Country: Peru

MAAP #233: Current situation of gold mining in the Peruvian Amazon

Posted on by Matt Finer
Base Map. Gold mining in the Peruvian Amazon.

Gold mining continues to increase in the Peruvian Amazon. Following the initial success of the major multisectoral government intervention Operation Mercury in southern Peru in early 2019 (MAAP #104, MAAP #121, MAAP #130), the illegal mining activity rebounded during the COVID-19 pandemic, as the government withdrew from the area (Vadillo, 2022).

The current increase, directly linked to soaring international gold prices, has led to expanding mining activity: continuing mining in southern Peru, and emerging mining fronts in the central and northern parts of the country.

This report presents information on the current state of gold mining activity, in both forests and rivers, across all of the Peruvian Amazon.

Notably, we report that gold mining has spread to nine regions across the Peruvian Amazon: Amazonas, Cajamarca, Cusco, Huánuco, Loreto, Madre de Dios, Pasco, Puno, and Ucayali.

Total gold mining deforestation has reached 139,169 hectares (343,894 acres) as of mid-2025, the vast majority (97.5%) in the Madre de Dios region of southern Peru. The Huánuco and Puno regions have also experienced rising mining deforestation (1,262 and 1,014 hectares, respectively).

Moreover, alluvial gold mining is also expanding in numerous rivers across the Peruvian Amazon, especially in the northern regions of Loreto and Amazonas. We have identified 989 mining dredges in Loreto since 2017, followed by 174  in Amazonas.

Overall, we have documented gold mining activity in 225 water bodies (rivers and streams) across the Peruvian Amazon.

Below, we present the detailed results of this report in three regional sections: northern Peru (Amazonas, Cajamarca, and Loreto); central Peru (Huánuco, Pasco, and Ucayali); and southern Peru (Cusco, Madre de Dios, and Puno). Each section presents information about mining in forests (deforestation) and rivers.

Base Map. Data: ACA, ACCA, CINCIA, FEMA, SZF, IBC, SERNANP, Mapbiomas Perú

 

Northern Peru

Gold mining has spread to both the forests and rivers of Amazonas, Cajamarca, and Loreto regions of the northern Peruvian Amazon (Figure 1).

Gold mining deforestation has impacted 491 hectares, located near rivers and within Indigenous communities (see red areas in Figure 1). The mining deforestation has been localized along the Chinchipe River in Cajamarca, and near the Marañón River in Amazonas and Loreto.

Figure 1. Gold mining in the northern Peruvian Amazon. Data: ACCA, FEMA, SZF, IBC, SERNANP
Figure 1A. Gold mining deforestation along the Sawintsa River, Amazonas region. Data: ACCA, Maxar

We highlight the recent mining deforestation along the Sawintsa River near the Peru-Ecuador border in the Amazonas and Cajamarca regions (Figura 1A).

 

 

 

 

 

 

 

 

 

 

Figure 1B. Mining dredges identified in the Nanay River (Loreto). Data: Planet, ACCA

In addition, river-based mining has emerged as a critical issue in northern Peru, where we have documented mining barges in at least 14 rivers (see yellow dots in Figure 1).

Loreto is the most impacted region, where we have documented 989 mining dredges between 2017 and 2025.

The Nanay River, located in Loreto, is the most impacted by mining dredges Figure 1B. We have identified 841 mining dredges since 2017, including 275 in 2025. This mining activity extends into Indigenous communities and the Alto Nanay – Pintuyacu – Chambira Regional Conservation Area.

Mining also impacts the Cenepa and Santiago Rivers, located in Amazonas. We have identified 137 and 51 mining dredges, respectively, in these rivers since 2022. Some of this mining activity surrounds Indigenous communities in Amazonas.

 

 

 

Central Peru

Gold mining also impacts both the forests and rivers of Huánuco, Pasco and Ucayali regions in the central Peruvian Amazon (Figure 2).

Gold mining deforestation has reached 1,320 hectares, located along rivers, in Indigenous communities, in the Carpish Montane Forest Regional Conservation Area, and in the buffer zone of the El Sira Communal Reserve (see red areas in Figure 2).

Figure 2. Gold mining in the central Peruvian Amazon. Data: ACCA
Figure 2A. Gold mining deforestation due in Puerto Inca province, Huánuco region. Data: Maxar, ACCA

The Huánuco region is the most impacted by mining deforestation in central Peru, with the vast majority (97%) occurring in the province of Puerto Inca (Figure 2A).

 

 

 

 

 

 

 

 

 

 

Figura 2b. Deforestación por minería de oro aledaño al río Chinchihuani, región Pasco. Datos: Maxar, ACCA

In the Pasco region, gold mining deforestation has been recorded in pending mining concessions along the Chinchihuani River since August 2024 (Figure 2B).

Gold mining in the Ucayali region has been located along the Abujao River.

 

 

 

 

 

 

 

 

 

Figure 2C. Mining dredges in the Aguaytía River, Ucayali region. Data: Maxar, ACCA

In addition, river-based mining is impacting the Aguaytía River, in the Ucayali region (see yellow dots in Figure 2).

We first detected mining dredges in mid-2024 (Figure 2C) in this area,  located near the buffer zone of Cordillera Azul National Park.

In total, we have identified 26 mining dredges in the Aguaytía River in 2024 and  2025.

 

 

 

 

 

 

 

 

Southern Peru

Gold mining deforestation has had major impacts in the regions of Cusco, Madre de Dios, and Puno, in the southern Peruvian Amazon. Note in Figure 3 that mining deforestation (indicated in red) is the dominant impact, and not mining barges as seen in the northern Peruvian Amazon.

We have documented the gold mining deforestation of ​​137,558 hectares (339,913 acres) in these southern regions, accounting for 98.7% of total mining deforestation in the Peruvian Amazon. This massive gold mining deforestation started in 1984 in Madre de Dios.

Figure 3. Gold mining in the southern Peruvian Amazon. Data: ACA, ACCA, CINCIA, Mapbiomas Perú, AMW
Figure 3A. Gold mining deforestation in the buffer zone of Tambopata National Reserve. Data: Planet

Madre de Dios has the highest gold mining deforestation of all the regions in Peru (135,939 hectares), accounting for 97.5% of the national total.

This widespread mining deforestation in Madre de Dios has extended into Indigenous communities and the buffer zones of protected areas, such as Tambopata National Reserve (Figure 3A) and Amarakaeri Communal Reserve.

 

 

 

 

 

 

 

 

Figura 3b. Deforestación por minería oro en la Concesión para Conservación Camanti Sostenible. Datos: Maxar

In the Cusco region, gold mining deforestation has spread to various areas around the Araza and Nusiniscato Rivers.

Además, parte de la deforestación por minería se ha extendido al interior de la zona de amortiguamiento de la Reserva Comunal Amarakaeri y en la Concesión para Conservación Camanti Sostenible (Figura 3b). 

 

 

 

 

 

 

 

 

 

Figure 3C. Gold mining deforestation near the Huari Huari River. Source: ACCA, Maxar

The Puno region has experienced gold mining deforestation near the Inambari and Huari Huari Rivers (Figure 3C), surrounding the buffer zone of the Bahuaja Sonene National Park.

 

 

 

 

 

 

 

 

 

 

Figura 3d. Tracas en pozas mineras en la zona de amortiguamiento de la Reserva Nacional Tambopata. Fuente: Planet

In Madre de Dios, we have detected over 2,000 pieces of mining infrastructure, such as drills, chutes, dredges, and mining rafts (Figure 3D) (ACCA, 2022).

 

 

 

 

 

 

 

 

 

 

 

Policy recommendations for gold mining in Peru:

Gold mining in Peru represents one of the country’s greatest socio-environmental challenges, impacting Amazonian forests, rivers, and local communities (Arana Cardó, M, 2024). In response, we present five policy proposals aimed at minimizing this impact, focusing on 1) implementing gold traceability, 2) strengthening the Artisanal and Small-scale mining (ASM) Law, 3) establishing environmental obligations, 4) strengthening supervision, and 5) promoting clean technologies (including banning mercury).

1. Implement an effective gold traceability system that links production, marketing, and export

Foto: ACCA

Currently, the Special Registry of Gold Traders and Processors, created by Ministerial Resolution No. 249-2012-MEM-DM, lacks effective mechanisms for cross-referencing information.

Therefore, it is recommended to consolidate a comprehensive traceability system that covers not only producers, traders, processors, and exporters, including the jewelry industry, but also the control of critical inputs such as mercury and fuels, in order to guarantee supply chains free of contamination and illegal activities.

This system must integrate real-time digital controls, cross-reference information between what is declared as production and what is actually traded, prevent the illegal export of gold in the form of jewelry, and align with international due diligence requirements.

 

2. Strengthening the Artisanal and Small-scale mining (ASM) Law & improving the formalizatin registry (REINFO)

Foto: ACCA

Regulations on small-scale and artisanal mining should establish clear categories based on production and technology, differentiating the formalization process (aimed at pre-existing informal miners and includes phased-in measures and technical support) from the ordinary permitting process, which requires full compliance with environmental and technical requirements for new projects.

The new law for Artisanal and Small-scale mining (ASM) should incorporate real incentives for formalization and the adoption of sustainable practices, effective oversight mechanisms, and the delimitation of exclusive zones for formalized activity, excluding natural Protected Areas, Indigenous reserves, bodies of water, and cultural heritage sites.

Additionally, this new regulation must establish mandatory due diligence throughout the gold value chain, linking the formalization process to the implementation of a traceability system. Thus, formalized miners must not only comply with basic legal requirements but also ensure that their production is free of illegal inputs such as mercury, meeting international standards of transparency and sustainability.

Likewise, given the formalization extension granted until December 31, 2025, in Supreme Decree No. 012-2025-EM, it is essential that the government improve the Comprehensive Registry of Mining Formalization (REINFO in Spanish), permanently removing those who do not meet the minimum requirements established in Law No. 32213 and its regulations, as indicated by its update through Supreme Decree No. 009-2025-EM. Furthermore, proportional sanctioning mechanisms must be evaluated to discourage the misuse of the registry. Only in this way will it be possible to prevent this registry from continuing to be used as a shield of impunity against the actions of the Public Prosecutor’s Office and the National Police, and to ensure that formalization translates into an effective change in mining practices.

3. Establish environmental obligations from the beginning of mining formalization & ensure their supervision

Foto: ACCA

Regulations should establish that all small-scale and artisanal mining activities must be subject to the respective environmental obligations from the initial formalization process, in order to ensure early and effective oversight.

During this process, operations must be subject to governmental oversight by the Environmental Assessment and Oversight Agency (OEFA in Spanish), the Supervising Agency for Investment in Energy and Mining (OSINERGMIN in Spanish), and the National Superintendence of Labor Inspection (SUNAFIL in Spanish). Likewise, administrative and criminal sanctions must be applied to responsible authorities who fail to fulfill their oversight duties.

Additionally, forest zoning should be promoted and advanced, in accordance with the provisions of the Forestry Law (Law No. 29763), with an emphasis on the Amazon regions of Peru. This should be integrated into the mining formalization process and become a formal requirement for granting permits. The integration of zoning will prevent the granting of new permits in priority forests for conservation, reducing deforestation and misuse of forests by directing mining toward areas of lower impact and prohibiting it in critical areas. This would require mining formalization authorities to consult zoning maps from the outset. That is, applicants must include the forest zoning category of their plot and demonstrate compatibility before issuing a permit.

