MAAP #251: Transboundary illegal gold mining: Brazil (Puruê River) & Colombia (Puré River)

Figure 1. Base map of transboundary mining area Colombia-Brazil. Data: ACA/MAAP

*This transboundary report is in collaboration with the Field Museum of Natural History, as part of a Rapid Biological and Social Inventory of the Alto Rio Japurá e Puruê, coordinated by the Field Museum in partnership with 11 research organizations and Indigenous federations in Brazil.

In a recent report (MAAP #245), we revealed the increasing gold mining deforestation along the Puré River, which flows through the heart of Puré River National Park in the southeastern Colombian Amazon.

Specifically, we reported that this mining deforestation emerged in 2024, escalated in 2025, and impacted over 500 hectares by May 2026.

Here, we highlight that the Puré River crosses into the northwestern Brazilian Amazon and becomes the Puruê River, a tributary of the Japurá River, which eventually flows into the upper Amazon River (see Figure 1 – Base Map).

This remote, but threatened, Puré-Puruê River region is critically important due its extraordinary biodiversity and high carbon stocks, and is home to Indigenous communities, including Indigenous peoples living in voluntary isolation (specifically, the Yurí and Passé). 

In this report, we present novel data for the gold mining deforestation along the entire Puré (Colombia) – Puruê (Brazil) River region as an important transboundary case study.

In summary, we documented the gold mining deforestation of 7,900 hectares between 2001 and 2026 in the Puré-Puruê River transboundary region. While we first detected mining on the Brazil side as early as 2001, 88% has occurred since 2022, indicating that mining in the area has been recently escalating. The vast majority of the mining (92%) has occurred on the Brazil side (Puruê River), but has recently encroached and increased on the Colombia side (Puré River).

Transboundary Gold Mining Deforestation (Graph)

Figure 2 indicates the gold mining deforestation along the Puruê River in Brazil (orange bars) and the Puré River in Colombia (yellow bars). 

We first detected mining deforestation in 2001 on the Brazil side, which then slowly increased over the next 20 years, reaching a cumulative total of 980 hectares by the end of 2021. 

There was then a major peak in mining deforestation on the Brazil side in 2022 and 2023 (4,130 hectares in just these two years). 

Starting in 2024, the mining deforestation also extended to the Colombia side. While lower than the previous peak years, the combined mining deforestation in both countries was  relatively high from 2024 to June 2026 (2,791 hectares during these three years). 

In total, we estimate the cumulative gold mining deforestation of 7,901 hectares in both countries, as of June 2026. Of this total, 92% (7,307 hectares) has occurred on the Brazil side (Puruê River), and 8% (594 hectares) on the Colombia side (Pure River).

Figure 2. Gold mining deforestation in study area. Data: Amazon Conservation/MAAP

Government Operations

In response to the increasing gold mining activity and deforestation, there have been a series of 7 recent government operations targeting illegal mining in both the Puruê and Puré Rivers (see purple lines in Figure 2).

Three of these operations have featured binational coordination between authorities in both countries, and four have been focused on just the Brazil side.

The first record of a binational operation took place in December 2023. While there was no mining deforestation in Colombia yet at this time, there were mining barges on the Puré River. 

There were then two major binational operations in 2025 (May and November), when the mining deforestation was escalating in Colombia. These operations were coordinated among Colombian entities—the Attorney General’s Office (via its Directorate for Specialized Crimes against the Environment), the Colombian Aerospace Force, and the Colombian National Army—and Brazilian entities—the Ministry of Defense, the Brazilian Army, the Federal Police, and ICMBio.

These operations appeared to have short term effectiveness, but then mining quickly returned. For example, following the May 2025 operation, the mining deforestation subsequently declined on the Colombia side in June and July 2025, but then spiked again by November.

Similarly, following the November 2025 operation, the mining deforestation subsequently declined in December 2025 and January 2026 on the Colombia side, but then started to rise again by March.

Transboundary Gold Mining Deforestation (Maps)

Figure 3. Gold mining deforestation in study areas. Data: Amazon Conservation/MAAP

Figure 3 illustrates the gold mining deforestation along the Puré-Puruê River in both Colombia and Brazil, respectively.

As noted above, we estimate the total gold mining deforestation of 7,901 hectares as of June 2026, with 92% on the Brazil side (Puruê River).

The initial mining deforestation of 980 hectares over the first 20 years (2001-2021) is indicated in yellow, the peak in 2022 and 2023 (4,130 ha) is indicated in orange, and the most recent period of 2024-June 2026 is in red (2,791 ha).

On the Brazil side, note the mining deforestation on the Puruê River extends from the confluence with the Japurá River all the way to the Colombian border, including up several southern tributaries. The mining extended to the Colombia side (Pure River) in 2024.

Given this vast area, the mining deforestation data is relatively difficult to visualize. To better highlight this data, below we zoom in on four representative areas (two in each country).

 

 

 

 

 

Zooms of gold mining deforestation

In each of the four zooms below, we show the mining deforestation data followed by a before/after panel of satellite imagery. See Boxes 1-4 in Figure 3 for the location of each zoom (two in each country).

Zoom 1: Puruê River (Brazil)

Zoom 2: Puruê River (Brazil)

Zoom 3: Pure River (Colombia)

Zoom 4: Pure River (Colombia)

Policy Implications

Above, we have documented an important case of Amazonian transboundary illegal gold mining in the remote border area between southeast Colombia and northeast Brazil.

On the Brazilian side (Puruê River), the scale and persistence of illegal gold mining point to a problem that can no longer be addressed through intermittent enforcement operations alone. Brazil accounts for the overwhelming majority of the mining-related deforestation documented in the Puré–Puruê corridor (92%; over 7,300 hectares), with impacts extending from the lower Puruê near its confluence with the Japurá to the Colombian border and into tributaries. The recent decline in the rate of new mining deforestation following government operations is important, but the repeated reappearance of mining activity demonstrates the need to complement enforcement with a long-term strategy for territorial protection, governance, and permanent monitoring.

On the Colombia side (Puré River), while the overall gold mining deforestation is less (8%, over 500 hectares), it is more recent and accelerating. In addition, all of the documented gold mining deforestation is taking place within Puré River National Park, a strictly protected area where land use is not designated for mining operations of any kind. Thus, we have documented nearly 600 hectares of illegal gold mining deforestation in the park between 2024 and mid 2026 (MAAP #245). It is worth noting that prior to the emergence of this deforestation, we reported the presence of more than 50 mining dredges along the course of the Puré River within the National Park in 2024 and 2025 (MAAP #228).

A central issue across both countries is the impact of illegal gold mining on Indigenous peoples living in voluntary isolation. Evidence from the broader Puré–Puruê landscape indicates that isolated peoples may circulate across a transboundary forest landscape rather than according to the administrative boundary between Brazil and Colombia. On the Colombian side, the Yurí and Passé are formally recognized and protected within Puré River National Park; on the Brazilian side, indications of isolated peoples require urgent investigation and precautionary protection by the competent authorities. Until their presence, patterns of movement, and territorial use can be more fully assessed, continued expansion of mining creates major risks of rights violations against Indigenous peoples derived from violent encounter, disease transmission, mercury contamination, displacement, and loss of access to essential territories and resources.

The impacts of mining also extend beyond the areas directly cleared for extraction and include mercury contamination. Mercury used in illegal gold mining enters the Puré-Puruê–Japurá aquatic system and creates risks for downstream populations whose food security, livelihoods, and health depend heavily on fish and other aquatic resources. Mining activity can likewise generate spillover pressures on neighboring protected areas, including the Juami-Japurá Ecological Station, and on Indigenous territories connected to the wider Japurá landscape. The policy response therefore needs to consider the Puruê not simply as a collection of illegal mining sites, but as part of a connected river and forest system in which environmental contamination, biodiversity loss, and territorial insecurity can be transmitted far downstream and beyond the immediate mining frontier.

It is important to note that Colombia instituted a total ban on mercury in 2023, building off an initial ban issued in 2013. This prohibition covers the import and export of mercury to and from the national territory. Despite the ban within Colombia, mercury is still heavily used for illegal gold mining in border zones, such as those examined in this report.

It is also important to note that the mining economy is increasingly intertwined with a broader security challenge. 

The municipalities of Japurá and Maraã, which serve as key logistical bases for people, fuel, equipment, and supplies moving toward mining areas, are seeing a growing presence of organized criminal factions. This convergence between illegal mineral extraction, river transportation networks, and organized crime raises the stakes well beyond environmental enforcement. It calls for sustained coordination among environmental, Indigenous affairs, public-security, and defense institutions, together with their Colombian counterparts. Protecting the Puré–Puruê corridor will ultimately require simultaneously disrupting the logistical and financial networks that sustain illegal mining, protecting downstream and neighboring populations and territories, and establishing durable territorial protections for one of the most remote and vulnerable areas of the Brazil–Colombia border.

In conclusion, as illegal Amazonian gold mining continues to expand along the remote Colombia-Brazil border, our findings indicate that binational law enforcement operations appear effective in the short term, yet illegal gold mining inevitably returns relatively quickly (within months). The challenge lies in implementing long-term strategies in a remote, binational region that is also impacted by organized crime and home to vulnerable isolated and uncontacted Indigenous groups. The overall challenge, therefore, lies in strengthening sustained efforts to build a mining prevention strategy, while also continuing to develop operational response capabilities and coordinate binational actions across the border region.

Coordinated government actions are key given that supplies, dredges, and mining infrastructure are provided by business operators from municipalities in Brazil—specifically Japurá (the urban center closest to this area), Maraã, and Jutaí. Furthermore, the river routes used to transport supplies and machinery also serve to move the gold extracted in these zones—from the Puré-Puruê river corridor, across the Japurá and Tefé rivers, and finally to the city of Manaus.

Finally, we note that Colombia has activated protection mechanisms (established in 2018) for the Puré River National Park in response to risk reports. More recently, the Ministry of the Interior issued an Early Warning (#1635) in August 2026, mandating a coordinated institutional response among the Ministries of Health, Defense, and Foreign Affairs; however, follow‑up has so far been limited to administrative coordination and inter‑agency meetings, without new operational deployments on the ground. Satellite monitoring continues to show incursions, with dozens of mining rafts and hundreds of hectares deforested inside protected areas. Although the system aims to guarantee the territorial integrity and isolation of the Yurí and Passé peoples through health contingency protocols, collaboration with neighboring indigenous groups, and coordination with local governments—while also relying on binational security operations with Brazil—the problem remains unresolved.

Overall, the appropriate legal tools are in place, yet the capacity to resolve the current situation hinges on the national government allocating funding and demonstrating the political will to implement measures on the ground, moving beyond legal formalities to an operational presence that effectively dismantles the illegal mining infrastructure along the border.

Acknowledgments

We thank the Field Museum of Natural History for its important contributions (co-designing and co-writing) to this report.

MAAP #250: Amazon Tipping Point – Where Are We? (2026 Update)

Figure 1. Amazon primary forest loss. Data: Amazon Conservation/MAAP, UMD.

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

Generally defined, this tipping point is where parts of the rainforest will convert into drier ecosystems due to disrupted precipitation patterns caused by increasing deforestation.

The Amazon uniquely generates much of its own rainfall by recycling water from its source in the east (Atlantic Ocean) all the way west to the Andes Mountains and beyond, in a phenomenon known as flying rivers (see MAAP #232 and the follow-up white paper). Thus, high deforestation in the eastern Amazon may lead to downwind impacts (reduced precipitation) in the western Amazon. Importantly, these flying rivers follow different pathways during the wet season (northern route) vs. the dry season (southern route), implying that the tipping point is not a uniform event across the Amazon biome, as some areas are more vulnerable to atmospheric moisture (flying rivers) disruptions than others.

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

In a previous report published in 2022 (MAAP #164), we reconstructed the likely extent of the original Amazon biome forest prior to European colonization, and then estimated accumulated total Amazon forest loss (through 2021). Based on this analysis, we estimated that 13.2% of the original Amazon biome primary forests were lost to deforestation and fires.

Here, for our 250th report, we update this estimate by incorporating forest loss data through 2025. From 2022 to 2025 we found an additional forest loss of 13 million hectares, including the record-breaking year of 2024 for fires. Our updated estimate is that 15% of the original Amazon biome primary forest has been lost, mostly due to deforestation and fires (Figure 1).

In addition, breaking the results by seasonal moisture flow routes (see Figure 3 below), we find that moisture flows during the dry and transition seasons are most affected and disrupted (9.1% and 8.6% forest loss, respectively). This finding is critical because during the critical dry and transition seasons, the role of forest-driven moisture recycling is especially important to maintain rainforests in the southwest Amazon. In contrast, we find that the wet season moisture flow is more intact, with just 3.2% total forest loss.

Original Amazon Forest

As first presented in MAAP #164, we merged several datasets to estimate the extent of the original Amazon forest (Figure 2). We define this original forest as the extent of the Amazon forest before European colonization (and thus may include changes from pre-European indigenous populations). 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).

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

We found that the original Amazon primary forest covered 647.6 million hectares (equivalent to 1.6 billion acres).

Of this total, 61.4% occurred within the current border of 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%.

Figure 2. Original Amazon biome forest. Data: Amazon Conservation/MAAP. Source MAAP#164.

Amazon Forest Loss

In MAAP #164, we reported the historical accumulated Amazon primary forest loss, as of the end of 2021. We documented the total loss of 85.5 million hectares, or 13.2% of the original Amazon.

For this report, we updated the data as of the end of 2025. This data is broken down into three time periods:

By 2000, we estimate that the original Amazon forest had lost 36 million hectares (MAAP #164).

The 2001-2021 estimate of primary forest cover loss was reduced from 49.5 million to 48 million hectares due to adjustments in the forest loss methodology used by the University of Maryland (UMD). It is important to highlight that this finding includes forest loss from both fire (7.3M ha) and non-fire (40.7M ha) causes, and does not include forest gain/regeneration.

A novel 2022-2025 estimate was generated based on the most recent UMD data, adding 13.04 million hectares, including the record-breaking year of 2024 that was mainly driven by forest fires following the strong El Niño event of 2023 (see MAAP #229 and #248). Similarly, this includes forest loss from both fire (5.43M ha) and non-fire (7.61M ha) causes. This total loss over just four years is the equivalent size of the US state of Louisiana.

Combining these three periods gives an updated total of 97.06 million hectares lost (equivalent to 240 million acres). This includes forest loss from both fire (12.78 M ha) and deforestation (84.28 M ha) causes.

The largest loss occurred in Brazil (79.4%), followed by Bolivia (6.2%),  Peru (5.8%), Colombia (4.5%), Venezuela (1.7%), Guyana (0.8%), Ecuador (0.7%), Suriname (0.6%), and French Guiana (0.2%).

Taking this updated forest loss total of 97.06 million hectares in relation to the original 647.6 million hectares gives our key finding of 15% of the original Amazon forest lost, mostly due to deforestation and fire (Figure 1). This estimate also includes natural causes such as landslides and windstorms.  

Figure 3 further illustrates the results broken down by seasonal moisture flow routes (as presented in MAAP #232). We found the transition season moisture flow is most threatened and impacted (9.1% total forest loss), followed by the dry season moisture flow (8.6%).

This finding is important because during the critical dry and transition seasons, the role of flying rivers to carry moisture to water-stressed forest in the southwest Amazon is especially important. In other words, extensive deforestation in the eastern and central parts of these pathways could negatively impact the downwind western part, which means that the tipping point event is not a single and homogenous one across the Amazon biome and there will be geographical areas that will be impacted sooner and harder.

In contrast, we find that the wet season moisture flow is more intact, with just 3.2% total forest loss.

Figure 3. Amazon forest loss in flying rivers pathways. Data: Amazon Conservation/MAAP

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.

As presented in MAAP #164, 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. As noted above, we define this original forest as the extent of the Amazon forest before European colonization (and thus may include changes from pre-European indigenous populations).

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 original Amazon forest,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 used the Global Forest Change (GFC) and Global forest loss due to fire datasets developed by the University of Maryland (UMD) for the period 2001–2025. We then derived annual forest loss from the loss year layer of GFC. Subsequently, we separated fire-related from non-fire-related forest loss using the annual Global forest loss due to fire dataset. Areas classified with medium to high certainty of fire attribution (codes 3 and 4) were considered fire-related forest loss, whereas codes 1 and 2 were used to identify non-fire-related forest loss, representing areas of forest loss attributed to other drivers. This classification was applied to minimize potential overestimation of fire-related forest loss. All data processing and analyses were conducted using Google Colaboratory.

It is important to note that for the more modern post-2000 era (2001-25), data is available for forest loss due to both fire and non-fire causes. This data represents our best estimate or proxy for primary forest loss.  Non-fire loss can be considered more permanent, such as deforestation, while fire loss may be considered more as degradation. The results above combine both types of data to be consistent with the original results presented in MAAP #164.

