GEOG 30N
Environment and Society in a Changing World

case study on deforestation in amazon forest

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Case Study: The Amazon Rainforest

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The Amazon in context

Tropical rainforests are often considered to be the “cradles of biodiversity.” Though they cover only about 6% of the Earth’s land surface, they are home to over 50% of global biodiversity. Rainforests also take in massive amounts of carbon dioxide and release oxygen through photosynthesis, which has also given them the nickname “lungs of the planet.” They also store very large amounts of carbon, and so cutting and burning their biomass contributes to global climate change. Many modern medicines are derived from rainforest plants, and several very important food crops originated in the rainforest, including bananas, mangos, chocolate, coffee, and sugar cane.

Aerial view of the Amazon tributary

In order to qualify as a tropical rainforest, an area must receive over 250 centimeters of rainfall each year and have an average temperature above 24 degrees centigrade, as well as never experience frosts. The Amazon rainforest in South America is the largest in the world. The second largest is the Congo in central Africa, and other important rainforests can be found in Central America, the Caribbean, and Southeast Asia. Brazil contains about 40% of the world’s remaining tropical rainforest. Its rainforest covers an area of land about 2/3 the size of the continental United States.

There are countless reasons, both anthropocentric and ecocentric, to value rainforests. But they are one of the most threatened types of ecosystems in the world today. It’s somewhat difficult to estimate how quickly rainforests are being cut down, but estimates range from between 50,000 and 170,000 square kilometers per year. Even the most conservative estimates project that if we keep cutting down rainforests as we are today, within about 100 years there will be none left.

How does a rainforest work?

Rainforests are incredibly complex ecosystems, but understanding a few basics about their ecology will help us understand why clear-cutting and fragmentation are such destructive activities for rainforest biodiversity.

trees in the tropical rain forest

High biodiversity in tropical rainforests means that the interrelationships between organisms are very complex. A single tree may house more than 40 different ant species, each of which has a different ecological function and may alter the habitat in distinct and important ways. Ecologists debate about whether systems that have high biodiversity are stable and resilient, like a spider web composed of many strong individual strands, or fragile, like a house of cards. Both metaphors are likely appropriate in some cases. One thing we can be certain of is that it is very difficult in a rainforest system, as in most other ecosystems, to affect just one type of organism. Also, clear cutting one small area may damage hundreds or thousands of established species interactions that reach beyond the cleared area.

Pollination is a challenge for rainforest trees because there are so many different species, unlike forests in the temperate regions that are often dominated by less than a dozen tree species. One solution is for individual trees to grow close together, making pollination simpler, but this can make that species vulnerable to extinction if the one area where it lives is clear cut. Another strategy is to develop a mutualistic relationship with a long-distance pollinator, like a specific bee or hummingbird species. These pollinators develop mental maps of where each tree of a particular species is located and then travel between them on a sort of “trap-line” that allows trees to pollinate each other. One problem is that if a forest is fragmented then these trap-line connections can be disrupted, and so trees can fail to be pollinated and reproduce even if they haven’t been cut.

The quality of rainforest soils is perhaps the most surprising aspect of their ecology. We might expect a lush rainforest to grow from incredibly rich, fertile soils, but actually, the opposite is true. While some rainforest soils that are derived from volcanic ash or from river deposits can be quite fertile, generally rainforest soils are very poor in nutrients and organic matter. Rainforests hold most of their nutrients in their live vegetation, not in the soil. Their soils do not maintain nutrients very well either, which means that existing nutrients quickly “leech” out, being carried away by water as it percolates through the soil. Also, soils in rainforests tend to be acidic, which means that it’s difficult for plants to access even the few existing nutrients. The section on slash and burn agriculture in the previous module describes some of the challenges that farmers face when they attempt to grow crops on tropical rainforest soils, but perhaps the most important lesson is that once a rainforest is cut down and cleared away, very little fertility is left to help a forest regrow.

What is driving deforestation in the Amazon?

Many factors contribute to tropical deforestation, but consider this typical set of circumstances and processes that result in rapid and unsustainable rates of deforestation. This story fits well with the historical experience of Brazil and other countries with territory in the Amazon Basin.

Population growth and poverty encourage poor farmers to clear new areas of rainforest, and their efforts are further exacerbated by government policies that permit landless peasants to establish legal title to land that they have cleared.

At the same time, international lending institutions like the World Bank provide money to the national government for large-scale projects like mining, construction of dams, new roads, and other infrastructure that directly reduces the forest or makes it easier for farmers to access new areas to clear.

The activities most often encouraging new road development are timber harvesting and mining. Loggers cut out the best timber for domestic use or export, and in the process knock over many other less valuable trees. Those trees are eventually cleared and used for wood pulp, or burned, and the area is converted into cattle pastures. After a few years, the vegetation is sufficiently degraded to make it not profitable to raise cattle, and the land is sold to poor farmers seeking out a subsistence living.

Regardless of how poor farmers get their land, they often are only able to gain a few years of decent crop yields before the poor quality of the soil overwhelms their efforts, and then they are forced to move on to another plot of land. Small-scale farmers also hunt for meat in the remaining fragmented forest areas, which reduces the biodiversity in those areas as well.

Another important factor not mentioned in the scenario above is the clearing of rainforest for industrial agriculture plantations of bananas, pineapples, and sugar cane. These crops are primarily grown for export, and so an additional driver to consider is consumer demand for these crops in countries like the United States.

These cycles of land use, which are driven by poverty and population growth as well as government policies, have led to the rapid loss of tropical rainforests. What is lost in many cases is not simply biodiversity, but also valuable renewable resources that could sustain many generations of humans to come. Efforts to protect rainforests and other areas of high biodiversity is the topic of the next section.

Deforestation, warming flip part of Amazon forest from carbon sink to source

  • July 14, 2021
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The study area, which represents about 20 percent of the Amazon basin, has lost 30 percent of its rainforest

New results from a nine-year research project in the eastern Amazon rainforest finds that significant deforestation in eastern and southeastern Brazil has been associated with a long-term decrease in rainfall and increase in temperature during the dry season, turning what was once a forest that absorbed carbon dioxide into a source of planet-warming carbon dioxide emissions.

The study, published in the journal Nature , explored whether these changes had altered how much carbon the Amazon stored in its vast forests. 

“Using nearly 10 years of CO 2   (carbon dioxide ) measurements, we found that the more deforested and climate-stressed eastern Amazon, especially the southeast, was a net emitter of CO 2 to the atmosphere, especially as a result of fires,” said John Miller, a scientist with NOAA’s Global Monitoring Laboratory and a co-author. “On the other hand, the wetter, more intact western and central Amazon, was neither a carbon sink nor source of atmospheric CO 2 , with the absorption by healthy forests balancing the emissions from fires.”   

In addition to storing vast amounts of carbon, Amazonia is also one of the wettest places on Earth, storing immense amounts of water in its soils and vegetation. Transpired by leaves, this moisture evaporates into the atmosphere, where it fuels prodigious rainfall, averaging more than seven feet per year across the basin. For comparison the average annual rainfall in the contiguous U.S. is two and half feet. Several studies have estimated that water cycling through evaporation is responsible for 25 to 35 percent of total rainfall in the basin. 

But deforestation and global warming over the last 40 years have affected rainfall and temperature with potential impacts for the Amazon’s ability to store carbon. Conversion of rainforest to agriculture has caused a 17 percent decrease in forest extent in the Amazon, which stretches over an area almost as large as the continental U.S.. Replacing dense, humid forest canopies with drier pastures and cropland has increased local temperatures and decreased evaporation of water from the rainforest, which deprives downwind locations of rainfall. Regional deforestation and selective logging of adjacent forests further reduces forest cover, amplifying the cycle of drying and warming.  This, in turn, can reduce the capacity of the forests to store carbon,  and increase their vulnerability to fires.

The  2.8 million square miles of jungle in the Amazon basin represents more than half of the tropical rainforest remaining on the planet. The Amazon is estimated to contain about 123 billion tons of carbon above and below ground, and is one of Earth’s most important terrestrial carbon reserves. As global fossil-fuel burning has risen, the Amazon has absorbed CO 2 from the atmosphere, helping to moderate global climate.  But there are indications from this study and previous ones that the Amazon’s capacity to act as a sink may be disappearing.

Over the past several decades, intense scientific interest has focused on the question of whether the combined effects of climate change and the ongoing conversion of jungle to pasture and cropland could cause the Amazon to release more carbon dioxide than it absorbs. 

In 2010, lead author Luciana Gatti, who led the international team of scientists from Brazil, the United Kingdom, New Zealand and the Netherlands, set out to explore this question. During the next nine years, Gatti, a scientist with Brazil’s National Institute for Space Research and colleagues obtained airborne measurements of CO 2  and carbon monoxide concentrations above Brazilian Amazonia. Analysis of CO 2 measurements from over 600 aircraft vertical profiles, extending from the surface to around 2.8 miles above sea level at four sites, revealed that total carbon emissions in eastern Amazonia are greater than those in the west. 

“The regions of southern Pará and northern Mato Grosso states represent a worst-case scenario,” said Gatti. 

The southeast region, which represents about 20 percent of the Amazon basin, and has experienced 30 percent deforestation over the previous 40 years. Scientists recorded a 25 percent reduction in precipitation and a temperature increase of at least 2.7 degrees Fahrenheit during the dry months of August, September and October, when trees are already under seasonal stress. Airborne measurements over nine years revealed this region was a net emitter of carbon, mainly as a result of fires, while areas further west, where less than 20 percent of the forest had been removed, sources balanced sinks. The scientists said the increased emissions were likely due to conversion of forest to cropland by burning, and by reduced uptake of CO 2 by the trees that remained. 

These findings help scientists better understand the long-term impacts of interactions between climate and human disturbances on the carbon balance of the world’s largest tropical forest.

“The big question this research raises is if the connection between climate, deforestation, and carbon that we see in the eastern Amazon could one day be the fate of the central and western Amazon, if they become subject to stronger human impact,” Miller said.  Changes in the capacity of tropical forests to absorb carbon will require downward adjustments of the fossil fuel emissions compatible with limiting global mean temperature increases to less than 2.0 or 1.5 degrees Celsius, he added.

This research was supported by NOAA’s Global Monitoring Laboratory and by funding from the State of Sao Paulo Science Foundation, UK Environmental Research Council, NASA, and the European Research Council. 

For more information, contact Theo Stein, NOAA Communications: [email protected]

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Deforestation and Forest Degradation in the Amazon - Status and trends up to year 2021

  • August 2022
  • Report number: EUR 31180 EN
  • Affiliation: European Commission

René Beuchle at European Commission

  • European Commission

Achard Frédéric at European Commission

  • Commission Joint Research Center, Ispra

Abstract and Figures

Forest disturbances in the Pan-Amazon humid forest from 2002-2021. The geographic basis are the areas of "Amazonia Sensu Stricto" and "Guiana", according to Eva and Huber [2]. GFC statistics appear as grey dashed line. The stars (2019/2020) indicate that the distribution of the two classes within the yearly overall forest disturbances is an "educated guess" while the black bar for 2021 indicates that a separation of disturbance classes is not yet possible.

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UConn Today

September 7, 2021 | Combined Reports - UConn Communications

Study Shows the Impacts of Deforestation and Forest Burning on Biodiversity in the Amazon

Since 2001, between 40,000 and 73,400 square miles of Amazon rainforest have been impacted by fires

Ring of fire: Smoke rises through the understory of a forest in the Amazon region. Plants and animals in the Amazonian rainforest evolved largely without fire, so they lack the adaptations necessary to cope with it.

Ring of fire: Smoke rises through the understory of a forest in the Amazon region. Plants and animals in the Amazonian rainforest evolved largely without fire, so they lack the adaptations necessary to cope with it. (Credit: Paulo Brando)

A new study, co-authored by a team of researchers including UConn Ecology and Evolutionary Biology researcher Cory Merow provides the first quantitative assessment of how environmental policies on deforestation, along with forest fires and drought, have impacted the diversity of plants and animals in the Amazon. The findings were published in the Sept. 1 issue of Nature .

Researchers used records of more than 14,500 plant and vertebrate species to create biodiversity maps of the Amazon region. Overlaying the maps with historical and current observations of forest fires and deforestation over the last two decades allowed the team to quantify the cumulative impacts on the region’s species.

They found that since 2001, between 40,000 and 73,400 square miles of Amazon rainforest have been impacted by fires, affecting 95% of all Amazonian species and as many as 85% of species that are listed as threatened in this region. While forest management policies enacted in Brazil during the mid-2000s slowed the rate of habitat destruction, relaxed enforcement of these policies coinciding with a change in government in 2019 has seemingly begun to reverse this trend, the authors write. With fires impacting 1,640 to 4,000 square miles of forest, 2019 stands out as one of the most extreme years for biodiversity impacts since 2009, when regulations limiting deforestation were enforced.

“Perhaps most compelling is the role that public pressure played in curbing forest loss in 2019,” Merow says. “When the Brazilian government stopped enforced forest regulations in 2019, each month between January and August 2019 was the worse month on record (e.g. comparing January 2019 to previous January’s) for forest loss in the 20-year history of available data. However, based on international pressure, forest regulation resumed in September 2019, and forest loss declined significantly for the rest of the year, resulting in 2019 looking like an average year compared to the 20-year history.  This was big: active media coverage and public support for policy changes were effective at curbing biodiversity loss on a very rapid time scale.”

The findings are especially critical in light of the fact that at no point in time did the Amazon get a break from those increasing impacts, which would have allowed for some recovery, says senior study author Brian Enquist, a professor in UArizona’s Department of Ecology and Evolutionary Biology .

“Even with policies in place, which you can think of as a brake slowing the rate of deforestation, it’s like a car that keeps moving forward, just at a slower speed,” Enquist says. “But in 2019, it’s like the foot was let off the brake, causing it to accelerate again.”

Known mostly for its dense rainforests, the Amazon basin supports around 40% of the world’s remaining tropical forests. It is of global importance as a provider of ecosystem services such as scrubbing and storing carbon from the atmosphere, and it plays a vital role in regulating Earth’s climate. The area also is an enormous reservoir of the planet’s biodiversity, providing habitats for one out of every 10 of the planet’s known species. It has been estimated that in the Amazon, 1,000 tree species can populate an area smaller than a half square mile.

“Fire is not a part of the natural cycle in the rainforest,” says study co-author Crystal N. H. McMichael at the University of Amsterdam. “Native species lack the adaptations that would allow them to cope with it, unlike the forest communities in temperate areas. Repeated burning can cause massive changes in species composition and likely devastating consequences for the entire ecosystem.”

Since the 1960s, the Amazon has lost about 20% of its forest cover to deforestation and fires. While fires and deforestation often go hand in hand, that has not always been the case, Enquist says. As climate change brings more frequent and more severe drought conditions to the region, and fire is often used to clear large areas of rainforest for the agricultural industry, deforestation has spillover effects by increasing the chances of wildfires. Forest loss is predicted reach 21 to 40% by 2050, and such habitat loss will have large impacts on the region’s biodiversity, according to the authors.

“Since the majority of fires in the Amazon are intentionally set by people, preventing them is largely within our control,” says study co-author Patrick Roehrdanz, senior manager of climate change and biodiversity at Conservation International. “One way is to recommit to strong antideforestation policies in Brazil, combined with incentives for a forest economy, and replicate them in other Amazonian countries.”

Policies to protect Amazonian biodiversity should include the formal recognition of Indigenous lands, which encompass more than one-third of the Amazon region, the authors write, pointing to previous research showing that lands owned, used or occupied by Indigenous peoples have less species decline, less pollution and better-managed natural resources.

The authors say their study underscores the dangers of continuing lax policy enforcement. As fires encroach on the heart of the Amazon basin, where biodiversity is greatest, their impacts will have more dire effects, even if the rate of forest burning remains unchanged.

The research was made possible by strategic investment funds allocated by the Arizona Institutes for Resilience at UArizona and the university’s Bridging Biodiversity and Conservation Science group. Additional support came from the National Science Foundation’s Harnessing the Data Revolution program . Data and computation were provided through the Botanical Information and Ecology Network , which is supported by CyVerse , the NSF’s data management platform led by UArizona.

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Amazon Deforestation and Climate Change

Join Gisele Bundchen when she meets with one of Brazil’s top climate scientists to discuss the complexity of the Amazon rainforest and its connection to Earth’s atmosphere.

Anthropology, Geography

High on a tower overlooking the lush Amazon canopy, Gisele Bundchen and Brazilian climate scientist Antonio Nobre talk about the importance of the rainforest and the impact of cutting down its trees.

As Nobre explains, the rainforest is not only home to an incredible diversity of species, it also has a critical cooling effect on the planet because its trees channel heat high into the atmosphere. In addition, forests absorb and store carbon dioxide (CO 2 ) from the atmosphere—CO 2 that is released back into the atmosphere when trees are cut and burned.

Nobre warns that if deforestation continues at current levels, we are headed for disaster. The Amazon region could become drier and drier, unable to support healthy habitats or croplands.

Find more of this story in the “Fueling the Fire” episode of the National Geographic Channel’s Years of Living Dangerously series.

Transcript (English)

- Growing up in Southern Brazil, my five sisters and I ate meat pretty much every day. It's just part of the culture here. Per capita, Brazilians are one of the top consumers of beef on the planet. Now, with the world's growing appetite for beef, Brazil has also become a major exporter and is aiming to increase its market share, partly by selling to the US, the world's biggest consumer of beef, and to China, where demand for beef has grown 25% in just 10 years. I understand the need to develop and grow, but does that have to come at the expense of the rainforest and the climate? The Amazon Rainforest is about the same size as the continental United States. One-fifth of the world's fresh water runs through it, and it is home to more species of animals and plants than anywhere on Earth. The Amazon represents more than half of the remaining rainforests on the planet. This forest is so vast, but it is not indestructible. To find out what's at stake, I'm going to talk to one of Brazil's top climate scientist, Dr. Antonio Nobre. So Antonio, tell us a little bit about this amazing green carpet of heaven over here.

- Well, most people don't have the opportunity to come from the top of the forest. If you see all this many shades of green as you see here, it's because biodiversity is the essence of this type of forest. Every species of trees has thousands of species of bugs, and also if you get a leaf of one of the species, and you look to the microbes that is sitting on the top of leaf, you find millions of species, millions, and this is all below our radar screen, so to speak, because we don't realize, it's invisible. And the trees are shooting water from the ground, groundwater up high in the sky, and this goes up into the atmosphere and releases the heat out there, and this radiates to space. And this is very important as a mechanism to cool the planet. They're like air conditioners. Open air conditioning, that's what the forest is.

- So in other words, if we lose all these trees, we are losing the air conditioning that cools off the whole planet.

- Not only that.

- Not only that?

- No. The trees are soaking up carbon, you know the pollution that we produce, like carbon dioxide? Yeah, yeah, yeah.

- Burning gasoline in our cars, you release carbon dioxide in the air, or burning coal, and the trees use carbon dioxide as a raw material.

- So the trees are storing all this carbon, so if you come and cut it down and burn it out, does that mean that all that carbon goes up in the air?

- Absolutely. Yeah.

- What would happen if this forest was gone?

- When the forest is destroyed, climate changes, and then forest that's left is damaged as well. And then the forest grows drier and drier and eventually catch fire. So in the extreme, the whole area becomes a desert. And that's what is in store if we deforest. So we have to quit deforestation yesterday, not 2020 or '30. And there is no plan C. You know, you have plan A. Plan A is business as usual. Keep plundering with all the resources and using as if it were infinite. Plan B is what many people are attempting, changing the matrix of energy and using clean sources, stop eating too much meat, and replanting forests If that doesn't work, then we go to plan C. What's plan C? I have no idea.

- Going to another planet.

- But we can't do that.

- We don't have another planet, so either we work with plan B or we're-

- Basically, yeah. We're done, and so plan B has to work. It has to work.

- People have to take accountability, 'cause it can't just be like, I'm leaving over here and whatever happens over there, who cares?

- It's not my problem.

- It's not my problem, because it is everyone's problem.

- Yes. People should wake up. It's like when you're in the midst of an unfolding disaster, what do you do? You panic? No. You move it. Move, move, move, move. That's what we need to do.

Transcripción (Español)

- El año en que vivimos en peligro.