4. Strengthen ASM supervision at the regional level through inter-institutional agreements

Foto: ACCA

We propose the signing of agreements between OEFA and the Amazonian regional governments, accompanied by technical support and technological equipment for real-time monitoring of operations in remote areas.

Furthermore, following the Organisation for Economic Co-operation and Development (OECD) guidelines, the formation of specialized multidisciplinary teams to support field supervision is recommended, helping to close capacity gaps and ensure the effectiveness of environmental monitoring in critical territories.

 

 

 

 

 

 

5. Promote clean technologies and ban the use of mercury by 2030.

Foto: ACCA

In compliance with the Minamata Convention, Peru must adopt a policy to phase out mercury in gold mining.

To this end, it is recommended that miners be facilitated access to clean technologies through loans, subsidies, or tax benefits, ensuring safer processes for the environment and public health, so that the technological transition increases gold recovery and reduces impacts on rivers and local communities.

However, this policy must be accompanied by specific goals for the protection of forest resources, as well as stricter sanctions for those who continue to use mercury and generate deforestation, thus ensuring true environmental and public health protection. Furthermore, these goals must be expressly incorporated into the Minamata Convention’s National Action Plan, ensuring its effective and coordinated implementation throughout the country.

 

Methodology

The identification of gold mining deforestation in Peru was based on the visual interpretation of high- and very high-resolution satellite imagery available on Planet, Maxar, and Google Earth Pro for the regions of Amazonas, Cajamarca, Cusco, Huánuco, Loreto, Pasco, Puno, and Ucayali. We conducted a preliminary review of maps and platforms related to mining detection in Peru (the Early Detection and Environmental Monitoring System of the Peruvian Ministry of the Environment, Amazon Mining Watch, and Mapbiomas Perú) to locate potential mining areas. In addition, we compiled reports and newspaper articles related to gold mining in different regions of the country  to identify mining areas, as well as direct communications from representatives of different institutions regarding signs of mining activity at the local level. Based on these preliminary processes, we identified gold mining deforestation using satellite imagery. Additionally, we conducted monitoring of mining-related deforestation using monthly Planet NICFI mosaics (4.7 m spatial resolution) to track the expansion of mining-related deforestation and identify new nearby mining areas.

The identification of gold mining deforestation in Madre de Dios used historical mining deforestation information generated by the Amazon Scientific Innovation Center (CINCIA) for the years 1984 – 2019, by Mapbiomas Perú for the year 2020, and by Amazon Conservation (ACA) for the period January 2021 – March 2024. Then, we used the LandTrendR algorithm to identify forest loss in monthly mosaics of Planet NICFI for the period April 2024 – July 2025. Subsequently, we conducted a manual review to identify forest loss resulting from gold mining and other causes.

The identification of river-based mining was based on the visual interpretation of very high-resolution satellite imagery available on Planet, Maxar, and Google Earth Pro for various Amazonian rivers and mining areas in Peru. In addition, confidential reports and direct communications from various institutions regarding the presence of mining infrastructure in Amazonian rivers were included.

 

References

Arana Cardó, M. (2024). Minería ilegal en la Amazonía peruana: Informe sobre las actividades mineras en las regiones amazónicas de Loreto, San Martín, Amazonas, Ucayali, Madre de Dios y Huánuco. Fundación para la Conservación y el Desarrollo Sostenible Perú (FCDS). https://fcds.org.pe/wpcontent/uploads/2024/07/Resumen_Ejecutivo_informe_mineria_compressed-1.pdf

Conservación Amazónica (ACCA), Proyecto Prevenir – USAID. (2022). Estimación de la población minera informal e ilegal en el departamento de Madre de Dios, a partir del uso de imágenes satelitales sub métricas. https://repositorio.profonanpe.org.pe/handle/20.500.14150/2744

Delfino, E. (20 de julio de 2025). Minería ilegal en Perú: “Hay una presión internacional por el oro y los principales países consumidores no realizan una debida diligencia respecto al origen” | ENTREVISTA. Mongabay. https://es.mongabay.com/2025/07/mineria-ilegal-peru-oro-amazonia-contaminacion/

OCDE (2016). OECD Due Diligence Guidance for Responsible Supply Chains of Minerals from Conflict-Affected and High-Risk Areas: Third Edition. OECD Publishing. https://doi.org/10.1787/9789264252479-en.

Vadillo Vila, J. (2022). La minería ilegal y su impacto en tiempos de pandemia. Diario El Peruano. https://elperuano.pe/noticia/170967-la-mineria-ilegal-hoy

Zapata Perez, M., Arana Cardo, M., Ramires Valle, D., Castro Sánchez-Moreno, M., Garay Tapia, K., Rivadeneyra Tello, G., Vega Ruiz, C. y Cabanillas Vasquez, F. (2025). 10 propuestas para la formalización efectiva de la pequeña minería y minería artesanal. Observatorio de Minería Ilegal. https://www.observatoriomineriailegal.org.pe/wp-content/uploads/2025/05/10_propuestas_ley_MAPE_020525.pdf

Citation

Pacsi R, Novoa S, Yupanqui O, Quispe M, La Torre S, Balbuena H, Huamán B, Valdivia G, Castañeda C, Soria M, Finer M, Santana A (2025) Current situation of gold mining in the Peruvian Amazon. MAAP: 233.

Acknowledgments

This report is part of a series focusing on gold mining in the Peruvian Amazon, through a strategic collaboration between Amazon Conservation and Conservación Amazónica – Peru (ACCA), with support from the Gordon and Betty Moore Foundation.

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

Posted on by Matt Finer
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 – Perú
–
Co-chair of ANDEX: A regional Hydroclimate Initiative for the Andes – GEWEX
Coordinator of the AMANECER Project (Amazon-Andes Connectivity)

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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MAAP #229: Amazon Deforestation & Fire Hotspots 2024

Posted on by Matt Finer
Base Map. Deforestation and fire hotspots across the Amazon in 2024. Data: UMD/GLAD, Amazon Conservation/MAAP.

Continuing our annual series, we present a detailed look at the major 2024 Amazon forest loss hotspots, based on the final 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 for the Amazon specifically.

This forest loss dataset serves as a consistent source across all nine countries of the Amazon, distinguishing 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 (such as landslides and windstorms). Previous research has confirmed that nearly all Amazon fires are human-caused (MAAP #189).

With this context, we are able to present both estimated deforestation and fire hotspots across the Amazon (see Base Map and Graph 1). 

In 2024, the deforestation was the fifth highest on record (since 2002), at over 1.7 million hectares (4.3 million acres) across the Amazon. This value represents a major increase (34%) from 2023, but a decrease (12%) from the recent peak in 2022 (1.98 million hectares). The majority of the deforestation occurred in Brazil (54.7%), followed by Bolivia (27.3%), Peru (8.1%), and Colombia (4.7%) as the clear top four in 2024.

The big story in 2024, however, was the record-breaking impact of fires on primary forests, with a total of 2.8 million hectares (6.9 million acres). This total shattered the previous record of 1.7 million hectares in 2016. The vast majority (95%) of this fire impact occurred in just two countries: Brazil and Bolivia, which both set annual fire records of their own (along with Peru, Guyana, Suriname, and French Guiana). Overall, this fire data may be interpreted as forest degradation, in contrast to the more permanent impacts of deforestation.

In terms of spatial patterns, the Base Map indicates that most of the intense forest loss hotspots were due to fire. These fire hotspots were especially concentrated in the soy and cattle frontiers of the southeast Brazilian Amazon and southeast Bolivian Amazon. The deforestation hotspots (without major associated fires) were largely due to agriculture and gold mining across the Amazon, notably in Bolivia, Brazil, Colombia, Ecuador, and Peru. See Annex 1 for the overall forest loss hotspots (without the specific fire loss data).

Previous research has revealed the tight link between deforestation and fires in the Amazon (MAAP #189). That is, many major fires are burning recently deforested areas, and sometimes escape into surrounding forests, especially with extended dry conditions.

In total, 4.5 million hectares (11.2 million acres) of primary forest were impacted by deforestation and fire combined. This total is the highest on record by far, surpassing 2016 (3.4 million hectares) by over a million hectares.

Since 2002, we estimate the deforestation of 33.7 million hectares (83.4 million acres) of primary forest, greater than the size of the state of New Mexico. An additional 10.6 million hectares (26.2 million acres) have been impacted by fires.

Below, we zoom in on the four countries with the highest deforestation (Brazil, Bolivia, Peru, and Colombia), plus additional highlights from around the Amazon (Guyana, Venezuela, and Ecuador).

Amazon Primary Forest Loss, 2002-2024

Graph 1 shows the historical trend of Amazonian primary forest loss, from 2022 to present.

Graph 1. Amazon Forest Loss, 2002-24. Data: UMD/GLAD, Amazon Conservation/MAAP.

Amazon Primary Forest Loss (By Country), 2002-2024

Graph 2a shows 2024 Amazon primary forest loss for all nine countries. In Annex 2, Graph 2b removes Brazil and Bolivia to see the other countries in greater detail.

Graph 2a. Amazon primary forest loss for all nine countries. Data: UMD

Brazilian Amazon

Figure 2. Deforestation and fire hotspots in the Brazilian Amazon. Data: UMD.

In 2024, the Brazilian Amazon lost 954,126 hectares (2.4 million acres) of primary forest to deforestation. Although this total marked a 13.6% increase from 2023, it was historically relatively low (16th highest overall since 2002).

The bigger story is that fires directly impacted an additional 1.9 million hectares (4.6 million acres). This fire impact was the highest on record, surpassing the previous high of 2016 (1.6 million hectares).

All of the most intense forest loss hotspots were characterized by intense fires. Many of these hotspots were concentrated in the southeast Brazilian Amazon (Figure 2). These areas include along the major north-south road in the state of Pará (BR-163), and further to the east of this road. The hotpots also expanded south into the soy frontier of Mato Grosso state.

Fire hotspots were also located in the northern state Roraima, and along the other major road networks, especially road BR-230 (Trans-Amazonian Highway) in the states of Pará and Amazonas, and road BR-364 in the state of Acre.

Previous research has revealed that over 70% of major fires in the Brazilian Amazon are burning recently deforested areas (MAAP #189). In extended dry conditions, such as 2016 and 2024, these major fires escape into surrounding forests.

 

 

Graph 3. Deforestation and fire trends in the Brazilian Amazon. Data: UMD.

Bolivian Amazon

Figure 3. Deforestation and fire hotspots in the Bolivian Amazon. Data: UMD.

In 2024, the Bolivian Amazon lost 476,030 hectares (1.2 million acres) of primary forest to deforestation. This total was the highest on record, surpassing the previous high of 2022 (245,177 hectares).

In an even bigger shattering record, fires directly impacted an additional 779,960 hectares (1.9 million acres). This total crushed the previous record of 2023 (250,843 hectares).

Like Brazil, the most intense forest loss hotspots were characterized by intense fires.

These fires were concentrated in the soy frontier located in the southeastern department of Santa Cruz (Figure 3). We emphasize that this particular hotspot is further north than in previous years, indicating a northern expansion of soy plantations.

