rainforest deforestation case study

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Case Study: The Amazon Rainforest

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.

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.

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.

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

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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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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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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

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  

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 Debate
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Deforestation and Forest Loss

Explore long-term changes in deforestation and deforestation rates across the world today., which countries are gaining, and which are losing forests.

Before we look specifically at trends in deforestation across the world, it's useful to understand the net change in forest cover. The net change in forest cover measures any gains in forest cover — either through natural forest expansion or afforestation through tree planting — minus deforestation.

This map shows the net change in forest cover across the world. Countries with a positive change (shown in green) are gaining forests faster than they're losing them. Countries with a negative change (shown in red) are losing more than they're able to restore.

A note on UN FAO forestry data

Data on net forest change, afforestation, and deforestation is sourced from the UN Food and Agriculture Organization's Forest Resources Assessment . Since year-to-year changes in forest cover can be volatile, the UN FAO provides this annual data averaged over five-year periods.

How much deforestation occurs each year?

Net forest loss is not the same as deforestation — it measures deforestation plus any gains in forest over a given period.

Between 2010 and 2020, the net loss in forests globally was 4.7 million hectares per year. 1 However, deforestation rates were much higher.

The UN FAO estimates that 10 million hectares of forest are cut down each year.

This interactive map shows deforestation rates across the world.

Read more about historical deforestation here:

The world has lost one-third of its forest, but an end of deforestation is possible

Over the last 10,000 years the world has lost one-third of its forests. An area twice the size of the United States. Half occurred in the last century.

Global deforestation peaked in the 1980s. Can we bring it to an end?

Since the end of the last ice age — 10,000 years ago — the world has lost one-third of its forests. 2 Two billion hectares of forest — an area twice the size of the United States — has been cleared to grow crops, raise livestock, and for use as fuelwood.

Previously, we looked at this change in global forests over the long run. What this showed was that although humans have been deforesting the planet for millennia, the rate of forest loss accelerated rapidly in the last few centuries. Half of the global forest loss occurred between 8,000 BCE and 1900; the other half was lost in the last century alone.

To understand this more recent loss of forest, let’s zoom in on the last 300 years. The world lost 1.5 billion hectares of forest over that period. That’s an area 1.5 times the size of the United States.

In the chart, we see the decadal losses and gains in global forest cover. On the horizontal axis, we have time, spanning from 1700 to 2020; on the vertical axis, we have the decadal change in forest cover. The taller the bar, the larger the change in forest area. This is measured in hectares; one hectare is equivalent to 10,000 m².

Forest loss measures the net change in forest cover: the loss in forests due to deforestation plus any increase in forest through afforestation or natural expansion. 3

Unfortunately, there is no single source that provides consistent and transparent data on deforestation rates over this period of time. Methodologies change over time, and estimates — especially in earlier periods — are highly uncertain. This means I’ve had to use two separate datasets to show this change over time. As we’ll see, they produce different estimates of deforestation for an overlapping decade — the 1980s — which suggests that these are not directly comparable. I do not recommend combining them into a single series, but the overall trends are still applicable and tell us an important story about deforestation over the last three centuries.

The first series of data comes from Williams (2006), who estimates deforestation rates from 1700 to 1995. 4 Due to poor data resolution, these are often given as average rates over longer periods — for example, annual average rates are given over the period from 1700 to 1849 and 1920 to 1949. That’s why these rates look strangely consistent over a long period of time.

The second series comes from the UN Food and Agriculture Organization (FAO). It produces a new assessment of global forests every five years. 5

The rate and location of forest loss changed a lot. From 1700 to 1850, 19 million hectares were being cleared every decade. That’s around half the size of Germany.

Most temperate forests across Europe and North America were being lost at this time. Population growth meant that today’s rich countries needed more and more resources such as land for agriculture, wood for energy, and construction. 6

Moving into the 20th century, there was a stepwise change in demand for agricultural land and energy from wood. Deforestation rates accelerated. This increase was mostly driven by tropical deforestation in countries across Asia and Latin America.

Global forest loss appears to have reached its peak in the 1980s. The two sources do not agree on the magnitude of this loss: Williams (2006) estimates a loss of 150 million hectares — an area half the size of India — during that decade.

Interestingly, the UN FAO 1990 report also estimated that deforestation in tropical ‘developing’ countries was 154 million hectares. However, it was estimated that the regrowth of forests offset some of these losses, leading to a net loss of 102 million hectares. 7

The latest UN Forest Resources Assessment estimates that the net loss in forests has declined in the last three decades, from 78 million hectares in the 1990s to 47 million hectares in the 2010s.

