potential to impact the nearby territory of  indigenous groups in voluntary isolation. See this recent report from Diálogo Chino for more information about this road and its status and impacts.

Zoom A. Boca Manu Road. Data: MTC, MINAM, ACA, ACCA, RAISG.

B. Pucallpa – Cruzeiro do Sul Road (Peru – Brazil)

This proposed road would connect the Peruvian city of Pucallpa with the edge of the existing road network in western Brazil, near the town of Cruzeiro do Sul. Although the potential route has several options, it would sure cut through or near Sierra del Divisor National Park in Peru and the adjacent Serra do Divisor National Park in Brazil. This area is characterized by vast primary forests, thus creating a new binational route connecting the deforestation fronts in each country could obviously trigger significant impacts. See this recent report from Diálogo Chino for more information about this road and its status and impacts.

Zoom B. Pucallpa – Cruzeiro do Sul Road. Data: MTC, MINAM, ACA, CSF, Diálogo Chino, RAISG.

C. Yurua Road (Peru)

The new/proposed road that we refer to here as the Yurua road would connect the Peruvian towns of Nueva Italia on the Ucayali River and Breu on the Yurua River. This 200 km route was originally built as a logging road in the late 1980s to access remote timber areas in the central Peruvian Amazon, but had fallen into disrepair by the early 2000s. A recent MAAP analysis (see MAAP #146) found that between 2010 and 2021 much of the route had been rehabilitated, triggering elevated deforestation along the way. If this road were ever to be paved then impacts would likely continue to rise, including with native communities along the route. See MAAP #146 for more information about this road and its status and impacts.

Zoom C. Yurua Road. Data: MTC, MINAM, ACA, ACCA, RAISG.

D. Genaro Herrera – Angamos Road (Peru)

This new/proposed road would build off an old track through the vast forests connecting the northern Peruvian towns of Genaro Herrera and Angamos, in the region of Loreto. In 2021, clearing began along this route, advancing over 100 kilometers from both ends. If completed and paved, the final road project would impact protected areas on both sides (including the Matsés National Reserve to the south) and pose a major threat to indigenous people in voluntary isolation reportedly living to the north. See this recent report for more information about this road and its status and impacts.

Zoom D. Genaro Herrera – Angamos Road. Data: MTC, ACA, RAISG.

E. Cachicamo – Tunia Road (Chiribiquete National Park, Colombia)

Chiribiquete National Park, located in the heart of the Colombian Amazon, has been experiencing increasing deforestation pressures, partly due to expanding road networks around and even within the park. For example, the Cachicamo-Tunia Road, constructed in 2020, has triggered a new deforestation front in the northwest section of the park. Note this road is also impacting an adjacent Indigenous Reserve.

Zoom E. Cachicamo – Tunia Road. Data: FCDS, RAISG, ACA.

F.  Manaus – Porto Velho Road (BR-319, Brazil)

Arguably the most controversial project on the list: paving the middle section of BR-319 in the heart of the Brazilian Amazon. This nearly 900 km road connects the remote city of Manaus (otherwise only reachable by air or water) with the rest of Brazilian road network in Humaitá and Porto Velho to the south. It was built in the early 1970s but abandoned and impassable by the late 1980s, isolating Manaus once again. Since 2015, a basic maintenance program has made the road generally passable, but the main project remains: paving the 400 km middle section that passes through the core western Amazon. This paving would effectively connect Manaus with the existing highways in the south, and most likely trigger massive forest loss by extending the arc of deforestation northwards, including within and around the protected areas that surround the road. This road project has been the subject of numerous recent press reports, including investigative pieces by the Washington Post and El Pais.

Zoom F. Manaus – Porto Velho Road. Data: Ministério da Infraestrutura, ACA, RAISG.

G. Ixiamas – Chivé Road (Bolivia)

In recent years, Bolivia has been seeking financing for a 250 km road linking the current frontier town Ixiamas with the isolated town Chivé, located near the Peruvian border on the Madre de Dios river. This road would cross extensive tracts of primary Amazon forest and savannah in the north of the La Paz department, including the newly created Bajo Madidi Municipal Conservation Area and the Tacana II indigenous territory.

Zoom G. Ixiamas – Chivé Road. Data: ABT, ACEAA, ACA, RAISG.

Methodology

Our analysis and maps focus on the western Amazon (Bolivia, Colombia, Ecuador, Peru, and western Brazil).

Most of the new roads were constructed in the past five years and were digitized from satellite imagery. Note that for some of these new roads, just initial rehabilitation/improvement of a rough road started and there is still potential for future impacts from paving.

Most of the proposed roads were obtained from official government data sets (and complemented by civil society reports).

We credit the following data sources: Ministerio de Transportes y Comunicaciones (Peru), Geobosques/MINAM (Peru), Ministério da Infraestrutura (Brazil),  Autoridad de Fiscalización y Control Social de Bosques y Tierra – ABT (Bolivia), Gobierno Autonomo Descentralizado Provincial de Napo (Ecuador), Fundación para la Conservación y el Desarrollo Sostenible – FCDS (Colombia), Fundación EcoCiencia (Ecuador), Diálogo Chino, Conservation Strategy Fund, RAISG, Conservación Amazónica – ACCA (Peru), Conservación Amazónica – ACEAA (Bolivia), and Amazon Conservation (digitalization of some new and proposed roads).

Reference:
Vilela et al (2020) A better Amazon road network for people and the environment. PNAS 17 (13) 7095-7102.

Acknowledgments

We especially thank Diálogo Chino for their support of this report. We also thank E. Ortiz, S. Novoa, S. Villacis, D. Larrea, M. Terán, and D. Larrea for helpful comments on earlier drafts of the text and images.

Citation

Finer M, Mamani N (2022) New and Proposed Roads Across the Western Amazon. MAAP: 157.