There was also a concentration of fire hotspots along the Beni and Pando departments’ border, and closer to the Andes Mountains in the departments of La Paz and Beni.

Deforestation hotspots (without fires) were concentrated in the soy frontier in the southeast.

 

 

 

 

Graph 4. Deforestation and fire trends in the Bolivian Amazon. Data: UMD.

Peruvian Amazon

Figure 4. Deforestation and fire hotspots in the Peruvian Amazon. Data: UMD.

In 2024, the Peruvian Amazon lost 141,781 hectares (350,341 acres) of primary forest to deforestation. This total marks the 6th highest on record since 2002.

Breaking a record, fires impacted an additional 47,574 hectares (117,554 acres). This total more than doubled the previous high of 2023 (20,042 hectares). As noted above, this fire data may be interpreted as forest degradation, in contrast to the more permanent impacts of deforestation.

Like both Brazil and Bolivia, all of the most intense forest loss hotspots were characterized by intense fires. These fires were concentrated in the central and southeast Amazon (Ucayali and Madre de Dios regions, respectively) (Figure 4).

Deforestation hotspots were concentrated in the gold mining frontier in the southern Amazon and throughout the central Amazon. The very high hotspot in central Peru corresponds to the latest deforestation by Mennonite colonies (see MAAP #222 for context).

 

 

 

 

 

 

 

Graph 5. Deforestation and fire trends in the Peruvian Amazon. Data: UMD

Colombian Amazon

Figure 5. Deforestation and fire hotspots in the Colombian Amazon. Data: UMD.

In 2024, the Colombian Amazon lost 81,396 hectares (201,129 acres) of primary forest to deforestation. This total marked a striking 82.5% increase from the recent low recorded in 2023. It was the 7th highest on record, continuing the trend of elevated forest loss since the FARC peace agreement in 2016 (all top seven deforestation annual totals have occurred since 2016).

Major fires were less of an issue in the Colombian Amazon, but did directly impact an additional 5,184 hectares (8th highest on record).

As described in previous reports (see MAAP #120), Figure 5 shows that there continues to be an “arc of deforestation” in the northwest Colombian Amazon (Caqueta, Meta, Putumayo and Guaviare departments). Most notably, there is a pair of very high deforestation areas surrounding Chiribiquete National Park, and high deforestation areas within Tinigua and Macarena National Parks.

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

 

 

 

 

Graph 6. Deforestation and fire trends in the Colombian Amazon. Data: UMD.

Rest of the Amazon

Other important highlights from around the Amazon include:

Deforestation and fire hotspots in northeast Guyana. In total, Guyana lost 25,858 hectares of primary forest to deforestation, and an additional 38,314 hectares to fires, both of which shattered previous records.

Deforestation in the Venezuelan Amazon was the highest on record (32,240 hectares), and additional fire impacts were the second highest (36,471 hectares).

Deforestation in the Ecuadorian Amazon was the second highest on record (18,615 hectares), just behind 2022 (18,902 hectares). Deforestation hotspots were concentrated in the northern Amazon, areas characterized by high gold mining activity (MAAP #227, MAAP #221, MAAP #219). As in Colombia, major fires were less of an issue in the northwest Amazon overall, but did directly impact an additional 1,540 hectares (4th highest on record).

Fires were the highest on record in Suriname (7,926 ha) and French Guiana (635 ha).

Policy Implications

The dominant policy development of 2024 was the record-breaking fire season across the Amazon. These fire records were not only region-wide but also country-specific, occurring in Brazil, Bolivia, Peru, Guyana, Suriname, and French Guiana.

The 2024 records are particularly significant given that the Amazon has experienced several intense fire years over the past two decades. The most notable, and previous record-breaker, occurred in 2016, following the “Godzilla” El Niño event of 2015-16. However, the extreme drought conditions of 2023 and 2024, also associated with El Niño,  exceeded those past benchmarks, creating extreme conditions for widespread fires across the Amazon.

As a result, fire policy is now emerging as a central pillar of Amazon conservation, alongside longstanding efforts to curb deforestation. This growing prominence is directly related to climate change, both in terms of intensifying dry seasons and the projected increase in the frequency, length, and severity of El Niño events.

These policies must be centered on how to avoid fires in the first place, and then how to effectively respond to major fires once they appear.

Previous research has revealed the tight link between deforestation and fires in the Brazilian Amazon (MAAP #189). That is, many major fires are burning recently deforested areas, and sometimes escape into surrounding forests, especially with extended dry conditions. Therefore, strengthening deforestation control remains one of the most effective fire mitigation strategies in Brazil and other Amazonian countries.

There is also a strong link between deforestation and fire in the Bolivian Amazon. While deforestation often precedes fires, as in Brazil, there is also a second round of deforestation following the fires

In both contexts, real-time fire monitoring, such as the MAAP Fire Tracker,  should be integrated into national response protocols and field-level coordination. 

Beyond fire, high rates of forest loss continue to be driven by deforestation across other parts of the Amazon. In Colombia’s arc of deforestation, we detected very high deforestation around Chiribiquete National Park, as well as high deforestation within Tinigua and Macarena National Parks. Although the national government is engaged on the issue of deforestation, these losses are closely tied to the presence and influence of armed groups in the country, which exert substantial control over land-use and deforestation dynamics (explaining shifts such as the dip in 2023 and the rise again in 2024). The major deforestation drivers in Colombia are roads, land grabbing (and associated cattle pastures), and coca cultivation.

Other high forest loss areas include gold mining fronts in northern Ecuador and southern Peru, Mennonite colonies in central Peru, the soy frontier in southeast Bolivia, and along major existing roads in Brazil. Although there is gold mining in both Venezuela and Guyana, the most intense forest loss hotspots were associated with fires surrounding agricultural areas.

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 absolute numerical differences. 

Annex 1

Annex 1. Forest loss hotspots in relation to fire specific hotspots across the Amazon in 2024. Data: UMD/GLAD, ACA/MAAP.

 

Annex 2

Graph 2b. Amazon primary forest loss for seven countries (except Brazil and Bolivia). Data: UMD

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 was ‘low’ certainty of forest loss due to fire (code 2), and forest loss due to other ‘non-fire’ drivers (code 1).

For the baseline, it was defined to establish areas with >30% tree canopy density in 2000. Importantly, we applied a filter to calculate only primary forest loss by intersecting the forest cover loss data with the additional dataset “primary humid tropical forests” as of 2001 (Turubanova et al 2018). For more details on this part of the methodology, see the Technical Blog from Global Forest Watch (Goldman and Weisse 2019).

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

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

Search Radius: 15000 layer units (meters)
Kernel Density Function: Quartic kernel function
Cell Size in the map: 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).

Acknowledgements

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

We also thank colleagues from the following organizations for helpful comments on the report: Conservación Amazónica – ACEAA in Bolivia, Conservación Amazónica – ACCA in Peru, Fundación EcoCiencia in Ecuador, and Instituto Centro de Vida (ICV) in Brazil.

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

Citation

Finer M, Ariñez A, Mamani N, Cohen M, Santana A (2025) Amazon Deforestation & Fire Hotspots 2024. MAAP: 229.

MAAP #226: AI to detect Amazon gold mining deforestation – 2024 update

Posted on by Matt Finer
Intro Image. Amazon Mining Watch interactive map.

As gold prices continue to increase, small-scale gold mining activity also continues to be one of the major deforestation drivers across the Amazon. 

It often targets remote areas, thus impacting carbon-rich primary forests. Moreover, in many cases, we presume that this mining is illegal based on its location within conservation areas (such as protected areas and Indigenous territories) and outside mining concessions.

Given the vastness of the Amazon, however, it has been a challenge to accurately and regularly monitor mining deforestation across all nine countries of the biome, in order to better inform related policies in a timely manner.

In a previous report (MAAP #212) we presented the initial results of the new AI-based dashboard (known as Amazon Mining Watch) designed to address the issue of gold mining and related policy implications. Amazon Mining Watch (AMW) is a partnership between Earth Genome, the Pulitzer Center’s Rainforest Investigations Network, and Amazon Conservation.

This online tool (see Intro Image) analyzes satellite imagery archives to estimate annual mining deforestation footprints across the entire Amazon, from 2018 to 2024 (Note 1). Although the data is not designed for precise area measurements,  it can be used to give timely estimates needed for management and conservation purposes.  

For example, the cumulative data can be used to estimate and visualize the overall Amazon-wide mining deforestation footprint, and the annual data can be used to identify trends and emerging new mining areas. 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.

The only tool of this kind to be truly regional (Amazon-wide) in coverage, AMW can also help foster regional cooperation, in particular in transfrontier areas where a lack of interoperability between official monitoring systems might hamper interventions.

The Amazon Mining Watch partnership is currently working to enhance the functionality and conservation impact of the dashboard, AMW will be a one-stop shop platform including real-time visualization of: 1) AI-based detection of mining deforestation across all nine Amazonian countries, with quarterly updates; 2) Hotspots of urgent mining cases, including river-based mining; and 3) the socio-environmental costs of illegal gold mining with the Conservation Strategy Fund (CSF) Mining Impacts Calculator.

Here, we present an update focused on the newly added 2024 data and its context within the cumulative dataset (since 2018).

MAJOR FINDINGS

In  the following sections, we highlight several major findings:

  • Gold mining is actively causing deforestation in all nine countries of the Amazon. This impact is concentrated in three major areas: southeast Brazil, the Guyana Shield, and southern Peru. In addition, mining in Ecuador is escalating.
  • The cumulative mining deforestation footprint in 2024 was over 2 million hectares (nearly 5 million acres) and has increased by over 50% in the past six years.
  • Over half of all Amazon mining deforestation occurred in Brazil, followed by Guyana, Suriname, Venezuela, and Peru.
  • While the cumulative footprint continues to grow, the rate of increase slowed in 2023 and 2024 after peaking in 2022, likely due to increased enforcement in Brazil.
  • Over one-third of the mining deforestation has occurred within protected areas and Indigenous territories, where much of it is likely illegal. We highlight the most impacted areas.
  • These results have important policy implications.
Base Map. Mining deforestation footprints, 2018-2024. Data: AMW, Amazon Conservation/MAAP.

Amazon & National Scale Patterns

The Base Map presents the gold mining footprint across the Amazon, as detected by the AMW algorithm. This data serves as our estimate of gold mining deforestation.

Yellow indicates the accumulated mining deforestation footprint for the years 2018- 2023; that is, all areas that the algorithm classified as a mining site vs other types of terrain, such as forest or agriculture. Red indicates the new mining areas detected in 2024.

Three major Amazon gold mining regions stand out: southeast Brazil (between the Tapajos, Xingu, and Tocantis Rivers), Guyana Shield (Venezuela, Guyana, Suriname, and French Guiana), and southern Peru (Madre de Dios).  In addition, Ecuador has emerged as an important mining deforestation front.

 

 

 

 

Graph 1. Amazon mining deforestation footprint. Data: AMW

Graph 1 quantifies the spatial data detected by the AMW algorithm. 

The cumulative mining deforestation footprint in 2024 was 2.02 million hectares (4.99 million acres)

For context, the initial mining deforestation footprint was around 970,000 hectares in 2018, the first year of Amazon Mining Watch data.