- Cuando era niña en el sur de Brasil, mis cinco hermanas y yo comíamos carne casi todos los días. Es parte de la cultura aquí. Per cápita, los brasileños son uno de los mayores consumidores de carne de res en el planeta. Ahora, con el creciente apetito mundial por la carne de res, Brasil también se ha convertido en un importante exportador y está buscando aumentar su participación en el mercado, en parte vendiendo a los Estados Unidos, el mayor consumidor de carne de res del mundo, y a China, donde la demanda de carne de res ha crecido un 25 % en tan solo 10 años. Entiendo la necesidad de desarrollarse y crecer, pero ¿tiene que ser a expensas de la selva tropical y el clima? La selva amazónica tiene casi el mismo tamaño que los Estados Unidos continentales. Una quinta parte del agua dulce del mundo fluye a través de ella. Y es hogar de más especies de animales y plantas que cualquier otro lugar en la Tierra. El Amazonas representa más de la mitad de las selvas tropicales restantes en el planeta. Estado Mato Grosso, Brasil Esta selva es tan vasta, pero no es indestructible. Para descubrir lo que está en juego, voy a hablar con uno de los principales científicos climáticos de Brasil, el Dr. Antonio Nobre. Antonio, cuéntanos un poco acerca de esta increíble alfombra verde de cielo que tenemos aquí.

- Bueno, la mayoría de las personas no tienen la oportunidad de venir hasta la cima de la selva. Si ves todos los diferentes tonos de verde como estos aquí, es porque la biodiversidad es la esencia de este tipo de selva. Cada especie de árboles tiene miles de especies de insectos, y también si tomas una hoja de una de las especies, y miras a los microbios en la parte superior de la hoja, encuentras millones de especies, millones, y todo esto queda por debajo de nuestro radar, porque no nos damos cuenta, es invisible. Y los árboles están extrayendo agua del subsuelo, hasta lo alto en el cielo, y esto sube a la atmósfera y libera el calor allí, y esto se irradia al espacio. Este es un mecanismo muy importante para enfriar el planeta. Son como aires acondicionados. Aire acondicionado al aire libre, eso es el bosque.

- En otras palabras, si perdemos todos estos árboles, estamos perdiendo el aire acondicionado que enfría todo el planeta.

- No solo eso.

- ¿No solo eso?

- No. Los árboles están absorbiendo carbono, ¿la contaminación que producimos, como el dióxido de carbono?

- Al quemar gasolina en los autos, se libera dióxido de carbono al aire, o quemando carbón, y los árboles usan el dióxido de carbono como materia prima.

- Entonces los árboles están almacenando todo este carbono, así que si lo cortas y lo quemas, ¿eso significa que todo ese carbono sube al aire?

- Absolutamente. Sí.

- ¿Qué pasaría si este bosque desapareciera?

- Cuando el bosque es destruido, el clima cambia, y luego el bosque que queda también se daña. Luego el bosque se vuelve cada vez más seco y eventualmente se incendia. En caso extremo, toda el área se convierte en un desierto. Eso es lo que nos espera si deforestamos. Así que tenemos que dejar de deforestar desde ayer, no en 2020 o 2030. No hay un plan C. Tienes un plan A. El plan A es seguir como siempre. Continuar saqueando todos los recursos y usarlos como si fueran infinitos. El plan B es lo que muchos están intentando, cambiar la matriz de energía y usar fuentes limpias, dejar de comer demasiada carne y reforestar bosques. Si eso no funciona, entonces pasamos al plan C. ¿Cuál es el plan C?

- No tengo idea.

- Ir a otro planeta.

- Pero no podemos hacer eso.

- No tenemos otro planeta, así que o trabajamos con el plan B o estamos-

- Acabados.

- Básicamente, sí. Estamos acabados, así que el plan B tiene que funcionar. Tiene que funcionar.

- Las personas deben asumir responsabilidad, porque no puedes nada más pensar, yo vivo aquí y lo que suceda por allá, ¿a quién le importa?

- A mí qué.

- No es mi problema, porque es un problema de todos.

- Sí. La gente debería despertar. Es como cuando estás en medio de un desastre en desarrollo, ¿qué haces? ¿Entrar en pánico? No. Lo mueves. Que se mueva. Eso es lo que necesitamos hacer.

The Amazon rain forest absorbs one-fourth of the CO2 absorbed by all the land on Earth. The amount absorbed today, however, is 30% less than it was in the 1990s because of deforestation. A major motive for deforestation is cattle ranching. China, the United States, and other countries have created a consumer demand for beef, so clearing land for cattle ranching can be profitable—even if it’s illegal. The demand for pastureland, as well as cropland for food such as soybeans, makes it difficult to protect forest resources.

Many countries are making progress in the effort to stop deforestation. Countries in South America and Southeast Asia, as well as China, have taken steps that have helped reduce greenhouse gas emissions from the destruction of forests by one-fourth over the past 15 years.

Brazil continues to make impressive strides in reducing its impact on climate change. In the past two decades, its CO2 emissions have dropped more than any other country. Destruction of the rain forest in Brazil has decreased from about 19,943 square kilometers (7,700 square miles) per year in the late 1990s to about 5,180 square kilometers (2,000 square miles) per year now. Moving forward, the major challenge will be fighting illegal deforestation.

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  • Published: 01 September 2021

How deregulation, drought and increasing fire impact Amazonian biodiversity

  • Xiao Feng   ORCID: orcid.org/0000-0003-4638-3927 1   na1 ,
  • Cory Merow 2   na1 ,
  • Zhihua Liu   ORCID: orcid.org/0000-0002-0086-5659 3   na1 ,
  • Daniel S. Park   ORCID: orcid.org/0000-0003-2783-530X 4 , 5   na1 ,
  • Patrick R. Roehrdanz   ORCID: orcid.org/0000-0003-4047-5011 6   na1 ,
  • Brian Maitner   ORCID: orcid.org/0000-0002-2118-9880 2   na1 ,
  • Erica A. Newman 7 , 8   na1 ,
  • Brad L. Boyle 7 , 9 ,
  • Aaron Lien 8 , 10 ,
  • Joseph R. Burger 7 , 8 , 11 ,
  • Mathias M. Pires 12 ,
  • Paulo M. Brando   ORCID: orcid.org/0000-0001-8952-7025 13 , 14 , 15 ,
  • Mark B. Bush   ORCID: orcid.org/0000-0001-6894-8613 16 ,
  • Crystal N. H. McMichael   ORCID: orcid.org/0000-0002-1064-1499 17 ,
  • Danilo M. Neves 18 ,
  • Efthymios I. Nikolopoulos 19 ,
  • Scott R. Saleska 7 ,
  • Lee Hannah 6 ,
  • David D. Breshears   ORCID: orcid.org/0000-0001-6601-0058 10 ,
  • Tom P. Evans   ORCID: orcid.org/0000-0003-4591-1011 20 ,
  • José R. Soto 10 ,
  • Kacey C. Ernst 21 &
  • Brian J. Enquist 7 , 22   na1  

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  • Biodiversity
  • Biogeography

Biodiversity contributes to the ecological and climatic stability of the Amazon Basin 1 , 2 , but is increasingly threatened by deforestation and fire 3 , 4 . Here we quantify these impacts over the past two decades using remote-sensing estimates of fire and deforestation and comprehensive range estimates of 11,514 plant species and 3,079 vertebrate species in the Amazon. Deforestation has led to large amounts of habitat loss, and fires further exacerbate this already substantial impact on Amazonian biodiversity. Since 2001, 103,079–189,755 km 2 of Amazon rainforest has been impacted by fires, potentially impacting the ranges of 77.3–85.2% of species that are listed as threatened in this region 5 . The impacts of fire on the ranges of species in Amazonia could be as high as 64%, and greater impacts are typically associated with species that have restricted ranges. We find close associations between forest policy, fire-impacted forest area and their potential impacts on biodiversity. In Brazil, forest policies that were initiated in the mid-2000s corresponded to reduced rates of burning. However, relaxed enforcement of these policies in 2019 has seemingly begun to reverse this trend: approximately 4,253–10,343 km 2 of forest has been impacted by fire, leading to some of the most severe potential impacts on biodiversity since 2009. These results highlight the critical role of policy enforcement in the preservation of biodiversity in the Amazon.

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Data availability.

The plant occurrences from the BIEN database are accessible using the RBIEN package ( https://github.com/bmaitner/RBIEN ). The climatic data are accessible from http://worldclim.org and the soil data are available from http://soilgrids.org . MODIS active fire and burned area products are available at http://modis-fire.umd.edu . The MODIS Vegetation Continuous Fields data are publicly available from https://lpdaac.usgs.gov/products/mod44bv006/ . The annual forest loss layers are available from http://earthenginepartners.appspot.com/science-2013-global-forest . The plant range maps are accessible at https://github.com/shandongfx/paper_Amazon_biodiversity_2021 . The vertebrate range maps are available from https://www.iucnredlist.org/resources/spatial-data-download . The SPEI data are available from SPEI Global Drought Monitor ( https://spei.csic.es/map ).

Code availability

The code to process the remote-sensing data is available at https://github.com/shandongfx/paper_Amazon_biodiversity_2021 .

Yachi, S. & Loreau, M. Biodiversity and ecosystem productivity in a fluctuating environment: the insurance hypothesis. Proc. Natl Acad. Sci. USA 96 , 1463–1468 (1999).

Article   ADS   CAS   PubMed   PubMed Central   Google Scholar  

Oliver, T. H. et al. Biodiversity and resilience of ecosystem functions. Trends Ecol. Evol. 30 , 673–684 (2015).

Article   PubMed   Google Scholar  

Barlow, J., Berenguer, E., Carmenta, R. & França, F. Clarifying Amazonia’s burning crisis. Glob. Change Biol. 9 , 1 (2019).

Google Scholar  

Brando, P. M. et al. The gathering firestorm in southern Amazonia. Sci. Adv. 6 , eaay1632 (2020).

IUCN. IUCN Red List of Threatened Species version 6.2 . https://www.iucnredlist.org/ (2019).

Flores, M. et al. WWF’s Living Amazon Initiative (Grambs Corporación Gráfica, 2010).

Hubbell, S. P. et al. How many tree species are there in the Amazon and how many of them will go extinct? Proc. Natl Acad. Sci. USA 105 Suppl. 1 , 11498–11504 (2008).

Nepstad, D. C., Stickler, C. M., Filho, B. S.- & Merry, F. Interactions among Amazon land use, forests and climate: prospects for a near-term forest tipping point. Philos. Trans. R. Soc. Lond. B 363 , 1737–1746 (2008).

Article   Google Scholar  

Rankin-de-Mérona, J. M. et al. Preliminary results of a large-scale tree inventory of upland rain forest in the Central Amazon. Acta Amazon. 22 , 493–534 (1992).

Sakschewski, B. et al. Resilience of Amazon forests emerges from plant trait diversity. Nat. Clim. Change 6 , 1032–1036 (2016).

Article   ADS   Google Scholar  

Poorter, L. et al. Biomass resilience of Neotropical secondary forests. Nature 530 , 211–214 (2016).

Article   ADS   CAS   PubMed   Google Scholar  

Beisner, B. E., Haydon, D. T. & Cuddington, K. Alternative stable states in ecology. Front. Ecol. Environ. 1 , 376–382 (2003).

Lovejoy, T. E. & Nobre, C. Amazon tipping point. Sci. Adv. 4 , eaat2340 (2018).

Article   ADS   PubMed   PubMed Central   Google Scholar  

Veldman, J. W. Clarifying the confusion: old-growth savannahs and tropical ecosystem degradation. Philos. Trans. R. Soc. Lond. B 371 , (2016).

Arruda, D., Candido, H. G. & Fonseca, R. Amazon fires threaten Brazil’s agribusiness. Science 365 , 1387 (2019).

Article   ADS   PubMed   CAS   Google Scholar  

Ter Steege, H. et al. Estimating the global conservation status of more than 15,000 Amazonian tree species. Sci. Adv. 1 , e1500936 (2015).

Gomes, V. H. F., Vieira, I. C. G., Salomão, R. P. & ter Steege, H. Amazonian tree species threatened by deforestation and climate change. Nat. Clim. Change 9 , 547–553 (2019).

Brando, P. et al. Amazon wildfires: scenes from a foreseeable disaster. Flora 268 , 151609 (2020).

Balch, J. K. et al. The susceptibility of southeastern Amazon forests to fire: insights from a large-scale burn experiment. Bioscience 65 , 893–905 (2015).

Barlow, J. et al. The critical importance of considering fire in REDD+ programs. Biol. Conserv. 154 , 1–8 (2012).

Cochrane, M. A. & Schulze, M. D. Fire as a recurrent event in tropical forests of the eastern Amazon: effects on forest structure, biomass, and species composition. Biotropica 31 , 2–16 (1999).

Brando, P. M. et al. Prolonged tropical forest degradation due to compounding disturbances: Implications for CO 2 and H 2 O fluxes. Glob. Change Biol. 25 , 2855–2868 (2019).

Barlow, J. & Peres, C. A. Fire-mediated dieback and compositional cascade in an Amazonian forest. Philos. Trans. R. Soc. Lond. B 363 , 1787–1794 (2008).

Cochrane, M. Tropical Fire Ecology: Climate Change, Land Use and Ecosystem Dynamics (Springer, 2010).

Uhl, C. & Kauffman, J. B. Deforestation, fire susceptibility, and potential tree responses to fire in the eastern Amazon. Ecology 71 , 437–449 (1990).

Cochrane, M. A. Fire science for rainforests. Nature 421 , 913–919 (2003).

Cochrane, M. A. & Laurance, W. F. Synergisms among fire, land use, and climate change in the Amazon. Ambio 37 , 522–527 (2008).

Nepstad, D. C. et al. Large-scale impoverishment of Amazonian forests by logging and fire. Nature 398 , 505–508 (1999).

Article   ADS   CAS   Google Scholar  

Aragão, L. E. O. C. et al. 21st Century drought-related fires counteract the decline of Amazon deforestation carbon emissions. Nat. Commun. 9 , 536 (2018).

Article   ADS   PubMed   PubMed Central   CAS   Google Scholar  

Nepstad, D. et al. Slowing Amazon deforestation through public policy and interventions in beef and soy supply chains. Science 344 , 1118–1123 (2014).

Hope, M. The Brazilian development agenda driving Amazon devastation. Lancet Planet. Health 3 , e409–e411 (2019).

Brown, J. H. On the relationship between abundance and distribution of species. Am. Nat. 124 , 255–279 (1984).

Barnagaud, J.-Y. et al. Ecological traits influence the phylogenetic structure of bird species co-occurrences worldwide. Ecol. Lett. 17 , 811–820 (2014).

Šímová, I. et al. Spatial patterns and climate relationships of major plant traits in the New World differ between woody and herbaceous species. J. Biogeogr. 45 , 895–916 (2018).

Enquist, B. J. et al. The commonness of rarity: Global and future distribution of rarity across land plants. Sci. Adv. 5 , eaaz0414 (2019).

May, P. H., Gebara, M. F., de Barcellos, L. M., Rizek, M. B. & Millikan, B. The Context of REDD+ in Brazil: Drivers, Agents, and Institutions, 3rd edition, https://doi.org/10.17528/cifor/006338 (Center for International Forestry Research, 2016).

Neves, D. M., Dexter, K. G., Baker, T. R., Coelho de Souza, F. & Oliveira-Filho, A. T. Evolutionary diversity in tropical tree communities peaks at intermediate precipitation. Sci. Rep. 10 , 1188 (2020).

Cadotte, M. W., Cardinale, B. J. & Oakley, T. H. Evolutionary history and the effect of biodiversity on plant productivity. Proc. Natl Acad. Sci. USA 105 , 17012–17017 (2008).

Hopkins, M. J. G. Modelling the known and unknown plant biodiversity of the Amazon Basin. J. Biogeogr. 34 , 1400–1411 (2007).

Wilson, E. O. in Biodiversity (eds Wilson E. O. & Peter F. M.) Ch. 1 (National Academies Press, 1988).

Brooks, T. M. et al. Habitat loss and extinction in the hotspots of biodiversity. Conserv. Biol. 16 , 909–923 (2002).

Gibbs, H. K. et al. Brazil’s soy moratorium. Science 347 , 377–378 (2015).

Alix-Garcia, J. & Gibbs, H. K. Forest conservation effects of Brazil’s zero deforestation cattle agreements undermined by leakage. Glob. Environ. Change 47 , 201–217 (2017).

Escobar, H. There’s no doubt that Brazil’s fires are linked to deforestation, scientists say. Science https://doi.org/10.1126/science.aaz2689 (2019).

Amazon fires: Brazil sends army to help tackle blazes. BBC News https://www.bbc.co.uk/news/world-latin-america-49452789 (24 August 2019).

Marengo, J. A., Tomasella, J., Soares, W. R., Alves, L. M. & Nobre, C. A. Extreme climatic events in the Amazon basin. Theor. Appl. Climatol. 107 , 73–85 (2012).

Malhi, Y. et al. Exploring the likelihood and mechanism of a climate-change-induced dieback of the Amazon rainforest. Proc. Natl Acad. Sci. USA 106 , 20610–20615 (2009).

Swann, A. L. S. et al. Continental-scale consequences of tree die-offs in North America: identifying where forest loss matters most. Environ. Res. Lett. 13 , 055014 (2018).

McCoy, T. Amazon fires dropped unexpectedly in September, after summer spike. Washington Post https://www.washingtonpost.com/world/the_americas/amazon-fires-dropped-unexpectedly-in-september-after-spiking-over-the-summer/2019/10/02/4ddc0026-e516-11e9-b403-f738899982d2_story.html (2 October 2019).

Moutinho, P., Guerra, R. & Azevedo-Ramos, C. Achieving zero deforestation in the Brazilian Amazon: what is missing? Elementa 4 , 000125 (2016).

Olson, D. M. et al. Terrestrial ecoregions of the world: a new map of life on Earth: A new global map of terrestrial ecoregions provides an innovative tool for conserving biodiversity. Bioscience 51 , 933–938 (2001).

Hansen, M. C. et al. High-resolution global maps of 21st-century forest cover change. Science 342 , 850–853 (2013).

Giglio, L., Schroeder, W. & Justice, C. O. The collection 6 MODIS active fire detection algorithm and fire products. Remote Sens. Environ. 178 , 31–41 (2016).

Giglio, L. MODIS Collection 6 Active Fire Product User’s Guide Revision A (Univ. Maryland, 2015).

Barlow, J., Lagan, B. O. & Peres, C. A. Morphological correlates of fire-induced tree mortality in a central Amazonian forest. J. Trop. Ecol. 19 , 291–299 (2003).

Brando, P. M. et al. Fire-induced tree mortality in a neotropical forest: the roles of bark traits, tree size, wood density and fire behavior. Glob. Change Biol. 18 , 630–641 (2012).

Gibbs, H. K. et al. Tropical forests were the primary sources of new agricultural land in the 1980s and 1990s. Proc. Natl Acad. Sci. USA 107 , 16732–16737 (2010).

Barlow, J. & Peres, C. in Emerging Threats to Tropical Forests (eds. Laurance, W. F. & Peres, C. A.) 225–240 (Univ. Chicago Press, 2006).

Barlow, J. et al. Wildfires in bamboo-dominated Amazonian forest: impacts on above-ground biomass and biodiversity. PLoS ONE 7 , e33373 (2012).

Gerwing, J. J. Degradation of forests through logging and fire in the eastern Brazilian Amazon. For. Ecol. Manage. 157 , 131–141 (2002).

Brando, P. M. et al. Abrupt increases in Amazonian tree mortality due to drought-fire interactions. Proc. Natl Acad. Sci. USA 111 , 6347–6352 (2014).

Barlow, J. & Peres, C. A. Avifaunal responses to single and recurrent wildfires in Amazonian forests. Ecol. Appl. 14 , 1358–1373 (2004).

Paolucci, L. N., Schoereder, J. H., Brando, P. M. & Andersen, A. N. Fire-induced forest transition to derived savannas: cascading effects on ant communities. Biol. Conserv. 214 , 295–302 (2017).

Roy, D. P. & Kumar, S. S. Multi-year MODIS active fire type classification over the Brazilian Tropical Moist Forest Biome. Int. J. Digital Earth 10 , 54–84 (2017).

Giglio, L., Schroeder, W., Hall, J. V. & Justice, C. O. MODIS Collection 6 Active Fire Product User’s Guide Revision B (Univ. Maryland, 2018).

Barriopedro, D., Fischer, E. M., Luterbacher, J., Trigo, R. M. & García-Herrera, R. The hot summer of 2010: redrawing the temperature record map of Europe. Science 332 , 220–224 (2011).

Chen, Y. et al. Forecasting fire season severity in South America using sea surface temperature anomalies. Science 334 , 787–791 (2011).

Giglio, L. et al. Assessing variability and long-term trends in burned area by merging multiple satellite fire products. Biogeosciences 7 , 1171–1186 (2010).

Justice, C. O. et al. The MODIS fire products. Remote Sens. Environ. 83 , 244–262 (2002).

Giglio, L., Boschetti, L., Roy, D. P., Humber, M. L. & Justice, C. O. The Collection 6 MODIS burned area mapping algorithm and product. Remote Sens. Environ. 217 , 72–85 (2018).