It is also important to note that our estimates do not include forest gain/regeneration.

Finally, we estimate the amount of primary forest loss in the major seasonal moisture flow pathways (wet, dry, and transition seasons), as presented in  MAAP #232.

References

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.

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.

Acknowlegments

This work was supported by NORAD (Norwegian Agency for Development Cooperation).

Citation

Finer M, Mamani N, Ariñez A, Castillo H (2026) Amazon Tipping Point – Where Are We? (2026 Update).

MAAP #248: Implications of upcoming major El Niño event on Amazon fires

Figure 1. El Niño 2023. Data: Google Gemini

In our annual series on forest loss trends in the Amazon (MAAP #244 & MAAP #229), we observed that the two most recent intense fire seasons, 2016 and 2024, immediately followed major El Niño events. 

For example, extreme drought conditions created by a strong El Niño in late 2023 created extreme drought conditions the following year, enabling widespread fires across the Amazon in 2024. In contrast, the reduced fires of 2025 were associated with the moister conditions of La Niña.

For background, the definition of El Niño is based on warm sea surface temperature in a specific zone of the Pacific Ocean several hundred kilometers off the coast of South America (Figure 1).

Specifically, a Sea Surface Temperature Anomaly (SSTA) above 0.5 degrees Celsius in the El Niño 3.4 Zone is classified as an El Niño event (See Methods section for details). Anomalies above 1 degree C are a moderate event, and above 2 degrees C, a very strong event.

We took this SSTA data annually from 2002 to 2025 for the 3-month period of October-November-December, which typically correlates with peak temperature anomalies.

We then analyzed this data in relation to the following year’s fire-caused primary forest loss (data from the University of Maryland). We focused the analysis on years with at least a weak El Niño (SSTA > 0.5).

Results

Figure 2. El Niño and Amazon Fires. Data: UMD, NOAA

Filtering the dataset for El Niño years (SSTA > 0.5 degrees C) isolates 8 specific historical events (2002, 2004, 2006, 2009, 2014, 2015, 2018, and 2023). 

Of these events:

Four were Weak El Niño (SSTA 0.5- 0.9): 2004, 2006, 2014, and 2018;

Two were Moderate (SSTA 1.0 – 1.4): 2002, 2009;

One was Strong (SSTA 1.5 to 1.9): 2023;

And one was Very Strong (SSTA ≥ 2.0): 2015.

To analyze the delayed (lagged) impact, the SSTA from each year (Year t) is paired directly with the Fire Primary Forest Loss Area from the following year (Year t+1). 

See Figure 2 for the visual correlation between El Niño events (blue) and primary forest loss from fires (red).

Note the initial observation that prompted this study: the major peak in fires in 2016 following the Very Strong El Niño of 2015, followed by the record-breaking fire season in 2024 following the Strong El Niño of 2023.

Despite a limited sample size (only 8 El Niño events since 2000) and limited statistical power, the analysis reveals a clear, strong positive relationship between the strength of El Niño events (that is, magnitude of the sea surface temperature anomaly) and the severity of the following fire season. 

The strength of this relationship approaches the traditional margin of statistical significance (probability value under  0.05), with a probability value of 0.08 (see the Annex for details).

Thus, the data do indicate a potential escalating relationship between El Niño and Amazon fires.

Most notably, the two highest sea surface temperature anomalies —2015 (+2.34) and 2023 (+1.49)—directly preceded the two largest fire seasons, 2016 (1.76 million hectares) and 2024 (2.79 million hectares), respectively.

Low-tier warm anomalies (like +0.52 or +0.73) correspond to lagged fire sizes under 160,000 hectares.

Discussion

As detailed above, the available data indicates a strong positive correlation between the severity of El Niño events and the intensity of the Amazon fire season the following year.

This correlation is anchored by two key events that prompted this analysis in the first place: the peak fire season in 2016 following the Very Strong El Niño of 2015; and the record-breaking fire season in 2024 (see MAAP #229) following the Strong El Niño of 2023.

There is currently an urgency regarding these findings due to the predicted Very Strong El Niño event (that is, SSTA > 2 degrees C) in late 2026 and implications for the 2027 fire season. Some predictions have the SSTA as the highest on record, even approaching 3 degrees C by November to December 2026. 

The current SSTA (for May-June-July 2026) is +0.98 degrees C (Weak to Moderate El Niño), rapidly coming out of last year’s La Niña phase, and warming fast.

Thus, the best recent analogue is the Very Strong El Niño of 2015, and the subsequent burning of nearly 1.8 million hectares of primary Amazon forest the following year in 2016. The most recent analogue is 2023 (see Figure 1), and the subsequent record-breaking fire season of 2024.

We also raise the possibility that the impact on fires carries over to a second year following a major El Niño – this could account for the severe fire seasons of 2017 (1 million hectares) and 2025 (1.5 million hectares).

The weaker El Niño years show a consistent directional pattern but without the same magnitude response.

We also note a major structural break in the data: in general, fires are much greater starting in 2016 (average fire area pre-2016: ~150k ha; Post-2016: ~1.0M ha). This time frame slightly precedes, overlaps, and then continues after the President Bolsonaro administration (2019-2023), which weakened illegal deforestation enforcement policies. Thus, there may be a new modern elevated baseline of fire activity in the Brazilian Amazon.

Since El Niño typically peaks in November to December, which corresponds to the onset of the wet (monsoon) season, the mechanism for this correlation may be shutting down the convection engine driving the rainy season. The disruption of the wet season moisture flow could extend the dry and transition seasons, reducing precipitation, creating drier conditions, and preventing the soil from recovering its moisture, setting up the Amazon for an intense fire season.

It is worth noting that another recent study found that the years with the largest burned areas in the Peruvian Amazon between 2013 and 2024 coincide with the occurrence of El Niño events and drought conditions (Reference 10).

How ready are Amazonian countries for the upcoming 2027 El Niño fire season?

Experience of 2024

The 2023 El Niño and subsequent 2024 fire season exposed the depth of the preparedness gap across the Amazon basin. The responses that emerged were largely reactive, deployed well into a crisis that monitoring systems had anticipated months earlier. Brazil, Peru, and especially Bolivia were most affected among the Amazonian countries, and this review of institutional preparedness focuses on these three countries. Drier conditions created by El Niño, however, created an increased fire risk across the entire biome, affecting all countries.

Brazil mounted the most substantial national response, though it arrived belatedly. By August 2024 — almost three months since the wildfires started — a state of emergency was decreed in 45 municipalities and 48 Brazilian cities were put on high alert (Reference 1). In the end, fires directly impacted 1.9 million hectares, the highest on record (MAAP #229).

Peru also declared a national emergency during the 2024 crisis, unlocking emergency coordination powers and international assistance. In the end, however, fires impacted 47,574 hectares, more than double the previous high (MAAP #229).

Bolivia also had its worst fire season on record in 2024, as fires directly impacted  779,960 hectares, far surpassing the previous record (MAAP #229). The main cause of deforestation and subsequent fires was likely agrarian speculation. Two supreme decrees in 2024 granted zero tariffs and tax incentives to agribusiness, which triggered a surge in demand for land for monocultures of soy, sugarcane, and seed oils. This expansion was supported by existing regulations that expedite the clearing of up to 20 hectares.  The government declared a national emergency and later a national disaster, but the response was hampered by weak enforcement: Bolivia’s fines for illegal forest burning (under $20/hectare) are roughly 2% of Brazil’s, and tensions between national and local government further slowed emergency coordination. To contain the disaster, the government declared an Ecological Environmental Pause, which suspended burning permits and placed the burned public lands under quarantine for five years. The Inter-American Commission on Human Rights’ special rapporteur documented how tensions between national and local governments hindered emergency responses, while policies aimed at aggressively expanding industrial agriculture had dried out large areas of the country, leaving ecosystems vulnerable to fire.

Changes implemented in 2025

Fire impact was much lower in 2025 relative to 2024 (1.5 million vs 2.8 million hectares of primary forest burned, respectively) (MAAP #244). Several Amazonian countries implemented stronger fire management policies in response to the 2024 fire season. The reduced burnt area, however, cannot be solely attributed to better institutional preparedness, as climate conditions were also more favorable, with La Niña bringing relief through higher humidity levels across the biome. 

In February 2025, Brazil’s Environment Minister Marina Silva decreed a pre-emptive environmental emergency ahead of the fire season, giving authorities extra powers and resources to contain wildfires before they spread. The federal government committed to hiring an additional 250 federal firefighters and allocated 45 million reais to bolster state-level fire brigades across six Amazonian states (Reference 3). Other structural measures followed: Brazil’s Supreme Court ordered the federal government and all Amazon and Pantanal states to draw up emergency fire management plans, while the Ministry of Environment announced “governance offices” in 70 Amazon municipalities — supported by FUNBIO and UNDP — to provide vehicles, boats, drones, and training for fire prevention (Reference 4). The Prevfogo program, managed by IBAMA, was expanded as a platform integrating satellite-based detection with ground response. These combined efforts contributed to a measurable decline in fire activity in 2025 compared with the previous year (MAAP #244).

In Peru, in response to the 2024 events, the Ministry of Environment proposed a Forest Fire Prevention and Control Law to establish regional firefighting brigades and prohibit land-use change in areas affected by wildfires, though recent amendments to the Forest Law (Law No. 31973) may undermine this approach (Reference 5). Seven of Peru’s 24 regions have published forest fire prevention and risk reduction plans, and a Multisectoral Plan for Wildfire Response 2025–2027 is currently being developed, drawing on risk assessments that classify nearly 20% of national territory as high or very high fire risk.

In Bolivia, the legislative trajectory since 2024 has moved in the opposite direction. Agribusiness lobbies have pressured to roll back burning fines, and a land reform that would have accelerated deforestation in Santa Cruz and Beni, the departments that burned most severely in 2024, was enacted in the first half of 2026, and then repealed in the face of social protests (Reference 6). The country has been navigating its worst economic and political crisis in decades, and institutional preparedness for the 2027 fire season could be severely challenged under these conditions. 

In terms of regional cooperation, the most significant recent development is the Operational Understanding for Preparedness and Response, approved by ACTO member countries in early 2026. This non-binding regional cooperation framework establishes mechanisms for coordinating mutual assistance among Amazonian countries when the magnitude of forest fires requires a joint response, facilitating the articulation of national capacities, exchange of operational information, and technical support during fire-related emergencies. Concurrent with its adoption, member countries agreed to establish the Forest Fire Response Committee (CRIF), a regional body tasked with developing technical instruments, operational procedures, and coordination mechanisms to improve preparedness and joint response (Reference 7).

In conclusion, the reduction in burnt area observed across the three countries in 2025 occurred under favorable climate conditions, which, as our analysis shows, are unlikely to be seen in 2027. The true test of institutional preparedness will come under El Niño-driven stress. The regional architecture, meanwhile, can only perform as well as its weakest national link. Under a degraded political landscape and without policy improvements since 2024, Bolivia could become the epicenter of the 2027 fire season.

Outlook for 2026 – 2027

From the FAO’s El Niño Fire Readiness checklist (Reference 8), there are five major components of readiness for next year’s 2027 fire season.

First is “Fire Awareness”, which includes understanding historical trends that distinguish an average season from an anomaly season, and what drives major fires (such as fuel load from recently deforested areas) that could be incorporated into Risk Reduction strategies.

As noted above, annual MAAP reports (MAAP #229, MAAP #244) provide historical trends for the Amazon regarding fire impact to primary forests. These reports allow for the identification of intense, or anomalous, fire seasons (such as 2024).

In terms of what drives major fires, previous MAAP reports have revealed the tight link between deforestation and fires in the Amazon (MAAP #189). That is, most major fires are burning recently deforested areas, and then may escape into surrounding forests, especially with extended dry conditions such as 2016 and 2024. For example, over 70% of major fires in the Brazilian Amazon burn recently deforested areas  (MAAP #189). There is also a strong link between deforestation and fire in the Bolivian Amazon, where deforestation also often precedes fires, which may then escape into surrounding forests or savannahs.

Thus, one of the key strategies to minimize major fires in 2027 is to minimize new deforestation in 2026.

Second is the establishment of “Fire Danger Rating and Early Warning” systems and the provision of this information to stakeholders.

As the El Niño intensifies throughout 2026, this could include the monitoring of moisture or drought conditions and issuing respective warnings.

Third is “Fire Preparedness,” and includes guidance for prevention, detection, and suppression of fires based on the above rating and warning system.

In terms of prevention, fire-free agricultural practices could be promoted in 2026 and more strictly enforced in 2027, coordinating closely with local rural unions and cooperatives (Reference 9). Local community initiatives represent a critical component of this preparedness, serving as tangible examples of prevention, detection, and suppression mechanisms.

For instance, the Territorial Strengthening Actions implemented across the Amazon basin demonstrate this integrated approach: communities in Colombia, Peru, Bolivia and Ecuador are actively developing local capacities for fire detection, sustainable management (safe fire use) and early response, while promoting alternative practices to slash-and-burn agriculture. 

This community-based approach is further strengthened by broader regional efforts, such as the CoRAmazonia program. This initiative promotes an Integrated Fire Management strategy that integrates technical, scientific, and traditional indigenous knowledge. Through platforms like ExpoMIF and the Amazon Network for Integrated Fire Management (RAMIF), the program highlights the crucial role of Indigenous peoples and traditional communities in fire governance, emphasizing the importance of community brigades, territorial monitoring, and the rescue of affected wildlife.

Fourth is “Pre-fire Season Activities,” which highlights whether agencies are adequately engaging stakeholders and setting up national agreements.

Fifth is “Fire Detection, Communication, and Dispatching,” which forms the real-time fire Response procedures and mechanisms.

In terms of detection, real-time fire monitoring should be integrated into national response protocols and field-level coordination.

For communication and dispatching, there could be the establishment of contingency plans to extinguish forest fires rapidly before they spread, focusing heavily on fires starting in recently deforested areas and expanding towards protected areas or Indigenous territories.

In Peru specifically (Reference 10), the most critical districts are concentrated in the Ucayali, Madre de Dios, and Huánuco regions. Regarding public budget allocation, there are gaps in the prevention of and response to forest fires, resulting in limited operational capabilities and significant disparities in the allocation and execution of public resources for disaster risk management. Overall, there is the need to strengthen systems for monitoring, early warning, planning, and institutional response regarding forest fires, prioritizing areas with the greatest historical vulnerability.

Methods

The analysis combined two primary data sources: 1) Relative Oceanic Niño Index (RONI) based on sea surface temperature anomaly (SSTA) and 2) annual primary forest loss from fires.

RONI, the standard used by NOAA for classifying El Niño (warm) and La Niña (cool) events in the eastern tropical Pacific, is the running 3-month average sea surface temperature (SST) for the Niño 3.4 region, minus the overall average tropical 3-month sea surface temperature anomaly (SSTA). For this study, we used the 3-month period of October-December for each year. 

Events are defined as 5 consecutive overlapping 3-month periods at or above the +0.5 anomaly for warm (El Niño) events and at or below the -0.5 anomaly for cool (La Niña) events.  The threshold is further broken down into Weak (with a 0.5 to 0.9 SST anomaly), Moderate (1.0 to 1.4), Strong (1.5 to 1.9), and Very Strong (≥ 2.0) events. 

In addition to warm SSTA in the Pacific Ocean, Amazon drought conditions may also be influenced by warm SSTA in the North Tropical Atlantic Ocean (Reference 10), but our study did not account for this.

The fire 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 Global Forest Loss due to fire dataset 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).

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).

The analysis was supported and reviewed by AI: Gemini and Claude

Annex

Because we have a constrained subset (N = 8), the statistical power is limited, but a clear, strong positive pattern is evident across several major metrics.

The Pearson Linear Correlation indicates a strong positive linear relationship between the magnitude of the warm anomaly and the next year’s fire area (r = +0.6146), approaching the traditional margin of statistical significance (p-value = 0.1049). This correlation is even stronger when we take the natural log of the fire area to account for natural fire activity  (p-value = 0.0827).

Spearman Rank Correlation reaffirms that higher SSTA values rank alongside worse fire outcomes in the succeeding year ( +0.5476; p-value= 0.1600).

  • Log-Transformed Pearson Correlation (r log): +0.6474
  • Wildfire spread typically behaves exponentially rather than linearly. When we take the natural log of the fire area (ln{Fire}_t+1) to correct for this, the correlation strengthens to nearly +0.65, approaching the traditional margin of statistical significance (p < 0.10).