Between 2019 and 2024, we estimate that the gold mining deforestation grew by 1.06 million hectares (2.61 million acres).

Thus, over half (52.3%) of the cumulative footprint has occurred in just the past six years.

Note that while the cumulative footprint continues to grow, the rate of increase slowed in 2023 and 2024 after peaking in 2022.

 

 

 

Graph 2 shows that, of the total accumulated mining (2.02 million hectares), over half has occurred in Brazil (55.3%), followed by Guyana (15.4%), Suriname (12.4%), Venezuela (7.3%), and Peru (7.0%).

Graph 2. Gold mining deforestation across the Amazon, by country. Data: AMW, Amazon Conservation/MAAP

Graph 3 digs deeper into the AMW data, revealing additional trends between years. This data highlights the annual changes in detected mining deforestation. Note the trend across the entire Amazon at the top in green for overall context, followed by each country. Note that Brazil (orange line) accounts for much of the annual mining (over 50%).

In 2024, we documented the new gold mining deforestation of 111,603 hectares (275,777 acres). This total represents a decrease of 35% relative to the previous year 2023 and 45% relative to the peak year 2022.

The countries with the highest levels of new gold mining deforestation in 2024 were 1) Brazil (57,240 ha), 2) Guyana (19,372 ha), 3) Suriname (15,323 ha), 4) Venezuela (9,531 ha), and 5) Peru (6,020 ha). However, all five of these countries saw a major decrease in 2024, between 33% (Brazil and Suriname) and 46% (Peru).

Graph 3. Annual changes in new mining deforestation. Data: AMW
Figure 1. Protected areas & Indigenous territories impacted by mining deforestation. Data: AMW, ACA/MAAP.

Protected Areas & Indigenous Territories

We estimate that 36% of the accumulated mining deforestation in 2024 (over 725,000 hectares) occurred within protected areas and Indigenous territories (Figure 1; Note 2), where much of it is likely illegal.

Notably, the vast majority of this overall mining deforestation in protected areas and Indigenous territories has occurred in Brazil (88%).

 

 

 

 

 

 

 

 

 

Figure 2a. Top 10 impacted protected areas & Indigenous territories. Data: AMW, ACA/MAAP.

Figure 2a illustrates the top ten for both protected areas and Indigenous territories, in terms of both accumulated mining deforestation footprint and new mining deforestation in 2024. Figures 2b-d show zooms of the three main mining areas: southeast Brazil (2b), Guyana Shield (2c), and southern Peru (2d).

The top nine most impacted protected areas (in terms of accumulated footprint) are all in Brazil, led by Tapajós Environmental Protection Area. This area has lost over 377,000 hectares, followed by Amanã and Crepori National Forests, Rio Novo National Park, Urupadi, Jamanxim, and Itaituba National Forests, Jamanxim National Park, and Altamira National Forest. The top ten is rounded out by Yapacana National Park in Venezuela.

The three most impacted Indigenous territories are also in Brazil: Kayapó, Mundurucu, and Yanomami. Together, these three territories had a mining footprint of nearly 120,000 hectares. Fourth on the list is Ikabaru in Venezuela, followed by three in southern Peru (San Jose de Karene, Barranco Chico, and Kotsimba) with mining impact of over 17,000 hectares. Rounding out the top ten are Sai Cinza and Trincheira/Bacajá in Brazil, and San Jacinto in Peru.

We also estimate the expansion of over 38,000 hectares of new mining deforestation in protected areas and Indigenous territories in 2024. The protected area with the highest levels of new mining deforestation in 2024 was Tapajós Environmental Protection Area (nearly 19,000 hectares), followed by Amanã and Urupadi National Forests in Brazil, Rio Novo and Jamanxim National Parks in Brazil, Crepori National Forest in Brazil, Campos Amazonicos National Park in Brazil, Yapacan National Park in Venezuela, Guyane Regional Park in French Guiana, and Brownsberg Nature Reserve in Suriname.

Finally, the Indigenous territory with the highest levels of new mining deforestation in 2024 was Kayapó in Brazil (over 2,100 hectares), followed by Ikabaru in Venezuela, Yanomami, Aripuana, and Mundurucu in Brazil, Baramita in Guyana, Kuruáya in Brazil, Isseneru and Kamarang Keng, San Jose de Karene in Peu. It is worth noting that Kayapó, Mundurucu, and Yanomami territories in Brazil all experienced declines in the mining deforestation rate in 2024. For example, Yanomami went from its peak in 2021 to the lowest on record in 2024.

Most impacted areas in eastern Brazilian Amazon

Figure 2b. Most impacted areas in eastern Brazilian Amazon. Data: AMW, Amazon Conservation/MAAP.

Most impacted areas in the Guyana Shield

Figure 2c. Most impacted areas in the Guyana Shield. Data: AMW, Amazon Conservation/MAAP.

Most impacted areas in the southern Peruvian Amazon

Figure 2d. Most impacted areas in the southern Peruvian Amazon. Data: AMW, Amazon Conservation/MAAP.

Conclusion & Policy Implications

Despite a recent downward trend in the rate of gold mining deforestation, the cumulative gold mining deforestation footprint continues to grow across the Amazon.

Our analysis shows that over one-third of this mining occurs within protected areas and Indigenous territories, the vast majority in Brazil. However, since the return of the Lula administration in 2023, Brazil has been ramping up enforcement efforts. This has contributed to the rapid decrease in area lost to mining across the Amazon, given Brazil’s outsized contribution to regional figures. This highlights again the importance of protected areas and Indigenous territories as a crucial policy instrument for the protection of the region’s ecosystems.

Although advances have been made in reducing illegal mining from protected areas in southern Peru, it continues to impact several Indigenous territories (MAAP #208, MAAP #196), particularly those surrounding the government-designated Mining Corridor. In fact, the most affected Indigenous territory in Peru, San Jose de Karene, has already lost over a third of its total area to illegal gold mining.  These territories are part of a regional organization known as FENAMAD, which has been supporting legal actions to help the government make decisions for a rapid response to illicit activities (such as illegal mining) that affect indigenous territories. This process led to five government-led operations between 2022 and 2024, in three communities: Barranco Chico, Kotsimba and San José de Karene (MAAP #208).

In Ecuador, mining deforestation continues to threaten numerous sites, including protected areas and Indigenous territories, along the Andes-Amazon transition zone (MAAP #206, MAAP #221, MAAP #219). An upcoming series of reports will detail these threats.

AMW is an emerging and powerful new tool, but it does have some caveats. One is that any mining activity less than 500 square meters may not be accurately detected. For example, we have been monitoring small-scale mining in several protected areas, such as Madidi National Park in Bolivia and Puinawai National Park in Colombia, that are not yet detected by the algorithm. In these cases, direct real-time monitoring with satellites is still needed. These areas will soon be added to the AMW as mining “Hotspots” (MAAP#197).

This is also the case for river-based mining that does not cause a large footprint on the ground. Imagery with very high resolution has revealed active river barge mining in northern Peru (MAAP #189) and along the Colombia/Brazil border (MAAP#197). These areas will also soon be added to the AMW as mining “Hotspots.”

Gold mining in the Amazon is certain to stay a major issue in the coming years as gold prices continue to skyrocket, reaching over $3,000 an ounce in April 2025, driven by global economic uncertainty. While there are encouraging signs of effective enforcement in Brazil, governments here and across the region will have to compete with this rising financial incentive for mining activities.

Tools such as the Amazon Mining Watch, which will eventually publish quarterly updates of newly detected mining deforestation areas, can help governments, civil society, and local community defenders spot new fronts of gold mining and take action in near real-time. In a feature developed by Conservation Strategy Fund (CSF), it will also evaluate the economic costs of socio-environmental mining damages necessary for communities and managers to declare punitive damages.

The only dashboard of this kind to be fully regional in coverage, the AMW can also help foster regional cooperation, in particular in transfrontier areas where a lack of interoperability between official monitoring systems might hamper interventions that are aimed at combating a phenomenon that is linked to other nature crimes and is mostly controlled by international organized crime. 

In the coming years, the MAAP and AMW teams will continue to publish both quarterly and annual reports of the dynamic mining situation in each country and across the Amazon, in addition to confidential reports directly to governments and community leaders on the most urgent cases.

Notes

1. 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, southeast Colombia, and northwest Brazil; see 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. 

2. 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.

Acknowledgments

We thank colleagues from partner organizations around the Amazon for helpful comments on the report, including: Earth Genome, Conservación Amazónica (ACCA & ACEAA) & Federación Nativa del Río Madre de Dios y Afluentes (FENAMAD), Fundación EcoCiencia, Fundación para la Conservación y el Desarrollo Sostenible (FCDS), and Instituto Centro de Vida (ICV) & Instituto Socioambiental (ISA).

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

MAAP #220: Carbon across the Amazon (part 3): Key Cases of Carbon Loss & Gain

Posted on by dcadmin
Graph 1. The Amazon biome functions as a narrow carbon sink from 2013 to 2022. Data: Planet, ACA/MAAP.

In part 1 of this series (MAAP #215), we introduced a critical new dataset (Planet’s Forest Carbon Diligence) with wall-to-wall estimates for aboveground carbon at an unprecedented 30-meter resolution between 2013 and 2022. This data uniquely merges machine learning, satellite imagery, airborne lasers, and a global biomass dataset from GEDI, a NASA mission.

In part 2 (MAAP #217), we highlighted which parts of the Amazon are currently home to the highest (peak) aboveground carbon levels and the importance of protecting these high-integrity forests (see Annex 1).

Here, in part 3, we focus on aboveground carbon loss and gain across the Amazon over the 10 years for which we have data (2013-22; see Base Map below).

The Amazon loses carbon to the atmosphere due to deforestation, logging, human-caused fires, and natural disturbances, while it gains carbon from forest regeneration and old-growth forests continuing to sequester atmospheric carbon.4

Overall, we find that the Amazon still narrowly functions as a carbon sink (meaning the carbon gain is greater than the loss) during this period, gaining 64.7 million metric tons of aboveground carbon between 2013 and 2022 (see Graph 1).

This finding underscores the importance of both primary and secondary forests in countering widespread deforestation. Moreover, it highlights the critical potential of primary forests to continue accumulating carbon if left undisturbed.

This gain, however, is quite small relative to the total 56.8 billion metric tons of aboveground carbon contained in the Amazon biome (that is, a gain of just +0.1%), reinforcing concerns that the Amazon could flip to a carbon source in the coming years (with carbon loss becoming greater than its gain) due to increasing deforestation, degradation, and fires.1  See Annex 2 for more details, including how the Amazon became a carbon sink following the 2015 drought, but since rebounded.

The countries with the largest carbon gain are 1) Brazil, 2) Colombia, 3) Suriname, 4) Guyana, and 5) French Guiana. In contrast, the countries with the greatest carbon loss are 1) Bolivia, 2) Venezuela, 3) Peru, and 4) Ecuador.

Zooming in to the site level yields additional insights. For example, we can now estimate the carbon loss from major deforestation events across the Amazon from 2013 to 2022. On the flip side, we can also calculate the carbon gain from both secondary and primary forests.