Nóbrega, C. C., Brando, P. M., Silvério, D. V., Maracahipes, L. & de Marco, P. Effects of experimental fires on the phylogenetic and functional diversity of woody species in a neotropical forest. For. Ecol. Manage. 450 , 117497 (2019).

Alencar, A., Nepstad, D. & Diaz, M. C. V. Forest understory fire in the Brazilian Amazon in ENSO and Non-ENSO years: area burned and committed carbon emissions. Earth Interact. 10 , 1–17 (2006).

Siegert, F., Ruecker, G., Hinrichs, A. & Hoffmann, A. A. Increased damage from fires in logged forests during droughts caused by El Niño. Nature 414 , 437–440 (2001).

Cochrane, M. A. & Laurance, W. F. Fire as a large-scale edge effect in Amazonian forests. J. Trop. Ecol. 18 , 311–325 (2002).

Ray, D., Nepstad, D. & Moutinho, P. Micrometeorological and canopy controls of fire susceptibility in a forested Amazon landscape. Ecol. Appl. 15 , 1664–1678 (2005).

Silvério, D. V. et al. Fire, fragmentation, and windstorms: a recipe for tropical forest degradation. J. Ecol. 107 , 656–667 (2019).

Guisan, A. & Zimmermann, N. E. Predictive habitat distribution models in ecology. Ecol. Modell. 135 , 147–186 (2000).

Fegraus, E. Tropical Ecology Assessment and Monitoring Network (TEAM Network). Biodivers. Ecol. 4 , 287–287 (2012).

Peet, R. K., Lee, M. T., Jennings, M. D. & Faber-Langendoen, D. VegBank: a permanent, open-access archive for vegetation plot data. Biodivers. Ecol. 4 , 233–241 (2012).

DeWalt, S. J., Bourdy, G., Chavez de Michel, L. R. & Quenevo, C. Ethnobotany of the Tacana: quantitative inventories of two permanent plots of Northwestern Bolivia. Econ. Bot. 53 , 237–260 (1999).

USDA Forest Service. Forest Inventory and Analysis National Program, http://www.fia.fs.fed.us/ (2013).

Wiser, S. K., Bellingham, P. J. & Burrows, L. E. Managing biodiversity information: development of New Zealand’s National Vegetation Survey databank. N. Z. J. Ecol. 25 , 1–17 (2001).

Anderson-Teixeira, K. J. et al. CTFS-ForestGEO: a worldwide network monitoring forests in an era of global change. Glob. Change Biol. 21 , 528–549 (2015).

Enquist, B. & Boyle, B. SALVIAS – the SALVIAS vegetation inventory database. Biodivers. Ecol. 4 , 288 (2012).

GBIF.org. GBIF Occurrence Download https://doi.org/10.15468/dl.yubndf (2018).

Dauby, G. et al. RAINBIO: a mega-database of tropical African vascular plants distributions. PhytoKeys 74 , 1–18 (2016).

Arellano, G. et al. A standard protocol for woody plant inventories and soil characterisation using temporary 0.1-ha plots in tropical forests. J. Trop. For. Sci. 28 , 508–516 (2016).

O’Connell, B. M. et al. The Forest Inventory and Analysis Database: Database Description and User Guide for Phase 2 (version 6.1), https://doi.org/10.2737/fs-fiadb-p2-6.1 (USDA Forest Service, 2016).

Oliveira-Filho, A. T. NeoTropTree, Flora arbórea da Região Neotropical: Um Banco de Dados Envolvendo Biogeografia, Diversidade e Conservação, http://www.neotroptree.info (Univ. Federal de Minas Gerais, 2017).

Peet, R. K., Lee, M. T., Jennings, M. D. & Faber-Langendoen, D. VegBank: The Vegetation Plot Archive of the Ecological Society of America , http://vegbank.org (accessed 2013).

Boyle, B. et al. The taxonomic name resolution service: an online tool for automated standardization of plant names. BMC Bioinf. 14 , 16 (2013).

Goldsmith, G. R. et al. Plant-O-Matic: a dynamic and mobile guide to all plants of the Americas. Methods Ecol. Evol. 7 , 960–965 (2016).

McFadden, I. R. et al. Temperature shapes opposing latitudinal gradients of plant taxonomic and phylogenetic β diversity. Ecol. Lett. 22 , 1126–1135 (2019).

Enquist, B. J., Condit, R., Peet, R. K., Schildhauer, M. & Thiers, B. M. Cyberinfrastructure for an integrated botanical information network to investigate the ecological impacts of global climate change on plant biodiversity. Preprint at https://doi.org/10.7287/peerj.preprints.2615v2 (2016).

Maitner, B. S. et al. The BIEN R package: A tool to access the Botanical Information and Ecology Network (BIEN) database. Methods Ecol. Evol. 9 , 373–379 (2017).

Phillips, S. J. & Dudik, M. Modeling of species distributions with Maxent: new extensions and a comprehensive evaluation. Ecography 31 , 161–175 (2008).

Merow, C. & Silander, J. A. A comparison of Maxlike and Maxent for modelling species distributions. Methods Ecol. Evol. 5 , 215–225 (2014).

Aiello-Lammens, M. E., Boria, R. A., Radosavljevic, A., Vilela, B. & Anderson, R. P. spThin: an R package for spatial thinning of species occurrence records for use in ecological niche models. Ecography 38 , 541–545 (2015).

Grubbs, F. E. Sample criteria for testing outlying observations. Ann. Math. Statist. 21 , 27–58 (1950).

Article   MathSciNet   MATH   Google Scholar  

Komsta, L. outliers: Tests for outliers. R package v.0.14 (2011).

Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1-km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37 , 4302–4315 (2017).

Hijmans, R. J., Cameron, S. E., Parra, J. L., Jones, P. G. & Jarvis, A. Very high resolution interpolated climate surfaces for global land areas. Int. J. Climatol. 25 , 1965–1978 (2005).

Mueller-Dombois, D. & Ellenberg, H. Aims and Methods of Vegetation Ecology (Wiley, 1974).

Friedman, J., Hastie, T. & Tibshirani, R. glmnet: Lasso and elastic-net regularized generalized linear models. R package v.4.0-2 (2020).

Phillips, S. J., Anderson, R. P. & Schapire, R. E. Maximum entropy modeling of species geographic distributions. Ecol. Modell. 190 , 231–259 (2006).

Drake, J. M. Range bagging: a new method for ecological niche modelling from presence-only data. J. R. Soc. Interface 12 , 20150086 (2015).

Article   PubMed   PubMed Central   Google Scholar  

Cardoso, D. et al. Amazon plant diversity revealed by a taxonomically verified species list. Proc. Natl Acad. Sci. USA 114 , 10695–10700 (2017).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Warton, D. I. & Shepherd, L. C. Poisson point process models solve the “pseudo-absence problem” for presence-only data in ecology. Ann. Appl. Stat. 4 , 1383–1402 (2010).

MathSciNet   MATH   Google Scholar  

Renner, I. W. et al. Point process models for presence-only analysis. Methods Ecol. Evol. 6 , 366–379 (2015).

Dinerstein, E. et al. An ecoregion-based approach to protecting half the terrestrial realm. Bioscience 67 , 534–545 (2017).

Roberts, D. R. et al. Cross-validation strategies for data with temporal, spatial, hierarchical, or phylogenetic structure. Ecography 40 , 913–929 (2016).

Phillips, S. J. Transferability, sample selection bias and background data in presence-only modelling: a response to Peterson et al . (2007). Ecography 31 , 272–278 (2008).

Merow, C., Smith, M. J. & Silander, J. A. Jr. A practical guide to MaxEnt for modeling species’ distributions: what it does, and why inputs and settings matter. Ecography 36 , 1058–1069 (2013).

Qiao, H. et al. An evaluation of transferability of ecological niche models. Ecography 42 , 521–534 (2019).

Peterson, A. T., Papeş, M. & Soberón, J. Rethinking receiver operating characteristic analysis applications in ecological niche modeling. Ecol. Modell. 213 , 63–72 (2008).

Allouche, O., Tsoar, A. & Kadmon, R. Assessing the accuracy of species distribution models: prevalence, kappa and the true skill statistic (TSS). J. Appl. Ecol. 43 , 1223–1232 (2006).

Jung, M. et al. Areas of global importance for terrestrial biodiversity, carbon, and water. Preprint at https://doi.org/10.1101/2020.04.16.021444 (2020).

Carlson, C. J. et al. Climate change will drive novel cross-species viral transmission. Preprint at https://doi.org/10.1101/2020.01.24.918755 (2020).

BirdLife International. IUCN Red List for Birds http://www.birdlife.org (2019).

Brooks, T. M. et al. Measuring terrestrial area of habitat (AOH) and its utility for the IUCN Red List. Trends Ecol. Evol. 34 , 977–986 (2019).

de Area Leão Pereira, E. J., de Santana Ribeiro, L. C., da Silva Freitas, L. F. & de Barros Pereira, H. B. Brazilian policy and agribusiness damage the Amazon rainforest. Land Use Policy 92 , 104491 (2020).

Garcia, R. T. After Brazil’s summer of fire, the militarization of the Amazon remains. Foreign Policy https://foreignpolicy.com/2019/11/19/militarization-amazon-legacy-brazil-forest-fire-bolsonaro/ (19 November 2019).

Vicente-Serrano, S. M., Beguería, S. & López-Moreno, J. I. A multiscalar drought index sensitive to global warming: The Standardized Precipitation Evapotranspiration Index. J. Clim. 23 , 1696–1718 (2010).

Feldpausch, T. R. et al. Amazon forest response to repeated droughts. Global Biogeochem. Cycles 30 , 964–982 (2016).

Marin, P.-G., Julio, C. J., Arturo, R.-T. D. & Jose, V.-N. D. Drought and spatiotemporal variability of forest fires across Mexico. Chin. Geogr. Sci. 28 , 25–37 (2018).

Adams, H. D. et al. Temperature sensitivity of drought-induced tree mortality portends increased regional die-off under global-change-type drought. Proc. Natl Acad. Sci. USA 106 , 7063–7066 (2009).

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Acknowledgements

We acknowledge the herbaria that contributed data to this work: HA, FCO, MFU, UNEX, VDB, ASDM, BPI, BRI, CLF, L, LPB, AD, TAES, FEN, FHO, A, ANSM, BCMEX, RB, TRH, AAH, ACOR, AJOU, UI, AK, ALCB, AKPM, EA, AAU, ALU, AMES, AMNH, AMO, ANA, GH, ARAN, ARM, AS, CICY, ASU, BAI, AUT, B, BA, BAA, BAB, BACP, BAF, BAL, COCA, BARC, BBS, BC, BCN, BCRU, BEREA, BG, BH, BIO, BISH, SEV, BLA, BM, MJG, BOL, CVRD, BOLV, BONN, BOUM, BR, BREM, BRLU, BSB, BUT, C, CAMU, CAN, CANB, CAS, CAY, CBG, CBM, CEN, CEPEC, CESJ, CHR, ENCB, CHRB, CIIDIR, CIMI, CLEMS, COA, COAH, COFC, CP, COL, COLO, CONC, CORD, CPAP, CPUN, CR, CRAI, FURB, CU, CRP, CS, CSU, CTES, CTESN, CUZ, DAO, HB, DAV, DLF, DNA, DS, DUKE, DUSS, E, HUA, EAC, ECU, EIF, EIU, GI, GLM, GMNHJ, K, GOET, GUA, EKY, EMMA, HUAZ, ERA, ESA, F, FAA, FAU, UVIC, FI, GZU, H, FLAS, FLOR, HCIB, FR, FTG, FUEL, G, GB, GDA, HPL, GENT, GEO, HUAA, HUJ, CGE, HAL, HAM, IAC, HAMAB, HAS, HAST, IB, HASU, HBG, IBUG, HBR, IEB, HGI, HIP, IBGE, ICEL, ICN, ILL, SF, NWOSU, HO, HRCB, HRP, HSS, HU, HUAL, HUEFS, HUEM, HUSA, HUT, IAA, HYO, IAN, ILLS, IPRN, FCQ, ABH, BAFC, BBB, INPA, IPA, BO, NAS, INB, INEGI, INM, MW, EAN, IZTA, ISKW, ISC, GAT, IBSC, UCSB, ISU, IZAC, JBAG, JE, SD, JUA, JYV, KIEL, ECON, TOYA, MPN, USF, TALL, RELC, CATA, AQP, KMN, KMNH, KOR, KPM, KSTC, LAGU, UESC, GRA, IBK, KTU, KU, PSU, KYO, LA, LOMA, SUU, UNITEC, NAC, IEA, LAE, LAF, GMDRC, LCR, LD, LE, LEB, LI, LIL, LINN, AV, HUCP, MBML, FAUC, CNH, MACF, CATIE, LTB, LISI, LISU, MEXU, LL, LOJA, LP, LPAG, MGC, LPD, LPS, IRVC, MICH, JOTR, LSU, LBG, WOLL, LTR, MNHN, CDBI, LYJB, LISC, MOL, DBG, AWH, NH, HSC, LMS, MELU, NZFRI, M, MA, UU, UBT, CSUSB, MAF, MAK, MB, KUN, MARY, MASS, MBK, MBM, UCSC, UCS, JBGP, OBI, BESA, LSUM, FULD, MCNS, ICESI, MEL, MEN, TUB, MERL, CGMS, FSU, MG, HIB, TRT, BABY, ETH, YAMA, SCFS, SACT, ER, JCT, JROH, SBBG, SAV, PDD, MIN, SJSU, MISS, PAMP, MNHM, SDSU, BOTU, MPU, MSB, MSC, CANU, SFV, RSA, CNS, JEPS, BKF, MSUN, CIB, VIT, MU, MUB, MVFA, SLPM, MVFQ, PGM, MVJB, MVM, MY, PASA, N, HGM, TAM, BOON, MHA, MARS, COI, CMM, NA, NCSC, ND, NU, NE, NHM, NHMC, NHT, UFMA, NLH, UFRJ, UFRN, UFS, ULS, UNL, US, NMNL, USP, NMR, NMSU, XAL, NSW, ZMT, BRIT, MO, NCU, NY, TEX, U, UNCC, NUM, O, OCLA, CHSC, LINC, CHAS, ODU, OKL, OKLA, CDA, OS, OSA, OSC, OSH, OULU, OXF, P, PACA, PAR, UPS, PE, PEL, SGO, PEUFR, PH, PKDC, SI, PMA, POM, PORT, PR, PRC, TRA, PRE, PY, QMEX, QCA, TROM, QCNE, QRS, UH, R, REG, RFA, RIOC, RM, RNG, RYU, S, SALA, SANT, SAPS, SASK, SBT, SEL, SING, SIU, SJRP, SMDB, SNM, SOM, SP, SRFA, SPF, STL, STU, SUVA, SVG, SZU, TAI, TAIF, TAMU, TAN, TEF, TENN, TEPB, TI, TKPM, TNS, TO, TU, TULS, UADY, UAM, UAS, UB, UC, UCR, UEC, UFG, UFMT, UFP, UGDA, UJAT, ULM, UME, UMO, UNA, UNM, UNR, UNSL, UPCB, UPNA, USAS, USJ, USM, USNC, USZ, UT, UTC, UTEP, UV, VAL, VEN, VMSL, VT, W, WAG, WII, WELT, WIS, WMNH, WS, WTU, WU, Z, ZSS, ZT, CUVC, AAS, AFS, BHCB, CHAM, FM, PERTH and SAN. X.F., D.S.P., E.A.N., A.L. and J.R.B. were supported by the University of Arizona Bridging Biodiversity and Conservation Science program. Z.L. was supported by NSFC (41922006) and K. C. Wong Education Foundation. The BIEN working group was supported by the National Center for Ecological Analysis and Synthesis, a centre funded by NSF EF-0553768 at the University of California, Santa Barbara, and the State of California. Additional support for the BIEN working group was provided by iPlant/Cyverse via NSF DBI-0735191. B.J.E., B.M. and C.M. were supported by NSF ABI-1565118. B.J.E. and C.M. were supported by NSF ABI-1565118 and NSF HDR-1934790. B.J.E., L.H. and P.R.R. were supported by the Global Environment Facility SPARC project grant (GEF-5810). D.D.B. was supported in part by NSF DEB-1824796 and NSF DEB-1550686. S.R.S. was supported by NSF DEB-1754803. X.F. and A.L. were partly supported by NSF DEB-1824796. B.J.E. and D.M.N. were supported by NSF DEB-1556651. M.M.P. is supported by the São Paulo Research Foundation (FAPESP), grant 2019/25478-7. D.M.N. was supported by Instituto Serrapilheira/Brazil (Serra-1912-32082). E.I.N. was supported by NSF HDR-1934712. We thank L. López-Hoffman and L. Baldwin for constructive comments.

Author information

These authors contributed equally: Xiao Feng, Cory Merow, Zhihua Liu, Daniel S. Park, Patrick R. Roehrdanz, Brian Maitner, Erica A. Newman, Brian J. Enquist

Authors and Affiliations

Department of Geography, Florida State University, Tallahassee, FL, USA

Eversource Energy Center and Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USA

Cory Merow & Brian Maitner

CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China

Department of Biological Sciences, Purdue University, West Lafayette, IN, USA

Daniel S. Park

Purdue Center for Plant Biology, Purdue University, West Lafayette, IN, USA

The Moore Center for Science, Conservation International, Arlington, VA, USA

Patrick R. Roehrdanz & Lee Hannah

Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, USA

Erica A. Newman, Brad L. Boyle, Joseph R. Burger, Scott R. Saleska & Brian J. Enquist

Arizona Institutes for Resilience, University of Arizona, Tucson, AZ, USA

Erica A. Newman, Aaron Lien & Joseph R. Burger

Hardner & Gullison Associates, Amherst, NH, USA

Brad L. Boyle

School of Natural Resources and the Environment, University of Arizona, Tucson, AZ, USA

Aaron Lien, David D. Breshears & José R. Soto

Department of Biology, University of Kentucky, Lexington, KY, USA

Joseph R. Burger

Departamento de Biologia Animal, Universidade Estadual de Campinas, Campinas, Brazil

Mathias M. Pires

Department of Earth System Science, University of California, Irvine, Irvine, CA, USA

Paulo M. Brando

Woodwell Climate Research Center, Falmouth, MA, USA

Instituto de Pesquisa Ambiental da Amazônia (IPAM), Brasilia, Brazil

Insitute for Global Ecology, Florida Institute of Technology, Melbourne, FL, USA

Mark B. Bush

Department of Ecosystem and Landscape Dynamics, Institute for Biodiversity and Ecosystem Dynamics, University of Amsterdam, Amsterdam, The Netherlands

Crystal N. H. McMichael

Institute of Biological Sciences, Federal University of Minas Gerais, Belo Horizonte, Brazil

Danilo M. Neves

Department of Mechanical and Civil Engineering, Florida Institute of Technology, Melbourne, FL, USA

Efthymios I. Nikolopoulos

School of Geography, Development and Environment, University of Arizona, Tucson, AZ, USA

Tom P. Evans

Department of Epidemiology and Biostatistics, College of Public Health, University of Arizona, Tucson, AZ, USA

Kacey C. Ernst

The Santa Fe Institute, Santa Fe, NM, USA

Brian J. Enquist

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Contributions

X.F. conceived the idea, which was refined by discussion with D.S.P., C.M., B.M., P.R.R., E.A.N., B.L.B., A.L., J.R.B., D.D.B., J.R.S., K.C.E. and B.J.E.; X.F. and Z.L. processed the remote-sensing data; C.M., X.F., B.M., B.L.B., D.S.P. and B.J.E. conducted the analyses of plant data; P.R.R., C.M., B.M., X.F. and D.S.P. conducted the analyses of vertebrate data; X.F., C.M., S.R.S. and E.A.N. processed the drought data; D.S.P., X.F., C.M., P.R.R. and B.M. designed the illustrations with help from B.J.E., D.D.B., K.C.E. and E.A.N.; E.A.N., X.F., and D.S.P. conducted the statistical analyses with help from B.J.E.; X.F., B.J.E., B.M., A.L., J.R.B., D.S.P., C.M., E.A.N., Z.L. and P.R.R. wrote the original draft; all authors contributed to interpreting the results and the editing of manuscript drafts. B.J.E., C.M., K.C.E. and D.D.B. led to the acquisition of the financial support for the project. X.F., C.M., B.M., D.S.P., P.R.R., Z.L., E.A.N. and B.J.E. contributed equally to data, analyses and writing.

Corresponding author

Correspondence to Xiao Feng .

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Extended data figures and tables

Extended data fig. 1 fire-impacted forest and forest loss in the amazon basin..

a – h , Visualization of fire-impacted forest ( a , b ), forest loss without fire ( c , d ), fire-impacted forest with forest loss ( e , f ), and fire-impacted forest without forest loss ( g , h ) in the Amazon Basin based on MODIS burned area (left panels) and active fire (right panels). Data in a – d are resampled from the 500m (MODIS burned area) or 1 km (MODIS active fire) to 10 km resolution using mean function and thresholded at 0.01 to illustrate the temporal dynamics. Black represents non-forested areas masked out from this study. The cumulative fire-impacted forest is classified into two categories: fire-impacted forest with forest loss ( e , f ) and fire-impacted forest without forest loss ( g , h ). Data in e – h are resampled to 10 km using mean function to illustrate the cumulative percentages of impacts.