This data maps an expected pathway based on what we know from how human-forest interactions evolve.

As we explore in more detail later on , countries tend to follow a predictable development in forest cover, a U-shaped curve. 8 They lose forests as populations grow and demand for agricultural land and fuel increases, but eventually, they reach the so-called ‘forest transition point’ where they begin to regrow more forests than they lose.

That is what has happened in temperate regions: they have gone through a period of high deforestation rates before slowing and reversing this trend.

However, many countries — particularly in the tropics and sub-tropics — are still moving through this transition. Deforestation rates are still very high.

Deforestation rates are still high across the tropics

Large areas of forest are still being lost in the tropics today. This is particularly tragic because these are regions with the highest levels of biodiversity.

Let’s look at estimates of deforestation from the latest UN Forest report. This shows us raw deforestation rates without any adjustment for the regrowth or plantation of forests, which is arguably not as good for ecosystems or carbon storage.

This is shown in the chart below.

We can see that the UN does estimate that deforestation rates have fallen since the 1990s. However, there was very little progress from the 1990s to the 2000s and an estimated 26% drop in rates in the 2010s. In 2022, the FAO published a separate assessment based on remote sensing methods; it did not report data for the 1990s, but it also estimated a 29% reduction in deforestation rates from the early 2000s to the 2010s.

This is progress, but it needs to happen much faster. The world is still losing large amounts of primary forests every year. To put these numbers in context, during the 1990s and first decade of the 2000s, an area almost the size of India was deforested. 9 Even with the ‘improved’ rates in the 2010s, this still amounted to an area around twice the size of Spain. 10

The regrowth of forests is a positive development. In the chart below, we see how this affects the net change in global forests. Forest recovery and plantation ‘offsets’ a lot of deforestation such that the net losses are around half the rates of deforestation alone.

But we should be cautious here: it’s often not the case that the ‘positives’ of regrowing on planting one hectare of forest offset the ‘losses’ of one hectare of deforestation. Cutting down one hectare of rich tropical rainforest cannot be completely offset by the creation of on hectare of plantation forest in a temperate country.

Forest expansion is positive but does not negate the need to end deforestation.

The history of deforestation is a tragic one, in which we have lost not only wild and beautiful landscapes but also the wildlife within them. But, the fact that forest transitions are possible should give us confidence that a positive future is possible. Many countries have not only ended deforestation but have actually achieved substantial reforestation. It will be possible for our generation to achieve the same on a global scale and bring the 10,000-year history of forest loss to an end.

If we want to end deforestation, we need to understand where and why it’s happening, where countries are within their transition, and what can be done to accelerate their progress through it. We need to pass the transition point as soon as possible while minimizing the amount of forest we lose along the way.

In this article , I look at what drives deforestation, which helps us understand what we need to do to solve it.

Forest definitions and comparisons to other datasets

There is no universal definition of what a ‘forest’ is. That means there are a range of estimates of forest area and how this has changed over time.

In this article, in the recent period, I have used data from the UN’s Global Forest Resources Assessment (2020). The UN carries out these global forest stocktakes every five years. These forest figures are widely used in research, policy, and international targets, such as the Sustainable Development Goals .

The UN FAO has a very specific definition of a forest. It’s “land spanning more than 0.5 hectares with trees higher than 0.5 meters and a canopy cover of more than 10%, or trees able to reach these thresholds in situ.”

In other words, it has criteria for the area that must be covered (0.5 hectares), the minimum height of trees (0.5 meters), and a density of at least 10%.

Compare this to the UN Framework Convention on Climate Change (UNFCCC), which uses forest estimates to calculate land use carbon emissions, and its REDD+ Programme, where low-to-middle-income countries can receive finance for verified projects that prevent or reduce deforestation. It defines a forest as having a density of more than 10%, a minimum tree height of 2-5 meters, and a smaller area of at least 0.05 hectares.

It’s not just forest definitions that vary between sources. What is measured (and not measured) differs, too. Global Forest Watch is an interactive online dashboard that tracks ‘tree loss’ and ‘forest loss’ across the world. It measures this in real time and can provide better estimates of year-to-year variations in rates of tree loss.

However, the UN FAO and Global Forest Watch do not measure the same thing.

The UN FAO measures deforestation based on how land is used. It measures the permanent conversion of forested land to another use, such as pasture, croplands, or urbanization. Temporary changes in forest cover, such as losses through wildfire or small-scale shifting agriculture, are not included in deforestation figures because it is assumed that they will regrow. If the use of land has not changed, it is not considered deforestation.