Areas with carbon gain in intact areas indicate excellent candidates for the High Integrity Forest (HIFOR) initiative, a new financing instrument uniquely focused on maintaining intact tropical forests.2 Importantly, a HIFOR unit represents a hectare of high-integrity tropical forest within a high-integrity landscape that has been “well-conserved” for over a decade.3  Intact areas with carbon gain between 2013-22 may indicate decadally “well-conserved” areas that can be overlapped with areas of high ecological integrity.

Below, we illustrate these findings with a series of novel maps zooming in on emblematic cases of large carbon loss and gain across the Amazon from 2013 – 2022. These cases include forest loss driven by agriculture, gold mining, and roads, as well as forest gain in remote primary forests.

Base Map – Amazon Carbon Loss & Gain (2013-2022)

The Base Map shows wall-to-wall estimates of aboveground carbon loss and gain across the Amazon between 2013 and 2022.

Carbon loss is indicated by yellow to red, indicating low to high carbon loss. Carbon gain is indicated by light to dark green, indicating low to high carbon gains.

Below, we present a series of notable cases of high carbon loss and gain indicated in Insets A-I.

Base Map. Areas of major carbon loss and gain across the Amazon between 2013 and 2022. Source: Amazon Conservation/MAAP, Planet.

Emblematic Cases of Carbon Loss & Gain

Figure 1 highlights emblematic cases of carbon loss (Insets A-F in red) and carbon gain (Insets G-I in green). Below we highlight a series of emblematic cases.

Figure 1. Emblematic cases of carbon loss and gain across the Amazon. Source: Amazon Conservation/MAAP, Planet.

Carbon Loss

We can now estimate the carbon loss from major deforestation events across the Amazon during the past ten years, directly from a single dataset. These cases include forest loss from agriculture, gold mining, and roads. Note that the presented values represent just the carbon loss featured in the selected area.

A. Colombia – Arc of Deforestation

Figure 1A. Carbon loss in the Colombian Amazon’s arc of deforestation. Source: Amazon Conservation/MAAP, Planet.

Figure 1A shows the extensive carbon emissions (39.5 million metric tons) associated with the major deforestation within and surrounding protected areas and Indigenous territories in the Colombian Amazon‘s arc of deforestation.

The carbon loss within the protected areas and Indigenous territories is likely from illegal deforestation.

See MAAP #211 for more details.

 

 

 

 

 

 

 

 

 

B. Peru – Mennonite Colonies

Figure 1B. Carbon loss by new Mennonite colonies in the Peruvian Amazon. Source: Amazon Conservation/MAAP, Planet.

Figure 1B shows the carbon emissions of 224,300 metric tons associated with the recent deforestation carried out by new Mennonite colonies arriving in the central Peruvian Amazon starting in 2017.

See MAAP #188 for more details, including information regarding the legality of  the deforestation causing the carbon loss.

 

 

 

 

 

 

 

 

 

 

C. Peru – Gold Mining

Figure 1C. Carbon loss associated with gold mining deforestation in  southern Peruvian Amazon. Source: ACA/MAAP, Planet.

Figure 1C shows the extensive carbon emissions (11.3 million metric tons) associated with gold mining deforestation in the southern Peruvian Amazon.

Most of the carbon loss within the protected areas (and their buffer zones) and Indigenous territories is likely from illegal deforestation.

See MAAP #208 for more information, including details regarding the legality of the deforestation causing the carbon loss.

 

 

 

 

 

 

 

 

 

D. Brazil – Road BR-364

Figure 1D. Carbon loss along BR-364 in the southwest Brazilian Amazon. Source: ACA/MAAP, Planet.

Figure 1D shows the carbon emissions along road BR-364 that crosses the state of Acre in the southwest Brazilian Amazon.

This road was opened in the 1960s and paved in the 1980s.

 

 

 

 

 

 

 

 

 

 

 

E. Brazil – Road BR-319

Figure 1E. Carbon loss along paved roads. Source: ACA/MAAP, Planet.

Figure 1E shows a controversial road paving project that would effectively link the arc of deforestation to the south with more intact forests to the north in Amazonas and Roraima states.

Note that the current carbon loss is concentrated along the paved roads.

The paving of road BR-319 has recently caused headlines as President Luiz Inácio Lula da Silva recently authorized the paving of 20 km of the road and plans to bid for an additional 32 km (thus, paving of 52 km in total).

Modeling studies predict extensive new deforestation from this road construction, and thus additional associated carbon loss.

 

 

 

 

 

 

 

 

F. Brazil – Road BR-163

Figure 1F. Carbon loss along BR-163 in the eastern Brazilian Amazon. Source: ACA/MAAP, Planet.

Figure 1F shows the extensive carbon emissions (71.4 million metric tons) along a recently paved stretch of road BR-163 which crosses the state of Pará in the eastern Brazilian Amazon.

Importantly, this stretch of road has been presented as a case study of what may happen along road BR-319 if it is paved.

 

 

 

 

 

 

 

 

 

 

 

Carbon Gain

We can also calculate the carbon gain from both secondary and primary forests. These cases include forest gain from remote primary forests that may be good candidates for the HIFOR initiative.

Figure 1G. Carbon gains in the southeast Colombian Amazon. Source: ACA/MAAP, Planet.

G. Southeast Colombia

Figure 1G shows the carbon gain of over 52.5 million metric tons in the remote southeast Colombian Amazon.

This area is anchored by three national parks and several large indigenous territories.

 

 

 

 

 

 

 

 

 

 

Figure 1H. Carbon gains along the border of eastern Ecuador and northern Peru. Source: ACA/MAAP, Planet.

H. Ecuador – Peru border

Figure 1H shows the carbon gain of nearly 40 million metric tons along the border in eastern Ecuador and northern Peru.

Note this area is anchored by numerous protected areas, including Yasuni National Park in Ecuador and Pucacuro National Reserve in Peru, and Indigenous territories.

 

 

 

 

 

 

 

 

 

Figure 1I. Carbon gains in the tri-border region of the northeast Amazon. Source: ACA/MAAP, Planet.

I. Northeast Amazon

Figure 1I shows the carbon gain of 164.7 million metric tons in the tri-border region of the northeast Amazon (northern Brazil, French Guiana, and Suriname).

For example, note the carbon gains in Montanhas do Tumucumaque National Park and Tumucumaque Indigenous territory in northeast Brazil.

Also note that this was an Amazonian “peak carbon area,” as described in MAAP #217.

 

 

 

 

 

 

 

 

 

Annex 1

Annex 1. Peak carbon areas in relation to the carbon loss and gain data. Source: Amazon Conservation/MAAP, Planet.

In part 2 of this series (MAAP #217), we highlighted which parts of the Amazon are currently home to the highest (peak) aboveground carbon levels.

Annex 1 shows these peak carbon areas in relation to the carbon loss and gain data presented above.

Note that both peak carbon areas (southeast and northeast Amazon) are largely characterized by carbon gain.

 

 

 

 

 

 

 

 

 

Annex 2

Annex 2. Amazon biome functions as a narrow carbon sink from 2013 to 2022, but became a source in between. Data: Planet, ACA/MAAP.

Annex 2 shows all ten years of aboveground carbon data grouped by two-year intervals (thus, it is an extension of Graph 1 above, adding data for the intermediate years).

In this context, black indicates our baseline of 2013-14, red indicates a decrease from the baseline (carbon source), and green indicates an increase from the baseline (carbon sink).

Importantly, there was a decrease in aboveground carbon from 2015-18, which likely reflects the severe droughts of 2015 and 2016 and subsequent severe fire seasons of 2016 and 2017. Aboveground carbon rebounded from 2019-22.

This trend supports the hypothesis that the Amazon biome is teetering on being an aboveground carbon source vs sink.

It also raises the possibility that the Amazon may return to being a carbon source following the intense drought and fires of 2024.

.

.

Notes

1 In part 1 of this series (MAAP #215), we found the Amazon “is still functioning as a critical carbon sink”. As pointed out in a companion blog by Planet, however, the net carbon sink of +64 million metric tons is quite small relative to the total estimate of 56.8 billion metric tons of aboveground carbon across the Amazon. That is a net positive change of just +0.1%. As the blog notes, that’s a “very small buffer” and there’s “reason to worry that the biome could flip from sink to source with ongoing deforestation.”

2 High Integrity Forest (HIFOR) units are a new, non-offset asset that recognizes and rewards the essential climate services and biodiversity conservation that intact tropical forests provide, including ongoing net removal of CO2 from the atmosphere. HIFOR rewards the climate services that intact tropical forests provide, including ongoing net carbon removal from the atmosphere, and complements existing instruments to reduce emissions from deforestation and degradation (REDD+) by focusing on tropical forests that are largely undegraded. A HIFOR unit represents a hectare of well-conserved, high-integrity tropical forest where ‘well-conserved’ means that high ecological integrity is maintained over a decade of monitoring as part of equitable, effective management of a site and ‘high ecological integrity’ means a score of >9.6 on the Forest Landscape Integrity Index. For more information see https://www.wcs.org/our-work/climate-change/forests-and-climate-change/hifor

3 Two additional important references regarding HIFOR methodology and application:

High Integrity Forest Investment Initiative, Methodology for HIFOR units, April 2024. Downloaded from https://www.wcs.org/our-work/climate-change/forests-and-climate-change/hifor

Forest Landscape Integrity Index metric used by HIFOR: www.forestintegrity.com

4 In Planet’s Forest Carbon Diligence product, carbon loss and gain are detected via changes in canopy cover and canopy height during the given periods (in this case, 2013 vs 2022).

Acknowledgments

Through a generous sharing agreement with the satellite company Planet, we have been granted access to this data across the entire Amazon biome for the analysis presented in this series.

We also thank D. Zarin (WCS) for helpful comments regarding the implications of our findings for the HIFOR initiative.

This report was made possible by the generous support of the Norwegian Agency for Development Cooperation (NORAD)

Citation

Finer M, Mamani N, Anderson C, Rosenthal A (2024) Carbon across the Amazon (part 3): Key Cases of Carbon Loss & Gain. MAAP: 220.

MAAP #222: Mennonite Colonies Continue Major Deforestation in Peruvian Amazon

Posted on by Matt Finer
Base Map. Mennonite Colonies in the Peruvian Amazon. Data: ACA/MAAP.

In a series of reports, we have demonstrated that the Mennonites have become a leading cause of large-scale deforestation in the Peruvian Amazon.

The Mennonites, a global religious group dating back to the 1600s, often require vast tracts of land to support their characteristic industrialized agricultural activity. As such lands have become scarce in other parts of Latin America, new Mennonite colonies began appearing in the Peruvian Amazon as of 2017.

In October 2019, we first reported on the deforestation of 2,500 hectares across three colonies (Masisea, Vanderland, and Osterreich; MAAP #112). A year later, in October 2020, this deforestation increased to 3,440 hectares (MAAP #127).

By the end of 2021, two new colonies (Providencia and Chipiar) had appeared, and the total deforestation had reached 3,968 hectares (MAAP #149).

Deforestation across all five colonies increased to 4,819 hectares by October 2022 (MAAP #166) and 7,032 hectares by August 2023 (MAAP #188).

Here, we update our findings, showing that deforestation across all five colonies has increased to 8,660 hectares (21,400 acres), as of October 2024.