References

1. Lancet Regional Health – Americas / PMC. (2025). The 2024 South America ablaze: Health impacts and policy imperatives for protecting population health in an era of wildfires

2. IACHR (2025) REDESCA publishes report on wildfires in Bolivia and calls for urgent action to address impacts on human rights and ecosystems

3. Mongabay (2025). Brazil declares environmental emergency ahead of 2025 fire season.

4. Muggah, R., & Szabo, I. / Mongabay. (2025). Brazil is speeding-up forest fire prevention to avoid dangerous tipping points in the Amazon. 

5. Lancet Regional Health – Americas / PMC. (2025). The 2024 South America ablaze. (See footnote 3.) Peru-specific governance section

6. Copa Pabón, M. V. (2026, May 15). Indigenous protest forces repeal of land privatization law in Bolivia.

7. ACTO. (2026, February–March). ACTO member countries approve Operational Understanding for Preparedness and Response to Forest Fires in the Amazon Region.

8. FAO El Niño Fire Readiness checklist (2024) As presented in the Global Fire Management Hub and informed by its Integrated Fire Management Voluntary Guidelines

9. Brown F, et al (2026). Alert related to the coming severe dry period, heat waves, fires, smoke and climate in the Madre de Dios-Peru, Acre-Brazil, Pando-Bolivia (MAP) Region – 30 April 2026. Foster Brown

10. ACCA (2026) El Niño y los incendios forestales en la Amazonía peruana, ¿qué podemos esperar para la temporada 2026-2027?

Citation

Finer M, Bodin B (2026) Implications of upcoming major El Niño event on Amazon fires. MAAP: 248.

Acknowledgements

We thank colleagues from the following organizations for helpful comments on the report: Conservación Amazónica – ACEAA in Bolivia and Conservación Amazónica – ACCA in Peru.

This work was supported by Norad (Norwegian Agency for Development Cooperation).

MAAP #246: Illegal gold mining in protected areas in the Juruena River region, Mato Grosso (Brazilian Amazon)

Base Map. Illegal mining, Juruena National Park and Igarapés do Juruena State Park. Data: ICV.

The Brazilian state of Mato Grosso plays a pivotal role along the southeastern frontier of the Amazon, located at a critical transition zone between the Amazon, Cerrado, and Pantanal biomes. This unique location allows the state to serve as a shield against the encroachment of deforestation into the Amazon rainforest’s interior from the more impacted biomes.

Recent monitoring, however, indicates increasing deforestation in Mato Grosso (INPE and MapBiomas), particularly due to agricultural and mining expansion.

Regarding the threat from mining specifically, the sector in the state is governed by a legal framework, but challenges related to governance, transparency, and the oversight of mining activities persist (Amazon Mining Watch). In addition, recent legislative changes (such as Supplementary Law No. 788/2024, which addresses the relocation of legal reserves for mining purposes) have sparked debates concerning the easing of environmental protections on private properties and the indirect impact on public lands.

In part due to this weakened legal framework, the Juruena River basin, located in the northern tip of Mato Grosso, faces a critical situation regarding the expansion of illegal small-scale gold mining (OPAN, 2026). Mining in this region has been ongoing since the 1970s, when colonization incentive projects and road construction facilitated access to the area, attracting miners from various parts of the country. Since then, mining has played a major role in the regional economy, developing predominantly without effective government oversight.

Mining-related regulations have existed in the region since the 1990s (OPAN, 2021), and various environmental and law enforcement agencies have carried out successive operations to combat illegal mining from 2006 to 2024 (specifically, in 2006, 2008, 2017, 2020, 2021, 2023, and 2024).

Over the last two decades, and intensifying in recent years, the expansion of small-scale mining has encroached upon the two key conservation units in the Juruena River region: Juruena National Park and Igarapés do Juruena State Park (see Base Map).

This illegal activity is not only occurring in both national and state-level protected areas, but also operating outside the scope of concessions granted by the National Mining Agency

Both areas, however, are situated in a region facing intense formalized mining pressure, with a predominance of applications in the initial request stage in the immediate vicinity (see Figure A1), indicating a growing risk of mining expansion and intensifying indirect impacts on these protected areas.

Figure A1: Active mining processes. Source: National Mining Agency (ANM, June 2026)

Protected Areas Threatened

The scenario described above has created major mining-related impacts in the Juruena River basin, including deforestation, siltation, and mercury contamination, thereby compromising biodiversity and the food security of local communities.

This report details the evidence of this encroachment, analyzing the pressures exerted on Juruena’s protected areas between July 2025 and April 2026, as well as the challenges regarding enforcement and the region’s territorial integrity.

Juruena National Park

The illegal gold mining activity in Juruena National Park is concentrated in the southwestern part of the protected area (Figure B1).

Figure B1. Area affected by artisanal mining in Juruena National Park. Source: Planet.

The specific area affected by illegal mining deforestation in Juruena National Park showed a major increase between 2025 and 2026 (Figure B2). In August 2025, the impacted area was 10.5 hectares (left panel), increasing to 79.5 hectares by April 2026 (right panel).

Figure B2. Mining deforestation in Juruena National Park (2025-26). Data: (Skysat)

In addition to the deforestation described above, we also detected mining camps, equipment, and access roads (Figure B3), indicating the establishment of the basic infrastructure to support extraction activities.

Figure B3. Mining camps and equipment in Juruena National Park. Data: Planet (Skysat)

The analysis presented above focused on the most recent gold mining deforestation in Juruena National Park, from August 2025 to April 2026. Additional data from the Amazon Mining Watch platform provides more historical context of the mining activity in the park since 2018 (Figure B4). According to the platform, the cumulative area affected by mining within the conservation unit increased from 240 hectares in 2018 to 730 hectares by June 2026, highlighting the continuous expansion of the activity over recent years.

Figure B4: Amazon Mining Watch results for Juruena National Park.
Figure B5. Embargo area in the Juruena National Park. Data: (ICMBio)

We noted a record of environmental enforcement action regarding the illegal mining activity in Juruena National Park (ICMBio 2026).

In April 2025, an embargo was issued for a 17.4-hectare area affected by mining operations (Figure B5).

According to the enforcement record, the sanction was imposed due to the operation of an activity utilizing environmental resources—deemed actually or potentially polluting—without the required license from the competent environmental agency.

The measure aimed to halt the ongoing activity, prevent the expansion of environmental impacts, and ensure the protection of Juruena National Park’s natural resources.

According to information provided by IBAMA/ICMBio, 15 operations targeting illegal mining within the boundaries of Juruena National Park have been carried out since 2010. The most recent one took place in June 2026. The agency also noted that illicit mining activities intensified starting in 2020.

In total, the operations resulted in approximately 11 notices of violation, 35 asset seizure records, 37 embargo orders, 32 records of the destruction or rendering unusable of seized items, 3 demolition orders, and 1 custody order.

However, this entire history of enforcement—and, more recently, the issuance of violation notices and imposition of stop-work orders—has not prevented the continuation and expansion of illegal mining in this area of ​​Juruena National Park.

This situation highlights the chronic nature of the problem and, above all, underscores the importance of maintaining monitoring and enforcement efforts and taking swift action to counter the resurgence of these illegal activities in the region.

Igarapés do Juruena State Park

The illegal gold mining deforestation is concentrated in the south-central region of Igarapés do Juruena State Park (Figure C1).

Figure C1. Gold mining in Igarapés do Juruena State Park. Data: Planet (Skyat)

The specific area affected by illegal mining deforestation in Igarapés do Juruena State Park showed a major increase between 2025 and 2026 (Figure C2). In June 205 the impacted area was 8.6 hectares (left panel), and then increased to 43.7 hectares in March 2026 (right panel).

Figure C2. Increase in mining deforestation in Igarapés do Juruena State Park, 2025-26. Data: Planet (Skysat)

In addition to the deforestation described above, we also detected mining camps, equipment, and access roads (Figure C3), indicating the establishment of the basic infrastructure to support extraction activities.

Figure C3. Mining camps and equipment in Igarapés do Juruena State Park. Data: Planet (Skysat)
Figure C4. Environmental enforcement actions in Igarapés do Juruena State Paek. Data: SEMA-MT

Regarding environmental enforcement actions related to mining activities in Igarapés do Juruena State Park, we identified a violation notice, issued by the Mato Grosso State Secretariat of Environment (SEMA-MT in Portuguese) in August 2020 and addressed to an overlapping rural property in the municipality of Colniza (Figure C4).

Subsequently, in September 2025, records show the issuance of another notice of violation by SEMA-MT due to mineral extraction without an environmental license, resulting in an administrative fine. In March 2026, a formal embargo order was issued for the area in question and recorded in the Rural Environmental Registry (CAR in Portuguese).

This measure mandated the suspension of all activities across a 13.7-hectare area due to the unauthorized clearing of native vegetation within a Legal Reserve Area and the conduct of small-scale mining without an environmental license. The embargo aimed to halt environmental degradation, prevent the expansion of impacts on the conservation unit, and promote the recovery of the affected area.

The sequence of violation notices and administrative measures—initially in 2020 and subsequently in 2025 and 2026—highlights the recurring enforcement actions in the area and the persistent pressure that mining activities exert on the Igarapés do Juruena State Park.

In this context, constant monitoring and rapid field responses are essential to prevent the resurgence and expansion of illegal mining practices.

Policy Implications

The occurrence of illegal mining within strictly protected conservation units indicates limitations in the monitoring and control mechanisms for these areas. This scenario is particularly concerning in the Juruena River region, where the expansion of gold mining has encroached upon two key protected areas (Juruena National Park and Igarapés do Juruena State Park), causing major impacts such as deforestation and mercury contamination.

The National System of Nature Conservation Units (SNUC in Portuguese, established by Law No. 9.985/2000), stipulates that “Full Protection” categories—such as Ecological Stations, Biological Reserves, National Parks, Natural Monuments, and Wildlife Refuges—permit only the indirect use of natural resources (for example, research, tourism, and environmental education). Consequently, the continuation of small-scale mining activities in these areas violates the provisions of the Federal Constitution and the SNUC framework, while compromising the ecological integrity of these territories.

Data from Amazon Mining Watch indicates that mining deforestation identified within Conservation Units in the Juruena region is taking place outside authorized mining concessions, strongly suggesting illegality. Although legal instruments exist to regulate mining and restrict natural resource use in Full Protection Conservation Units, the occurrence of small-scale mining outside areas authorized by the National Mining Agency highlights weaknesses in the mechanisms for control, oversight, and monitoring of territorial protection measures.

Given this scenario, it is essential to strengthen oversight and monitoring mechanisms for Conservation Units. Adopting an integrated geospatial information platform—combining satellite-based alert systems with up-to-date data on mining concessions and the boundaries of protected areas (such as Conservation Units and Indigenous Territories)—could facilitate more effective monitoring and response by public authorities.

In this context, improvements to the Mining Registry platform—managed by the National Mining Agency (ANM)—could represent an important step forward in transparency and territorial oversight regarding mining activity in the Juruena region, as well as in other areas of Mato Grosso facing pressure from small-scale mining. Key improvements could include consolidating data from the mining registry (Cadastro Mineiro), the Mining Geographic Information System (SIGMINE), and the Geological Survey of Brazil (SGB) geographic portal. This would enable, for instance, the integration of mining and geological data layers within a single mapping environment, alongside more comprehensive details on mining applications, such as their procedural history. Other potential enhancements include the ability to issue official certificates—once the mining registry and SIGMINE are integrated—and the automated cross-referencing of mining concession polygons with protected areas and Indigenous territories, thereby facilitating the identification of overlaps, inconsistencies, and potential irregularities. Peru’s GeoCatmin system could serve as a reference for implementing these improvements.

Beyond strengthening state oversight capabilities, such an integrated public tool would expand access to information for civil society and research institutions, contributing to environmental governance, the prevention of illegal activities, and a more agile response to pressures on areas of high socio-environmental importance.

Given the recurring nature of small-scale mining practices and the severe environmental impacts they cause, it is crucial that authorities intensify monitoring, enforcement, and suppression measures, ensuring the effective protection of the Juruena region’s conservation units and the preservation of its biodiversity.

Methodology

The organization Amazon Conservation generated the baseline mining deforestation alerts in Juruena National Park and Igarapés do Juruena State Park for the period from June 2025 to April 2026, based on early warning forest loss alerts from the University of Maryland and analysis with high-resolution satellite imagery from Planet.

The Brazilian organization Instituto Centro de Vida (ICV) then led the verification of these alerts, delineation of affected areas, and characterization of infrastructure associated with illegal mining based on the visual interpretation of very-high-resolution satellite imagery from Planet (SkySat, 50 cm). The analysis considered elements characteristic of artisanal mining activity, such as access roads, camps, machinery, and other mining support structures.

ICV also analyzed the GeoPortal of the Mato Grosso State Secretariat of Environment (SEMA-MT) to identify enforcement actions targeting areas affected by mining within Igarapés do Juruena State Park.

Finally, for Juruena National Park, ICV analyzed platforms and databases belonging to the federal agencies responsible for the unit’s management and enforcement, including the Geoservices Platform of the Chico Mendes Institute for Biodiversity Conservation (ICMBio) and the Pamgia portal of the Brazilian Institute of the Environment and Renewable Natural Resources (Ibama). They examined records of enforcement actions related to mining activity in the study area, such as notices of violation, embargoes, and other administrative measures applied by the competent authorities.

References

  1. ANM. AGÊNCIA NACIONAL DE MINERAÇÃO (ANM). Dados geoespaciais de processos minerários – SIGMINE. Disponível em: https://geo.anm.gov.br/portal/apps/webappviewer/index.html?id=6a8f5ccc4b6a4c2bba79759aa952d908. Acesso em: 24 jun. 2026. 
  2. BRASIL. Lei nº 9.985, de 18 de julho de 2000. Dispõe sobre o Sistema Nacional de Unidades de Conservação da Natureza. Disponível em: https://www.planalto.gov.br/ccivil_03/leis/l9985.htm. Acesso em: 15 jun. 2026.
  3. BRASIL. Constituição da República Federativa do Brasil de 1988. Disponível em: https://www.planalto.gov.br/ccivil_03/constituicao/constituicao.htm. Acesso em: 15 jun. 2026.
  4. ICMBio. INSTITUTO CHICO MENDES DE CONSERVAÇÃO DA BIODIVERSIDADE. 2026. Dados geoespaciais – Autos de infração (shapefile). Disponível em: https://www.gov.br/icmbio/pt-br/dados-icmbio/dados_geoespaciais/mapa-tematico-e-dados-geoestatisticos-das-unidades-de-conservacao-federais/autos_infracao_icmbio_shp.zip. Acesso em: 02 jun. 2026. 
  5. EARTH GENOME. Amazon Mining Watch. 2022. Disponível em: https://amazonminingwatch.org/. Acesso em: 15 jun. 2026.
  6. OPAN. OPERAÇÃO AMAZÔNIA NATIVA. 2026. Boletim de pressões e ameaças às terras indígenas na bacia do rio Juruena. Cuiabá: OPAN. Disponível em: https://amazonianativa.org.br/pub/boletim-de-pressoes-e-ameacas-as-terras-indigenas-na-bacia-do-rio-juruena-2/. Acesso em: 29 jun. 2026. 
  7. OPAN. OPERAÇÃO AMAZÔNIA NATIVA. 2021. Processos minerários na bacia do rio Juruena: implicações para os povos indígenas e a conservação da biodiversidade. Cuiabá: OPAN. Disponível em: https://amazonianativa.org.br/wp-content/uploads/2021/12/OPAN_RT_Processos-minerarios-Juruena-v4.pdf. Acesso em: 25 jun. 2026.
  8. SEMA. Secretaria de Estado de Meio Ambiente de Mato Grosso. 2026. Geoportal – Autos de Infração e Embargos. Disponível em: https://geoportal.sema.mt.gov.br/. Acesso em: 13 mai. 2026.

Acknowledgements

This report was produced in collaboration with the Brazilian organization Instituto Centro de Vida (ICV), and with the support of the Gordon and Betty Moore Foundation.

MAAP #244: Amazon Deforestation & Fire Hotspots 2025

Base Map. Deforestation and fire hotspots across the Amazon in 2025. Data: UMD/GLAD, Amazon Conservation/MAAP

Continuing our annual series, we present a detailed look at the major 2025 Amazon forest loss hotspots and trends, based on the annual data recently released by the University of Maryland and featured on Global Forest Watch. As in other reports of the series, we take this global dataset and analyze it specifically for the Amazon.

This dataset, which serves as a consistent source across all nine countries of the Amazon, distinguishes forest loss from fire and non-fire causes. We use the non-fire forest loss as a proxy for human-caused deforestation, although it also includes some natural loss. In addition, we apply a filter to focus just on primary forest loss.

With this context, we are able to identify the primary forest loss hotspots from fire and non-fire (deforestation proxy) causes across the Amazon in 2025 (see Base Map). 