Extended Data Fig. 2 Scatter plot of species’ range impacted by fire.

Scatter plot of species’ range size in Amazon forest (x-axis) and percentage of total range impacted by fire (red) and forest loss without fire (black) up to 2019 for plants (left panel) and vertebrates (right panel).

Extended Data Fig. 3 Density plot of species’ cumulative range impacted by fire.

Density plot of species’ cumulative range impacted by fire. The different colours represent years 2001-2019. The x-axis is log10 transformed.

Extended Data Fig. 4 Summary of forest impacts in the Amazon Basin.

Areas of forest impact in the Amazon Basin estimated from MODIS burned area (top) and MODIS active fire (bottom).

Extended Data Fig. 5 Cumulative impacts on biodiversity in the Amazon Basin.

Cumulative effects of forest loss without fire on biodiversity in the Amazon rainforest. In the left panels, the black and grey shading represent the cumulative forest loss without fire based on MODIS burned area and MODIS active fire, respectively. Coloured areas represent the lower and upper bounds of cumulative numbers of a , plant and c , vertebrate species’ ranges impacted. Right panels depict the relationships between the cumulative forest loss without fire (based on MODIS burned area) and cumulative number of b , plant and d , vertebrate species. Coloured lines represent predicted values of an ordinary least squares linear regression and grey bands define the two-sided 95% confidence interval (two-sided, p values = 0.00). The silhouette of the tree is from http://phylopic.org/ ; silhouette of the monkey is courtesy of Mathias M. Pires.

Extended Data Fig. 6 Fire-impacted forest in Brazil.

Newly fire-impacted forest in Brazil (based on MODIS active fire). a shows the area of fire-impacted forest not explained by drought conditions. Different colours represent years from different policy regimes: pre-regulations in light red (mean value in dark red), regulation in grey (mean value in black dashed line), and 2019 in blue. The y-axis represents the difference between actual area and area predicted by drought conditions calibrated by data from regulation years ( Methods ). A positive value on the y-axis represents more area than expected, using the regulation years as a baseline. b shows a scatter plot of newly fire-impacted forest in Brazil and drought conditions (SPEI); The lines represent the ordinary least squares linear regression between fire-impacted forest and drought conditions for pre-regulation (red) and regulation (black) respectively.

Extended Data Fig. 7 Fire-impacted forest in different countries.

The contribution (0–1) of different countries to the newly fire-impacted forest each year based on MODIS active fire (top) and MODIS burned area (bottom).

Extended Data Figure 8 Impacts of fire on forest and biodiversity in Brazil.

a , Newly fire-impacted forest, b , new range impact on plants and c , new range impacts on vertebrate species in Brazil each year (based on MODIS active fire) that are not predicted by drought conditions. The colours represent three policy regimes: pre-regulation in red, regulation in grey and 2019 in blue. The y-axis represents the difference between actual value (area or range impacted by fire) and the values predicted by drought conditions calibrated by data from regulation years ( Methods ). A positive value on the y-axis represents more area or range impacted by fire than the expectation using the regulation years as a baseline. The dotted lines represent a smooth curve fitted to the values based on the loess method.

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Feng, X., Merow, C., Liu, Z. et al. How deregulation, drought and increasing fire impact Amazonian biodiversity. Nature 597 , 516–521 (2021). https://doi.org/10.1038/s41586-021-03876-7

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Issue Date : 23 September 2021

DOI : https://doi.org/10.1038/s41586-021-03876-7

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case study on deforestation in amazon forest

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Climate Transform

Deforestation: Case Studies

Deforestation is putting our planet at risk, as the following case studies exemplify. It is responsible for at least 10 per cent of global greenhouse gas emissions 1 and wipes out 137 species of plants, animals and insects every day 2 . The deplorable practice degenerates soil, losing half of the world’s topsoil over the past 150 years. 3 Deforestation also leads to drought by reducing the amount of water in the atmosphere. 4

Since the 1950s, deforestation has accelerated significantly, particularly in the tropics. 5 This is primarily due to rapid population growth and a resultant increase in demand for food and resources. 6 Agriculture drives about 80 per cent of deforestation today, as land is cleared for livestock, growing animal feed or other crops. 7 The below deforestation case studies of Brazil’s Amazon rainforest and the Congo Basin provide further insights into modern deforestation. 

Deforestation case study: Brazil

Nearly two-thirds of the Amazon rainforest – the largest rainforest in the world – is within Brazil’s national borders. 8 Any examination of deforestation case studies would be incomplete without considering tree felling in Brazil. 

History of deforestation in Brazil

Humans first discovered the Amazon rainforest about 13,000 years ago. But, it was the arrival of Europeans in the late 15th century that spurred the conversion of the forest into farmland. Nevertheless, the sheer size of the Amazon meant that the rainforest remained largely intact until the early 20th century. It was in the latter half of the 20th century that things began to change. 9

Hoatzin bird native to amazon rainforest

Industrial activities and large-scale agriculture began to eat away the southern and eastern fringes of the Amazon, from the 1950s onwards. 10 Deforestation in Brazil received a significant boost in 1964 when a military dictatorship took power and declared the jungle a security risk. 11 By the 1970s, the government was running television ads encouraging land conversion, provoking millions to migrate north into the forest. 12 Settlements replaced trees, and infrastructure began to develop. Wealthy tycoons subsequently bought the land for cattle ranches or vast fields of soy. 13

By the turn of the 21st century, more than 75 per cent of deforestation in the Amazon was for cattle ranching. But, environmentalists and Indigenous groups drew international attention to the devastation caused and succeeded in curtailing it by 2004. Between 2004 and the early 2010s, annual forest cover loss in Brazil reduced by about 80 per cent. The decline is attributed to “increased law enforcement, satellite monitoring, pressure from environmentalists, private and public sector initiatives, new protected areas, and macroeconomic trends”. 14  

Brazil’s deforestation of the Amazon rainforest since 2010

Unfortunately, however, efforts to curtail deforestation in Brazil’s Amazon have stalled since 2012. 15 Tree felling and land conversion have been trending upwards ever since. The economic incentive for chopping the rainforest down has overcome the environmental benefits of leaving it standing. 16 Political movements and lax government legislation have leveraged this to their advantage. President Jair Bolsonaro won the 2018 election with a promise to open up the Amazon to business. 17 Since his inauguration, the rate of deforestation has leapt by as much as 92 per cent. 18

However, there is still hope for the Amazon rainforest. Bolsonaro’s principal international ally was US President Trump. Now that environmentally-conscious Joe Biden has replaced him in the White House, international pressure regarding deforestation will increase heavily. 19 Biden has made this clear with a promise of USD $20 billion to protect the Amazon. 20

The impact of continued deforestation in Brazil

For its three million plant and animal species and one million Indigenous inhabitants, it is imperative that Amazonian deforestation is massively and immediately reduced. 21 As much as 17 per cent of the Amazon has been lost already. 22 If this proportion increases to over 20 per cent, a tipping point will be reached. 23 This will irreversibly break the water cycle, and at least half of the remaining forest will become savannah. 24

Impact on climate change

Losing the Amazon would also mean losing the fight against climate change. Despite the rampant deforestation in recent years, the remaining Amazon rainforest still absorbs between 5 to 10 per cent of all human CO2 emissions. 25 Cutting trees down increases anthropogenic emissions. When felled, burned or left to rot, trees release sequestered carbon. 26 A combination of reducing greenhouse gas emissions and preserving existing forests is crucial to preventing dangerous levels of global warming. 27  

Deforestation case study: The Congo Basin

The Congo Basin is the second-largest rainforest in the world. 28 It has been described as the ‘second lungs’ of the Earth because of how much carbon dioxide it absorbs and how much oxygen it produces. 29 But, just as the world’s first lungs – the Amazon – is being destroyed by humans, the Congo’s rainforest is also suffering heavy casualties. 30

60 per cent of the Congo Basin is located within the Democratic Republic of the Congo (DRC). 31 The DRC is one of the world’s largest and poorest countries, though it has immense economic resources. 32 Natural resources have fuelled an ongoing war that has affected all the neighbouring countries and claimed as many as six million lives. 33 The resultant instability combined with corruption and poor governance have led to an ever-increasing rate of deforestation within the DRC’s borders. 34

Deforestation in the Democratic Republic of the Congo (DRC)

Compared to the Amazon and Southeast Asia, deforestation in the Congo Basin has been low over the past few decades. 35 Nevertheless, great swathes of primary forest have been lost. Between 2000 and 2014, an area of forest larger than Bangladesh was destroyed. 36 From 2015 until 2019, 6.37 million hectares of tree cover was razed. 37 In 2019 alone, 475,000 hectares of primary forest disappeared, placing the DRC second only to Brazil for total deforestation that year. 38 Should the current rate of deforestation continue, all primary forest in the Congo Basin will be gone by the end of the century. 39

Drivers of deforestation in the DRC’s Congo Basin

Over the past 20 years, the biggest drivers of deforestation in the DRC has been small-scale subsistence agriculture. Clearing trees for charcoal and fuelwood, urban expansion and mining have also contributed to deforestation. Industrial logging is the most common cause of forest degradation. It opens up deeper areas of the forest to commercial hunting. There has been at least a 60 per cent drop in the region’s forest elephant populations over the past decade due to hunting and poaching. 40  

case study on deforestation in amazon forest

Between 2000 and 2014, small-scale farming contributed to about 90 per cent of the DRC’s deforestation. This trend has not changed in recent years. The majority of small-scale forest clearing is conducted with simple axes by people with no other livelihood options. The region’s political instability and ongoing conflict are therefore inciting the unsustainable rate of deforestation within the Congo Basin. 41

In future, however, industrial logging and land conversion to large-scale agriculture will pose the greatest threats to the Congo rainforest. 42 There are fears that demand for palm oil, rubber and sugar production will promote a massive increase in deforestation. 43 The DRC’s population is also predicted to grow to almost 200 million people by 2050. 44 This increase will threaten the remaining rainforest further, as they try to earn a living in a country deprived of opportunities. 45

The impact of deforestation in the Congo Basin

80 million people depend upon the Congo Basin for their existence. It provides food, charcoal, firewood, medicinal plants, and materials for building and other purposes. But, this rainforest also indirectly supports people across the whole of sub-Saharan Africa. Like all forests, it is instrumental in regulating rainfall, which can affect precipitation hundreds of miles away. The Congo Basin is a primary source of rainfall for the Sahel region, doubling the amount of rainfall in the air that passes over it. 46

The importance of the Congo Basin’s ability to increase precipitation cannot be understated. Areas such as the Horn of Africa are becoming increasingly dry. Drought in Ethiopia and Somalia has put millions of people on emergency food and water rations in recent years. Destroying the DRC’s rainforest would create the largest humanitarian crisis on Earth. 47  

It would also be devastating for biodiversity. The Congo Basin shelters some 10,000 animal species and more than 600 tree species. 48 They play a hugely important role in the forest, which has consequences for the entire planet. For instance, elephants, gorillas, and other large herbivores keep the density of small trees very low through predation. 49 This results in a high density of tall trees in the Congo rainforest. 50 Larger trees store more carbon and therefore help to prevent global warming by removing this greenhouse gas from the atmosphere. 51  

Preserve our forests

Preserving the Amazon and Congo Basin rainforests is vital for tackling climate change, as these deforestation case studies demonstrate. We must prioritise protecting and enhancing our existing trees if we are to limit the global temperature increase to 1.5°C, as recommended by the IPCC. 52

  • Rainforest Alliance. (2018). What is the Relationship Between Deforestation And Climate Change? [online] Available at: https://www.rainforest-alliance.org/articles/relationship-between-deforestation-climate-change.
  • www.worldanimalfoundation.com. (n.d.). Deforestation: Clearing The Path For Wildlife Extinctions. [online] Available at: https://www.worldanimalfoundation.com/advocate/wild-earth/params/post/1278141/deforestation-clearing-the-path-for-wildlife-extinctions#:~:text=Seventy%20percent%20of%20the%20Earth.
  • World Wildlife Fund. (2000). Soil Erosion and Degradation | Threats | WWF. [online] Available at: https://www.worldwildlife.org/threats/soil-erosion-and-degradation.
  • Butler, R.A. (2001). The impact of deforestation. [online] Mongabay. Available at: https://rainforests.mongabay.com/09-consequences-of-deforestation.html.
  • The Classroom | Empowering Students in Their College Journey. (2009). The History of Deforestation. [online] Available at: https://www.theclassroom.com/the-history-of-deforestation-13636286.html.
  • Greenpeace USA. (n.d.). Agribusiness & Deforestation. [online] Available at: https://www.greenpeace.org/usa/forests/issues/agribusiness/.
  • Yale.edu. (2015). The Amazon Basin Forest | Global Forest Atlas. [online] Available at: https://globalforestatlas.yale.edu/region/amazon.
  • Time. (2019). The Amazon Rain Forest Is Nearly Gone. We Went to the Front Lines to See If It Could Be Saved. [online] Available at: https://time.com/amazon-rainforest-disappearing/.
  • Butler, R. (2020). Amazon Destruction. [online] Mongabay.com. Available at: https://rainforests.mongabay.com/amazon/amazon_destruction.html.
  • the Guardian. (2020). Amazon deforestation surges to 12-year high under Bolsonaro. [online] Available at: https://www.theguardian.com/environment/2020/dec/01/amazon-deforestation-surges-to-12-year-high-under-bolsonaro.
  • Earth Innovation Institute. (2020). Joe Biden offers $20 billion to protect Amazon forests. [online] Available at: https://earthinnovation.org/2020/03/joe-biden-offers-20-billion-to-protect-amazon-forests/.
  • Brazil’s Amazon: Deforestation “surges to 12-year high.” (2020). BBC News. [online] 30 Nov. Available at: https://www.bbc.co.uk/news/world-latin-america-55130304.
  • Carbon Brief. (2020). Guest post: Could climate change and deforestation spark Amazon “dieback”? [online] Available at: https://www.carbonbrief.org/guest-post-could-climate-change-and-deforestation-spark-amazon-dieback.
  • Union of Concerned Scientists (2012). Tropical Deforestation and Global Warming | Union of Concerned Scientists. [online] www.ucsusa.org. Available at: https://www.ucsusa.org/resources/tropical-deforestation-and-global-warming#:~:text=When%20trees%20are%20cut%20down.
  • Milman, O. (2018). Scientists say halting deforestation “just as urgent” as reducing emissions. [online] the Guardian. Available at: https://www.theguardian.com/environment/2018/oct/04/climate-change-deforestation-global-warming-report.
  • Bergen, M. (2019). Congo Basin Deforestation Threatens Food and Water Supplies Throughout Africa. [online] World Resources Institute. Available at: https://www.wri.org/blog/2019/07/congo-basin-deforestation-threatens-food-and-water-supplies-throughout-africa.
  • www.esa.int. (n.d.). Earth from Space: “Second lungs of the Earth.” [online] Available at: https://www.esa.int/Applications/Observing_the_Earth/Earth_from_Space_Second_lungs_of_the_Earth [Accessed 26 Feb. 2021].
  • Erickson-Davis, M. (2018). Congo Basin rainforest may be gone by 2100, study finds. [online] Mongabay Environmental News. Available at: https://news.mongabay.com/2018/11/congo-basin-rainforest-may-be-gone-by-2100-study-finds/.
  • Mongabay Environmental News. (2020). Poor governance fuels “horrible dynamic” of deforestation in DRC. [online] Available at: https://news.mongabay.com/2020/12/poor-governance-fuels-horrible-dynamic-of-deforestation-in-drc/ [Accessed 26 Feb. 2021].
  • DR Congo country profile. (2019). BBC News. [online] 10 Jan. Available at: https://www.bbc.co.uk/news/world-africa-13283212.
  • Butler, R.A. (2001). Congo Deforestation. [online] Mongabay. Available at: https://rainforests.mongabay.com/congo/deforestation.html.
  • Mongabay Environmental News. (2020). Poor governance fuels “horrible dynamic” of deforestation in DRC. [online] Available at: https://news.mongabay.com/2020/12/poor-governance-fuels-horrible-dynamic-of-deforestation-in-drc/.
  • Butler, R. (2020). The Congo Rainforest. [online] Mongabay.com. Available at: https://rainforests.mongabay.com/congo/.
  • Editor, B.W., Environment (n.d.). Large trees are carbon-storing giants. www.thetimes.co.uk. [online] Available at: https://www.thetimes.co.uk/article/large-trees-are-more-valuable-carbon-stores-than-was-thought-k8hnggzs8#:~:text=The%20world [Accessed 26 Feb. 2021].
  • IPCC (2018). Summary for Policymakers — Global Warming of 1.5 oC. [online] Ipcc.ch. Available at: https://www.ipcc.ch/sr15/chapter/spm/.

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Deforestation in the Amazon Rainforest: causes, effects, solutions

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Deforestation in the Amazon is an environmental issue that continues to be a major concern across Latin America and beyond. Tropical forests play a critical role in both local and global ecosystems. They provide habitat for wildlife, sequester carbon dioxide from the atmosphere, protect biodiversity, and provide valuable resources for nearby communities. It is estimated that over 20% of global rainforests have already been destroyed due to land clearing for agricultural production, logging, mining, and other human activities. In addition to its devastation of the natural environment, deforestation also contributes significantly to changing climates by releasing tonnes of carbon dioxide into the atmosphere.

Deforestation in the Amazon, biodiversity, ecosystems, habitat protection, forests

This article will examine the large-scale destruction of the forest cover in the Amazon for cattle pastures and other human activities, as well as the resulting impacts on air quality, climate, biodiversity loss, and Indigenous rights. It will also discuss strategies for reducing deforestation and protecting the Amazon's delicate ecosystems.

What is deforestation?

Deforestation , as the name suggests, is the process of clearing a forest or a large area of trees to make space for other land uses, such as agriculture, commercial development, or urbanisation. While deforestation can occur in any part of the world, the rate of deforestation in the Amazon Rainforest in Brazil is one of the most severe worldwide.

Read more: Top 10 causes of deforestation

Deforestation can happen naturally, for example, when forests are destroyed by wildfires, disease, or insect infestations. However, human activities like logging, mining, and agriculture are the main drivers of deforestation in the Amazon Rainforest and globally.

Tropical deforestation is a significant concern because tropical rainforests play a crucial role in regulating the Earth's climate, supporting biodiversity , and providing essential resources for human survival. The Amazon Rainforest alone is home to millions of plant and animal species and produces around 20% of the world's oxygen.

Read more: What are the effects of deforestation?

Deforestation has harmful effects on the environment and the economy. The loss of forests contributes to climate change by releasing carbon dioxide into the atmosphere and reducing the planet's ability to absorb it. Deforestation also leads to soil erosion, loss of biodiversity, and potential water shortages.

Thus, deforestation is a complex issue with significant implications for our planet's health and the wellbeing of all living things. By understanding the causes and consequences of deforestation, we can work towards implementing solutions for a more sustainable future.

Help reduce deforestation by investing in our carbon credits

Deforestation in the Amazon, biodiversity, ecosystems, habitat protection, forests

Brief overview of the Amazon Rainforest

The Amazon Rainforest, the largest rainforest in the world, is a lush and vibrant ecosystem spanning across nine countries in South America, covering an area of over 5.5 million square kilometres, of which almost 60% is in Brazil. It is famously known as the 'lungs of the world,' producing 20% of the Earth's oxygen and playing a crucial role in regulating the planet's climate.

But it's not just the ecological importance that makes the Amazon Rainforest a wondrous place. The rainforest is home to over one million Indigenous people and millions of species of plants and animals, many of which are found nowhere else in the world. From jaguars and macaws to medicinal plants and exotic fruits, the Amazon Rainforest is a treasure trove of biodiversity.

Read more: Impact of forests on biodiversity

However, the Amazon Rainforest is facing significant threats given the rates of deforestation, mainly from human activities like deforestation, mining, and agriculture, but also from natural events like forest fires. These activities have devastating impacts on the ecosystem and the people who depend on it, including Indigenous communities who have called the rainforest home for thousands of years.

Despite these challenges, the Amazon Rainforest can be restored with collective support. Many organisations and individuals are working to protect the rainforest through sustainable practices, conservation efforts, and education initiatives. And we can all do our part, whether it's reducing our consumption of products linked to deforestation or supporting eco-friendly practices.

The Amazon Rainforest is undoubtedly one of our planet's most incredible and important ecosystems . It's up to us to protect it so future generations can enjoy its beauty and benefits for years to come.