Below, we illustrate the increase in Mennonite deforestation over the past eight years and show the pattern in each colony with satellite images.

In addition, there is mounting evidence that this massive deforestation is illegal, with numerous ongoing investigations by the Peruvian government (see the Legal Summary, below).

 

 

Graph 1. Deforestation caused by Mennonites in the Peruvian Amazon from 2019 to 2024. Data: ACA/MAAP.

The increasing deforestation of the Mennonites in Peru

 

Graph 1 illustrates the rapid increase in Mennonite deforestation in the Peruvian Amazon, from zero in 2017 to over 8,660 hectares in 2024.

It is the clearest evidence yet that authorities need a more effective strategy to avoid continued escalating deforestation.

 

 

 

 

 

 

Deforestation in Mennonite Colonies (Peruvian Amazon)

Chipiar Colony

Figure 1. Deforestation in the Chipiar Mennonite colony. Data: ACA/MAAP, Planet.

This colony is located on both sides of the border between the departments of Ucayali and Loreto, originating in the district of Padre Marquez on the Loreto side.

It is the newest colony, where deforestation began in 2020.

This deforestation escalated in 2021, peaked in 2022, and continues to expand in 2023 in 2024.

We document the deforestation of 2,708 hectares in the Chipiar colony since 2020.

 

 

 

 

 

 

 

 

 

Vanderland, Osterreich & Providencia Colonies

Figure 2. Deforestation in the Vanderland, Osterreich & Providencia Mennonite colonies. Data: ACA/MAAP, Planet.

These three colonies are located near the town of Tierra Blanca, in the Loreto region.

We have documented the deforestation of 4,824 hectares since 2017.

 

 

 

 

 

 

 

 

 

 

 

 

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Masisea Colony

Figure 3. Deforestation in the Masisea Mennonite colony. Data: ACA/MAAP, Planet.

This colony, located in the Ucayali region, was the first to be established in Peru (2017) and was occupied by settlers who arrived from Bolivia.

Deforestation of 963 hectares has been documented in the Masisea colony since 2017.

Deforestation was most intense between 2017 and 2019, with a small expansion between 2022 and 2024.

 

 

 

 

 

 

 

 

 

 

 

 

Legal Summary

MAAP #188 details the legal actions taken by the Peruvian government. The Specialized Prosecutor’s Office for Environmental Matters (FEMA in Spanish) is conducting ongoing investigations against all five Mennonite colonies.

In addition, National Forestry and Wildlife Service (SERFOR in Spanish) has received five complaints for deforestation activities without authorizations for clearing, which have been referred to the competent entities.

Likewise, through a judicial process, before the Second Criminal Appeals Chamber of the Superior Court of Justice of Ucayali, it ratified the suspension of predatory deforestation and logging activities by the colony in July 2023.

Since August 2024, the Regional Forestry and Wildlife Management of Ucayali – GERFFS, especially the Illegal Logging Directorate, has been coordinating prioritization actions for this case with other competent actors such as the Specialized Prosecutor’s Office for Environmental Matters – FEMA and the National Police of Peru – PNP.

 

Citation

Finer M, Mamani N, Ariñez A (2024) Mennonite Colonies Continue Major Deforestation in Peruvian Amazon. MAAP: 222.

MAAP #217: Carbon across the Amazon (part 2): Peak Carbon Areas

Posted on by dcadmin
Figure 1. Example of peak carbon areas in southern Peru and adjacent western Brazil. Data: Planet.

In part 1 of this series (MAAP #215), we introduced a critical new resource (Planet Forest Carbon Diligence) that provides wall-to-wall estimates for aboveground carbon density at an unprecedented 30-meter resolution. This data uniquely merges machine learning, satellite imagery, airborne lasers, and a global biomass dataset from GEDI, a NASA mission.4

In that report, we showed that the Amazon contains 56.8 billion metric tons of aboveground carbon (as of 2022), and described key patterns across all nine countries of the Amazon biome over the past decade.

Here, in part 2, we focus on the peak carbon areas of the Amazon that are home to the highest aboveground carbon levels.

These peak carbon areas correspond to the upper one-third of aboveground carbon density levels (>140 metric tons per hectare).1

They likely have experienced minimal degradation (such as selective logging, fire, and edge/fragmentation effects)2 and are thus a good proxy for high-integrity forests.

Figure 1 shows an important example of peak carbon areas in southern Peru and adjacent western Brazil.

The peak carbon areas are often found in the remote primary forests of protected areas and Indigenous territories, but some are located in forestry concessions (specifically, logging concessions) or undesignated lands (also referred to as undesignated public forests).

Our goal in this report is to leverage unprecedented aboveground carbon data to reinforce the importance of these designated areas and draw attention to the remaining undesignated lands.

For example, peak carbon areas would be excellent candidates for the High Integrity Forest (HIFOR) initiative, a new financing instrument that uniquely focuses on maintaining intact tropical forests.3 HIFOR rewards the climate services that intact tropical forests provide, including ongoing net carbon removal from the atmosphere, and complements existing instruments to reduce emissions from deforestation and degradation (REDD+) by focusing on tropical forests that are largely undegraded.

Below, we detail the major findings and then zoom in on the peak carbon areas in the northeast and southwest Amazon.

Peak Carbon Areas in the Amazon   

The Base Map below illustrates our major findings.

The peak carbon areas (>140 metric tons per hectare; indicated in pink) are concentrated in the southwest and northeast Amazon, covering 27.8 million hectares (11 million ha in the southwest and 16.8 million ha in the northeast).
k

Base Map. Planet Forest Carbon Diligence across the Amazon biome for the year 2022. Data: Planet.

In the southwest Amazon, peak carbon levels are found in southern & central Peru, and adjacent western Brazil.

In the northeast Amazon, peak carbon levels are found in northeast Brazil, much of French Guiana, and parts of Suriname.

By country, Brazil and Peru have the largest area of peak carbon (10.9 million and 10.1 million hectares respectively), followed by French Guiana (4.7 million ha), and Suriname (2.1 million ha).

Protected areas and Indigenous territories cover much (61%) of the peak carbon area (16.9 million hectares).

The remaining 39% remains unprotected, and arguably threatened, in undesignated lands (9.4 million hectares) and forestry concessions (1.5 million ha), respectively.

In addition, high carbon areas (>70 metric tons per hectare; indicated by the greenish-yellow coloration in the Base Map) are found in all nine countries of the Amazon biome, notably Colombia, Ecuador, Bolivia, Venezuela, and Guyana.

Southwest Amazon

­Southern Peru

Figure 2a. Peak carbon area in the southern Peruvian Amazon. Data: Planet, SERNANP, RAISG.

Figure 2a zooms in on the peak carbon area covering 7.9 million hectares in southern Peru (regions of Madre de Dios, Cusco, and Ucayali) and adjacent southwest Brazil (Acre).

Several protected areas (such as Manu and Alto Purús National Parks, and Machiguenga Communal Reserve) anchor this area.

It is also home to numerous Indigenous territories (such as Mashco Piro, Madre de Dios, and Kugapakori, Nahua, Nanti & Others Indigenous Reserves).

 

 

 

 

 

 

 

 

 

 

Figure 2b highlights the major land designations within the peak carbon area of southern Peru.

Figure 2b. Peak carbon areas (outlined in pink), categorized by land designation in southern Peru and adjacent western Brazil. Data: Planet, NICFI, SERNANP, SERFOR, RAISG.

Protected areas and Indigenous territories cover 77% of this area (green and brown, respectively).

The remaining 23% could be considered threatened, as they are located in forestry concessions or undesignated lands (orange and red, respectively). Thus, these areas are ideal candidates for increased protection to maintain their peak carbon levels.

 

 

 

 

 

 

 

 

 

 

 

Central Peru

Figure 3a. Peak carbon area in the central Peruvian Amazon. Data: Planet, SERNANP, RAISG.

Figure 3a zooms in on the peak carbon area in the central Peruvian Amazon, which covers 3.1 million hectares in the regions of Ucayali, Loreto, Huánuco, Pasco, and San Martin.

Several protected areas (including Sierra del Divisor, Cordillera Azul, Rio Abiseo, and Yanachaga–Chemillén National Parks, and El Sira Communal Reserve) anchor this area.

It is also home to numerous Indigenous territories (such as Kakataibo, Isconahua, and Yavarí Tapiche Indigenous Reserves).

 

 

 

 

 

 

 

 

 

 

Figure 3b. Peak carbon areas (outlined in pink), categorized by land designation in central Peru. Data: Planet, NICFI, SERNANP, SERFOR, RAISG.

Figure 3b highlights the major land designations within the peak carbon area of central Peru.

Protected areas and Indigenous territories cover 69% of this area (green and brown, respectively).

The remaining 31% could be considered threatened, as they are located in forestry concessions or undesignated lands (orange and red, respectively), and are ideal candidates for increased protection.

 

 

 

 

 

 

 

 

 

 

 

 

 

Northeast Amazon

Figure 4a. Peak carbon area in the tri-border region of the northeast Amazon. Data: Planet, RAISG.

Figure 4a zooms in on the peak carbon area in the tri-border region of the northeast Amazon, which covers 16.8 million hectares in northern Brazil, French Guiana, and Suriname.

Several protected areas (including Montanhas do Tumucumaque National Park in northeast Brazil, Amazonien de Guyane National Park in French Guiana, and Central Suriname Nature Reserve) anchor this area.

It is also home to numerous Indigenous territories (such as Tumucumaque, Rio Paru de Este, and Wayãpi in northeast Brazil).

 

 

 

 

 

 

Figure 4b. Peak carbon areas (outlined in pink), categorized by land designation in northeast Amazon. Data: Planet, NICFI, RAISG.

Figure 4b highlights the major land designations within the peak carbon area of the northeast Amazon.

Protected areas and Indigenous territories cover just over half (51%) of this area (green and brown, respectively).

The remaining 49% could be considered threatened, as they are located in undesignated lands, and are ideal candidates for increased protection.

 

 

 

 

 

 

 

 

 

Notes

1 We selected this value (upper 33%) to capture the highest aboveground carbon areas and include a range of high carbon areas. Additional analyses could target different values, such as the highest 10% or 20% of aboveground carbon.

2  A recent paper documented a strong relationship between selective logging and aboveground carbon loss (Csillik et al. 2024, PNAS). The link between forest edges and carbon is presented in Silva Junior et al, Science Advances.

3 High Integrity Forest (HIFOR) units are a new tradable asset that recognizes and rewards the essential climate services and biodiversity conservation that intact tropical forests provide, including ongoing net removal of CO2 from the atmosphere. For more information see https://www.wcs.org/our-work/climate-change/forests-and-climate-change/hifor

4 For more information, see the “What is Forest Carbon Diligence?” section in this recent blog from Planet.

Citation

Finer M, Mamani N, Anderson C, Rosenthal A (2024) Carbon across the Amazon (part 2): Peak Carbon Areas. MAAP #217.

Acknowledgments

This report was made possible by the generous support of the Norwegian Agency for Development Cooperation (NORAD)

MAAP #218: Killing of Environmental Defenders in the Peruvian Amazon

Posted on by dcadmin

 

Peruvian environmental defender Edwin Chota was murdered by illegal loggers in 2014 for attempting to protect his Indigenous community from Exploitation. See Illegal Logging section. Photo: NYT/Tomas Munita.