The non-fire (proxy for deforestation) hotspots were largely due to agriculture and gold mining across the Amazon. These hotspots were concentrated in the:

  • Soy frontiers of southeast Brazil (Area A; see MAAP #161) and southern Bolivia (Area B; MAAP #179),
    .
  • Along major roads in Brazil, such as the Trans-Amazonian Highway (Area C) and BR-364 (Area D). There is also agricultural expansion along an expansive road network in northern Brazil (Area K).
    .
  • Agricultural areas in central Peru (Area E), including lands occupied by Mennonite colonies (MAAP #222),
    .
  • Arc of deforestation in northwest Colombia (Area F) associated with roads, land grabbing (and associated cattle pastures), and coca cultivation (MAAP #224),
    .
  • Gold mining areas in southern and central Peru (Area G; MAAP #233, MAAP #241), northern Ecuador (Area H)  (MAAP #230, MAAP #227, MAAP #219), northeast Amazon (Venezuela, Guyana, Suriname – for example, Area I), and Indigenous territories in Brazil (for example, Area J; MAAP #239).

 

The fire hotspots were concentrated in the soy and cattle frontiers of the southeast Brazilian Amazon and southeast Bolivian Amazon (including the important ecosystem of the Chiquitano dry forests), and also northeast Bolivia. This fire data may be interpreted as forest degradation, in contrast to the more permanent impacts of deforestation.

Amazon Primary Forest Loss, 2002-2025

In 2025, the major story was that fires were down from the record-breaking year of 2024 (Graph 1). Fires were still historically high, however (1.5 million hectares), marking the 3rd-highest since 2002 (behind only the peak fire seasons of 2016 and 2024).

Non-fire forest loss was also down from 2024 (Graph 1). While still just above 1 million hectares, it was the lowest total over the past 10 years and the 5th-lowest since 2002.

Cumulatively, we estimate the non-fire forest loss of 34.8 million hectares of primary forest since 2002, about the size of Germany or the U.S. state of Montana. An additional 12.2 million hectares have been impacted by fires.

Note that Graph 1 is interactive: The reader can click items in the legend (Non-fire and Fire-caused forest loss), and on the circles for each year to visualize the data point.

Amazon Primary Forest Loss, 2025

In 2025, the majority of non-fire primary forest loss occurred in Brazil (55%), followed by Bolivia (20%), Peru (14%), and Colombia (6%) as the clear top four (Graph 2a; Annex 1).

Notably, Brazil had the lowest annual loss on record since 2002, at around 560,475 hectares. 

Bolivia‘s non-fire primary forest loss (200,000 ha) was still historically high (4th highest on record), but lower than the previous peak three years of 2022-24.

Peru’s non-fire primary forest loss was the 5th highest on record (147,480 ha), and the highest over the past 5 years.

Colombia’s non-fire primary forest loss (66,310 ha) was the second lowest since the FARC peace agreement in 2016.

The vast majority (97%) of fire-caused primary forest loss occurred in just two countries: Brazil and Bolivia. Peru added 2% (26,580 ha). All three countries’ fire impact was much lower than last year’s record-breaking fire season.

Note that Graph 2a is interactive: The reader can click the bars for each country for non-fire forest loss (purple bars) and fire forest loss (orange bars). To see the data for the countries with less forest loss, click on the “Log” option in the upper right (or see Annex 1, further below).

Amazon Primary Forest Loss Rate, 2025

Standardizing for area, we show that Bolivia has the highest non-fire primary forest loss rate, followed by Peru, Colombia, then Brazil (Graph 2b).

Bolivia also has, by far, the highest fire-caused primary forest loss rate, followed by Brazil, and more distantly, Peru.

Note that Graph 2b is interactive: The reader can click the bars for each country for non-fire forest loss (purple bars) and fire forest loss (orange bars).

Amazon Deforestation 2025

In a novel analysis, we directly estimate Amazonian deforestation for the first time. As noted above, the primary forest loss data described above is a good proxy for deforestation, but also includes loss associated with natural events, such as landslides, windstorms, and meandering rivers.

Using the “WRI Google Drivers of Tree Cover Loss” dataset, we estimate the primary forest loss directly caused by agriculture, mining, and infrastructure. That is, directly estimate human-caused deforestation.

In 2025, we estimate the deforestation of 736,484 hectares across the Amazon (Graph 3). The vast majority (94.6%) of this deforestation came from agriculture (both permanent and shifting). An additional 5.3% came from hard commodities, mostly gold mining. The remaining 0.1% was caused by roads and infrastructure.

Over half (55.2%) of this deforestation occurred in Brazil, followed by Peru (16.8%), Bolivia (13.8%), and Colombia (8.5%).

Peru had the most mining deforestation, followed by Brazil, Guyana, Suriname, and Venezuela. However, we note that Amazon Mining Watch indicates that Brazil had higher mining deforestation than Peru in 2025.

Note that Graph 3 is interactive: The reader can click on the bars for each country. To see the data for the countries with less forest loss, click on the “Log” option in the upper right

Amazon Deforestation 2025 in Protected Areas & Indigenous Territories

Of the 2025 Amazon deforestation noted above, nearly 132,000 hectares (18%) occurred in protected areas and Indigenous territories (Graph 4). This may be considered a general estimate for illegal deforestation.

Agriculture accounted for 89% of this deforestation, and mining for the remaining 11%.

Brazil had the most deforestation in protected areas and Indigenous territories (33%), followed by Bolivia (25%), Peru (20%), Colombia (10%), Venezuela (6%), and Ecuador (4%).

Specifically for gold mining, Brazil had the most deforestation in protected areas and Indigenous territories, followed by Peru and Venezuela.

Note that Graph 4 is interactive: The reader can click items in the legend (Agriculture and Mining, by designation), and on the bars to visualize the data for each country.

Annex 1

Note that Annex 1 is interactive: The reader can click on the countries in the legend, and on the circles for each year to visualize the data point. To see the data for the countries with less forest loss, click on the “Log” option in the upper right.

Policy Implications

Following the record-breaking fire season of 2024, fire impact in 2025 was still historically high (3rd highest on record) but much reduced from the previous year’s peak. As detailed in MAAP #229, the 2024 fire season was associated with a strong El Niño event, creating extremely dry conditions across the Amazon. In contrast, 2025 was associated with the moister conditions of La Niña. This correlation has major implications for the predicted upcoming super El Niño season and will be the subject of an upcoming report.

Instead of fires, the major story in 2025 was relatively positive: the lowest non-fire primary forest loss over the past 10 years, and the 5th lowest on record.

However, in 2025 an additional 1 million hectares of primary forest was lost, bringing the cumulative total lost to 34.8 million hectares since 2002, the size of Germany or Montana.

As in previous years, the countries with the highest primary forest loss were Brazil, Bolivia, Peru, and Colombia, respectively. 

Notably, Brazil had the lowest annual loss on record since 2002, and Colombia was the second lowest since the FARC peace agreement in 2016. In contrast, Bolivia and Peru were both relatively high, but with different trends: Bolivia was lower than the previous peak years, while Peru was the highest over the past 5 years.

Standardizing for area, Bolivia had the highest primary forest loss rate, followed by Peru, Colombia, and then Brazil.

In terms of spatial patterns, non-fire primary forest loss hotspots were detected in all countries. Major agricultural deforestation areas occurred in southeast Brazil, southern Bolivia, central Peru, and northwest Colombia. Major mining areas were detected in southern and central Peru, northern Ecuador, the northeast Amazon (Venezuela, Guyana, Suriname), and Indigenous territories in Brazil.

Finally, in a novel analysis, we directly estimate Amazonian deforestation for the first time using a new dataset from WRI and Google. In 2025, we estimate the deforestation of 736,484 hectares across the Amazon. The vast majority (94.6%) of this deforestation came from agriculture (both permanent and shifting). An additional 5.3% came from hard commodities, mostly gold mining. The remaining 0.1% was caused by roads and infrastructure.

Over half (55.2%) of this deforestation occurred in Brazil, followed by Peru, Bolivia, and Colombia. Peru had the most mining deforestation, followed by Brazil, Guyana, Suriname, and Venezuela.

While agriculture accounts for the greatest impact in terms of total number of hectares deforested, much of this impact occurs in expanding deforestation zones and along roads. Key examples include expanding deforestation along the major roads of the eastern and southern Brazilian Amazon, expanding soy deforestation in the southern Bolivian Amazon, expanding deforestation by Mennonite colonies in the central Peruvian Amazon, and the arc of deforestation in the northwest Colombian Amazon. 

Gold mining, on the other hand, has the greatest impact in terms of targeting sensitive areas. In contrast to agricultural deforestation following roads, gold mining, particularly illegal gold mining, often targets the most remote and intact areas, such as protected areas and Indigenous territories. Key examples include the southern Peruvian Amazon, northern Ecuadorian Amazon, border between the Colombian and Brazilian Amazon, Indigenous territories of the Brazilian Amazon, and the northeast Amazon (Venezuela, Suriname, and Guyana).

It is important to note that the data presented here may differ from national data presented by governments. This difference may be due to methodology (we focus on impact on primary forests), spatial resolution (30 meters in our case), and Amazon boundaries (we employ a hybrid boundary designed for maximum inclusion of both watershed and biogeography). Due to these potential differences among sources, it is best to focus on the convergence of overall trends and patterns, and not overly focus on the absolute numerical difference.

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). This fire data may be interpreted as forest degradation, in contrast to the more permanent impacts of deforestation.

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 were ‘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.

Protected areas and Indigenous territory data from RAISG and official sources. In case of an overlap, data was included in the protected areas category. Note that Suriname does not have titled Indigenous territories.

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: 50 x 50 meters (0.25 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%. These percentages correspond to the concentration of forest loss pixels, with a pixel size of 50 x 50 meters (0.25 hectares).

Using the “WRI Google Drivers of Tree Cover Loss” dataset, we then estimated human-caused deforestation. The main challenge was analyzing this 1 km resolution dataset in relation to the 30 m resolution annual forest loss dataset described above.

Building upon the annual forest loss by confidence level )—from which fire-related loss was excluded based on confidence levels 3 and 4—a second layer, designated “Forest Loss Non-Fire” (confidence levels 1 and 2), was generated; onto this layer, the cumulative “Drivers” layer (2001–2025) was overlaid to analyze which underlying causes were associated with the recorded loss.

The result was an artificial scale 30 m resolution; it should be noted here that the spatial correlation is not exact. Since Driver’s original data has a resolution of 1 km—which encompasses multiple 30-meter pixels—this value has been replicated (downscaled). Through layer merging, a layer was obtained containing forest loss pixel values ​​accompanied by a confidence level and an assigned driver—meaning the probable primary cause of the loss has been identified.

To estimate human-caused deforestation, we focused on just four of the drivers: agriculture (both permanent and shifting), hard commodities, and roads & infrastructure. In other words, we did not include Natural forest loss, Wildfires, or Logging.

Acknowledgements

We thank colleagues from the following organizations for helpful comments on the report: Conservación Amazónica – ACEAA in Bolivia, Conservación Amazónica – ACCA in Peru, and  Fundación EcoCiencia in Ecuador.

This work was supported by Norad (Norwegian Agency for Development Cooperation).

 

Citation

Finer M, Ariñez A, Bodin B, Santana A (2026) Amazon Deforestation & Fire Hotspots 2025. MAAP: 244.

MAAP #242 Illegal gold mining in Yanomami Indigenous Territory (northern Brazilian Amazon)

Photo 1. Gold mining in Yanomami Indigenous Territory. Photo credit: Lucas Silva/Platô/ISA

Yanomami Indigenous Territory, located in the northern Brazilian Amazon (along the border with Venezuela), is one of the territories most impacted by gold mining in the Amazon (MAAP #226).

This report details the results of geospatial monitoring of illegal gold mining activity in Yanomami Indigenous Territory, based on data collected up to December 2025. This territory is located in the northern Brazilian Amazon, along the border with Venezuela.

This monitoring effort, based on the analysis of high-resolution satellite imagery and data from collaborative monitoring carried out by the Yanomami and Ye’kwana communities, takes place in a context of operational transition in the territory, marked by the current government’s efforts to remove illegal occupants and the persistence of certain mining hotspots (see Note 1 below).

In recent years, this territory has faced an escalation of illegal mining that peaked in 2022, resulting in an unprecedented humanitarian and health crisis. Current data produced by the Brazilian organization Instituto Socioambiental (see below for details) reveals that the total area impacted by mining reached 5,564 hectares in 2025.

However, time series analysis demonstrates a critical inflection point: after the peak in 2022, the annual increase in newly impacted mining areas showed major and successive decreases in the years 2023 through 2025. Comparatively, while the accumulated area up to 2023 represents the vast majority of the impact (around 5,500 ha), there has been a documented increase of 129 hectares in 2024 and 2025 (83.95 ha and 45.2 ha, respectively).

This recent slowdown in the rate of mining expansion is a direct result of the command and control operations initiated by the Brazilian government in 2023, shortly after the official recognition of the public health emergency (see Note 2). The data, however, also serves as a warning: although the mining expansion has slowed, the continued detection in both 2024 and 2025 confirms that mining activity has not been completely eradicated. 

Monthly monitoring indicates that illegal mining continues to exert pressure on the territory, miners are adapting to enforcement operations and maintain mining nodes of resistance that require continuity and improvement of territorial protection and monitoring strategies.

Analysis of illegal gold mining in Yanomami Indigenous Territory 

Methodology

Photo 2. Gold mining in Yanomami Indigenous Territory. Photo credit: Lucas Silva/Platô/ISA

The data presented in this report is based on monitoring led by the Brazilian organization Instituto Socioambiental (ISA). This analysis is carried out monthly based on the visual interpretation of satellite images from Planet (monthly mosaics) and the European Space Agency’s Sentinel 2. Mining impact polygons were then generated by incorporating: 1) recent mining deforestation, 2) active mining areas with bare soil, 3) recently abandoned areas with initial vegetation growth (grasses covering gravel pits), and 4) tailings ponds. 

Every month, the impacted regions are revisited to refine the mapping and check for possible misinterpretations. The analysis takes into account not only the spectral response of the objects but also the context. Therefore, all mapping is carried out considering the location of the communities and their cultivated areas, among other information about the Yanomami territory such as airstrips and health posts, which ensures differentiation between the removal of forest cover for traditional agricultural management and deforestation associated with mineral or other types of exploitation.

The systematic remote monitoring of Yanomami Indigenous Territory began in 2018, experimenting with different methodologies. Beginning in 2020, the refinement of impacted areas began using Planet mosaics (3 m spatial resolution). For this reason, 2020 is used as the initial year of detailed analysis.

In the Notes section, we also compare this ISA-led monitoring data with information obtained from Amazon Mining Watch.

In addition to remote monitoring, since 2023 a collaborative monitoring tool has been implemented to record events that pose risks to communities and people in the Yanomami Indigenous Territory. The ‘Wãnori’ Alert System receives and qualifies reports, aiming to strengthen communication between indigenous communities, their organizations, and the Public Authorities. Through a free application (ODK Collect), an alert monitor can report an adverse health event, environmental or territorial threat, using an offline form composed of geographic coordinates and a description of the problem in audio and/or photo. The system uses the form/application as its primary tool for receiving complaints, but it continues to receive information from other sources, such as WhatsApp messages, letters, and radio broadcasts, incorporating this information into a single flow. All alerts are compiled into weekly bulletins and sent to Brazilian authorities.

Results

By December 2025, the total area impacted by illegal mining in the Yanomami Indigenous Territory was mapped at 5,564 hectares (see Note 3 for comparison with Amazon Mining Watch). As seen in Graph 1 (with 2020 baseline at 400 ha), the annual mining impact increased in 2021 (just over 1,000 ha) and peaked in 2022 (nearly 1,800 ha), followed by major decreases in 2023 (330 ha), 2024 (84 ha), and 2025 (45 ha), respectively. This reduction was a result of the intervention of the Brazilian government, which initiated a process of removing illegal miners from the territory in 2023, after recognizing the humanitarian crisis caused by illegal mining among the Yanomami and Ye’kwana peoples.

Graph 1 – Annual increase in the area affected by illegal mining in Yanomami Indigenous Territory.

The monitoring documented 45 hectares (across 121 polygons) of new mining deforestation within Yanomami Indigenous Territory in 2025. The vast majority (90%) of the polygons were small mining expansions of less than 1 hectare. This recent mining impact was mostly distributed across six areas: 1) Ericó; 2) Cabeceira do Aracaju; 3) Hokomawaë; 4) Parima-Parafuri; 5) Surucucus/Feijão Queimado; 6) Couto Magalhães (see Figure 1).

Figure 1. Illegal gold mining in Yanomami Indigenous Territory, highlighting areas with highest impact in 2025.

The two largest polygons (almost 4 hectares) were identified in Parima (Area 5) and Surucucus, near the Feijão Queimado airstrip (Area 6).