Deforestation in the Amazon, biodiversity, ecosystems, habitat protection, forests

Causes for deforestation in the Amazon

Deforestation in the Amazon is one of the biggest ecological crises of our time. The Amazon Rainforest is unmatched in its biodiversity, with millions of plant and animal species that call it home. However, human activities such as agriculture, mining, and logging are causing significant damage to the rainforest. Here are some of the main causes of Amazonian deforestation:

Agriculture: Cattle ranches and soybean production are the largest drivers of deforestation in the Amazon. Soybeans are in high demand globally, and the Amazon is a prime location for growing this crop due to its fertile soil. Unfortunately, clearing forests to create new agricultural land is often the easiest and cheapest solution for farmers. Brazil is one of the world's largest beef exporters, and to raise their cattle, ranchers need huge tracts of land.

Read more: How regenerative agriculture is transforming sustainable farming

Logging: Logging for commercial purposes is another major cause of deforestation. Trees are cut down for timber used in furniture, paper, and other products.

Mining: The demand for minerals like gold and iron ore drives mining in the Amazon. Mining activities are causing widespread destruction to the rainforest, including water pollution and soil degradation.

Human activity: The growth of human populations in and around the Amazon is increasing pressure on the rainforest. Infrastructure development, such as roads, dams, and hydropower projects, is also contributing to deforestation.

The negative impact of forest loss in the Amazon is vast. It leads to habitat loss for millions of species, including endangered animals like the jaguar and giant otter. Deforestation also contributes to greenhouse gas emissions and climatic instability, as the forest serves as a natural carbon sink, capturing carbon emissions.

Read more: Why should endangered species be protected?

To tackle deforestation in the Amazon, it is important to understand its root causes. By reducing demand for products linked to deforestation and supporting sustainable practices, we can all play a role in protecting this vital ecosystem.

The effects of deforestation in the Amazon

When we think about the Amazon forest, we imagine a lush, green forest teeming with wildlife and plants that are unique to this precious ecosystem. However, the reality is that deforestation is severely impacting this natural wonder, and the effects are alarming.

One of the most significant effects of deforestation in the Amazon is the displacement of Indigenous peoples. These communities have a deep connection with the land and depend on it for their survival. When forests are cut down, their homes, livelihoods, and very existence are threatened.

Read more: Why are tropical rainforests important?

Another impact of deforestation is the loss of biodiversity. The Amazon is home to an incredible array of species, many of which are found nowhere else in the world. When forests are destroyed, these animals lose their habitat, and many cannot survive. This, in turn, affects the balance of the entire ecosystem, and the consequences can be far-reaching.

Read more: Deforestation in the United States: causes, consequences, and cures

Deforestation in the Amazon, biodiversity, ecosystems, habitat protection, forests

Deforestation also leads to soil erosion, which affects the quality of the soil and its ability to support plant and animal life. The Amazon is known for its fertile soil. Even so, when forests are removed, the soil can quickly become depleted, leading to a loss of productivity and economic opportunities for local traditional communities.

Perhaps the most significant impact of deforestation in the Amazon is its effect on the climate. Trees are natural carbon sinks, and when they are cut down, large amounts of carbon dioxide are released into the atmosphere. This exacerbates the effects of climate change, contributing to rising temperatures, rising sea levels, and more frequent natural disasters.

Read more: Breathe easy: How trees are nature's air-cleaning machines

It's easy to see why deforestation in the Amazon is a cause for concern. From the loss of biodiversity to the displacement of Indigenous peoples, the effects are far-reaching and devastating. It's up to us to take action to protect this precious ecosystem, whether through supporting conservation efforts or living a more sustainable lifestyle.

Recent trends in deforestation rates

Deforestation has been a hot topic for quite some time now, and it's not going away anytime soon. In fact, in the past years, deforestation rates in the Amazon have been on the rise, and the consequences are dire. In 2022, the Brazilian Amazon Rainforest witnessed a dramatic peak  in deforestation: it lost the equivalent of nearly 3,000 soccer fields a day.

According to the Food and Agriculture Organization (FAO), approximately 10 million hectares of global forests are lost every year. Picture an area the size of Iceland but without the icy coolness. Instead, it's a wasteland. According to Brazil's National Institute for Space Research, deforestation in the Brazilian Amazon rose more than 50% in the first three months of 2020 compared to the same period in 2019.

Contribute to restoring nature by reducing your carbon footprint

The Amazon Rainforest loses an average of 1.4 billion trees each year. When trees are cut down, they release carbon dioxide, a significant contributor to the climate crisis we're facing. That is why deforestation is responsible for roughly 15% of global greenhouse gas emissions each year. That's on par with the entire transportation sector's emissions worldwide, including cars, planes, and ships.

So, what's driving this increase in deforestation rates? 

  • Deforestation is often driven by human activity, such as agriculture, human settlements, and infrastructure development. One major driver is agriculture, specifically the production of soybeans and cattle ranching. Cattle ranching and soybean farming are colossal culprits, with cattle ranching accounting for 80% of current deforestation in the Amazon. As demand for these products increases, more and more land is cleared to make room for crops and grazing.
  • Illegal logging is another significant contributor, with millions of trees lost to this illicit activity every year. Despite efforts by environmental agencies and the Brazilian federal government to crack down on the practice, it continues to happen at an alarming rate. Traditional communities and Indigenous land are often the targets of these illegal activities, displacing people and disrupting their way of life.
  • The dry season also plays a role in deforestation rates. During this time, it's easier for fires to ignite and spread, making it easier for land to be cleared quickly. Unfortunately, deforestation-related fires can lead to devastating consequences, such as the loss of homes and businesses and even the loss of life.

So, what can be done to combat these trends in deforestation rates? Sustainable development and economic incentives for landowners who preserve forests are a great place to start. Additionally, supporting Indigenous communities and traditional land use practices can help protect valuable ecosystems and promote biodiversity. We discuss these and other solutions in more detail later in this article.

The bottom line is that we can't afford to ignore deforestation's impact on our planet. It's time to take action and take responsibility for our actions. The future of our planet depends on it.

Moreover, it's not just the atmosphere that suffers from deforestation. Forests serve as habitats for a large portion of our planet's wildlife. Can you imagine losing over 80% of the world's terrestrial biodiversity and species due to deforestation?

Read more: From the brink of extinction: 4 endangered species that made a comeback

Although deforestation rates in the Amazon remained high in 2022, the good news is that in April 2023, deforestation rates dropped by 72% . This was due in part to increased enforcement of environmental laws and campaigns to promote sustainable agriculture and forestry practices. However, there is still much more work to be done to protect this vital ecosystem.

The Amazon Rainforest is not just a resource to be exploited. It is a precious and irreplaceable ecosystem that deserves our respect and protection. By educating ourselves on the factors driving deforestation and taking action to promote sustainable practices, we can all contribute to protecting this vital part of our planet.

Solutions to deforestation

Deforestation in the Amazon is a serious problem that threatens our planet's health and biodiversity. The Amazon Rainforest is often referred to as the 'lungs of the planet' because of its ability to absorb carbon dioxide and release oxygen. However, it's being destroyed at an alarming rate, which has negative consequences in the form of greenhouse gas emissions, habitat loss for animals, and a reduction in biodiversity. Let's explore four solutions to combat the Amazon deforestation:

1. Increased government regulations

One of the most practical ways to lessen deforestation in the Amazon is for the government to enforce laws that govern it. For example, the Brazilian government can create laws and regulations prioritising sustainable agricultural activities and forestry practices. The government can also implement measures that penalise individuals and companies that engage in illegal deforestation. This way, there will be a clear message to people that deforestation is impermissible.

2. Implementing nature-based solutions

Nature-based solutions are a promising pathway towards mitigating deforestation in the Amazon Rainforest. One such approach involves the restoration of degraded lands through reforestation efforts, which involves planting a diverse range of native tree species and allowing them to grow and regenerate over time. This can help prevent further deforestation by creating a barrier between remaining forests and areas susceptible to land-use change.

DGB develops large-scale nature-based projects that restore forests, rejuvenate biodiversity, and create vital habitats, all while offering many socio-economic benefits for local communities. Nature-based solutions are key to restoring our world's forests and offer many additional advantages. 

Explore DGB’s nature-based projects

Deforestation in the Amazon, biodiversity, ecosystems, habitat protection, forests

Another key method to prevent deforestation is through promoting sustainable development and providing economic incentives for landowners who preserve forests. A sustainable income through forest conservation and sustainable land management practices can provide economic incentives for local traditional communities to protect forests rather than exploit them for short-term gains. Additionally, supporting Indigenous communities and traditional land use practices can help protect valuable ecosystems and promote biodiversity. Implementing and ensuring the success of such solutions requires a concerted effort from various stakeholders, including governments, non-governmental organisations, and private sector actors. By prioritising nature-based solutions, it is possible to address deforestation in the Amazon while also safeguarding the region's biodiversity and supporting local livelihoods and Indigenous peoples.

Learn how you can restore forests with our carbon credits

3. Supporting nonprofit organisations

Supporting non-profit organisations that work towards protecting rainforests and planting trees is another way to combat deforestation. Rainforest Trust, Amazon Watch, and Rainforest Alliance are some of the many nonprofit organisations individuals can donate to. These organisations help reduce deforestation by purchasing land in the Amazon to protect it from logging and cattle ranching.

4. Offsetting your carbon footprint

Not all emissions are avoidable. By offsetting carbon emissions emissions that cannot be reduced or avoided, you can effectively reach net zero or carbon neutrality. This means that you strike a balance between the emissions you emit vs the emissions you remove from the atmosphere. This is achieved by implementing carbon-reduction strategies and offsetting hard-to-abate emissions.   Carbon offsetting   is a crucial tool to restore nature as it supports projects focussed on reforestation and nature restoration, such as those of DGB.  DGB's large-scale projects plant millions of trees to restore forests and combat deforestation. By offsetting your environmental footprint with DGB, you invest in nature and help to create a greener tomorrow.

To achieve global environmental goals in line with the US Paris Agreement and mitigate harm to nature, we all have to take action and address our environmental impact to ensure a better, more sustainable world where nature can continue to support us. The first step is measuring your carbon footprint, reducing emissions that can be reduced, and then offsetting remaining emissions.

Start your carbon footprint assessment today

DGB Group’s trust in nature-based solutions as an answer to deforestation

With the right combination of government regulations, nature-based solutions, non-profit organisations, and individual action, deforestation in the Amazon can be addressed and reversed. By implementing laws that protect forests, restoring degraded lands with reforestation efforts, supporting rainforest protection projects through nonprofit donations, and offsetting your carbon footprint, we can ensure a healthy environment for generations to come.

Start planting trees today

Through our work in designing and implementing large-scale nature-based solutions, DGB Group is confident that nature-based solutions are one of the surest ways to prevent further deforestation and even reverse it. With everyone doing their part by making sustainable choices and supporting environmental initiatives, we can make a meaningful difference in protecting our planet.

DGB strongly supports and implements reforestation efforts worldwide, knowing firsthand the devastating impact of deforestation on our planet and its precious biodiversity. Join us on our quest to save the planet. With our innovative carbon projects and collaborations with stakeholders, we're making a tangible difference in preserving healthy ecosystems. Our unwavering commitment to preventing further deforestation and promoting biodiversity is central to our mission and our contribution towards a sustainable, prosperous future.

Join our cause to reforest the planet with our carbon credits

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Analysis of environmental variables and deforestation in the amazon using logistical regression models

  • Published: 09 September 2024
  • Volume 196 , article number  911 , ( 2024 )

Cite this article

case study on deforestation in amazon forest

  • Helder J. F. da Silva 1 ,
  • Weber A. Gonçalves 2 ,
  • Bergson G. Bezerra 2 ,
  • Cláudio M. Santos e Silva 2 ,
  • Cristiano P. de Oliveira 2 ,
  • Jório B. Cabral Júnior 4 ,
  • Daniele T. Rodrigues 3 &
  • Fabrício D. S. Silva 5  

In this study, we applied a multivariate logistic regression model to identify deforested areas and evaluate the current effects on environmental variables in the Brazilian state of Rondônia, located in the southwestern Amazon region using data from the MODIS/Terra sensor. The variables albedo, temperature, evapotranspiration, vegetation index, and gross primary productivity were analyzed from 2000 to 2022, with surface type data from the PRODES project as the dependent variable. The accuracy of the models was evaluated by the parameters area under the curve (AUC), pseudo R 2 , and Akaike information criterion, in addition to statistical tests. The results indicated that deforested areas had higher albedo (25%) and higher surface temperatures (3.2 °C) compared to forested areas. There was a significant reduction of the EVI (16%), indicating water stress, and a decrease in GPP (18%) and ETr (23%) due to the loss of plant biomass. The most precise model (91.6%) included only surface temperature and albedo, providing important information about the environmental impacts of deforestation in humid tropical regions.

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Abreu, M. N. S., Siqueira, A. L., & Caiaffa, W. T. (2009). Regressão logística ordinal em estudos epidemiológicos. Revista Saúde Pública, 43 , 183–194. https://doi.org/10.1590/S0034-89102009000100025

Article   Google Scholar  

Alkama, R., & Cescatti, A. (2016). Biophysical climate impacts of recent changes in global forest cover. Science, 351 , 600–604. https://doi.org/10.1126/science.aac8083

Alvares, C. A., Stape, J. L., Sentelhas, P. C., Gonçlaves, J. L. M., & Sparovek, G. (2013). Koppen‟s climate classification map for Brazil. Meteorologische Zeitschrift, 22 , 711–728. https://doi.org/10.1127/0941-2948/2013/0507

Alves, L. M., Marengo, J. A., Fu, R., & Bombardi, R. J. (2017). Sensitivity of Amazon regional climate to deforestation. American Journal of Climate Change, 6 (1), 75–98. https://doi.org/10.4236/ajcc.2017.61005

Amelung, T. (1993). Tropical deforestation as an international economic problem. In: Giersch, H. (eds) Economic progress and environmental concerns. A Publications of the Egon-Sohmen-Foundation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-78074-5_10

Arekhi, S. (2011). Modeling spatial pattern of deforestation using GIS and logistic regression: A case study of northern Ilam forests, Ilam province, Iran. African Journal of Biotechnology, 10 , 6236–6249. https://doi.org/10.5897/AJB11.1122

Assunção, J., Gandour, C., & Rocha, R. (2015). Deforestation slowdown in the Brazilian Amazon: Prices or policies? Environment and Development Economics, 20 , 697–722. https://doi.org/10.1017/S1355770X15000078

Ayalew, L., & Yamagishi, H. (2005). The application of GIS-based logistic regression for landslide susceptibility mapping in the Kakuda-Yahiko Mountains, Central Japan. Geomorphology, 65 , 15–31. https://doi.org/10.1016/j.geomorph.2004.06.010

Barlow, J., Berenguer, E., Carmenta, R., & França, F. (2019). Clarifying Amazonia’s burning crisis. Global Change Biology, 26 , 319–321. https://doi.org/10.1111/gcb.14872

Bavaghar, M. P. (2015). Deforestation modeling using logistic regression and GIS. Journal of Forest Science, 61 , 193–199. https://doi.org/10.17221/78/2014-JFS

Bax, V., Francesconi, F., & Quinteroc, M. (2016). Spatial modeling of deforestation processes in the Central Peruvian Amazon. Journal for Nature Conservation, 29 , 79–88. https://doi.org/10.1016/j.jnc.2015.12.002

Biswas, S., Lasko, K. D., & Vadrevu, K. P. (2015). Fire disturbance in tropical forests of Myanmar—Analysis using MODIS satellite datasets. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 8 , 2273–2281. https://doi.org/10.1109/JSTARS.2015.2423681

Bragagnolo, L., da Silva, R. V., & Grzybowski, J. M. V. (2021). Amazon forest cover change mapping based on semantic segmentation by U-Nets. Ecological Informatics, 62 , 1–12. https://doi.org/10.1016/j.ecoinf.2021.101279

Brancalion, P. H., Broadbent, E. N., De-Miguel, S., Cardil, A., Rosa, M. R., Almeida, C. T., et al. (2020). Emerging threats linking tropical deforestation and the COVID-19 pandemic. Perspectives in Ecology and Conservation, 18 (4), 243–246. https://doi.org/10.1016/j.pecon.2020.09.006

Brown, F., Santos, G. P., Pires, F. F., & Costa, C. B. (2011). Brazil: Drought and fire response in the Amazon . World Resources Report Case Study: Washington DC, (1), 1–11. Retrieved March 18, 2021, from https://silo.tips/download/brazil-drought-and-fire-response-in-the-amazon

Bui, D. T., Tuan, T. A., Klempe, H., Pradhan, B., & Revhaug, I. (2016). Spatial prediction models for shallow landslide hazards: A comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree. Landslides, 13 (2), 361–378. https://doi.org/10.1007/s10346-015-0557-6

Cabral, A. I. R., Saito, C., Pereira, H., & Laques, A. E. (2018). Deforestation pattern dynamics in protected areas of the Brazilian Legal Amazon using remote sensing data. Applied Geography, 100 , 101–115. https://doi.org/10.1016/j.apgeog.2018.10.003

Cabral Júnior, J. B., Silva, C. M. S., de Almeida, H. A., et al. (2019). Detecting linear trend of reference evapotranspiration in irrigated farming areas in Brazil’s semiarid region. Theoretical and Applied Climatology, 138 , 215–225. https://doi.org/10.1007/s00704-019-02816-w

Cabral Júnior, J. B., Silva, H. J. F., & Reis, J. S. (2022). Características da Cobertura do Solo em Anos de Contrastes Climáticos (chuvoso e seco) no Oeste da Amazônia, Rio Branco-Acre, Utilizando Sensoriamento Remoto. Revista Brasileira de Geografia Física, 15 , 2704–2714. https://doi.org/10.26848/rbgf.v15.6.p2704-2714

Calef, M. P., McGuire, A. D., Epstein, H. E., Rupp, T. S., & Shugart, H. H. (2005). Analysis of vegetation distribution in Interior Alaska and sensitivity to climate change using a logistic regression approach. Journal of Biogeography, 32 (5), 863–878. https://doi.org/10.1111/j.1365-2699.2004.01185.x

Camarinha-Neto, G. F., Cohen, J. C. P., Dias-Júnior, C. Q., Sörgel, M., Cattanio, J. H., Araújo, A., Wolff, S., Kuhn, P. A. F., Souza, R. A. F., Rizzo, L. V., & Artaxo, P. (2021). The friagem event in the central Amazon and its influence on micrometeorological variables and atmospheric chemistry. Atmospheric Chemistry and Physics, 21 , 339–356. https://doi.org/10.5194/acp-21-339-2021

Campos, M. S., Adami, M., & Araújo, A. C. (2021). Análise do Albedo de Superfície da Palma de Óleo e Diferentes Usos e Coberturas do Solo no Leste da Amazônia. Revista Brasileira de Meteorologia, 36 , 15–21. https://doi.org/10.1590/0102-77863540070

Cardille, J. A., & Foley, J. A. (2003). Agricultural land-use change in Brazilian Amazonia between 1980 and 1995: Evidence from integrated satellite and census data. Remote Sensing of Environment, 87 , 551–562. https://doi.org/10.1016/j.rse.2002.09.001

Chatfield, C. (1995). Model uncertainty, data mining and statistical inference. Journal of the Royal Statistical Society, 158 , 419–466. https://doi.org/10.2307/2983440

Culf, A. D., Esteves, J. L., Marques Filho, A. O., & Rocha, H. R. (1996). Radiation, temperature and humidity over forest and pasture in Amazonia. In J. H. C. Gash, C. A. Nobre, J. Roberts, & R. L. Victoria (Eds.), Amazonian deforestation and climate (pp. 175–191). John Wiley.