 

 

 

 

 

 

 

 

 

 

 

 

 

Amazon Conservation’s MAAP program specializes in reporting on the most urgent deforestation threats facing the Amazon and producing big-picture analyses of key Amazon-wide issues.

This report uniquely presents a view into the complicated but critical issue of murders of environmental defenders, examining the relationship between the location of these killings and deforestation in the Peruvian Amazon to provide a better understanding of the context of their deaths.

Between 2010 and 2022, an estimated 29 Peruvian environmentalists and Indigenous leaders were killed while defending various parts of Peru’s Amazon from invaders seeking to exploit its resources (RAISG 2022).

Importantly, the frequency of these murders has increased in recent years, with nearly half (14 out of 29) occurring since 2020.

Our findings indicate that these murders are connected to five major issues in the Peruvian Amazon:
Illegal gold mining, Illegal logging, Illicit crops (coca), Land trafficking, and Protesting.

This report focuses on the first three (Illegal gold mining, Illegal logging, and Illicit crops).

Base Map

Base Map. Location of the 29 environmental defenders murdered in Peru and the suspected causes related to major environmental threats in the region 2010-2022. Sources: IBC, MINJUS, SERNANP, Conservación Amazónica-ACCA.

The Base Map shows the location of the 29 documented environmental defenders killed in Peru between 2010-2022.

It also indicates the environmental threat related to each death as the suspected or confirmed motive for the crime: Illegal Gold Mining, Illegal Logging, Illicit Crops (coca), Land Trafficking, and Protest.

Note that many of the murders occurred in geographic clusters that coincide with the major environmental conflict of that specific area.

For example, gold mining is a major cause of conflict in the southern Peruvian Amazon, while illegal logging and illicit crops are more common threats in the central Peruvian Amazon.

Murders related to Illegal Gold Mining

Illegal gold mining has long been, and continues to be, a major issue in the southern Peruvian Amazon (Madre de Dios region), particularly in Indigenous territories and protected area buffer zones (MAAP#208).

For example, Figure 1 illustrates the extensive gold mining deforestation (indicated in orange) in the Tambopata National Reserve buffer zone and surrounding Indigenous territories.

Figure 1. Three cases of environmental defender deaths related to illegal mining. Sources: IBC, MINJUS, SERNANP, Conservación Amazónica-ACCA.

Since 2015, three environmental defenders have been killed within or near the Tambopata National Reserve buffer zone (see yellow dots in Figure 1). All three cases involved forestry concessionaires trying to defend their concession from illegal mining invasion.

In 2015, Alfredo Vracko Neuenschwander was killed near the critical mining area known as “La Pampa” located in the core of the buffer zone. Note that during the two years prior to his death, more than 1,700 hectares were deforested in La Pampa due to illegal gold mining (MAAP #1). Vracko, who was president of the Madre de Dios Federation of Forestry and Reforestation Concessionaires at the time, is believed to have been killed by illegal miners who were scheduled to be evicted from his forestry concession on the same day. However, his murder remains officially unsolved.

In 2020, Roberto Carlos Pacheco Villanueva was killed just outside the Tambopata buffer zone. Villanueva owned a forestry concession that had been illegally deforested and burned by invaders linked to illegal mining. Having filed legal complaints about the illegal use of his land, Villanueva faced numerous threats against his life in the years leading up to his murder. While still unsolved, it is believed that his murder was committed by the same miners who invaded his concession.

More recently, in 2022, Juan Julio Fernández Hanco was murdered just off the Interoceanic Highway near the edge of the Tambopata buffer zone. During this period (2021-2023), nearly 24,000 hectares were deforested due to gold mining in this area (MAAP #195). The investigation is ongoing, with the suspects being illegal miners who invaded Juan Julio’s reforestation concessions.

Murders related to Illegal Logging

Illegal logging has been a significant problem across the Peruvian Amazon for years. A recent report revealed that over 20% of timber harvested in Peru in 2021 came from illegal origins (OSINFOR, 2024). Loreto, Madre de Dios, Amazonas, and Ucayali were identified as the regions with the highest levels of unauthorized timber extraction.

Figure 2. Four environmental defender deaths related to illegal logging. Sources: IBC, MINJUS, DEVIDA, SERNANP, ACCA.

In 2014, illegal loggers murdered four men from the community of Alto Tamaya-Saweto, in one of the most well-known murder cases of Peruvian environmental defenders. These defenders (Edwin Chota Valera, Francisco Pinedo Ramírez, Jorge Ríos Pérez, and Leoncio Quintisima Meléndez) were killed along the Peru-Brazil border (see orange dots in Figure 2), following a decade of complaints from Chota about the presence of criminal logging groups in their community. Ten years later, in April 2024, a group of loggers were found guilty of the murders and sentenced to nearly 30 years in prison. This case has since been appealed with the expectation of going to Peru’s supreme court.

Murders related to Illicit Crops (Coca)

Official data indicates that the surface area of coca production in Peru continues to increase, particularly in the central Peruvian Amazon along the Andes Mountains (in the regions of Ucayali and Huánuco). Since 2010, ten environmental defenders have been killed in this area related to their fight against coca-related activities (see red dots in Figure 3).

Figure 3. Ten cases of environmental defender deaths related to illegal coca production. Sources: IBC, MINJUS, DEVIDA, SERNANP, Conservación Amazónica-ACCA.

Three environmental defenders (Santiago Vega Chota, Yenes Ríos Bonsano, and Herasmo García Grau) were killed in 2020 and 2021 within or near their communities of Sinchi Roca and Puerto Nuevo in the region of Ucayali, following their attempts to monitor their communities’ territories for coca production. Both communities are located within a coca production zone known as Aguaytía, which experienced a 158% increase in coca cultivation between 2018 and 2022 (DEVIDA 2022).

Between 2010 and 2020, four environmental defenders (Segundo José Reategui, Manuel Tapullima, Justo Gonzales Sangama, and Arbildo Melendez) were murdered in or near the Unipacuyacu Indigenous community. These four deaths have been linked to illegal coca production by outsiders on community lands that have not yet been officially titled by the government, which has facilitated these invasions. Unipacuyacu is located within the Pichis-Palcazu-Pachitea coca production zone spanning the Huánuco and Pasco regions, where coca cultivation increased by more than 450% between 2018 and 2022 (DEVIDA 2022).

Finally, three other environmental defenders (Jesús Berti Antaihua Quispe, Gemerson Pizango Narvaes, and Nusat Parisada Benavides de la Cruz) were killed in 2022 in their communities of Santa Teresa and Cleyton. These two indigenous communities are located within and just outside of the in an area outside of the El Sira Communal Reserve buffer zone. During the four years leading up to their deaths, coca production in El Sira and its buffer zone increased by over 500% (DEVIDA 2022). While unconfirmed, it is believed that these murders were committed by mafias tied to drug trafficking and illegal mining.

Regulatory Basis

Peru ranks among the countries with the highest number of environmental defender deaths worldwide (Global Witness 2023).

Peru’s National Plan for Human Rights 2018-2021, defines an environmental defender as someone who: As an individual or collective, carries out a legitimate activity, paid or not, consisting of demanding and promoting, within the legally permitted framework, in a peaceful and nonviolent manner, the effectiveness of violated rights. Their efforts are usually manifested publicly through demands and raised through regular process channels, conforming with the framework devoted to these fundamental rights.

To address the vulnerability of environmental defenders, the Peruvian government, specifically the Ministry of Justice and Human Rights (MINJUSDH), has developed regulations to ensure their protection. The most important of these are:

Regulation Title Importance
 

Supreme Decree N 002-2018-JUS

  

National Plan for Human Rights 2018-2021

 Establishes that environmental defenders are a group of special protection and requests that the state adopts measures to protect them.
 

Supreme Decree 004-2021-JUS

  

Intersectoral Mechanism for the Protection of Human Rights Defenders

 Establishes the principles, measures, and proceedings to guarantee the prevention, protection, and access to justice for human rights defenders prior to risk situations, being the highest ranking standard in the country.
 

Ministerial Resolution 255-2020-JUS

  

Registry on Risk Situations for Human Rights Defenders

 

 Recognizes, analyzes, and manages information about the risks that human rights defenders face, and adopts actions to prevent threats.

 

Peru has also taken an intersectoral approach by coordinating participation among eight ministries: Ministry of Justice and Human Rights, Ministry of the Interior, Ministry of the Environment, Ministry of Culture, Ministry of Woman and Vulnerable Populations, Ministry of External Relations, Ministry of Energy and Mines, and Ministry of Agriculture and Irrigation Development. A public implementing agency, the National Commission for Development and Life Without Drugs (DEVIDA), also cooperates with this effort.

Despite these efforts, defenders continue to face criminalization, legal harassment, and threats of violence and murder. This shows the urgent need to strengthen their protection and institutional support in Peru.

In response, the Peruvian Congress has recently enacted three new laws to further protect human rights defenders. These include (i) Bill 4686/2022-CR, a law that recognizes and protects defenders of environmental rights, and (ii) Bill 2069/2021-PE, a law for the protection and assistance of communal and/or Indigenous or native leaders at risk. Moving forward, how the ongoing Alto Tamaya-Saweto case proceeds through Peru’s Supreme Court will be crucial to future efforts to protect environmental and human rights defenders.

References

Comisión Nacional Para El Desarrollo y Vida Sin Drogas (DEVIDA). 2023. Perú: Monitoreo de cultivos de coca 2022.

Global Witness 2023. Casi 2.000 personas defensoras de la tierra y el medioambiente asesinadas entre 2012 y 2022 por proteger el planeta.

Organismo de Supervisión de los Recursos Forestales y de Fauna Silvestre (OSINFOR). 2024. Estimación del índice y porcentaje de tala y comercio ilegal de madera en el Perú 2021.

Red Amazónica de Información Socioambiental Georreferenciada (RAISG). 2022. Presiones, amenazas y violencia en la Amazonía peruana.

Acknowledgments

This report was prepared with support from the Instituto de Bien Común (IBC).

Citation

Montoya M, Bonilla A, Novoa S, Tipula P, Salisbury D, Quispe M, Finer M, Folhadella A, Cohen M (2024) Killing of Environmental Defenders in the Peruvian Amazon. MAAP:218.

MAAP #215: Unprecedented Look at Carbon across the Amazon (part 1)

Posted on by dcadmin
Figure 1. Example of Planet Forest Carbon Diligence, focused on southern Peru and adjacent western Brazil.

The Amazon biome has long been one of the world’s largest carbon sinks, helping stabilize the global climate.

Precisely estimating this carbon, however, has been a challenge. Fortunately, new satellite-based technologies are providing major advances, most notably NASA’s GEDI mission (see MAAP #213) and, most recently, Planet Forest Carbon Diligence.1

Here, we focus on the latter, analyzing Planet’s cutting-edge new dataset, featuring a 10-year historical time series (2013 – 2022) with wall-to-wall estimates for aboveground carbon density at 30-meter resolution.

As a result, we can produce high-resolution aboveground carbon maps and estimates for anywhere and everywhere across the vast Amazon (see Figure 1).