Figure 2 – Comparison of images from January 2025 and November 2025 near the Feijão Queimado airstrip. New deforestation is noticeable in the upper part of image 2.
Figure 3 – Comparison between January 2025 and November 2025 in the Parima region.

The distribution of the new mining areas also indicates a trend towards fragmentation of activity, in contrast to the previous concentration around airstrips (such as Capixaba, Jeremias, Malária, Mucuim). With the exception of the Couto Magalhães river region (Area 6 in Figure 1), where the opening of new areas near old scars continued (Figure 4), the other centers of greater concentration, such as Alto Catrimani, Médio Uraricoera and Homoxi, appear to be relatively neutralized.

Figure 4. – Mapping of illegal mining in the Couto Magalhães River (Papiu and Kayanau regions)

In addition to decentralization, there is also a shift in activity to areas closer to the border with Venezuela (possible leakage or spillover effect), as is the case with the mapped areas in Parafuri-Parima, Hokomawë, and Cabeceira do Aracaçá (Areas 2-4 in Figure 1). It is known that part of this phenomenon is explained by the possibility of “circumventing” inspection by using logistical hubs located in Venezuelan territory, such as the airstrips in Dicão and Simada Ocho.

In 2025, the Yanomami Indigenous Territory’s alert system recorded at least five alerts regarding the movement of clandestine aircraft in the Auaris region. In most cases, the aircraft flew in the direction of Hokomawë, towards the Gaúcho Animal airstrip, located at the mouth of the Auaris River, or towards the airstrip located at the headwaters of the Aracaçá River (supposedly the Gongo airstrip). See Figure 5, which zooms in on Area 2 of Figure 1.

Figure 5 – Mapping of illegal mining at the headwaters of the Aracaçá River, near the Gongo airstrip and the border with Venezuela.

With respect to the ‘Wãnori’ Alert System, in 2025, it recorded a total of 66 territorial alerts, of which the vast majority (83%) were invasion alerts (Graph 2), which include information on the movement of clandestine aircraft, boats, barges, and other vehicles. There were also records of attacks and the entry of firearms. Cases of missing persons were resolved, without being actually associated with violence in the illegal mining areas.

Graph 2 – Territorial alerts in 2025 by alert type

Figure 6 illustrates the spatial distribution of the alerts, again highlighting the concentration in the north of the territory, near the border with Venezuela.

Figure 6 – Heat map of territorial alerts for 2024 and 2025

The area with the highest number of alerts, Apiaú  (Chart 3), was also among the regions that registered airspace intrusion alerts (see Annex 1 for photo evidence), possibly associated with illegal mining on the Couto Magalhães River. 

Alto Catrimani also had airspace alerts. In this case, the connection between this activity and illegal mining in the headwaters of the Orinoco River, in Venezuelan territory, is notable; this is one of the areas with the highest levels of illegal mining activity in recent years.

Other areas with airspace intrusion alerts include Auaris and Xitei (see Annex 2 for photo evidence). It should also be noted that, even though the Taboca airstrip is located in Venezuela, it supports the remaining fragments of illegal mining in the Alto Catrimani and Xitei regions, such as the mining operation located near the Pixahanapi community .It is worth noting that in the case of the Xitei mining operation (see Annex 3 for community alert), the warnings reinforce the residents’ concern regarding the entry of ammunition and firearms brought by the miners with the aim of recruiting young people and threatening leaders who oppose mineral exploration in the region. Since 2021, Xitei has been marked by violent conflicts associated with mining, and 2025 was no different. In 2025 alone, it is estimated that at least five people died due to these conflicts.

Graph 3 – Territorial alerts in 2025 by region

In addition to airspace violations, the alert system also recorded many instances of illegal incursions along the rivers of Yanomami Indigenous Territory, namel the Uraricoera, Catrimani, Apiaú, and Ajarani. In some cases, the river traffic was associated with the operation of barges and dredges, in others simply for the transport of cassiterite, or the entry of supplies to replenish the camps.

The Lower Catrimani region has reported the most instances of river invasion. From April to December 2025, nine alerts were issued regarding the presence of barges, dredges, and suspicious boats (Figure 7).

Figure 7 – Boat with supplies for illegal mining in the Lower Catrimani region and a mining dredge operating near the Yanomami community in the same region.

From Apiaú, reports have emerged of an alleged trail for ATVs that would serve to supply the mining operations located upstream and bypass the site where the new National Indigenous Foundation (Funai) base is being installed. The trail would connect existing secondary roads outside the territory and reach the Ingarana stream, a tributary of the Apiaú River (Figure 8).

Figure 8 – Map of the Apiaú region showing the location of the alleged portage.

Finally, another noteworthy region is Ericó, an area accessible via the Uraricaá River, where significant signs of deforestation associated with mining were observed in 2025. During the period from 2018 to 2022, there were records of dredges operating on the Uraricaá River; however, there were no clear signs of land-based mining in the region. With the intensification of operations in other parts of the territory, however, there appears to have been a spillover into this basin, which, being further from the main areas of surveillance, ended up becoming vulnerable. See Figure 9, which zooms in on Area 1 of Figure 1.

Figure 9 – Mapping of illegal mining in the Uraricaá River

Annex

Annex 1. Aircraft registration in service of the mining operation in Apiaú

Annex 2.Illegal mining plane registered in Xitei

Annex 3. Video sent to the Alert System, which records the presence of illegal miners operating at night, near the Pixahanapi community, Xitei.

Policy Implications & Recommendations

Analysis of the 2025 data indicates a significant inflection point in the dynamics of illegal mining. Although the total impacted area amounts to 5,564 hectares, there has been a substantial and successive decrease in the annual expansion of newly degraded areas since the peak in 2022. In 2025, only 45.2 hectares of new areas were recorded, distributed across 121 polygons, most of which are less than 1 hectare.

However, miners’ ability to adapt to the government operations is observed, by adopting some fragmentation and decentralization strategies, moving to areas closer to the border with Venezuela to utilize logistical distribution hubs outside the limits of inspection. Furthermore, the persistence of some extremely resilient mining nodes is noted, as is the case with the mining in the Couto Magalhães River.

With this in mind, to consolidate the results of land clearing operations and address the reentry of criminal activity within the territory, the following actions are recommended:

  • All enforcement agencies should maintain operations to combat illegal mining in the remaining areas, with the complete destruction of machinery used in mineral extraction and the application of the respective administrative sanctions;
  • To ensure continuous remote monitoring of Yanomami territory as well as rapid responses to new alerts from security forces;
  • To guarantee the maintenance of the physical structures and the minimum staff for the continuous operation of the existing Protection Posts (Ajarani, Xexena, Walopali, Serra da Estrutura and Pakilapi);
  • Finalize the construction of the Apiaú and Kayanau Protection Posts;
  • Install new Protection Posts on strategic rivers that serve as routes for illegal mining, specifically on the Uraricaá and Catrimani rivers;
  • Implement more efficient river barriers on the Uraricoera, Mucajaí, Uraricaá, and Catrimani rivers.
  • To promote regular State enforcement agencies’ patrols on the Uraricoera, Mucajaí, Ajarani, Apiaú, Uraricaá, Catrimani, Parima and Couto Magalhães rivers.
  • Enhanced airspace control and strict enforcement of the Brazilian Aeronautical Code.
  • Disabling all clandestine airstrips and seized aircraft within Yanomami territory (Integrated Territory of Yanomami).
  • To promote regular inspection actions on highways, gas stations, airports, and ports located around Yanomami territory. 
  • Support from the federal government for the implementation of the Indigenous Surveillance Plan, integrating information from the communities’ Alert System with state action;
  • Implement a strict sanitary and territorial protection cordon around the territory of the isolated groups, led by the Indigenous Peoples’ National Foundation (FUNAI) and the Health District (Distrito Sanitário) with support from the National Forces;
  • The FUNAI or the Government House (Casa de Governo) should lead the development of a plan to encourage voluntary disarmament in sensitive regions.
  • The Brazilian government should foster spaces for governance and dialogue, with members of the government, indigenous associations, and technical partners from civil society, to monitor the implementation of territorial protection actions.
  • The Brazilian government should develop, translate, and distribute regular newsletters to communities about territorial protection actions and their progress.
  • The national government should coordinate with the Venezuelan government joint actions to combat the logistical “hubs” located just across the border, which serve as refuge for illegal miners and escape routes.

Notes

1. Operational transition refers to the changes in the model, regularity, and intensity of enforcement actions taken following the change in government. https://g1.globo.com/rr/roraima/noticia/2024/02/29/casa-de-governo-com-foco-na-crise-yanomami-e-instalada-em-rr-com-orcamento-de-r-1-bilhao.ghtml

2. https://www.planalto.gov.br/ccivil_03/_ato2023-2026/2023/decreto/D11405.htm

3. For comparison, Amazon Mining Watch has detected 2,470 hectares in Yanomami Indigenous Territory between 2018 and 2025. This data also shows a peak in 2022 (increase of 850 ha), followed by declines in 2023 (250 ha) and 2024 (80 ha). AMW did not detect any new mining in 2025. Importantly, the overall detected spatial patterns are similar, with both monitoring systems highlighting the concentration in the northern part of the territory.

4. Protection bases are control points managed by Funai that provide support for operations by other enforcement agencies, such as Ibama and the Federal Police.

5. The River Barriers function as control points and nautical blockades managed by Funai, with support from Ibama and the Federal Police, to prevent logistical access by wildcat miners and intruders to the rivers of the Yanomami Indigenous Territory.

6. This should involve regulatory agencies alongside environmental enforcement and command-and-control bodies, such as the National Civil Aviation Agency – ANAC (for airfield inspections), the National Petroleum Agency – ANP (for fuel station inspections), and the National Land Transport Agency – ANTT (for road and highway inspections).

7. https://acervo.socioambiental.org/acervo/documentos/urihi-noamatima-thepe-plano-de-vigilancia-indigena-da-ti-yanomami

Acknowledgments 

This report is part of a series focusing on gold mining in the Amazon, through a strategic collaboration between Amazon Conservation and regional partners, with support from the Gordon and Betty Moore Foundation. In this case, we thank our partner Instituto Socioambiental (ISA) for leading this report

MAAP #240: Expansion of illegal gold mining in the Xingu Basin of the Brazilian Amazon (part 2. Protected Areas)

Base Map. Mining sites in the Xingu Socio-environmental Diversity Corridor. Data: ACA/MAAP, ISA.

We present the second of a two-part series on illegal gold mining deforestation in the Xingu River Basin, located in the eastern Brazilian Amazon (states of Pará and Mato Grosso). The current report examines mining in protected areas of the Xingu, while Part 1 focused on Indigenous territories (see MAAP #239)

The Xingu Basin is the site of the largest historical concentration of gold mining deforestation in the Brazilian Amazon (see MAAP #235). At the heart of this basin is the Xingu Socio-environmental Diversity Corridor, which is one of the largest continuous blocks (over 26 million hectares) of designated forests on the planet, connecting 24 Indigenous territories and 9 protected areas (see Base Map). Despite the official land designations, the area remains threatened, especially by the expansion of illegal gold mining driven by record high gold prices.

To address this challenge, the Xingu+ Network (Rede Xingu+) was created, a political alliance formed by a coalition of organizations representing the area. This network monitors deforestation and other pressures in the Xingu Corridor monthly, using the radar-based SiRAD X system. 

In 2025, the Xingu+ Network partnered with Amazon Conservation, facilitating access to high-resolution optical images (from Planet), allowing for validation of alerts and identification of drivers. This collaboration also incorporates the online public dashboard Amazon Mining Watch.

Both systems, SiRAD X and Amazon Mining Watch, have detected a major expansion of gold mining deforestation since 2018 in the Corridor, including continued illegal activity during 2025. Throughout the report, we present data for both systems, noting their slight differences due to varying methodologies (Note 1), but the overall patterns of both datasets are consistent. 

Between 2018 and 2024, the Sirad X monitoring system recorded the loss of around 11,500 hectares of forest within the Indigenous territories and protected areas of the Xingu Corridor (Amazon Mining Watch estimates around 16,000 ha), plus 400 hectares in 2025 (January – September), similar to the estimate of Amazon Mining Watch.

Both monitoring systems have detected recent mining deforestation in 6 protected areas in the Xingu Corridor (Note 2), in addition to the 5 Indigenous territories reported in part 1.

In Part 1, we detailed the recent gold mining deforestation in three of these Indigenous territories (Kuruaya, Baú, and Kayapó). 

Here, in part 2, we focus on the recent gold mining deforestation in three of these protected areas (Altamira National Forest, Terra do Meio Ecological Station, and Nascentes da Serra do Cachimbo Biological Reserve) in the Xingu Corridor, including the presentation of a series of high-resolution images.

The Base Map indicates the focal areas of this series, with Points A-C covered in the first report (Indigenous territories), and Points D-F in the current second report (protected areas). 

Mining in Protected Areas

Altamira National Forest

The Altamira National Forest (located in Pará state) is experiencing expanding illegal mining in three locations with notable increases in 2025. In just the first eight months of 2025, the area affected by illegal mining in the Altamira National Forest has already exceeded the total environmental damage recorded for the entire year of 2024, highlighting the urgent need for enforcement operations in the area.

Mining began in its northwestern and western sections between 2016 and 2018 and expanded 832 hectares by September 2025. Figure D1 shows recent mining deforestation in the western section, between October 2024 (left panel) and September 2025 (right panel). Although there are mining exploration applications for these sections, mining is not permitted in the area’s Management Plan or in its creation decree (Decree No. 2483, 1998). See Note 3 for comparison with AMW.

Figure D1 Data: Planet, NICFI

The mining in the southeastern section began in 2024 and expanded to a cumulative total of 36 hectares by October 2025, according to the Xingu+ Network monitoring. Gold mining in the southeastern section accounted for 45.7% of the area deforested by mining operations in 2025 within the National Forest, with the peak of its expansion occurring in June. Figure D2 shows recent mining deforestation in this section, between September 2024 (left panel) and September 2025 (right panel). 

Figure D2 Data: Planet, NICFI

Terra do Meio Ecological Station

The Terra do Meio Ecological Station has emerged as a new mining front. First identified in September 2024, the mining rapidly expanded to a cumulative total of 30 hectares by the end of 2025, according to the Xingu+ Network monitoring (see Note 4 for comparison with AMW). Figure E shows this expansion between December 2024 (left panel) and September 2025 (right panel).

Although the Terra do Meio Ecological Station faces other illegal activities, such as deforestation, the presence of illegal mining operations within its boundaries is particularly concerning. This case not only demonstrates how far the offenders have encroached on a strictly protected area, but also highlights their high level of operational capacities. This combination increases the risk that the activity will spread, causing environmental degradation in other parts of the protected area.

Figure E. Data: Planet, NICFI

Cachimbo Mountain Headwaters Biological Reserve

The Cachimbo Mountain Headwaters Biological Reserve is strategically located along the BR-163 highway in Pará. It is a strictly protected conservation area established by Decree No. – May 20, 2005, and is located between the municipalities of Altamira and Novo Progresso, in the Tapajós-Xingu interfluve, and adjacent to the Menkragnoti and Panará Indigenous Lands on its eastern boundary.

Illegal mining in the Biological Reserve began to expand, primarily starting in January 2025. At that time, the mining site—which had previously covered an area of two hectares—was the subject of a complaint filed in Official Letter No. 01/2025 by Rede Xingu+. In June, illegal mining in the Biological Reserve was reported again via Official Letter No. 15/2025, following an expansion of 18 ha, and in July, via Official Letter No. 18/2025, following a further expansion of 6.82 ha, totaling 26.82 ha.  

Two mining sites are located in the northeastern region of the Rebio, opened in November 2024 and March 2025, and another site in the eastern region, opened in June 2025. It is worth noting that the site in the eastern region was also the subject of a complaint in Official Letter No. 18/2025, as it is located on and causing pollution in a tributary of the Pitxatxá River, a river that borders the Menkragnoti Indigenous Territory and where six indigenous villages of the Kayapó people are located.

Illegal mining began in December 2024, expanding to a cumulative total of 19 hectares as of September 2025 across several locations in the protected area, according to the Xingu+ Network monitoring (see Note 5 for comparison with AMW).

Even after enforcement operations, gold mining activity continues to expand within the Cachimbo Mountain Headwaters Biological Reserve. Figures 1 and 2 show the rapid mining-deforestation expansion up to November 2025, and Figure 3 shows the construction of a landing strip between July and August, providing access to the gold mines in the eastern region.

Figure F1 shows recent mining deforestation in the northeast part of the Biological Reserve, between December 2024 (left panel) and November 2025 (right panel).

Figure F1 Data: Planet, NICFI

Figure F2 shows recent mining deforestation in the eastern part of the Biological Reserve, between June 2025 (left panel) and November 2025 (right panel).