Google Scholar  

da Rocha, H. R., Manzi, A. O., Cabral, O. M., et al. (2009). Patterns of water and heat flux across a biome gradient from tropical forest to savanna in Brazil. Journal of Geophysical Research, 114 (G00B12), 1–8. https://doi.org/10.1029/2007JG000640

da Silva, H. J. F., Santos, M. S., Cabral Júnior, J. B., & Spyrides, M. H. C. (2016). Modeling of reference evapotranspiration by multiple linear regression. Journal of Hyperspectral Remote Sensing, 6 (1), 44–58. https://doi.org/10.5935/2237-2202.20160005

da Silva, H. J. F., Gonçalves, W. A., & Bezerra, B. G. (2019). Comparative analyzes and use of evapotranspiration obtained through remote sensing to identify deforested areas in the Amazon. International Journal of Applied Earth Observation and Geoinformation, 78 , 163–174. https://doi.org/10.1016/j.jag.2019.01.015

da Silva, H. J. F., Gonçalves, W. A., Bezerra, B. G., Santos e Silva, C. M., Oliveira, CPd., & Mutti, P. R. (2022). Analysis of the influence of deforestation on the microphysical parameters of clouds in the Amazon. Remote Sensing, 14 (21), 5353. https://doi.org/10.3390/rs14215353

Dai, F. C., & Lee, C. F. (2002). Landslide characteristics and slope instability modeling using GIS Lantau Island, Hong Kong. Geomorphology, 42 , 213–238. https://doi.org/10.1016/S0169-555X(01)00087-3

Delgado, R. C., Pereira, M. G., Teodoro, P. E., Santos, G. L., Carvalho, D. C., Magistrali, I. C., & Vilanova, R. S. (2018). Seasonality of gross primary production in the Atlantic Forest of Brazil. Global Ecology and Conservation, 14 , 1–12. https://doi.org/10.1016/j.gecco.2018.e00392

Didan, K. (2015). MOD13A3 MODIS/Terra vegetation Indices Monthly L3 Global 1km SIN Grid V006. distributed by NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/MODIS/MOD13A3.006

Dlamini, W. M. (2016). Analysis of deforestation patterns and drivers in Swaziland using efficient Bayesian multivariate classifiers. Modeling Earth Systems and Environment, 2 , 1–14. https://doi.org/10.1007/s40808-016-0231-6

dos Santos Silva, F. D., da Costa, C. P. W., dos Santos Franco, V., Gomes, H. B., da Silva, M. C. L., dos Santos Vanderlei, M. H. G., Costa, R. L., da Rocha Júnior, R. L., Cabral Júnior, J. B., dos Reis, J. S., et al. (2023). Intercomparison of different sources of precipitation data in the Brazilian Legal Amazon. Climate, 11 (12), 241. https://doi.org/10.3390/cli11120241

Dreiseitl, S., & Machado, L. O. (2002). Logistic regression and artificial neural network classification models: A methodology review. Journal of Biomedical Informatics, 35 , 352–359. https://doi.org/10.1016/S1532-0464(03)00034-0

Dung, P. T., Chuc, M. D., Thanh, N. T. N., Hung, B. Q., & Chung, D. M. (2018). Comparison of resampling methods on different remote sensing images for Vietnam’s urban classification. Research and Development on Information and Communication Technology, 12 (15), 8–20. https://doi.org/10.32913/rd-ict.vol2.no15.663

Ekström, M., Esseen, P. A., Westerlund, B., Grafström, A., Jonsson, B. G., & Ståhl, G. (2018). Logistic regression for clustered data from environmental monitoring program. Ecological Informatics, 43 , 165–173. https://doi.org/10.1016/j.ecoinf.2017.10.006

Escobar, H. (2019). Brazilian president attacks deforestation data. Science, 365 , 419–419. https://doi.org/10.1126/science.365.6452.419

Evans, S. (2021, October 5). Which countries are historically responsible for climate change?. Carbon Brief: clear on climate . Retrieved January 7, 2023, from https://www.carbonbrief.org/analysis-which-countries-are-historically-responsible-for-climate-change

Fawcett, T. (2006). An introduction to ROC analysis. Pattern Recognition Letters, 27 , 861–874. https://doi.org/10.1016/j.patrec.2005.10.010

Fearnside, P. M. (2006). Desmatamento na Amazônia: Dinâmica, impactos e controle. Acta Amazonica, 36 (3), 395–400. https://doi.org/10.1590/S0044-59672006000300018

Fearnside, P. M. (2005). Deforestation in Brazilian Amazonia: History, rates, and consequences. Conservation Biology , 19 (3), 680–688. http://www.jstor.org/stable/3591054

Fernandes, A. A. T., Figueiredo-Filho, D. B., Rocha, E. C., & Nascimento. (2020). Read this paper if you want to learn logistic regression. Revista de Sociologia e Politica, 8 (74), 1–19. https://doi.org/10.1590/1678-987320287406en

Ferrante, L., & Fearnside, P. M. (2019). Brazil’s new president and ‘ruralists’ threaten Amazonia’s environment, traditional peoples and the global climate. Environmental Conservation, 46 , 261–263. https://doi.org/10.1017/S0376892919000213

Ferreira, R. R., Mutti, P., Mendes, K. R., Campos, S., Marques, T. V., Oliveira, C. P., Gonçalves, W., Mota, J., Difante, G., Urbano, S. A., Fernandes, L., Bezerra, B. G., & Santos e Silva, C. M. (2020). An assessment of the MOD17A2 gross primary production product in the Caatinga biome, Brazil. International Journal of Remote Sensing., 42 , 1275–1291. https://doi.org/10.1080/01431161.2020.1826063

Fohrer, N., Haverkamp, S., Eckhardt, K., & Frede, H. G. (2001). Hydrologic response to land use changes on the catchment scale. Physics and Chemistry of the Earth, 26 , 577–582. https://doi.org/10.1016/S1464-1909(01)00052-1

Fox, J., & Weisberg, S. (2018). An R companion to applied regression (3ª). Sage Publications.

Fox, J. C., Ades, P. K., & Bi, H. (2001). Stochastic structure and individual-tree growth models. Forest Ecology and Management, 154 (1–2), 261–276. https://doi.org/10.1016/S0378-1127(00)00632-0

Franca, R. R. (2015). Climatologia das chuvas em Rondônia – período 1981–2011. GEOgrafias, 11 (1), 44–58. https://doi.org/10.35699/2237-549X..13392

Freitas, S. R., Mello, M. C. S., & Cruz, C. B. M. (2005). Relationships between forest structure and vegetation indices in Atlantic Rainforest. Forest Ecology and Management, 218 , 353–362. https://doi.org/10.1016/j.foreco.2005.08.036

Galvão, L. S., Santos, J. R., Roberts, D. A., Breunig, F. M., Toomey, M., & Moura, Y. M. (2011). On intra-annual EVI variability in the dry season of tropical forest: A case study with MODIS and hyperspectral data. Remote Sensing of Environment, 115 , 2350–2359. https://doi.org/10.1016/j.rse.2011.04.035

Geoghegan, J., Villar, S. C., Klepeis, P., et al. (2001). Modeling tropical deforestation in the southern Yucatán peninsular region: Comparing survey and satellite data. Agriculture, Ecosystems and Environment, 85 (1–3), 25–46. https://doi.org/10.1016/S0167-8809(01)00201-8

Gholami, H., Mohamadifara, A., Sorooshianb, A., & Jansend, J. D. (2020). Machine-learning algorithms for predicting land susceptibility to dust emissions: The case of the Jazmurian Basin, Iran. Atmospheric Pollution Research, 11 (8), 1303–1315. https://doi.org/10.1016/j.apr.2020.05.009

Giam, X. (2017). Global biodiversity loss from tropical deforestation. Proceedings of the National Academy of Sciences, 114 , 5775–5777. https://doi.org/10.1073/pnas.1706264114

Gregoire, T. G., Schabenberger, O., & Barret, J. P. (1995). Linear modelling of irregularly spaced, unblanaced, longitudinal data from permanent-plot measurements. Canadian Journal of Forest Research, 25 (10), 237–256. https://doi.org/10.1139/x95-017

Griffiths, P., Jakimow, B., & Hostert, P. (2018). Reconstructing long term annual deforestation dynamics in Pará and Mato Grosso using the Landsat archive. Remote Sensing of Environment, 216 , 497–513. https://doi.org/10.1016/j.rse.2018.07.010

Grings, F., Roitberg, E., & Barraza, V. (2020). EVI time-series breakpoint detection using convolutional networks for online deforestation monitoring in Chaco forest. IEEE Transactions on Geoscience and Remote Sensing, 58 (2), 1303–1312. https://doi.org/10.1109/TGRS.2019.2945719

Hartkamp, A. D., de Beurs, K., Stein, A., & White, J. W. (1999). Interpolation techniques for climate variables. Geographic Information Systems , 99-01 , 1–24. https://original-ufdc.uflib.ufl.edu/UF00077518/00001/1j

Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic regression (2nd ed.). John Wiley & Sons.

Book   Google Scholar  

Hosmer, D. W., Hosmer, T., Cessie, S. L., & Lemeshow, S. (1997). A comparison of goodness-of-fit tests for the logistic regression model. Statistics in Medicine, 16 , 965–980. https://doi.org/10.1002/(SICI)1097-0258(19970515)16:9%3c965::AID-SIM509%3e3.0.CO;2-O

Huete, A. R., Didan, K., Shimabukuro, Y. E., Ratana, P., Saleska, S. R., Hutyra, L. R., Yang, W., Nemani, R. R., & Myneni, R. (2006). Amazon rainforests green-up with sunlight in dry season. Geophysical Research Letters, 33 , 1–4. https://doi.org/10.1029/2005GL025583

IBGE. (2022). Instituto Brasileiro de Geografia e Estatística. IBGE Estados. Rondônia . Retrieved July 14, 2024, from https://www.ibge.gov.br/cidades-e-estados/ro.html

INPE. (2024). Instituto Nacional de Pesquisas Espaciais – INPE, PRODES - Programa de desmatamento da Amazônia – Monitoramento da floresta amazônica por satélite.  Retrieved Marcy 20, 2024, from http://www.obt.inpe.br/OBT/assuntos/programas/amazonia/prodes

James, G., Witten. D., Hastie, T., & Tibshirani, R. (2014). An introduction to statistical learning: With applications in R. Springer Publishing Company, Incorporated (1st ed., pp. 99–204).  https://www.stat.berkeley.edu/users/rabbee/s154/ISLR_First_Printing.pdf

Japkowicz, N., & Stephen, S. (2002). The class imbalance problem: A systematic stud. Intelligent Data Analysis , 6 (5), 429–449. https://dl.acm.org/doi/10.5555/1293951.1293954

Jiang, X., Li, G., Lu, D., Moran, E., & Batistella, M. (2020). Modeling forest aboveground carbon density in the Brazilian Amazon with Integration of MODIS and Airborne LiDAR Data. Remote Sensing , 12 (20), 1–25. https://doi.org/10.3390/rs12203330

Khan, S. H., He, X., Porikli, F., & Bennamoun, M. (2017). Forest change detection in incomplete satellite images with deep neural networks. IEEE Transactions on Geoscience and Remote Sensing, 55 , 5407–5423. https://doi.org/10.1109/TGRS.2017.2707528

Kumar, R., Nandy, S., Agarwal, R., & Kushwaha, S. P. S. (2014). Forest cover dynamics analysis and prediction modeling using logistic regression model. Ecological Indicators, 45 , 444–455. https://doi.org/10.1016/j.ecolind.2014.05.003

Kummer, D. M., & Turner, B. L. (1994). The human causes of deforestation in Southeast Asia. BioScience, 44 , 323–328. https://doi.org/10.2307/1312382

Latimer, A. M., Wu, S., Gelfand, A. E., & Jr Silander, J. A. (2006). Building statistical models to analyze species distributions. Ecological Applications, 16 (1), 33–50. https://doi.org/10.1890/04-0609

Leite-Filho, A. T., Soares-Filho, B. S., Davis, J. L., Abrahão, G. M., & Börner, J. (2021). Deforestation reduces rainfall and agricultural revenues in the Brazilian Amazon. Nature Communicatons, 12 (2591), 1–7. https://doi.org/10.1038/s41467-021-22840-7

Li, J., & Heap, A. D. (2014). Spatial interpolation methods applied in the environmental sciences: A review. Environmental Modelling & Software, 53 , 173–189. https://doi.org/10.1016/j.envsoft.2013.12.008

Lindsey, R., & Dlugokencky, E. (2024, April 9). Climate change: Atmospheric carbon dioxide . Retrieved July 15, 2024, from https://www.climate.gov/news-features/understanding-climate/climate-change-atmospheric-carbon-dioxide

Lohmann, M., Santos, L. J. C., & Cumico, C. (2016). Avaliação de modelos regressivo logístico e baseado em rede neural para previsão da probabilidade de ocorrência de alagamentos em Curitiba - PR. Revista Brasileira de Geografia Física, 9 , 2247–2263. https://doi.org/10.5935/1984-2295.20160160

Ludeke, A. K., Maggio, R. C., & Reid, L. M. (1990). An analysis of antropogenic deforestation using logistic regression and GIS. Journal of Environmental Management, 31 , 247–259. https://doi.org/10.1016/S0301-4797(05)80038-6

Marengo, J. A. (2006). On the hydrological cycle of the Amazon basin: A historical review and current state-of-the-art. Revista Brasileira de Meteorologia, 21 , 1–19. https://doi.org/10.1590/0102-778620140049

Marengo, J. A., Nobre, C. A., & Culf, A. D. (1997). Climatic impacts of “Friagens” in forested and deforested areas of the Amazon basin. Journal of Applied Meteorology, 36 , 1553–1556. https://doi.org/10.1175/1520-0450(1997)036%3c1553:CIOFIF%3e2.0.CO;2

McElreath, R. (2020). Statistical rethinking: A Bayesian course with examples in R and Stan. CRC Press. Second Edition, USA. https://doi.org/10.1201/9780429029608

McFadden, D. (1987). Regression-based specification tests for the multinomial logit model. Journal of Econometrics, 4 (1–2), 63–82. https://doi.org/10.1016/0304-4076(87)90067-4

McRoberts, R., & Walters, B. (2012). Statistical inference for remote sensing-based estimates of net deforestation. Remote Sensing of Environment, 124 , 394–401. https://doi.org/10.1016/j.rse.2012.05.011

Miranda-Aragón, L., Treviño-Garza, E. J., Jiménez-Pérez, Aguirre-Calderón, O. A., González-Tagle, M. A., Pompa-García, M., & Aguirre-Salado, C. A. (2012). Modeling susceptibility to deforestation of remaining ecosystems in North Central Mexico with logistic regression. Journal of Forestry Research, 23 , 345–354. https://doi.org/10.1007/s11676-012-0230-z

Moore, N., & Messina, J. (2010). A landscape and climate data logistic model of tsetse distribution in Kenya. PLoS ONE, 5 , 1–10. https://doi.org/10.1371/journal.pone.0011809

Nandy, S., Kushwaha, S. P. S., & Mukhopadhyay, S. (2007). Monitoring the Chilla-Motichur wildlife corridor using geospatial tools. Journal for Nature Conservation, 15 (4), 237–244. https://doi.org/10.1016/j.jnc.2007.03.003

Nobre, C. A., Gash, J. H. C., Roberts, J. M., & Victoria, R. L. (1996). Conclusions from ABRACOS. In J. H. C. Gash, C. A. Nobre, J. Roberts, & R. L. Victoria (Eds.), Amazonian deforestation and climate. John Wiley.

Oliveira, G., & Moraes, E. C. (2013). Validação do balanço de radiação obtido a partir de dados MODIS/TERRA na Amazônia com medidas de superfície do LBA. Revista Acta Amazonica, 43 , 353–364. https://doi.org/10.1590/S0044-59672013000300011

Orriols, A., & Mansilla, E. B. (2005). The class imbalance problem in learning classifier systems: A preliminary study. Proc. 7th Annu. Workshop Genet. Evol. Comput., 74–78. https://doi.org/10.1145/1102256.1102271

Overmars, K. P., de Koning, G. H. J., & Veldkamp, A. (2003). Spatial autocorrelation in multi-scale land use models. Ecological Modelling, 164 (2–3), 257–270. https://doi.org/10.1016/S0304-3800(03)00070-X

Pereira da Silva, S. D., Santos, S. B., Pereira, P. C. G., Melo, M. R. S., & Eugenio, F. C. (2021). Landscape analysis in a municipality in the arc of deforestation of the Brazilian Amazon rainforest. Ecological Engineering, 173 , 106417. https://doi.org/10.1016/j.ecoleng.2021.106417

Petrie, M. D., Brunsell, N. A., Vargas, R., Collins, S. L., Flanagan, L. B., Hanan, N. P., Litvak, M. E., & Suyker, A. E. (2016). The sensitivity of carbon exchanges in Great Plains grasslands to precipitation variability. Journal of Geophysical Research: Biogeosciences, 121 , 280–294. https://doi.org/10.1002/2015JG003205

Phua, M. H., Tsuyuki, S., Furuya, N., & Lee, J. S. (2008). Detecting deforestation with a spectral change detection approach using multitemporal Landsat data: A case study of Kinabalu Park, Sabah, Malaysia. Journal of Environmental Management, 88 , 784–795. https://doi.org/10.1016/j.jenvman.2007.04.011

Pinheiro, T. F., Escada, M. I. S., Valeriano, D. M., Hostert, P., Gollnow, F., & Muller, H. (2016). Forest degradation associated with logging Frontier expansion in the Amazon: The BR-163 region in Southwestern Pará, Brazil. Earth Interactions, 20 (17), 1–16. https://doi.org/10.1175/EI-D-15-0016.1

Porwal, S., & Katiyar, S. K. (2014). Performance evaluation of various resampling techniques on IRS imagery. Seventh International Conference on Contemporary Computing, IC3, pp. 489–494. https://doi.ieeecomputersociety.org/10.1109/IC3.2014.6897222

Rajão, R., Soares-Filho, B., Nunes, F., Börner, J., Machado, L., Assis, D., Oliveira, A., Pinto, L., Ribeiro, V., Rausch, L., Gibbs, H., & Figueira, D. (2020). The rotten apples of Braziĺs agribusiness. Science, 369 (6501), 246–248. https://doi.org/10.1126/science.aba6646

Rondônia. (2002). Governo do Estado de Rondônia. Atlas Geoambiental de Rondônia . SEDAM: Secretaria de Estado do Desenvolvimento Ambiental (2 eds, pp. 1–142), Porto Velho, RO, Brasil.

Rossi, F. S., & Santos, G. A. A. (2020). Fire dynamics in Mato Grosso State, Brazil: The relative roles of gross primary productivity. Big Earth Data, 4 , 23–44. https://doi.org/10.1080/20964471.2019.1706832

Running, S., Mu, Q., Zhao, M. (2015). MOD17A2H MODIS/terra gross primary productivity 8-day L4 global 500m SIN grid V006, distributed by NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/MODIS/MOD17A2H.006

Running, S., Mu, Q., Zhao, M., & Moreno, A. (2019). MOD16A2GF MODIS/Terra net evapotranspiration gap-filled 8-day L4 global 500 m SIN grid V006. Distributed by NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/MODIS/MOD16A2GF.006 . Accessed 2021-07-15 .