Through a generous sharing agreement with Planet, we have been granted access to this data across the entire Amazon biome for the analysis presented in the following three-part series:

  1. Estimate and illustrate total aboveground forest carbon across the Amazon biome in unprecedented detail (see results of this first report, below).
    j
  2. Highlight which parts of the Amazon are home to the highest aboveground carbon levels, including protected areas and Indigenous territories (see second report, MAAP #217).
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  3. Present emblematic deforestation cases that have resulted in the highest aboveground carbon emissions across the Amazon (see third report, MAAP #220).

Major Results

Carbon across the Amazon

Based on our analysis of Planet Forest Carbon Diligence, we estimate that the Amazon contained 56.8 billion metric tons of aboveground carbon, as of 2022 (see Base Map). Applying a standard root-to-shoot ratio conversion (26%), this estimate increases to 71.5 billion metric tons of above and belowground carbon. This total is equivalent to nearly two years of global carbon dioxide emissions at the peak 2022 level (37.15 billion metric tons).5

The peak carbon levels are largely concentrated in the southwest Amazon (southern Peru and adjacent western Brazil) and northeast Amazon (northeast Brazil, French Guiana, and Suriname).

Base Map. Planet Forest Carbon Diligence across the Amazon biome.

Total Carbon by Country

As shown in Graph 1, countries with the most aboveground carbon are 1) Brazil (57%; 32.1 billion metric tons), 2) Peru (15%; 8.3 billion metric tons), 3) Colombia (7%; 4 billion metric tons), 4) Venezuela (6%; 3.3 billion metric tons), and 5) Bolivia (6%; 3.2 billion metric tons). These countries are followed by Guyana (3%; 2 billion metric tons), Suriname (3%; 1.6 billion metric tons), Ecuador (2%; 1.2 billion metric tons), and French Guiana (2%; 1.1 billion metric tons).

Overall, we documented the total gain of 64.7 million metric tons of aboveground carbon across the Amazon during the ten years between 2013 and 2022.2 In other words, the Amazon is still functioning as a critical carbon sink.

The countries with the most aboveground carbon gain over the past ten years are 1) Brazil, 2) Colombia, 3) Suriname, 4) Guyana, and 5) French Guiana. Note that we show Brazil as a carbon sink (gain of 102.8 million metric tons), despite other recent studies showing it as a carbon source.3 Also note the important gains in aboveground carbon across several key High Forest cover, Low Deforestation (HFLD) countries, namely Colombia, Suriname, Guyana, and French Guiana.4

In contrast, the countries with the most aboveground carbon loss over the past ten years are 1) Bolivia, 2) Venezuela, 3) Peru, and 4) Ecuador.

Graph 1. Planet Forest Carbon Diligence data across the Amazon biome, comparing 2013-14 with 2021-22. Note that a “+” symbol indicates that the country gained aboveground carbon, while a “-“ symbol indicates that the country lost aboveground carbon.

Carbon Density by Country

Standardizing for area, Graph 2 shows that countries with the highest aboveground carbon density (that is, aboveground carbon per hectare as of 2021-22) are located in the northeast Amazon: French Guiana (134 metric tons/hectare), Suriname (122 metric tons/hectare), and Guyana (85 metric tons/hectare). Ecuador is also high (94 metric tons/hectare).

Note that countries in the northeast Amazon (French Guiana, Suriname, and Guyana) have lower total aboveground carbon due to their smaller size (Graph 1), but high aboveground carbon density per hectare (Graph 2). This also applies to Ecuador.

Graph 2. Planet Forest Carbon Diligence data for aboveground carbon density by country across the Amazon, comparing 2013-14 with 2021-22. Note that a “+” symbol indicates that the country gained aboveground carbon, while a “-“ symbol indicates that the country lost aboveground carbon.

Notes & Citations

1 Anderson C (2024) Forest Carbon Diligence: Breaking Down The Validation And Intercomparison Report. https://www.planet.com/pulse/forest-carbon-diligence-breaking-down-the-validation-and-intercomparison-report/

2 In terms of uncertainty, the data contains pixel-level estimates, but not yet at national levels. To minimize annual uncertainty at the country level, we averaged 2013 and 2014 for the baseline and 2021 and 2022 for the current state.

3 Recently, in MAAP #144, we showed Brazil as a carbon source, based on data from 2001 to 2020. In contrast, Planet Forest Carbon Diligence is based on data from 2013 to 2022. Thus, one interpretation of the difference is that most carbon loss occurred in the first decade of the 2000s, which is consistent with historical deforestation data showing peaks in the early 2000s. It also highlights the likely importance of the interplay between forest loss/degradation (carbon loss) and forest regeneration (carbon gain) in terms of whether a country is a carbon source or sink during a given timeframe.

4 HFDL, or “High Forest cover, Low Deforestation” describes countries with both a) high forest cover (>50%) and low deforestation rates (<0.22% per year). For more information on HFDL, see https://www.conservation.org/blog/what-on-earth-is-hfld-hint-its-about-forests

5 Annual carbon dioxide (CO₂) emissions worldwide from 1940 to 2023

Citation

Finer M, Mamani N, Anderson C, Rosenthal A (2024) Unprecedented Look at Carbon across the Amazon. MAAP  #215.

Acknowledgments

This report was made possible by the generous support of the Norwegian Agency for Development Cooperation (NORAD)

 

MAAP #214: Agriculture in the Amazon: New data reveals key patterns of crops & cattle pasture

Posted on by dcadmin
Figure 1. Agricultural and pasture data in a section of the Brazilian Amazon.

A burst of new data and online visualization tools are revealing key land use patterns across the Amazon, particularly regarding the critical topic of agriculture. This type of data is particularly important because agriculture is the leading cause of overall Amazonian deforestation.

These new datasets include:

  • Crops. The International Food Policy Research Institute (IFPRI), a leading agriculture and food systems research authority, recently launched the latest version of their innovative crop monitoring product, the Spatial Production Allocation Model (SPAM).1 This latest version, developed with support from WRI’s Land & Carbon Lab, features spatial data for 46 crops, including soybean, oil palm, coffee, and cocoa. This data is mapped at 10-kilometer resolution across the Amazon and updated through 2020.2
    j
  • Cattle pasture. The Atlas of Pastures,3 developed by the Federal University of Goiás, facilitates access to data regarding Brazilian cattle pastures generated by MapBiomas. This data is mapped at 30-kilometer resolution and updated through 2022. We use Collection 5 from Mapbiomas for the rest of the Amazonian countries.4
    j
  • Gold mining. New mining data is included for additional context. Amazon Mining Watch uses machine learning to map open-pit gold mining.5 This data is mapped at 10-kilometer resolution across the Amazon and updated through 2023.

We merged and analyzed these new datasets to provide our first overall estimate of Amazonian land use, the most detailed effort to date across all nine countries of the biome. Figure 1 shows an example of this merged data in a section of the Brazilian Amazon.

Below, we present and illustrate the following major findings across the Amazon, and then zoom in on several regions across the Amazon to show the data in greater detail.

Major Findings

The Base Map illustrates several major findings detailed below.

Base Map. Overview of the merged datasets noted above for crops, pasture, and gold mining. Double-click to enlarge. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

1) Crops
We found that 40 crops in the SPAM dataset overlap with the Amazon, covering over 106 million hectares (13% of the Amazon biome).

Soybean covers over 67.5 million hectares, mostly in southern Brazil and Bolivia. Maize covers slightly more area (70 million hectares) but we consider this a secondary rotational crop with soy (thus, there is considerable overlap between these two crops).

Oil palm covers nearly 8 million hectares, concentrated in eastern Brazil, central Peru, northern Ecuador, and northern Colombia.

In the Andean Amazon zones of Peru, Ecuador, and Colombia, cocoa covers over 8 million hectares and the two types of coffee (Arabica and Robusta) cover 6.7 million hectares.

Other major crops across the Amazon include rice (13.8 million hectares), sorghum (10.9 million hectares), cassava (9.8 million hectares), sugarcane (9.6 million hectares), and wheat (5.8 million hectares).

2) Cattle Pasture
Cattle Pasture covers 76.3 million hectares (9% of the Amazon biome). The vast majority (92%) of the pasture is in Brazil, followed by Colombia and Bolivia.

3) Crops & Cattle Pasture
Overall, accounting for overlaps between the data, we estimate that crops and pasture combined cover 115.8 million hectares. This total is the equivalent of 19% of the Amazon biome.

In comparison, open-pit gold mining covered 1.9 million hectares (0.23% of the Amazon biome).

Zooms across the Amazon

Eastern Brazilian Amazon

Figure 2 shows the transition from the soy frontier to the cattle pasture frontier in the eastern Brazilian Amazon. Also note a mix of other crops, such as oil palm, sugarcane, and cassava, and some gold mining.

Figure 2. Eastern Brazilian Amazon. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

Andean Amazon (Peru and Ecuador)

Figure 3. Andean Amazon. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

The land use patterns are quite different in the Andean Amazon regions of Peru and Ecuador.

Figure 3 shows, that instead of soy and cattle pasture, there is instead oil palm, rice, coffee, and cocoa.

Also note the extension of the cattle pasture frontier in the western Brazilian Amazon, towards Peru and Bolivia.

 

 

 

 

 

 

 

 

 

 

 

 

Northeast Amazon (Venezuela, Guyana, Suriname, French Guiana)

Figure 4 shows the general lack of crops in the core Amazon regions Guyana, Suriname, and French Guiana, which is surely a major factor they are all considered High Forest cover, Low Deforestation countries (HFLD). In contrast, note there is abundant gold mining activity throughout this region.

Figure 4. Northeastern Amazon. Data: IFRI/SPAM, Lapig/UFG, Mapbiomas, AMW, ACA/MAAP.

Methods

For the SPAM data, we used the physical area, which is measured in a hectare and represents the actual area where a crop is grown (not counting how often production was harvested from it). We only considered values ​​greater than or equal to 100 ha per pixel.

For the Base Map, due to their importance as primary economic crops, we layered soybean and oil palm as the top two layers, respectively. From there, crops were layered in order of their total physical area across the Amazon. Thus, the full extensions of some crops are not shown if they overlap pixels with other crops that have greater physical area. For overlaps with crops and pasture, we favored the crops.

Notes & Data Sources

1 International Food Policy Research Institute (IFPRI), 2024, “Global Spatially-Disaggregated Crop Production Statistics Data for 2020 Version 1.0” https://doi.org/10.7910/DVN/SWPENT, Harvard Dataverse, V1

Spatial Production Allocation Model (SPAM)
SPAM 2020 v1.0 Global data (Updated 2024-04-16)

2 Note that the spatial resolution is rather low (10-kilometers) so all crop coverage data above should be interpreted as referential only.

3 The Atlas of Pastures (Atlas das Pastagens), open to the public, was developed by the Image Processing and Geoprocessing Laboratory of the Federal University of Goiás (Lapig/UFG), to facilitate access to results and products generated within the MapBiomas initiative, regarding Brazilian pastures.

https://atlasdaspastagens.ufg.br/

4 MapBiomas Collection 5;  https://amazonia.mapbiomas.org/en/

5 See MAAP #212 for more information on Amazon Mining Watch.

Citation

Finer M, Ariñez A (2024) Agriculture in the Amazon: New data reveals key patterns of crops & cattle pasture. MAAP: 214.