Figure F2 Data: Planet, NICFI

Figure F3 shows a new landing strip (opened in August 2025) in the eastern part of the Biological Reserve, between June 2025 (left panel) and November 2025 (right panel).

Figure F3 Data: Planet, NICFI

Conclusion and Recommendations

Based on the information presented above (and the previous MAAP #239), it is clear that illegal mining in the Xingu basin is not an isolated activity. It has spread to both Indigenous territories and protected areas, with illegal activity advancing into new territories, indicating the existence of a support network that provides the operational capacity and infrastructure necessary for the activity. Illegal mining poses a direct threat to protected areas by both deforestation and the contamination of rivers through the use of mercury, which affect sensitive ecosystems and the populations that depend on these resources. 

Below, we propose a number of recommendations to Brazilian authorities with regards to: (i) the design of enforcement actions; (ii) monitoring and restoration (iii) traceability of gold supply chains.

(i) The design of enforcement actions; 

Isolated enforcement actions have not been sufficient to guarantee the long-term protection of Protected Areas. Therefore, it is essential to establish a strategy coordinated with other agencies to dismantle the logistical structure that operates and fuels illegal mining. Alongside this, the structuring of preventive measures is fundamental.

  • Establish permanent advanced bases (operated by government agencies such as ICMBio) in the most critical protected aeass, ensuring a constant presence to break the cycle of miners returning after eviction operations.
  • Focus on disabling airstrips and seizing heavy machinery (hydraulic excavators) within protected areas, coordinating with National Civil Aviation agency (ANAC) and National Oil, Petroleum and Biofuel Agency (ANP) to block clandestine airfields and fuel stations in the areas surrounding protected lands.
  • Strengthen oversight in the surroundings of protected areas to prevent legalized mining in nearby areas from serving as a front for illegal extraction within the boundaries of protected areas. This process would include the National Mining Agency (ANM), with oversight from other agencies.

(ii) Monitoring and restoration 

Strengthening surveillance and environmental recovery is essential to discourage the return of illegal miners.

  • Support management councils and associations of riverine and traditional populations in implementing surveillance protocols, recognizing the role of these communities in maintaining the integrity of sustainable-use protected areas.
  • Implement Degraded Area Recovery Plans (PRADs) focused on the revegetation of riparian forests and the containment of siltation caused by mining sediments.In federal areas, it would be ICMBio; in state conservation units, the Institute for Forest and Biodiversity Development of the State of Pará (IDEFLOR-Bio).

(iii) Traceability of gold supply chains.

Implement a data-cross-referencing system that automatically blocks the issuance of Electronic Fiscal Invoices (NF-e) for minerals whose declared origin overlaps with Protected Area polygons. Improve legislation regarding documentation of sourcing area in traceability mechanisms, making it more difficult to “launder” minerals illegally extracted from Protected Areas.

Notes

1. Methodology of monitoring systems

For Sirad X monitoring, radar images from the Sentinel-1 satellite are used, which are processed by a series of algorithms on the Google Earth Engine (GEE) platform, along with optical images from the Landsat-9 satellite (OLI-2 sensor) and Sentinel-2 satellite (MSI sensor). A team of analysts examines the monitored area, visually searching for anomalies in the produced images. Each deforestation polygon is evaluated based on its proximity to other areas of degradation and the history of the region, and, if necessary, people familiar with the location are contacted to confirm the deforestation. Field knowledge is fundamental for data validation.

For Amazon Mining Watch, the mine detector is an artificial neural network, which we train to discriminate mines from other terrain by feeding it hand-labeled examples of mines and other key features as they appear in Sentinel-2 satellite imagery. The network operates on square patches of data extracted from the Sentinel-2 L1C data product. Each pixel in the patch captures the light reflected from Earth’s surface in twelve bands of visible and infrared light. We average (median composite) the Sentinel data across a period of many months to reduce the presence of clouds, cloud shadow, and other transitory effects. During run time, the network assesses each patch for signs of recent mining activity, and then the region of interest is shifted by half a patch width for the network to make a subsequent assessment. This process proceeds across the entire region of interest.

2-5. Comparisons with Amazon Mining Watch

2. Altamira National Forest, Terra do Meio Ecological Station, Iriri State Forest, Riozinho do Anfrísio Extractive Reserve, Nascentes da Serra do Cachimbo Biological Reserve, and Rio Iriri Extractive Reserve.

3. As a comparison, Amazon Mining Watch indicates the total mining deforestation of 620 hectares in Altamira National Forest between 2018 and 2025.

4. As a comparison, Amazon Mining Watch indicates the total mining deforestation of 3 hectares in Terra do Meio Ecological between 2018 and 2025.

5. As a comparison, Amazon Mining Watch indicates the total mining deforestation of 51 hectares in Cachimbo Mountain Headwaters Biological Reserve between 2018 and 2025.

Acknowledgments 

This report is part of a series focusing on gold mining in the Amazon, through a strategic collaboration between Amazon Conservation and regional partners, with support from the Gordon and Betty Moore Foundation. In this case, we thank our partner Instituto Socioambiental (ISA) for leading this report.

 

MAAP #239: Expansion of illegal gold mining in the Xingu Basin of the Brazilian Amazon (part 1. Indigenous Territories)

Base Map. Mining sites in the Xingu Diversity Corridor. Data: Amazon Conservation/MAAP, ISA.

Illegal mining continues to expand in the Brazilian Amazon, likely driven by rising gold prices. As of the end of 2025, the accumulated area of mining activity in the Brazilian Amazon is estimated to be 223,000 hectares, according to Amazon Mining Watch (see MAAP #197, MAAP #226, and MAAP #235 for additional context).

Notably, the largest concentration of gold mining deforestation is in the Xingu River Basin, which extends over 51 million hectares in the eastern Brazilian Amazon (states of Pará and Mato Grosso).

At the heart of this territory is the Xingu Socio-environmental Diversity Corridor, which is one of the largest continuous blocks (over 26 million hectares) of designated forests on the planet, connecting 24 Indigenous territories and 9 protected areas (see Base Map). Despite the official land designations, the area remains threatened due to the continual expansion of illegal gold mining, agriculture, logging, roads, and human-caused forest fires.

The corridor is home to 26 Indigenous groups, who have historically acted as guardians against the advance of the deforestation frontier. To address these challenges, the Xingu+ Network (Rede Xingu+) was created, a political alliance formed by 53 organisations (43 Indigenous, 5 riverine, and 5 civil society partners) representing the inhabitants of the Corridor. The origin of this alliance dates back to the resistance movements against the damming of the Xingu River in 1989, and, after decades of collaboration, the Network was formalised in 2013.

The Xingu+ Network monitors deforestation and other pressures in the Xingu Corridor monthly, using the radar-based SiRAD X (Xingu Remote Deforestation Alert System). The system also relies on a local network of partners who carry out on-site territorial surveillance activities.

In 2025, the Brazilian organization Instituto Socioambiental (ISA) partnered with Amazon Conservation, facilitating access to high-resolution optical images (from Planet), allowing for validation of alerts and identification of drivers. This collaboration also incorporates the online public dashboard known as Amazon Mining Watch, a partnership between Amazon Conservation, Earth Genome and the Pulitzer Center.

Both systems, SiRAD X and Amazon Mining Watch, have detected a major expansion of gold mining deforestation since 2018 in the Corridor, including continued illegal activity in the most recent time period of 2025. Throughout the report, we present data for both systems, noting their slight differences due to varying methodologies (Note 1), but the overall patterns of both datasets are consistent.

Between 2018 and 2024, the Sirad X monitoring system recorded the loss of around 11,500 hectares of forest within the Indigenous territories and protected areas of the Xingu Corridor (Amazon Mining Watch estimates around 16,000 ha), plus 400 hectares in 2025 (January – September), similar to the estimate of Amazon Mining Watch.

Overall, this mining deforestation currently impacts 5 Indigenous territories (Kayapó, Baú, Kuruaya, Trincheira Bacajá, and Apyterewa) and 5 protected areas (Altamira National Forest, Iriri State Forest, Riozinho do Anfrísio Extractive Reserve, Nascentes da Serra do Cachimbo Biological Reserve, and Rio Iriri Extractive Reserve) in the Xingu Corridor. 

We present a two-part series on this illegal gold mining deforestation in the Xingu Corridor. Part 1, detailed below, focuses on the Indigenous territories, while the upcoming Part 2 will focus on the protected areas.

In this Part 1, we detail the recent gold mining deforestation in 3 Indigenous territories (Kuruaya, Baú, and Kayapó), including the presentation of a series of high-resolution images.

The Base Map indicates the focal areas of this series, with Points A-C covered in this report (Indigenous territories), and the remaining Points D-F in the second report (protected areas).

Mining in Indigenous Territories

Kuruaya Indigenous Territory

The Kuruaya Indigenous Territory (state of Pará, municipality of Altamira) has experienced gold mining activity since the early 1980s, on the Curuá River, where the villages of the Kuruaya are located. The most intense recent mining has occurred on a tributary of the Curuá River, known as the Madalena.

Since 2023, the Xingu+ Network monitoring has recorded the expansion of illegal gold mining along the Madalena. That year, a formal complaint was filed (via Official Letter 42/2023-Rede Xingu+), which reported the loss of around 3 hectares due to gold mining. In 2024, the activity intensified with the deforestation of another 13.4 hectares, and from January to July 2025, the Madalena mining operation had already expanded by another 17.8 hectares, for a cumulative total of 34.2 hectares.

Figures A1 and A2 show the expansion of the illegal gold mining along the Madalena between 2024 (left panels) and 2025 (right panels). This mining is expanding primarily towards the confluence of the Madalena with the Curuá River. In addition, the activity has spread to new, smaller areas in the surrounding region.

Figure A1. Mining in Kuruaya Indigenous Territory. Data: Planet/NICFI
Figure A2. Mining in Kuruaya Indigenous Territory. Data: Planet/NICFI
Amazon Mining Watch results for Kuruaya Indigenous Territory.

Amazon Mining Watch indicates the cumulative mining deforestation of 33 hectares in Kuruaya Indigenous Territory, including 4 hectares in 2025 (click here to see on AMW).

This mining is taking place within an active gold concession registered in the SIGMINE digital cadaster. Per the Brazilian Constitution, however, this type of concession (“lavra garimpeira” or exploitation permit for artisanal mining) is irregular within Indigenous territories (Note 2).

 

 

 

 

 

 

 

Baú Indigenous Territory

The Baú Indigenous Territory (state of Pará, municipality of Altamira) is inhabited by the Mebengôkre (Kayapó) Mekrãgnoti and isolated Purô peoples across its vast 1.5 million hectares. Illegal mining has impacted this territory since at least 2019, and has been the scene of several armed conflicts between miners and Indigenous members.

In the first half of 2025, active illegal mining sites were detected in several parts of the territory, most notably in the central mining site of Pista Velha. Pista Velha is an old mining site, but it was in 2019 that its reactivation became the scene of several armed conflicts between Indigenous peoples and gold miners, putting the lives of the Kayapó at risk. Efforts to reclaim this gold mine are ongoing and have been reported on numerous times by Rede Xingu+. In July 2025, an overflight confirmed the presence of mining activity in Pista Velha (see photo).

Overflight photo: Pista Velha mining site (Baú Indigenous Territory) on July 19, 2025. Photo: Xingu+ Network.

Figure B illustrates the gold mining expansion at Pista Velha between 2024 (left panel) and 2025 (right panel).

Figure B. Mining in Baú Indigenous Territory. Data: Planet/NICFI
Amazon Mining Watch results for Bau Indigenous Territory.

Amazon Mining Watch indicates the cumulative mining deforestation of 110 hectares in Bau Indigenous Territory, including 10 hectares in 2025 (click here to see on AMW.

 

 

 

 

 

 

 

 

 

Kayapó Indigenous Territory

The Kayapó Indigenous Territory (state of Pará, across four municipalities) has a long history of illegal mining dating back to the 1960s, and is the territory with the largest area deforested by illegal mining in the Brazilian Amazon.

Government operations to remove illegal miners from the Kayapó Indigenous Territory began in May 2025, in compliance with a Supreme Federal Court ruling (ADP 709), which aims not only to protect Indigenous peoples but also to contain the advance of illegal mining.

The first phase of these operations appears effective, as less than 2 hectares of new mining was detected in June 2025 by SIRAD-X monitoring. However, data from October indicates a small increase in mining in the territory, with an increase of 15 hectares.

Figures C1 and C2 show the recent advance of illegal mining in two locations of Kayapó Indigenous Territory between 2024 (left panels) and 2025 (right panels).

Figure C1. Mining in Kayapó Indigenous Territory. Data: Planet/NICFI
Figure C2. Mining in Kayapó Indigenous Territory. Data: Planet/NICFI

Amazon Mining Watch indicates the cumulative mining deforestation of 7,940 hectares in Kayapo Indigenous Territory, including 140 hectares in 2025 (click here to see on AMW). But much of this increase was detected in the first half of the year, indicating it might be a remnant of the 2024 expansion. Thus, much of that recently detected mining activity by Amazon Mining Watch likely happened in late 2024/early 2025 before the government intervention in May, consistent with the SiRAD X results stated above.

Amazon Mining Watch results for Kayapo Indigenous Territory.

Conclusion and Recommendations

Based on the information presented above, it is clear that illegal mining in the Xingu basin is not an isolated activity. It has spread to both Indigenous territories and protected areas, indicating the existence of a support network that provides the operational capacity and infrastructure necessary for the activity. This expansion brings with it a series of serious risks to the region and its communities.

Illegal mining poses a direct threat to the territorial integrity and well-being of riparian and indigenous communities. The main consequences are the degradation of native areas and the contamination of rivers through the use of mercury. In addition to environmental damage, the expansion of illegal activity increases the risk of socio-environmental conflicts between miners and traditional communities, who seek to protect their territories and way of life.

Below, we propose a number of recommendations to Brazilian authorities with regards to: (i) the design of enforcement actions; (ii) community-based monitoring and restoration (iii) traceability of gold supply chains.

(i) Enforcement actions:

To ensure the long-term protection of indigenous territories from illegal mining, it is crucial to move beyond immediate removal operations and establish a sustainable, preventative framework. While the Brazilian government has initiated removal efforts in response to recent judicial orders, there is a notable absence of a long-term strategy to prevent the recurrence of these invasions. Effective and lasting solutions call for the involvement of various regulatory agencies and strategic interventions that extend beyond the geographical boundaries of the indigenous lands themselves. Therefore, the following policy actions are recommended:

  • Establish a permanent, multi-agency task force led by the President’s Chief of Staff (Casa Civil) to develop and implement a comprehensive, five-year strategic plan. This plan should focus on dismantling the external economic and logistical networks that sustain illegal mining, thereby preventing the return of invaders post-removal. The unique convening power of the Casa Civil is essential for orchestrating the necessary collaboration across different government ministries and agencies, ensuring a unified and effective national effort.
  • Promote integrated enforcement actions in the areas surrounding the territories to achieve the logistical strangulation of illegal operations. This should involve regulatory agencies alongside environmental enforcement and command-and-control bodies, such as the National Civil Aviation Agency – ANAC (for airfield inspections), the National Petroleum Agency – ANP (for fuel station inspections), and the National Land Transport Agency – ANTT (for road and highway inspections).
  • Strengthen agencies responsible for enforcement (IBAMA, ICMBio, and FUNAI) to ensure they have the capacity to operate regularly within the territories highlighted, by meeting their budgetary and personnel requirements.
  • Promote the implementation of long-term Protection Plans, guaranteeing a budget for the maintenance of regular enforcement and crime repression actions.

(ii) Community-based monitoring and restoration:

The promotion and strengthening of indigenous surveillance group initiatives for territory monitoring and restoration can complement government-led efforts. An additional benefit of these actions is that they represent sustainable economic alternatives within the territories and thus reduce the vulnerability of youth to recruitment by illegal groups. To this effect, the following actions could be undertaken: 

  • Support the construction and maintenance of “Surveillance Centers” at strategic points (river confluences, TI boundaries), managed by the communities to ensure the physical occupation of remote areas, that produce relevant information for more effective State action.
  • Develop and implement Payment for Environmental Services (PES) schemes for community agents, recognizing territorial surveillance as essential work for biome conservation.
  • Strengthen governance actions within the territories by supporting meetings, assemblies, and forums, and promoting the development of management tools such as Territorial and Environmental Management Plans (PGTAs) and Consultation Protocols.
  • Promote and finance environmental recovery and decontamination/remediation actions in the most affected areas, in addition to continuous monitoring of mercury levels in the population.

 

(iii) Traceability of the gold supply chain:

The Brazilian government has already taken some steps to improve the regulation of the gold supply chain and requires the formal registration of the main actors involved in the ASM gold supply chain (such as miners, traders, and exporters). In 2023, it implemented the Electronic Fiscal Invoice for Gold (NF-e ouro), a mandatory document that verifies and records the origin of the mineral. 