Saatchi, S., Asefi-Najafabady, S., Malhi, Y., Aragão, L. E. O. C., Anderson, L. O., Myneni, R. B., & Nemanim, R. (2013). Persistent effects of a severe drought on Amazonian forest canopy. Proceedings of the National Academy of Sciences of the United States of America (PNAS), 110 , 565–570. https://doi.org/10.1073/pnas.1204651110

Sabajo, C. R., le Maire, G., June, T., Meijide, A., Roupsard, O., & Knohl, A. (2017). Expansion of oil palm and other cash crops causes an increase of the land surface temperature in the Jambi province in Indonesia. Biogeosciences, 14 , 4619–4635. https://doi.org/10.5194/bg-14-4619-2017

Saha, S., Saha, M., Mukherje, K., Arabameri, A., Ngo, P. T. T., & Paul, G. C. (2020). Predicting the deforestation probability using the binary logistic regression, random forest, ensemble rotational forest, REPTree: A case study at the Gumani River Basin, India. Science of the Total Environment., 730 , 1–20. https://doi.org/10.1016/j.scitotenv.2020.139197

Sales, F., Santiago, T., Biggs, T. W., Mullan, K., Sills, E. O., & Monteverde, C. (2020). Impacts of protected area deforestation on dry-season regional climate in the Brazilian Amazon. JRG Atmospheres, 125 , 1–25. https://doi.org/10.1029/2020JD033048

Schaaf, C., & Wang, Z. (2015). MCD43A3 MODIS/Terra+Aqua BRDF/albedo daily L3 global - 500m V006, distributed by NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/MODIS/MCD43A3.006

Schultz, M., Clevers, J. G. P. W., Carter, S., Verbesselt, J., Avitabile, V., Quang, H. V., & Herod, M. (2016). Performance of vegetation indices from Landsat time series in deforestation monitoring. International Journal of Applied Earth Observation and Geoinformation., 52 , 318–327. https://doi.org/10.1016/j.jag.2016.06.020

Searle, S. R., Casella, G., & Mcculloch, C. E. (1992). Analysis of Variance estimation for unbalanced data, Wiley Series in Probability and Statistics; John Wiley: New York, NY, USA, Chapter 5, 168–231. https://doi.org/10.1002/9780470316856.ch5

Shimabukuro, Y. E., Santos, J. R., Formaggio, A. R., Duarte, V., Rudorff, B. F. T. (2012). The Brazilian Amazon monitoring program: PRODES and DETER projects. Global Forest Monitoring from Earth Observation, 1st edition , 354, https://doi.org/10.1201/b13040

Silva Dias, M. A., Avissar, R., & Silva Dias, P. (2009). Modeling the regional and remote climatic impact of deforestation. In: Amazonia and global change, 186, 251–260. Wiley, Washington. https://doi.org/10.1029/2008GM000778

Silva Junior, C. H. L., Aragão, L. E. O. C., Fonseca, M. G., Almeida, C. T., Vedovato, L. B., & Anderson, L. O. (2018). Deforestation-induced fragmentation increases forest fire occurrence in central Brazilian Amazonia. Forests, 9 (6), 1–16. https://doi.org/10.3390/f9060305

Silva Júnior, C. H. L., Pessôa, A. C. M., Carvalho, N. S., Reis, J. B., Anderson, L. O., & Aragão, E. O. C. (2021). The Brazilian Amazon deforestation rate in 2020 is the greatest of the decade. Nature Ecology & Evolution, 5 , 144–145. https://doi.org/10.1038/s41559-020-01368-x

Smith, V., Portillo-Quintero, C., Sanchez-Azofeifa, A., & Hernandez-Stefanoni, J. L. (2019). Assessing the accuracy of detected breaks in Landsat time series as predictors of small scale deforestation in tropical dry forests of Mexico and Costa Rica. Remote Sensing of Environment, 221 , 707–721. https://doi.org/10.1016/j.rse.2018.12.020

Spracklen, D. V., Baker, J. C. A., Garcia-Carreras, L., & Marsham, J. H. (2018). The effects of tropical vegetation on rainfall. Annual Review of Environment and Resources, 43 , 193–218. https://doi.org/10.1146/annurev-environ-102017-030136

Srivastava, S., Singh, T. P., Singh, H., Kushwaha, S. P. S., & Roy, P. S., (2002). Assessment of large-scale deforestation in Sonitpur district of Assam. Current Science , 82 (12), 1479–1484. https://www.jstor.org/stable/24106185

Studley, H., & Weber, K. T. (2011). Comparison of image resampling techniques for satellite imagery, in final report: Assessing post-fire recovery of sagebrush-steppe rangelands in southeastern Idaho. In K. T. Weber, & K. Davis (Eds.), Pocatello, ID: Idaho State Univ, pp. 185–196. https://www.semanticscholar.org/paper/Comparison-of-Image-Resampling-Techniques-for-Studley/fa316fc18b22fe466f818bcea0edae76d08c91f9

Tarazona, Y., & Miyasiro-López, M. (2020). Monitoring tropical forest degradation using remote sensing. Challenges and opportunities in the Madre de Dios region, Peru. Remote Sensing Applications: Society and Environment, 19 , 1–13. https://doi.org/10.1016/j.rsase.2020.100337

Taylor, K. E. (2001). Summarizing multiple aspects of model performance in a single diagram. Journal of Geophysical Research, 106 (7), 7183–7192. https://doi.org/10.1029/2000JD900719

Trambauer, P., Dutra, E., Maskey, S., Werner, M., Pappenberger, F., van Beek, L. P. H., & Uhlenbrook, S. (2014). Comparison of different evaporation estimates over the African continent. Hydrology and Earth System Sciences, 18 , 193–212. https://doi.org/10.5194/hess-18-193-2014

Twisk, J. W. R. (2006). Applied multilevel analysis. Cambridge University Press, Amsterdam. https://doi.org/10.1017/CBO9780511610806

Valeriano, D. M., Mello, E. M. K., Moreira, J. C., Shimabukuro, Y. E., Duarte, V. (2004). Monitoring tropical forest from space: The PRODES digital project. International Archives of Photogrammetry Remote Sensing and Spatial Information Sciences , 35 , 272–274. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.183.8466

Valeriano, D.M., Escada, M.I.S., Camara, G., Amaral, S.; Maurano, L.E., Rennó, C.D., Almeida, C.A., & Monteiro, A.M.V. (2012). O monitoramento do desmatamento. In: MARTINE, George; OJIMA, Ricardo; BARBIERI, Alisson; CARMO, Roberto do (Ed.). População e Sustentabilidade na era das mudanças ambientais globais. ABEP: [s.n.]. 223-238. ISBN 978-85-85543-25-9.

Varamesh, S., Hosseini, S. M., & Rahimzadegan, M. (2017). Detection of land use changes in Northeastern Iran by Landsat satellite data. Applied Ecology and Environmental Research, 15 , 1443–1454. https://doi.org/10.15666/aeer/1503_14431454

von Randow, C., Manzi, A. O., Kruijt, B., Oliveira, P. J., Zanchi, F. B., Silva, R. L., Hodnett, M. G., Gash, J. H. C., Elbers, J. A., Waterloo, M. J., Cardoso, F. L., & Kabat, P. (2004). Comparative measurements and seasonal variations in energy and carbon exchange over forest and pasture in South West Amazonia. Theoretical and Applied Climatology, 78 , 5–26. https://doi.org/10.1007/s00704-004-0041-z

Walker, W. S., Gorelik, S. R., Baccini, A., Aragon-Osejo, J. L., Josse, C., Meyer, C., et al. (2020). The role of forest conversion, degradation, and disturbance in the carbon dynamics of Amazon indigenous territories and protected areas. Proceedings of the National Academy of Sciences - PNAS, 117 (6), 3015–3025. https://doi.org/10.1073/pnas.1913321117

Wan, Z., Hook, S., & Hulley, G. (2015). MOD11A2 MODIS/Terra land surface temperature/emissivity 8-day L3 global 1km SIN grid V006, distributed by NASA EOSDIS Land Processes DAAC, https://doi.org/10.5067/MODIS/MOD11A2.006

Wang, D., Liang, S., He, T., Yu, W., Schaaf, C., & Wang, Z. (2015). Estimating daily mean land surface albedo from MODIS data. Journal of Geophysical Research: Atmospheres, 120 , 4825–4841. https://doi.org/10.1002/2015JD023178

Wilks, D. S. (2009). Extending logistic regression to provide full-probability-distribution MOS forecasts. Meteorological Applications, 16 (3), 361–368. https://doi.org/10.1002/met.134

Wilson, K., Newton, A., Echeverria, C., Weston, C., & Burgman, M. (2005). A vulnerability analysis of the temperate forests of south central Chile. Biological Conservation, 122 , 9–21. https://doi.org/10.1016/j.biocon.2004.06.015

Yamamoto, J. K., & Landim, P. M. B. (2013). Geoestatística: Conceitos e Aplicações. Oficina de Textos (1ª). São Paulo.

Yang, X., Ren, L., Singh, V. P., Liu, X., Yuan, F., Jiang, S., & Yong, B. (2012). Impacts of land use land cover changes on evapotranspiration and runoff at Shalamulun River watershed, China. Hdrology Research, 4 , 1–2. https://doi.org/10.2166/nh.2011.120

Zhang, L., & Gove, J. H. (2005). Spatial assessment of model errors from four regression techniques. Forest Science, 51 (4), 334–346. https://doi.org/10.1093/forestscience/51.4.334

Zhang, L., Ma, Z., & Guo, L. (2008). Spatially assessing model errors of four regression techniques for three types of forest stands. Forestry: An International Journal of Forest Research, 81 (2), 209–225. https://doi.org/10.1093/forestry/cpn014

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Acknowledgements

The authors would like to acknowledge the Federal University of Rio Grande do Norte (UFRN) for the encouragement of research through the Postgraduate Program in Climate Science (PPGCC).

The author Helder José Farias da Silva declares that the financial support was provided by the Coordination for the Improvement of Higher Education Personnel code 001. The authors would like to thank the Federal University of Rio Grande do Norte (UFRN) for the financial support through the Postgraduate Program in Climate Science (PPGCC) and the Coordenação de Aperfeiçoamento de Pessoal de Nivel Superior–Brasil (CAPES)—finance Code 001.

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Helder J. F. da Silva

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Weber A. Gonçalves, Bergson G. Bezerra, Cláudio M. Santos e Silva & Cristiano P. de Oliveira

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Helder J. F. Silva, Weber Gonçalves Andrade, Bergson Bezerra Guedes, Claudio Moises Santos e Silva, and Cristiano Prestrelo de Oliveira wrote the main text. Jorio Bezerra Cabral Junior, Daniele Rodrigues Torres, and Fabricio Daniel Santos e Silva prepared Fig.  3 and Tables 4 and 5 . All authors reviewed the manuscript.

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da Silva, H.J.F., Gonçalves, W.A., Bezerra, B.G. et al. Analysis of environmental variables and deforestation in the amazon using logistical regression models. Environ Monit Assess 196 , 911 (2024). https://doi.org/10.1007/s10661-024-13086-z

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Public Policies for the Protection of the Amazon Forest: What Works and How to Improve

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Public policy plays a fundamental role in protecting the native vegetation of the Amazon Forest. It guides the actions of the several different players needed for forest conservation, bringing together evidence-based approaches that are grounded in the use of state of the art technology and in the application of robust technical knowledge. Brazil is fully capable of developing and implementing a public policy agenda for Amazon protection that is innovative, strategic, and effective — it has done this before.

Over the past two decades, while the country gained broad experience in the use of policy instruments to protect its native vegetation, academia produced a robust body of empirical evidence on these instruments’ effectiveness and impact. This report consolidates the main findings of the academic literature that rigorously evaluates policies aimed at combating deforestation in the Brazilian Amazon. Additionally, it draws on empirical evidence to propose ways of strengthening Brazil’s policy agenda for protecting the Amazon Forest whilst promoting the region’s sustainable development. The report thereby aims to contribute to the design and implementation of an effective policy framework for Amazon conservation.

What Works to Protect the Amazon Forest?

Public policy efforts to combat deforestation significantly contributed to the Brazilian Amazon deforestation slowdown, when the rate of forest clearing fell by more than 80%, decreasing from 27,800 square kilometers in 2004 to 4,600 square kilometers in 2012 (INPE 2021a). The strengthening of environmental command and control was pivotal to this. In a context in which the bulk of deforestation was illegal, the pioneering use of near-real-time remote monitoring technology to detect forest loss and target environmental control operations greatly increased law enforcement’s capacity to apply binding and costly penalties to offenders. Monitoring and law enforcement inhibited illegal practices and curbed deforestation at scale. The evidence suggests that the reduction in forest clearings did not jeopardize local agricultural production. It also indicates that the policy was cost-effective and that it contributed to the expansion and permanence of secondary vegetation in the Amazon. 

In addition to enhanced monitoring and law enforcement, public policy innovations introduced targeted action in critical areas and conditioned the concession of subsidized rural credit upon proof of compliance with environmental and land tenure regulations. Both helped reduce forest loss in the Amazon. Brazil also started using territorial protection as a barrier to the advance of deforestation. Protected areas and indigenous lands in regions under high forest clearing pressure effectively shielded forests, but it is unclear if they significantly contributed to the reduction in the aggregate level of deforestation

These different policy efforts were carried out within the scope of a federal plan to combat deforestation in the Amazon, which has been highlighted in the academic literature as a central element for planning and coordinating strategic actions. Although there is still room to deepen understanding about the impacts of these multiple policies, there is a consensus that they were effective in reducing deforestation in the Brazilian Amazon. However, they were not the only forest protection measures implemented in Brazil within the last two decades. Several other policy efforts were enacted during this period, but the available empirical evidence on their causal effects is still limited. Examples include payment for environmental services mechanisms, supply chain agreements for zero deforestation, and subnational initiatives. Although this report addresses these efforts in less detail, this should not be interpreted as an indication that they are not relevant for the protection of the Amazon Forest. Rather, this is an acknowledgment of the weak empirical evidence currently associated with them, and a suggestion of relevant topics for future research.

The academic literature delivers a clear message: public policies are an effective way of protecting native vegetation in the Amazon. Brazil must use this knowledge to ensure the continuity of what has already proved effective, fill in the gaps in its understanding of forest conservation policy impacts, and seek innovative solutions for the challenges that remain.

Strengthening Amazon Forest Protection

After a strong reduction between 2004 and 2012, deforestation in the Amazon Forest started trending upwards and, as of 2019, has shown signs of acceleration (INPE 2021a, 2021b). Conservation policies enacted over the past two decades were effective in containing forest clearings, but these policies are no longer enough. In addition to improving its efforts to fight deforestation, Brazil must incorporate new dimensions of forest protection to its policy agenda for Amazon conservation. This report proposes three critical courses of action for strengthening Amazon protection:

Deforestation : It is imperative that Brazil eliminate the impunity currently associated with illegal forest clearings. To that effect, it is critical to uphold environmental governance that supports effective environmental sanctioning procedures and penalties, both of which are central to law enforcement’s capacity to inhibit illegal practices. Strategic efforts to combat deforestation should also target priority areas.

Forest Degradation : The country must deepen its understanding of forest degradation. How does it contribute to a process of forest loss in the Amazon? How does it relate to economic activity? How does it respond to public policy? Brazil can draw on this understanding to adopt a strategic approach to fight forest degradation in the Amazon and thereby enhance the impact of conservation efforts in the region.

S econdary Vegetation : Brazil must urgently monitor secondary vegetation in the Amazon. Although tropical forest regrowth covers vast areas, it remains invisible to forest monitoring systems. The country has the technology and technical expertise needed to develop the systematic monitoring of its secondary vegetation, but this requires support from public policy. Monitoring forest regrowth in the Amazon is vital both for its protection and for advancing the understanding about this phenomenon. This is key to incorporating secondary vegetation into a strategy for large-scale restoration of degraded ecosystems.

Amazon Forest Protection Requires Solid Support from Public Policy

Brazil has a unique opportunity to align the interests of diverse government entities, productive sectors, and civil society around a single effort. As it takes steps to better conserve its native vegetation, the country protects this precious environmental asset, along with all forms of life that depend on it directly or indirectly — but that’s not all. It also boosts production capacity and gains a competitive edge in global markets, while combating illegal activity and moving towards a position of global leadership on climate action.

Protecting the Amazon demands solid political leadership and an unwavering commitment to an evidence-based public policy agenda. In this context, the government is responsible for planning, supporting, and coordinating strategic activities across different spheres of action, thematic areas, and segments of society. The country knows what must be done and is fully capable of doing it. Brazil must treat the protection of its Amazon Forest with the necessary urgency.

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case study on deforestation in amazon forest

Forests are key for our survival as a species.

Keeping forests standing is crucial for a healthy planet and affects our daily lives without us knowing it.

Why Forests Matter to Us All

  • Seventy percent of the plants identified by the U.S. National Cancer Institute as useful in the treatment of cancer only grow in the rainforest.
  • Deforestation in forests accounts for 11 percent of human-caused greenhouse gas emissions.
  • The Amazon produces 20% of the oxygen we breathe
  • The Amazon stores 80-120 billion tons of carbon, stabilizing our planet’s climate
  • 1/5 of the world’s fresh water is found in the Amazon basin.
  • Forests provide direct livelihoods to millions of people living in and around them.
  • Forests provide a habitat for wildlife, insects, and plants, which are essential for the health of our planet

How We Are Keeping the Amazon Protected

Creating a model for creating protected areas with the purpose of conservation: conservation concessions.

We have created replicable conservation models for conservation, most notably the concept of conservation concessions, where a national government relies on a private partner such as us to manage public land for conservation.

In 2000, we created the 360,000-acre Los Amigos Conservation Concession, the first of its kind in the world, and have been successfully managing it since then.

This model of conservation has been successfully applied elsewhere in the region and around the world, helping remove the financial and operational burden of land management from strained governments.

case study on deforestation in amazon forest

Creating conservation corridors to connect forests and ensure their health

We protect landscapes with an eye toward the big picture of connecting tracts of protected areas over time, magnifying our impact for biodiversity conservation.

Our impact goes beyond the boundaries of the conservation areas we help create. We work in the vast land between conservation areas to ensure connectivity among them.

By doing so, we ensure animals can move across uninterrupted patches of tropical forests, which is vital for species preservation and a healthy forest.

case study on deforestation in amazon forest

Direct forest protection: creating conservation areas and helping manage forest lands sustainably

Directly protecting forests is at the core of all the conservation efforts we do.

We focus on identifying, creating and caring for parks, reserves, and other types of conservation areas.

We work with governments, individual landowners, indigenous communities, and others to build a network of protected lands in Peru and Bolivia, creating a living conservation mosaic.

case study on deforestation in amazon forest

Reforesting: Bringing back lost forests 

Amazon Conservation has reforested degraded lands with over 250,000 trees to date, most through community-based reforestation projects in the Manu National Park buffer zone.

We prioritize reforestation with native species, which help restore ecosystems and ensure continued provision of ecosystem services, such as carbon sequestration, water regulation, and soil conservation.

Our reforestation model is linked with a holistic approach to strengthening community land management, including territorial planning and reclaiming ancestral agricultural practices. This both improves long-term durability of conservation outcomes and increases household incomes.

case study on deforestation in amazon forest

Stopping threats to forests using the latest in science and technology

We defend the forests which cannot defend themselves.

By using cutting-edge technology like satellite imagery, radar, drones, and camera traps through our MAAP Project and our Southwest Amazon Drone Center, we are able to find, track, and expose deforestation happening on the ground in near-real time.

This enables us to alert the public and local authorities to mobilize and stop deforestation before it gets to a point of no return.

Providing a central hub for scientists to study the Amazon

Our research stations in Peru and Bolivia offer premier facilities in strategic locations of the Andean Amazon’s altitudinal gradient that allow scientists to conduct short-term and long-term studies on the ground.

These studies contribute to the global scientific community, raise awareness about tropical ecology and conservation, and inform our conservation decisions.

More on Conservation Concessions and Conservation Corridors

What is a conservation concession.

Conservation concessions and conservation corridors are critical to protecting forest cover and biodiversity across the southwestern Amazon.

It’s a public/private partnership designed to promote conservation, biodiversity, and sustainable development.

This groundbreaking concept– a “conservation concession” – facilitates the participation of private organizations in achieving national biodiversity conservation goals by entrusting the long-term protection of publicly-owned land to not-for-profit institutions in exchange for investments in conservation and sustainable development.

Conservation concessions are essential tools for environmental protection and we’re working with our sister organizations to create concessions throughout the Amazon rainforest.

Today, our Los Amigos conservation concession is among the Amazon’s most active centers for research, natural resource management training, and environmental education. The conservation concession model has now been replicated in other places throughout Peru, and even as far away as China, covering close to 5 million acres.

What is a Conservation Corridor?

Conservation corridors provide freedom of movement for animals and allow for biodiversity and the ecological and evolutionary processes.

A conservation corridor is a native wildlife habitat that is undisturbed by human activity that joins larger areas of similar wildlife habitat.  These corridors are critical to maintaining the natural ecological process, allowing the movement of animals throughout their natural space.

Manu – Tambopata Corridor: from Manu National Park to Tambopata National Reserve. The Manu – Tambopata (MAT) Corridor connects Peru’s Manu National Park with Bolivia’s Madidi National Park via ACA’s Los Amigos Conservation Concession and the Tambopata National Reserve.

The last unprotected stretch, a north-south corridor that crosses the Interoceanic Highway to the Malinowsky River, will protect over 518,920 acres (210,000 hectares) of tropical forest. ACA’s Los Amigos Biological Station (CICRA), one of the most productive research stations in the Amazon basin, is located here.

Castaña Corridor: from Las Piedras River in Peru to Manuripi National Reserve in Bolivia. The Castaña Corridor incorporates much of ACA’s earlier conservation efforts to develop the first Brazil nut concessions in Peru. We currently provide technical support and training to more than 420 families in northern Madre de Dios and several in the buffer zone of Tambopata National Reserve. These concessions cover 875,998 acres (354,504 hectares) of primary forest along the Interoceanic Highway.

The Castaña Corridor also protects the habitat of keystone species like jaguars in the Las Piedras River basin.

Yungas Corridor: from Manu National Park to Bahuaja Sonene National Park. The Yungas Corridor is designed to protect an unbroken stretch of forest from lowland valleys to Andean highlands between Manu and Bahuaja Sonene National Parks.

Climate change is expected to force species to migrate to higher elevations, and this corridor will provide a refuge for a genetically diverse population of plants and animals.

Los Amigos Conservation Hub

Amazon Conservation pioneers innovative conservation tools, creating models that others can follow, and, in 2001, Amazon Conservation and Conservación Amazónica-ACCA established the world’s first private conservation concession.

In Peru, as in other countries in Latin America, a substantial portion of the land is publicly owned. Although national conservation policies may contemplate the protection of these areas, governments frequently lack the human and financial resources to implement effective on-the-ground actions.

Amazon Conservation negotiated with the Peruvian government to develop a new way to help protect forests under state control. In Peru, the contracts are perpetually renewable, given for 40 years initially and subject to an evaluation of compliance every 5 years.

Today, the Los Amigos Conservation Concession protects the watershed of the Los Amigos River and 360,000 acres of old-growth Amazonian forest in the department of Madre de Dios in southeastern Peru.