Nevertheless, additional measures are still necessary to continue to improve gold traceability mechanisms and implement better legislation for the control of mineral production and trade, such as the creation of a digital public portal containing mining titles, licenses, embargoes, and monitored areas, allowing buyers to verify the mining site linked to the Gold NF-e. This would significantly improve traceability for companies and purchasers importing gold from Brazil, thereby promoting a more transparent supply chain.

*Notes

1. Methodology of monitoring systems

For Sirad X monitoring, radar images from the Sentinel-1 satellite are used, which are processed by a series of algorithms on the Google Earth Engine (GEE) platform, along with optical images from the Landsat-9 satellite (OLI-2 sensor) and Sentinel-2 satellite (MSI sensor). A team of analysts examines the monitored area, visually searching for anomalies in the produced images. Each deforestation polygon is evaluated based on its proximity to other areas of degradation and the history of the region, and, if necessary, people familiar with the location are contacted to confirm the deforestation. Field knowledge is fundamental for data validation.

For Amazon Mining Watch, the mine detector is an artificial neural network, which we train to discriminate mines from other terrain by feeding it hand-labeled examples of mines and other key features as they appear in Sentinel-2 satellite imagery. The network operates on square patches of data extracted from the Sentinel-2 L1C data product. Each pixel in the patch captures the light reflected from Earth’s surface in twelve bands of visible and infrared light. We average (median composite) the Sentinel data across a period of many months to reduce the presence of clouds, cloud shadow, and other transitory effects.During run time, the network assesses each patch for signs of recent mining activity, and then the region of interest is shifted by half a patch width for the network to make a subsequent assessment. This process proceeds across the entire region of interest.

2. Mining on Indigenous lands. 

Per the Brazilian Constitution, the concession of “lavra garimpeira” or exploitation permit for artisanal mining is irregular within indigenous territories. (Molina, Luísa Pontes, 2023. Terra rasgada: como avança o garimpo na Amazônia brasileira. Instituto Socioambiental).

In this specific case, the concession, awarded in 1981, predates the approval of the Indigenous Territory Kuruaya in 2001. Following the approval, the concession holder (the firm Brasinor) also submitted a number of concessions for exploration within the territory, which appear to have been rejected. However, a protocol related to the previously active concession was approved by the National Mining Agency on January 30, 2026. The legality of this act, as well as of the concession itself, should be investigated.

A well-established principle in Brazilian law is that Indigenous land rights are effective prior to their formal recognition, thus the fact that the concession predates the approval of the territory is immaterial. If the ANM authorization is found irregular, the constitutional interdiction of mining within indigenous territories should prevail, and the concession be rescinded. A decision from federal courts in 2019 determined that the National Mining Agency must negate any request for exploration or exploitation within indigenous territories, even prior to their approval.

 

Acknowledgments

This report is part of a series focusing on gold mining in the Amazon, through a strategic collaboration between Amazon Conservation and regional partners, with support from the Gordon and Betty Moore Foundation. In this case, we thank our partner Instituto Socioambiental (ISA) for leading this report.

 

 

 

 

 

MAAP #235: AI-powered detection of Amazon gold mining deforestation in real-time

Screen shot from the updated Amazon Mining Watch site.

As gold prices continue to skyrocket and shatter historical records, small-scale, but widespread, gold mining activity also continues to be one of the major deforestation drivers across the Amazon.

In collaboration with its network of partners in the region, MAAP has produced many reports documenting the expansion of gold mining across the Amazon over the years, highlighting often previously undocumented cases (see archive).

Given the vastness of the Amazon, however, it has been a challenge to systematically detect all new mining fronts in real-time. Such a timely and comprehensive system is crucial to ensure that monitoring can be the basis for a swift and consistent enforcement response from authorities.

Since 2023, Amazon Conservation, in partnership with Earth Genome and the Pulitzer Center, has been developing an online dashboard known as Amazon Mining Watch (MAAP #226). This online tool automates the analysis of satellite imagery through machine learning to identify areas affected by mining across the entire Amazon, from 2018 to 2024. 

In a major advance, we are glad to announce that Amazon Mining Watch (AMW) will now move to quarterly updates for this data, achieving systematic near-real-time detection of new artisanal gold mining fronts across the region.

Additional functionalities have been added to the AMW that will enhance the analysis related to illegal gold mining in the biome, namely: an analysis of the legality of mining sites, and an economic valuation of the social and environmental damage through the mining impacts calculator tool (see Annex).

FIRST QUARTERLY UPDATE REPORT: MINING EXPANSION ACROSS THE AMAZON

Here, we present our first quarterly update report based on this fresh data for quarters 2 and 3 of 2025 (April-September 2025). The following Base Map shows the locations of recent (Q3 of 2025) mining deforestation across the Amazon, in relation to the cumulative mining impact area previously detected.

Key findings from the first quarterly updates include:

  • We confirm the recent expansion of gold mining in all nine countries of the Amazon (37,109 hectares in 2025).
  • Brazil registered the largest recent mining expansion area (15,538 ha in 2025), followed by Peru (6,511 ha) and Guyana (4,942 ha).
    In addition,
    Venezuela, Suriname, Ecuador, and Bolivia all had over 2,000 hectares of recent impact.
  • Guyana and Suriname have the largest area of mining-related deforestation relative to their size.
  • The total area of gold mining expansion in the second quarter of 2025 represents over 19,000 hectares
  • Mining expansion accelerated in the third quarter (July-Sept) of 2025, with over 17,000 hectares of forest lost to mining, almost twice the rate observed in the first half of the year.
  • Despite experiencing relatively widespread river-based mining, Colombia is the only country in the region that had been so far mostly spared from the impacts of gold mining on land (also referred to as “alluvial mining”). The recent crossing of alluvial mining along the Rio Puré from Brazil into Colombia, further described below, could put an end to this exception and explains almost single-handedly the sharp uptick seen in the last quarter (+58%).
  • In 2025, over 200 (222) protected areas and Indigenous territories experienced new mining activity, and therefore likely to represent illegal mining. The estimated mined area of these 2025 mining events is over 14,000 hectares (14,004 ha). Of this total, 56% occurred in protected areas, and 44% in Indigenous territories.

CASES OF RECENT GOLD MINING DEFORESTATION ACROSS THE AMAZON

Base Map. Amazon gold mining deforestation highlighted cases Data: AMW, ACA/MAAP.

The Base Map shows the locations of confirmed recent (Q3 of 2025) mining deforestation across the Amazon, in relation to the cumulative mining impact area.

In each set of panels displayed below, we show high-resolution satellite imagery before (left panel) vs after (right panel) the recent gold mining deforestation. The red polygons indicate the pixels highlighted by the AI model as a new quarter 3 mining deforestation event. Yellow polygons are previously detected pixels.

 

 

 

 

 

 

 

 

 

A. Rio Puré, Colombia-Brazil border

The Q3 2025 detection revealed that alluvial gold mining has, for the first time, crossed the border between Brazil and Colombia, into the Rio Puré National Park. A relatively large-scale operation appears to be ongoing and expanding in one of the most remote corners of the Amazon, affecting one of the largest intact forest landscapes still remaining globally.

Mining along the Rio Puré is estimated to have started around 2018, gradually expanding along the whole Brazilian portion of the river between the border with Colombia and where it meets the Japurá river, itself one of the major tributaries of the Amazon river. The clear difference in the river’s color between the last two quarters also reveals the amount of sediments released from the mining operation, which greatly increased water turbidity. 

The verified expansion of the mining into the Colombian side, under National Park status, makes this a clear case for transboundary collaboration between the enforcement authorities of Brazil and Colombia. This incursion from Brazil represents the vast majority of mining-related deforestation in the country for the last quarter, and an almost 60% increase in area compared to the previous 7 years.

This case registers as a Very High probability of being illegal based on the legality layer. For more information, consult the scene on Amazon Mining Watch.

B. Northern Ecuador

Figure B shows the recent mining deforestation outside of the Cofán Bermejo Ecological Reserve in the northern Ecuadorian Amazon. This area has experienced increasing mining impact in recent years, as further described in MAAP #227. Note that this mining activity is within the Puma Kucha, Indigenous territory. This case registers as a High probability of being illegal based on the legality layer. For more information, consult the scene on Amazon Mining Watch.

C. San José de Karene Indigenous Territory, Peru

Figure C shows the recent mining deforestation in the San José de Karene Indigenous Territory in the southern Peruvian Amazon. As detailed in MAAP #208, much of the illegal mining deforestation in the southern Peruvian Amazon is occurring within the territory of Native Communities. This case registers as a High probability of being illegal based on the legality layer. For more information, consult the scene on Amazon Mining Watch.

D. Pemon Indigenous Territory, Venezuela 

The Pemon Indigenous territory stands out as the area most affected by gold mining in the last quarter, across all protected areas and indigenous territories of the region. The Pemon’s traditional territory is divided between an officially demarcated area, where mining increased by more than 100 hectares in the last quarter, and a much greater and yet-to-be-demarcated area, where mining increased by a staggering 700 ha in the last quarter only, a steep acceleration from the first semester of 2025. The Pemon’s territory encompasses part of the outstanding geological wonder Mount Roraima, a flat-topped mountain of immense cultural significance to local peoples. Mount Roraima harbors unique biodiversity and inspired Michael Crichton’s novel “The Lost World”.

This case registers as a High probability of being illegal based on the legality layer. For more information, consult the scene on the Amazon Mining Watch.

Brazil

Figure E shows the recent mining deforestation in the Amapá State Forest in the northeastern Brazilian Amazon. The forest is managed to benefit local communities through initiatives like sustainable agroecology and improved management of wood and non-forest products. This marks the first time this area has been highlighted by MAAP.  This case registers as a Very High probability of being illegal based on the legality layer. For more information, consult the scene on the Amazon Mining Watch.

Figure F shows the recent mining deforestation in the Tapajós Environmental Protection Area in the central Brazilian Amazon. It is in the western portion of the BR-163 Sustainable Forest District. As noted in MAAP #226, Tapajós EPA is one of the Amazon’s top ten most impacted protected areas (in terms of accumulated footprint), including high levels of new mining deforestation in 2024. This case registers as a Very High probability of being illegal based on the legality layer. For more information, consult the scene on the Amazon Mining Watch.

 

Figure G shows the recent mining deforestation in Jamanxim National Forest in the central Brazilian Amazon. As noted in MAAP #226, Jamanxim NF is one of the Amazon’s top ten most impacted protected areas (in terms of accumulated footprint). This case registers as a Very High probability of being illegal based on the legality layer. For more information, consult the scene on the Amazon Mining Watch.

Figure H shows the recent mining deforestation in the Grão-Pará Ecological Station in the northeast Brazilian Amazon, along the border with Guyana. It is the largest strictly protected tropical forest research station in the world. This marks the first time this area has been highlighted by MAAP. This case registers as a Very High probability of being illegal based on the legality layer. For more information, consult the scene on the Amazon Mining Watch.

Suriname

Figure I show recent mining deforestation in northeast Suriname. This marks the first time this specific area has been highlighted by MAAP. This case registers as a High probability of being illegal based on the legality layer. For more information, consult the scene on the Amazon Mining Watch.

Guyana

Figure J shows the recent mining deforestation in northwestern Guyana, near the border with Venezuela. This marks the first time this specific area has been highlighted by MAAP. For more information, consult the scene on the Amazon Mining Watch.

Annex

New functionality: Legality of mining sites

Based on an analysis of potential overlaps with land designations and applicable regulations, a location-based presumption of illegality of mining operations was incorporated into the AMW. We classified the presumption of illegality from very high to low, using the following descriptions:

  • Very High: Activity is occurring without a permit and within a protected area that doesn’t allow for any kind of resource exploitation
  • High: Activity if occurring outside of any explicit concession for doing so
  • Medium: Activity is happening within a concession, but active status could not be verified and/or concession doesn’t meet legal requirements
  • Low: Activity is happening within active concession, but compliance with all requirements could not be verified

This functionality is available for 5 countries: Bolivia, Brazil, Colombia, Ecuador and Peru, and will be extended to the rest of Amazonian countries in 2026. Based on national datasets of land designations, it provides an immediate overview of the likelihood of illegality of ASM in any area of analysis.

New functionality: Mining impacts calculator

The Mining Impacts Calculator, developed by Conservation Strategy Fund, is a tool to assess the social and environmental damage caused by gold mining. The tool uses an economic formula to estimate effects on the environment and society by inputting variables such as the size of the mine, the amount of gold produced and the time of extraction. The automated formula uses average mining productivity and data-driven impact parameters to deliver contextualized data to the user.

The calculator can be used for three main purposes: to estimate social and environmental damage values to calculate the amount of financial compensation needed to mitigate the costs, to estimate the most efficient investment amounts for future impact planning and the prevention of negative impacts, and to estimate the recommended amount of investment in mercury-free technologies needed.

Notes/Methodology

Note that in this report, we focus on mining activity that causes deforestation. The vast majority is artisanal or small-scale gold mining, but other mining activities have also been detected, such as iron, aluminum, and nickel mines in Brazil and Colombia. Additional critical gold mining areas in rivers that are not yet causing deforestation (such as in northern Peru (MAAP #233), southeast Colombia (MAAP #228), and northwest Brazil (MAAP #197), are not included in this report. This information is not yet displayed in Amazon Mining Watch, but future updates will include river-based mining hotspots.

Our data source for protected areas and Indigenous territories is from RAISG (Amazon Network of Georeferenced Socio-Environmental Information), a consortium of civil society organizations in the Amazon countries. This source (accessed in December 2024) contains spatial data for 5,943 protected areas and Indigenous territories, covering 414.9 million hectares across the Amazon.

Amazon Mining Watch (AMW) is a partnership between Earth Genome, the Pulitzer Center’s Rainforest Investigations Network, and Amazon Conservation. The algorithm is based on 10-meter-resolution imagery from the European Space Agency’s Sentinel-2 satellite and produces 480-meter resolution pixelated mining deforestation alerts. Although the data is not designed for precise area measurements, it can be used to give timely estimates needed for management and conservation purposes.

Acknowledgments

This report was made possible by the generous support of the Gordon and Betty Moore Foundation.

 

MAAP #232: The Amazon Tipping Point – Importance of Flying Rivers Connecting the Amazon

Intro Map. Amazon moisture flow (aerial river) for the southwest Amazon. Source: Amazon Conservation/MAAP

The Amazon biome, stretching over a vast area across nine countries in northern South America, is renowned for its extreme diversity (biological and cultural) and its abundant water resources. Indeed, the major features of the Amazon are linked by interconnected water flows, both on land and in the air (Beveridge et al. 2024).

The natural phenomenon of aerial moisture transport and recycling, also known as “aerial rivers” and popularized in the press as “flying rivers,” has emerged as an essential concept related to the conservation of the Amazon. In short, moisture flows from the Atlantic Ocean across the Amazon, uniquely facilitated by the rainforest itself. As they move westward, these flying rivers drop water onto the forest below. The forest subsequently transpires moisture back into them, thus recycling water and supporting rainforest ecosystems far from the Ocean source. For example, the Intro Map illustrates the aerial river for the southwest Amazon.

Continued deforestation and forest degradation, however, will disrupt and diminish the critical east-to-west aerial water flow, inducing a “tipping point” of impacted regions that would transition from rainforest to drier savannah ecosystems. 

In this report, we aim to both summarize the current state of knowledge on the movement of atmospheric moisture across the Amazon and develop novel analyses based on this information. Overall, we aim to show the critical connections between the eastern and western Amazon, and how these connections change during the major seasons (wet, dry, and transition) of the year.

Our analysis is divided into three main parts:

First, we summarize the state of knowledge on the movement of atmospheric moisture across the Amazon, drawing on a review of recent literature and exchanges with experts. Second, we identify the sensitive areas that are the most vulnerable to deforestation-caused disruption of moisture recycling. Third, we relate these sensitive areas in the west to their respective eastern key source areas for moisture for each of the three Amazonian seasons: wet, dry, and transition.

In summary, we identified the sensitive areas that are the most vulnerable to deforestation-caused disruption of moisture recycling from the Atlantic Ocean source are mostly located in the southwestern Amazon (Peru and Bolivia). For the wet season, much of the moisture flow to these sensitive areas crosses the continuous primary (non-deforested) forests of the northern Amazon. For the dry and transition seasons, however, the moisture flow to the sensitive areas must cross several major deforestation fronts located in the eastern Brazilian Amazon.

Thus, an important contribution of this work is to reveal that, contrary to the common perception that the tipping point is a single Amazon-wide event, certain parts of the Amazon are more vulnerable than others. Most notably, the southwestern Amazon (Peru and Bolivia) is most vulnerable to a possible tipping point, particularly stressed by disrupted dry season moisture flows over major deforestation fronts.

1. Movement of aerial moisture across the Amazon (moisture flow)

Figure 1. Amazon moisture flows by season for the SW Amazon. Data: ERA5, ACA/MAAP

Driven by permanent trade winds, aerial (atmospheric) moisture flows westward from its source in the Atlantic Ocean, across the Amazon lowlands, and toward the Andes Mountains. These moisture routes are recharged by evapotranspiration and discharged by precipitation, creating moisture recycling systems (Beveridge 2024, Weng et al. 2018, Staal 2018, Weng 2019). Evaporation recycling reloads atmospheric moisture after rainfall, while precipitation recycling removes this moisture. The Amazon forest is therefore a key component of a giant water pump, starting with water transported from the tropical Atlantic Ocean and helping push it westward  (Zemp 2017, Boers 2017). Aerial rivers are the long-term and large-scale preferential pathways of the moisture flows driving this pump (Arraut et al. 2012) (see Intro Image). Thus, aerial rivers are the overall average (coarse-scale) moisture flow pattern, while moisture recycling focuses more on the seasonal differences (finer-scale). 

Of all the rainfall in the Amazon, its trees have directly transpired 20% of it (Staal et al. 2018). Half of this precipitation (10%) is from moisture from one recycling event, and the other half (10%) is from multiple recycling events. This latter process of cascading precipitation, or cascading moisture recycling (Zemp et al. 2014), may happen multiple times (up to five or six), recycling water from the eastern to western Amazon, to areas increasingly distant from the Atlantic Ocean source (Lovejoy and Nobre 2019, Beveridge et al, 2024). Precipitation tends to increase exponentially as moist air travels over forests, but then drops off sharply once it moves beyond them, showing just how vital forests are in sustaining rainfall across large regions (Molina et al. 2019). Transpiration-driven moisture recycling is especially important during the dry season (Staal et al. 2018, Nehemy et al. 2025).

Thus, there are transboundary implications, as actions occurring in an eastern country can have an impact on a western country downwind of the moisture cascade. For example, deforestation in eastern Brazil can negatively impact moisture flow going to Colombia, Ecuador, Peru, and Bolivia, including the tropical Andean mountains (Ruiz-Vasquez et al., 2020; Sierra et al. 2022, Flores et al 2024). As moisture recycling also continues beyond the boundaries of the Amazon, there may also be impacts to agricultural areas in southern Brazil, Paraguay, northern Argentina, and northern Colombia (Martinez and Dominguez 2014; Ruiz-Vasquez et al., 2020).

The resulting terrestrial flow of water from the Andes mountains through the Amazon lowlands and back to the Atlantic Ocean as runoff and flow of the Amazon river and its tributaries results in the emerging concept known as the “Andes–Amazon– Atlantic” (AAA) pathway (Beveridge et al, 2024).

Importantly, the moisture flows change seasonally in the Amazon. Figure 1 illustrates these seasonal changes for the southwest Amazon, as an example.

In the rainy season (January–February), the moisture flow is both westward and southward, creating a giant arc (Arraut 2012). Thus, the continental moisture source is the northeast Amazon (Boers 2017, Weng et al. 2018, Sierra et al. 2022). 

In the dry (July–August) and the dry-to-wet transition (September-October) seasons, the moisture flow shifts more directly westward (Arraut 2012, Staal et al, 2018). Therefore, the continental moisture source is the southeast Amazon, and some studies have identified this region as the most important for maintaining overall Amazonian resilience (Zemp et al. 2017, Staal et al. 2018).

There is increasing evidence that future deforestation will reduce rainfall downwind – further west – of the moisture recycling networks, inducing a “tipping point” of impacted regions that would transition from rainforest to savannah ecosystems (Boers 2017, Staal 2018, Lovejoy & Nobre 2018). This has led to calls for forest protection strategies to maintain the cascading moisture recycling system fueling the pathway (Zemp 2017, Encalada et al. 2021). A recent review indicates limited evidence for a single, system-wide tipping point; instead, specific areas of the Amazon may be more vulnerable (Brando et al, 2025).

Scientists are already documenting impacts linked to increasing forest loss.  Several recent studies have found that Amazon deforestation has already caused a significant decrease in precipitation in the southeast Amazon, particularly during the dry season (Qin et al, 2025, Liu et al, 2025, Franco et al. 2025). Moreover, deforestation reduces rainfall upwind of the cleared areas, impacting the western Amazon as well (Qin et al, 2025). In addition, recent studies have shown that Amazon deforestation delays the onset of the wet season in southern Amazonia (Ruiz-Vasquez et al., 2020; Commar et al., 2023; Sierra et al., 2023).

Related to deforestation, additional climatic factors, such as increased temperature and the length of the dry season, are also contributing to the tipping point (Flores et al. 2024). Multiple sources have reported on the lengthening of the dry season in southern and eastern Amazonia in recent decades, with the largest dry season observed in 2023-2024 during the major drought reported in Amazonia (Marengo el al 2024; Espinoza et al., 2024). As a result of these drier conditions, recent years have experienced record-breaking fire seasons, most notably during the El Niño years of 2016 and 2024 (Finer et al 2025). Notably,  the predicted forest-to-savannah change is already happening in places experiencing increased wildfire frequency due to these hot and dry conditions (Flores et al. 2021).

2. Areas most dependent on moisture recycling in the Amazon (sensitive areas)

Figure 2. Merged sensitive areas. Data: Staal 2018, Weng 2018, Amazon Conservation/MAAP

A series of recent empirical and modeling studies indicate that the southwest Amazon (including the Peruvian and Bolivian ranges of the tropical Andes) is the major moisture sink – the area where precipitation is most dependent on moisture recycling (Boers et al. 2017, Zemp et al. 2017, Weng et al. 2018, Staal et al. 2018, Sierra et al. 2022). In fact, tree-transpired rainfall is greater than 70% in this region (Staal et al. 2018, Weng et al. 2018). 

Given its dependence on transpiration-driven precipitation, the impact of a reduction in rainfall from cascading moisture recycling is predicted to be greatest in the southwest Amazon (Zemp et al. 2017, Weng et al. 2018, Staal 2018, Sierra et al. 2022, Beveridge 2024). Indeed, the southwest Amazon forest may enter the bioclimatic equilibrium of savannas following projected extensive Amazon deforestation scenarios (Zemp, 2017). Forests in the northwest and Guyana Shield are also relatively dependent on forest-rainfall cascades (Hoyos et al 2018; Staal et al. 2018).

To precisely identify the most vulnerable areas in the Amazon to disruptions of transpiration-based moisture recycling in a spatially explicit manner, we merged two key studies featuring spatially explicit model outputs (Weng 2018, Staal 2018). These studies cover data for the dry season (Staal 2018) and yearly (both dry and wet seasons) (Weng 2018). 

Weng 2018 identifies “sensitive areas,” defined as areas having more than 50% of rainfall coming from Amazonian evapotranspiration (representing the 98th percentile of the highest sensitivity to Amazonian land use change). Staal 2018 estimates the effect of Amazon tree transpiration on Amazon forest resilience. We selected the areas with the highest resilience loss (0.8 and higher), quantified as the fraction of resilience that would be lost in the absence of tree transpiration by Amazonian trees.

Figure 2 illustrates the merged dataset, which we refer to as “merged sensitive areas.” Notably, both studies concur that the most vulnerable areas are located in the southwest Amazon, spanning the lowlands of only two of the nine countries of the Amazon Basin: Peru and Bolivia. This merged sensitive area covers a 1,750-kilometer-long swath along the Peruvian and Bolivian Andes. In this merged data map, we include Manu National Park as a reference point, located roughly in the middle of the sensitive areas. 

Weng et al. identified higher elevation areas of the Andean-Amazon transition area in both Peru (Junín, Cusco, and Puno regions) and Bolivia, while Staal et al (2018) identified slightly lower elevation areas in this same range. These regions are consistent with predicted areas of higher rainfall reduction due to deforestation (Sierra et al. 2022). Also, note that Staal indicates an additional area in the Venezuelan Amazon.

Although, as noted above, forests in the northwest and northeast (Guyana Shield) are also relatively dependent on forest-rainfall cascades, the forests of the southwest are the most dependent, likely given their location at the far end of the Atlantic-Amazon-Andes pathway.

3. Moisture flows to sensitive areas (by season)

Figure 3. Amazon moisture flows by season relative to sensitive areas in the southwest Amazon. Data: ERA5, ACA/MAAP

Given the reliance of western, especially southwest, Amazon forests on cascading moisture recycling, a key challenge is to identify the most important moisture source areas in the eastern Amazon. In this respect, the literature provides a less definitive answer, likely because the moisture recycling routes change with seasons, in contrast to the long-term path of the aerial rivers that represent overall preferential pathways (Arraut 2012, Staal 2018, Weng et al. 2018). 

We correlate the merged sensitive areas in the southwest Amazon with their respective moisture source areas by back-tracking the moisture flows upwind. This component of the work was inspired by the precipitation-shed concept, defined here as the terrestrial upwind surface areas providing evapotranspiration to a specific area’s precipitation (Keys et al. 2012, Weng et al. 2018). 

We determined that analyzing all three major seasons is essential because of the major seasonal variability (Staal et al, 2018) and that each plays a key role in the stability of the rainforests: During the wet season, nearly 50% of total annual precipitation falls over the region, and these wet periods recharge Amazonian groundwater reserves vital for sustaining forest transpiration rates during dry months (Miguez-Macho and Fan 2012, Sierra et al 2022). During the dry season, moisture recycling processes are particularly important to ensure that some of the limited precipitation reaches the western Amazon (Beveridge et al, 2024). Tree-transpired rainfall then peaks during September to November, when large parts of the Amazon are at the end of the dry season and transitioning to the wet season (Zanin et al., 2024).

To map the pathway of moisture flow between the western Amazon merged sensitive areas and their eastern moisture sources, we utilize moisture flow data from the ERA5 reanalysis (Hersbach 2023). Specifically, we merged vertically integrated data for both northward and eastward water vapour flux. We chose data from 2022 as a recent year not heavily influenced by extreme weather events such as El Niño or drought (Espinoza et al., 2024). For 2022, we downloaded and analyzed the moisture flow data for three separate time periods: January-February (representing the wet or monsoon season), July-August (dry season), and September-October (dry-to-wet transition season).

The results for all three seasons are illustrated in Figure 3, where the arrows represent the ERA5 reanalysis moisture flow data from the Atlantic Ocean to the merged sensitive areas in the southwest Amazon. 

Note that in the wet season (January-February), moisture flows from the Atlantic Ocean over the northeast Amazon (northern Brazil, French Guiana, Suriname, Guyana, and Venezuela) before taking a major southern turn (arc) through the southeast Colombian Amazon and northern Peru before reaching the Sensitive Areas. This general pattern is consistent with other studies focused on the wet season (Arraut 2012, Boers 2017, Sierra et al. 2022) and year-round (Weng et al. 2018).

In contrast, in the dry (July-August) and transition (September-October) seasons, the moisture flows from the Atlantic Ocean further south across the central Brazilian Amazon, and has a less pronounced arc near the border with Peru. Specifically, the dry season pattern is consistent with other studies focused on the dry season (Arraut 2012, Staal 2018, Zemp 2017 NC).  Note that the transition season flow is located between the wet season to the north and the dry season to the south.

For all three seasons, we emphasize that the entire trajectory from east to west is important for conservation regarding cascading moisture recycling. That is, the farthest away areas in the east represent the full cascading trajectory, while the closest areas in the west exert the strongest direct influence (Weng et al. 2018). 

While moisture recycling covers a vast area from east to west, much of the tree-induced rainfall in the southwest Amazon is transpired nearby (Stall 2018). That is, areas exerting the strongest and most efficient influence on the southwest Amazon are located just upwind, in the central-west Amazon (Weng 2018; Wongchuig et al., 2023). In sum, extensive forest loss anywhere along the cascading moisture pathway from the eastern to the western Amazon, far or near, may affect transpiration-based precipitation in the western Amazon, adding to its sensitivity.

The overall annual pattern, accounting for all three seasons, could then be described as aerial rivers. As indicated by Weng et al. (2018), this mostly matches the pattern of the wet season.

Figure 4. As in Figure 3, plus forest cover. Data: ERA5, Amazon Conservation/MAAP

For additional context, Figure 4 incorporates current land classification broken down into three major categories based on satellite imagery analysis: Forest, Non-forest (such as savannah), and accumulated Deforestation areas (as of 2022).

For January-February (wet season), note that much of the moisture flow crosses the continuous primary forest of the northern Amazon. That is, the moisture crosses predominantly non-deforested areas of northern Brazil, French Guiana, Suriname, Guyana, Venezuela, southeast Colombia, and northern Peru.

In contrast, the moisture flows for July-August (dry season) and September-October (transition season) cross several major deforestation fronts in the central Amazon, particularly during the dry season.

During the critical dry-to-wet transition season, the role of the local area’s tree evapotranspiration is especially important. The southern Amazon presents lower overall evapotranspiration values (Fassoni-Andrade 2021; Zanin et al., 2024). Due to the greater access of forest roots to deep soil water, however, evapotranspiration over forested areas is higher than croplands/grasslands during this time (von Randow et al. 2004). Since, during this transition season, the moisture transport to the southwestern Amazon passes over large deforested areas, the conservation of the remaining forest along this pathway is critical.

In addition, recent studies show that the main patterns of moisture flux can be altered at a continental scale due to deforestation (Commar et al., 2023; Sierra et al., 2023). As a result, reduced moisture transport from the Atlantic to the continent and delays in the onset of the wet season may occur in the future due to Amazon deforestation and climate change (Agudelo et al., 2023).

Conclusion

Above, in this initial technical report, we merged three key points that are critical to understanding the tipping point concept in the Amazon.

First, we presented an overview of aerial moisture flows originating from the Atlantic Ocean and then moving and recycling from the eastern to the western Amazon. Second, we identified the “sensitive areas” that are the most vulnerable to deforestation-caused disruption of moisture recycling, mostly located in the western Amazon (Peru and Bolivia).  Third, we relate these sensitive areas in the west to their respective eastern key source areas for moisture for each of the three Amazonian seasons: wet, dry, and transition. 

Incorporating updated land-use data, we found important differences by season. For the wet season, much of the moisture flow crosses the continuous primary (non-deforested) forests of the northern Amazon. For the dry and transition seasons, however, the moisture flow must cross several major deforestation fronts mainly located in the central Amazon.

Thus, an important contribution of this work is to reveal that, contrary to the common perception that the tipping point is a single Amazon-wide event, certain parts of the Amazon are more vulnerable than others. Most notably, the southwestern Amazon (Peru and Bolivia) is most vulnerable to a possible tipping point, particularly stressed by disrupted dry season moisture flows over major deforestation fronts.

We will soon build off of these results in an upcoming policy-focused report that presents the major implications of the maintenance of aerial moisture flows for conservation. This analysis will include how to identify key conservation areas for each season based on the key concept of maintaining cascading moisture flow to the sensitive areas, in relation to protected areas, Indigenous territories, and major road networks. It will also reveal several policy implications that require urgent attention and new approaches to national governance and international cooperation. For example, It considers the implications of planned roads (most notably BR-319) and fortifying existing conservation areas and creating new ones in undesignated public lands.

Acknowledgements

This work was supported by the Leo Model Foundation.

We thank the following colleagues for datasets and/or comments on earlier versions of the report:

Wei Weng
Potsdam Institute for Climate Impact Research
Potsdam, Germany  

Arie Staal
Assistant Professor
Environmental Sciences
Copernicus Institute of Sustainable Development
Utrecht University

Juan Pablo Sierra
Institut des Géosciences de l’Environnement,
Université Grenoble Alpes, IRD, CNRS,
Grenoble, France  

Jhan-Carlo Espinoza
Directeur de Recherche, Institut de Recherche pour le Developpement (IRD)
IGE Univ. Grenoble Alpes, IRD, CNRS (UMR 5001 / UR 252) – France
Pontificia Universidad Católica del Perú. Lima – Peru
Co-chair of ANDEX: A regional Hydroclimate Initiative for the Andes – GEWEX
Coordinator of the AMANECER Project (Amazon-Andes Connectivity)

Clara Zemp
University of Neuchâtel

Corine Vriesendorp
Director of Science
Conservación Amazónica – Peru (ACCA)

Federico E. Viscarra
Science Officer
Science Panel for the Amazon

Daniel Larrea
Director of the Science & Technology Program
Conservación Amazónica – Bolivia (ACEAA)

Citation

Finer M, Ariñez A, Sierra JP, Espinoza JC,, Weng W, Vriesendorp C, Bodin B, Beavers J (2025) The Amazon Tipping Point – Importance of Flying Rivers Connecting the Amazon. MAAP: 232.

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