Los Amigos is home to a remarkable diversity of plant and animal species. Bordering world-famous Manu National Park to the east, the Los Amigos watershed forms part of a 20 million-acre block of protected wilderness in southeastern Peru.

The landscape is a mosaic of terrestrial and aquatic habitats, including palm swamps, bamboo thickets, oxbow lakes, and various types of flooded and non-flooded forests. Wildlife is abundant, including 12 globally threatened species and abundant Amazonian fauna including giant otters, harpy eagles, spider monkeys, and jaguars. The area contains 13 species of primates. By way of comparison, all of Costa Rica holds only four.

Los Amigos Conservation Concession Goals

Our ongoing management of the Los Amigos Conservation Concession will:

  • Ensure lasting protection of the Los Amigos watershed
  • Develop a world-class research center and a model private protected area
  • Train a new generation of Latin American ecologists and natural resource managers
  • Create sustainable economic and social benefits for local populations
  • Develop new watershed conservation models for Amazonian eco-development
  • Develop new ecosystem management understanding and practices
  • Establish new models for sustainable long-term forest conservation by employing innovative conservation finance tools, such as carbon and biodiversity offset markets
  • Monitor and compare pristine ecosystems with those disrupted by logging, mining and agriculture
  • Empower a new generation of Peruvians who will act as the long-term guardians, mentors, and conservation planners in the region

ACA thanks the  International Conservation Fund of Canada (ICFC)  for their generous support to create and grow an endowment fund that provides funding for the management of Los Amigos Conservation Concession.

Haramba queros wachiperi conservation concession.

Haramba Queros is an indigenous community of the Wachiperi ethnicity living in the lush rainforests in the foothills of the Andes mountains, located 4 hours east of Cusco, Peru. They depend on their forest homeland for food, shelter, traditional clothing, and natural medicines.

In July 2008, the Haramba Queros Wachiperi Ecological Reserve became the world’s first conservation concession managed by an indigenous group. The Haramba Queros Wachiperi Conservation Concession protects 17,238 acres of highly diverse montane rainforest on the eastern slopes of Peru’s southern Andes.

It provides a buffer against the impacts of climate change, secures the Queros’ water supply and source of medicinal plants, sustains their access to forest products, and helps the community maintain its cultural traditions. These forests also serve as an ecological buffer zone for the world-renowned Manu National Park.

Amazon Conservation and its Peruvian sister organization, Conservación Amazónica-ACCA, provided technical support to the Wachiperi throughout the process of applying for the concession, creating its management plan, and seeking approval from the Peruvian forest service.

We continue to support the Queros community in their management and monitoring of the concession, as well as in the development of sustainable livelihoods activities, such as ecotourism and handicraft production, which help fund the management of the concession.

Conservation Concessions in Peru

Conservation concessions, an innovation written into Peruvian forestry legislation in 2000, provide a unique opportunity for the conservation of large state-owned lands that would otherwise be unmanaged. A conservation concession is a long-term contractual partnership between the national government and a non-government actor, whereby the civil society actor manages state-owned lands for purposes of ecosystem and biodiversity conservation.

In Peru, SERFORdr is the national agency overseeing conservation concessions.

SERFOR is required by law to approve a technical proposal drafted by the applicant organization prior to awarding a conservation concession. Once the technical proposal is approved, the applicant prepares a management plan that includes an investment commitment. The award process involves substantial public consultations with local and regional stakeholders, including local communities, regional authorities, and the private sector.

Once the concession is awarded, the concessionaire provides annual reports and inspections as well as comprehensive evaluation by SERFOR every five years to verify compliance with the management plan, if the concessionaire is found to comply with the management plan the contract is automatically extended for another forty-year period.

The Latest from the Amazon

New funds support sustainable management of regional conservation areas in peru’s cuzco region.

As part of a significant step in advancing the sustainable management of regional conservation areas in Peru, our sister organization in Peru Conservación Amazónica–ACCA donated 290,000 Peruvian Soles (about $77,100) to the Cuzco Regional Government in support of a project aiming to create a regional system of protected areas in the country’s Andes-Amazon region. This […]

Supporter Spotlight: Ryan Bailey

From Nashville to the Amazon: Linking Business, Sustainability, and Ecosystems Business supporters are one of Amazon Conservation’s favorite avenues to raise awareness and support for our work because of their unhindered desire to give back to the planet. Whether directly donating to our work, promoting awareness of the Amazon’s importance to their clients, running campaigns […]

New MAAP Series Follows Soy-Based Deforestation in the Bolivian Amazon

In the first two installments of a new series monitoring soy deforestation in Bolivia, we provide more accurate estimates of total soy production-based deforestation and some of the major actors driving this significant source of deforestation. It is generally well known that the production of commodities such as soy, oil palm, and cattle are major […]

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Living World - Amazon Case Study

The Amazon is the largest tropical rainforest on Earth. It sits within the Amazon River basin, covers some 40% of the South American continent and as you can see on the map below includes parts of eight South American countries: Brazil, Bolivia, Peru, Ecuador, Colombia, Venezuela, Guyana, and Suriname. The actual word “Amazon” comes from river.

Map of the Amazon

Amazing Amazon facts; • It is home to 1000 species of bird and 60,000 species of plants • 10 million species of insects live in the Amazon • It is home to 20 million people, who use the wood, cut down trees for farms and for cattle. • It covers 2.1 million square miles of land • The Amazon is home to almost 20% of species on Earth • The UK and Ireland would fit into the Amazon 17 times!

The Amazon caught the public’s attention in the 1980s when a series of shocking news reports said that an area of rainforest the size of Belgium was being cut down and subsequently burnt every year. This deforestation has continued to the present day according to the Sao Paulo Space Research Centre. In 2005 they had lost 17% of Amazon rainforest or 650000 square kilometres. Their satellite data is also showing increased deforestation in parts of the Amazon. The process of deforestation The Amazon helps a Newly Emerging Economy(NEE), Brazil, to make money. They build roads into the forest, logging firms then go in and take out valuable hard woods such as mahogany and cedar, worth thousands of pounds in richer economies like Europe. Then farmers, often cattle ranchers from big companies, burn the rest to make way for cattle pasture. 75% of cleared areas are used in this way. This is clearly shown on the map on figure 22 in red. Many of the deforested areas follow roads and branch off from there.  Deforestation is also worse in the South and South East of the Amazon basin, closer to major centres of population in Brazil.

Deforestation in the Amazon

© WWF   Source  Used with permission.

The causes of deforestation 1. Subsistence and commercial farming – subsistence farming is where poor farmers occupy plots of the forest to grow food to feed themselves and their families. They clear forest and then burn it, hence the name slash and burn.  They grow crops until the soil is exhausted and then move on.  This contributes to deforestation but not as much as commercial farming (Farming to sell produce for a profit to retailers or food processing companies). The Brazilian region of Mato Grosso was affected by deforestation in the 1980s and 1990s. 43% of rainforest losses were in this region, and area almost ½ the size of France. It has been replaced by fields for grain and cattle. This has allowed Brazil to overtake Australia as the largest exporter of beef in the world. The land is also flat and easy to farm. It also has high temperatures and lots of rainfall.

2. Logging – This involves cutting down trees for sale as timber or pulp.  The timber is used to build homes, furniture, etc. and the pulp is used to make paper and paper products.  Logging can be either selective or clear cutting. Selective logging is selective because loggers choose only wood that is highly valued, such as mahogany. Clear-cutting is not selective.  Loggers are interested in all types of wood and therefore cut all of the trees down, thus clearing the forest, hence the name- clear-cutting.

3. Road building – trees are also clear for roads.  Roads are an essential way for the Brazilian government to allow development of the Amazon rainforest.  However, unless they are paved many of the roads are unusable during the wettest periods of the year.  The Trans Amazonian Highway has already opened up large parts of the forest and now a new road is going to be paved, the BR163 is a road that runs 1700km from Cuiaba to Santarem. The government planned to tarmac it making it a superhighway. This would make the untouched forest along the route more accessible and under threat from development.

4. Mineral extraction – forests are also cleared to make way for huge mines. The Brazilian part of the Amazon has mines that extract iron, manganese, nickel, tin, bauxite, beryllium, copper, lead, tungsten, zinc and gold! 

Construction of the Belo Monte Dam

The Belo Monte dam site under construction, copyright  Used with the kind permission of Phil Clarke-Hill  - His website is amazing, click here to see it.

5. Energy development – This has focussed mainly on using Hydro Electric Power, and there are 150 new dams planned for the Amazon alone.  The dams create electricity as water is passed through huge pipes within them, where it turns a turbine which helps to generate the electricity.  The power in the Amazon is often used for mining.  Dams displace many people and the reservoirs they create flood large area of land, which would previously have been forest.  They also alter the hydrological cycle and trap huge quantities of sediment behind them. The huge Belo Monte dam started operating in April 2016 and will generate over 11,000 Mw of power.  A new scheme the 8,000-megawatt São Luiz do Tapajós dam has been held up because of the concerns over the impacts on the local Munduruku people.

Chief Raoni in Paris with his petition against Belo Monte Dam.

6. Settlement & population growth – populations are growing within the Amazon forest and along with them settlements.  Many people are migrating to the forest looking for work associated with the natural wealth of this environment. Settlements like Parauapebas, an iron ore mining town, have grown rapidly, destroying forest and replacing it with a swath of shanty towns. The population has grown from 154,000 in 2010 to 220,000 in 2012. The Brazilian Amazon’s population grew by a massive 23% between 2000 and 2010, 11% above the national average.

Impacts of deforestation – economic development, soil erosion, contribution to climate change. • Every time forest is cleared species are lost – so we lose BIODIVERSITY • Climate Change - Burning the forest releases greenhouse gasses like CO2.  This contributes to the warming of our planet via climate change and global warming.  In addition, the loss of trees prevents CO2 being absorbed, making the problem worse. The Amazon also helps to drive the global atmospheric system. There is a lot of rainfall there and changes to the Amazon could disrupt the global system. • Economic development – Brazil has used the forests as a way to develop their country.  The forest has many natural riches that can be exploited.  In addition, Brazil has huge foreign debt and lots of poor people to feed, so they want to develop the forest. May Brazilians see deforestation as a way to help develop their country and improve people’s standard of living. • Soil erosion - the soils of the Amazon forest are not fertile and are quickly exhausted once the forest is cleared. The farmers now artificially fertilise the soil when in the past the nutrient cycle would have done this naturally.  In addition, the lack of forest cover means that soils are exposed to the rainfall.  This washes huge amounts of soil into rivers in the process of soil erosion.

NEXT TOPIC - Living World - Sustainable Forest Management

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Internet Geography

Sustainable Management of the Amazon Rainforest

Tropical rainforest under canopy

The Amazon rainforest is located in the north of South America, spanning an area of around 8 million km2 including parts of Brazil, Columbia, Peru, Venezuela, Ecuador Bolivia, Suriname, Guyana and French Guyana.

In some areas of the Amazon rainforest, sustainable management strategies are in place to ensure people today can get the resources they need in a way that ensures future generations can also benefit from the ecosystem .

Sustainable management strategies are affected by political and economic factors .

Governance 

Governance relates to control of rainforests and who has a say in how rainforests are used. In some areas, rainforests are protected by national and international laws.

In Brazil, the largest protected area of rainforest is the Central Amazon Conservation Complex (CACC) . The CACC covers 60000 km2 as is classified as a World Heritage Site by the United Nations, which means it is protected by international treaties. Limits are placed on hunting , logging and fishing and access is limited.

Central Amazon Conservation Complex (CACC)

Central Amazon Conservation Complex (CACC)

In other areas local communities, with the help of NGOs, are involved in rainforest governance. In Columbia, an organisation known as Natütama is working with the local community in Puerto Nariño to protect river species such as the Amazon River dolphin. Local people are employed to teach members of the community on how to protect habitats and endangered river species. Local fishermen collect information about the number and distribution of species and report illegal hunting.

Commodity Value

Commodity value means assigning a value to different good and services in a rainforest. Sustainable management ensures rainforests are worth. more than the value of the timber and other resources that can be extracted, such as gold. An example of this is sustainable foresty, which balances the removal of trees to sell with the conservation of the forest.

Selective logging involves only removing a small number of trees, allowing the forest to regenerate naturally. This saves money in the long run as logging companies do not need to replace felled trees.

Sustainable logging companies such as Precious Woods Amazon place limits on the number of trees being cut down so the rainforest can recover. They also use a range of species so that none are over-exploited.

International agreements try to reduce illegal logging and ensure timber comes from sustainable sources. The Forestry Stewardship Council allows the use of its logo by companies that operate in a sustainable way so consumers know they are buying sustainable timber.

FSC certified wood

FSC certified wood

Ecotourism is a type of tourism that minimises damage to the environment and benefits local people.

An example of an ecotourism project is the Yachana Lodge in Equador. It is located in a remote area of the Amazon Rainforest where local people rely on subsistence farming.

Yachana Lodge

Yachana Lodge

The project employs local people. This provides a reliable source of income and a better quality of life. The project encourages local people to use the rainforest in a sustainable way so tourists continue to visit.

Volunteers work with local Amazon youth who study at the Yachana Technical High School where learning is focused on five main areas:

  • Rainforest conservation
  • Sustainable agriculture
  • Renewable energy
  • Animal husbandry
  • Micro-enterprise development .

Tourists are only allowed to visit in small groups, minimising their impact on the environment. Tourists take part in activities that help raise awareness of conservation issues.

Entrance fees are paid by the tourists which are invested in conservation and education projects.

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IMAGES

  1. Case Study

    case study on deforestation in amazon forest

  2. Ecology Case Study

    case study on deforestation in amazon forest

  3. Deforestation in Amazon Rainforest Rose By 17% In 2020

    case study on deforestation in amazon forest

  4. Record deforestation in the Amazon rainforest confirms official

    case study on deforestation in amazon forest

  5. Deforestation in the Amazon

    case study on deforestation in amazon forest

  6. Study Shows Impacts of Deforestation and Forest Burning on Amazon

    case study on deforestation in amazon forest

VIDEO

  1. Deforestation

  2. What are the social impacts of deforestation in the Amazon rainforest?

  3. Urgent Warning: Deforestation in the Amazon

  4. 💯 Deforestation #shorts #facts #deforestation #viral #forest #youtubeshorts

  5. Bolivia on fire

  6. Mapping Deforestation Patterns in Brazil and India with ArcGIS Pro's Living Atlas

COMMENTS

  1. Amazon Deforestation: A Regional Conservation Case Study

    The study, called "Contribution of the Amazon protected areas program to forest conservation," measured historical deforestation from 2008 to 2020 using satellite deforestation data called PRODES, and compared deforestation rates in ARPA supported areas to non-ARPA supported areas. It was determined that ARPA supported areas experienced 9-39% ...

  2. Amazon Rainforest Deforestation: A Case Study of Rondônia

    The motivation for choosing the impact of deforestation on the health of the Brazilian Amazon Rainforest for this report is due to its ecological importance and extensive biodiversity. The Amazon Rainforest is a massive terrestrial sink and maintains the balance of Earth's climate system (Malhi et al., 2008).

  3. Case Study: The Amazon Rainforest

    Case Study: The Amazon Rainforest | GEOG 30N

  4. Impacts of Deforestation on the Amazon Rainforest Over Time

    Previous studies have described that Earth loses an area of forest the size of 48 football fields every minute of every day- with deforestation in the Amazon accounting for the largest share. But, many believe that improved data quality and quantity about both the location of deforestation and human invasion on forests can help a quicker ...

  5. Deforestation, warming flip part of Amazon forest from carbon sink to

    The study area, which represents about 20 percent of the Amazon basin, has lost 30 percent of its rainforest. New results from a nine-year research project in the eastern Amazon rainforest finds that significant deforestation in eastern and southeastern Brazil has been associated with a long-term decrease in rainfall and increase in temperature during the dry season, turning what was once a ...

  6. (PDF) Deforestation and Forest Degradation in the Amazon

    The forest disturbance trends for Colombian humid forests in the last 20 years show incre ases and decreases. staying on a level between ca. 4,000 km2 a nd 8,0 00 km. The forest disturbance area ...

  7. "We are killing this ecosystem": the scientists tracking the Amazon's

    Trouble in the Amazon

  8. Amazon deforestation causes strong regional warming

    In this study, we examined both local and nonlocal effects due to forest loss across the Amazon biome where deforestation is dramatically changing the landscape ().Large-scale deforestation started in the 1970 s, and about 17% of the Amazon had been deforested by 2021, with rates of deforestation accelerating in the past few years (25, 26).A business-as-usual scenario of continued ...

  9. Critical transitions in the Amazon forest system

    Critical transitions in the Amazon forest system

  10. Study Shows the Impacts of Deforestation and Forest Burning on

    A new study, co-authored by a team of researchers including UConn Ecology and Evolutionary Biology researcher Cory Merow provides the first quantitative assessment of how environmental policies on deforestation, along with forest fires and drought, have impacted the diversity of plants and animals in the Amazon.

  11. Amazon Deforestation and Climate Change

    Destruction of the rain forest in Brazil has decreased from about 19,943 square kilometers (7,700 square miles) per year in the late 1990s to about 5,180 square kilometers (2,000 square miles) per year now. Moving forward, the major challenge will be fighting illegal deforestation. Join Gisele Bundchen when she meets with one of Brazil's top ...

  12. How deregulation, drought and increasing fire impact Amazonian

    How deregulation, drought and increasing fire impact ...

  13. PDF The Deforestation of the Amazon: A Case Study in Understanding

    Based on estimates of 1% annual tropical forest loss, the Amazon may be losing as many as 11 to 16 species per day (Wilson 1989), and the resulting ecosystems are often highly degraded (Buschbacher 1986). Te deforestation of Amazonia presents a challenging study of the interactions among people, their values, and the environment.

  14. Deforestation: Case Studies

    Nearly two-thirds of the Amazon rainforest - the largest rainforest in the world - is within Brazil's national borders. 8 Any examination of deforestation case studies would be incomplete without considering tree felling in Brazil. History of deforestation in Brazil. Humans first discovered the Amazon rainforest about 13,000 years ago.

  15. Deforestation in the Amazon Rainforest: causes, effects, solutions

    However, it's being destroyed at an alarming rate, which has negative consequences in the form of greenhouse gas emissions, habitat loss for animals, and a reduction in biodiversity. Let's explore four solutions to combat the Amazon deforestation: 1. Increased government regulations.

  16. Analysis of environmental variables and deforestation in the amazon

    In this study, we applied a multivariate logistic regression model to identify deforested areas and evaluate the current effects on environmental variables in the Brazilian state of Rondônia, located in the southwestern Amazon region using data from the MODIS/Terra sensor. The variables albedo, temperature, evapotranspiration, vegetation index, and gross primary productivity were analyzed ...

  17. The Amazon Domino Effect: How Deforestation Can Trigger ...

    The Amazon Domino Effect: How Deforestation Can ...

  18. Public Policies for the Protection of the Amazon Forest: What Works and

    This report consolidates the main findings of the academic literature that rigorously evaluates policies aimed at combating deforestation in the Brazilian Amazon. Additionally, it draws on empirical evidence to propose ways of strengthening Brazil's policy agenda for protecting the Amazon Forest whilst promoting the region's sustainable development. The report thereby aims to contribute to ...

  19. What are the effects of deforestation in the Amazon?

    What are the effects of deforestation in the Amazon?

  20. Amazon Forest

    Deforestation in forests accounts for 11 percent of human-caused greenhouse gas emissions. The Amazon produces 20% of the oxygen we breathe. The Amazon stores 80-120 billion tons of carbon, stabilizing our planet's climate. 1/5 of the world's fresh water is found in the Amazon basin. Forests provide direct livelihoods to millions of people ...

  21. Living World

    The Amazon is the largest tropical rainforest on Earth. It sits within the Amazon River basin, covers some 40% of the South American continent and as you can see on the map below includes parts of eight South American countries: Brazil, Bolivia, Peru, Ecuador, Colombia, Venezuela, Guyana, and Suriname. The actual word "Amazon" comes from river.

  22. Sustainable Management of the Amazon Rainforest

    Sustainable Management of the Amazon Rainforest

  23. Case Study

    Case Study - Deforestation in Amazon - Free download as PDF File (.pdf), Text File (.txt) or read online for free. The document provides information about deforestation in the Amazon rainforest, including: 1) The Amazon rainforest contains 390 billion trees and is one of Earth's defenses against climate change, but deforestation has surged to record highs in recent years.

  24. Detection of Deforestation Using Prisma Hyperspectral and Deep Learning

    Abstract: Accurate detection of deforestation and logging activities is useful to monitor large scale damages in the Amazon forests. In this study, we focused on the use of deep learning based one dimensional convolutional neural network (1D-CNN) with Hyperspectral Precursor of the Application Mission (PRISMA) hyperspectral data for the detection of deforestation in the Amazon Forest.