Global Forest Watch (GFW) measures temporary changes in forests. It can detect changes in land cover but does not differentiate the underlying land use. All deforestation would be considered tree loss, but a lot of tree loss would not be considered as deforestation.

As GFW defines ‘forest loss’, “Loss” indicates the removal or mortality of tree cover and can be due to a variety of factors, including mechanical harvesting, fire, disease, or storm damage. As such, “loss” does not equate to deforestation.”

Therefore, we cannot directly compare these sources. This article from Global Forest Watch gives a good overview of the differences between the UN FAO's and GFW's methods.

Since GFW uses satellite imagery, its methods continually improve. This makes its ability to detect changes in forest cover even stronger. But it also means that comparisons over time are more difficult. It currently warns against comparing pre-2015 and post-2015 data since there was a significant methodological change at that time. Note that this is also a problem in UN FAO reports, as I’ll soon explain.

What data from GFW makes clear is that forest loss across the tropics is still very high, and in the last few years, little progress has been made. Since UN FAO reports are only published in 5-year intervals, they miss these shorter-term fluctuations in forest loss. The GFW’s shorter-interval stocktakes of how countries are doing will become increasingly valuable.

One final point to note is that UN FAO estimates have also changed over time, with improved methods and better access to data.

I looked at how net forest losses in the 1990s were reported across five UN reports: 2000, 2005, 2010, 2015, and 2020.

Estimated losses changed in each successive report:

• 2000 report : Net losses of 92 million hectares
• 2005 report : 89 million hectares
• 2010 report : 83 million hectares
• 2015 report : 72 million hectares
• 2020 report : 78 million hectares

This should not affect the overall trends reported in the latest report: the UN FAO should — as far as is possible — apply the same methodology to its 1990s, 2000s, and 2010s estimates. However, it does mean we should be cautious about comparing absolute magnitudes across different reports.

This is one challenge in presenting 1980 figures in the main visualization in this article. Later reports have not updated 1980 figures, so we have to rely on estimates from earlier reports. We don’t know whether 1980s losses would also be lower with the UN FAO’s most recent adjustments. If so, this would mean the reductions in net forest loss from the 1980s to 1990s were lower than is shown from available data.

Forest transitions: why do we lose then regain forests?

Globally, we deforest around ten million hectares of forest every year. 11 That’s an area the size of Portugal every year. Around half of this deforestation is offset by regrowing forests, so overall, we lose around five million hectares each year.

Nearly all — 95% — of this deforestation occurs in the tropics . But not all of it is to produce products for local markets. 14% of deforestation is driven by consumers in the world’s richest countries — we import beef, vegetable oils, cocoa, coffee, and paper that has been produced on deforested land. 12

The scale of deforestation today might give us little hope for protecting our diverse forests. But by studying how forests have changed over time, there’s good reason to think that a way forward is possible.

Many countries have lost and then regained forests over millennia.

Time and time again, we see examples of countries that have lost massive amounts of forests before reaching a turning point where deforestation not only slows but forests return. In the chart, we see historical reconstructions of country-level data on the share of land covered by forest (over decades, centuries, or even millennia, depending on the country). I have reconstructed long-term data using various studies, which I’ve documented here .

Many countries have much less forest today than they did in the past. Nearly half (47%) of France was forested 1000 years ago; today that’s just under one-third (31.4%). The same is true of the United States; back in 1630, 46% of the area of today’s USA was covered by forest. Today, that’s just 34%.

One thousand years ago, 20% of Scotland’s land was covered by forest. By the mid-18th century, only 4% of the country was forested. But then the trend turned, and it moved from deforestation to reforestation. For the last two centuries, forests have been growing and are almost back to where they were 1000 years ago. 13

Forest Transitions: the U-shaped curve of forest change

What’s surprising is how consistent the pattern of change is across so many countries; as we’ve seen, they all seem to follow a ‘U-shaped curve.’ They first lose lots of forest but reach a turning point and begin to regain it again.

We can illustrate this through the so-called ‘Forest Transition Model.’ 14 This is shown in the chart. It breaks the change in forests into four stages, explained by two variables: the amount of forest cover a region has and the annual change in cover (how quickly it is losing or gaining forest). 15

Stage 1 – The Pre-Transition phase is defined as having high levels of forest cover and no or only very slow losses over time. Countries may lose some forest each year, but this is at a very slow rate. Mather refers to an annual loss of less than 0.25% as a small loss.

Stage 2 – The Early Transition phase is when countries start to lose forests very rapidly. Forest cover falls quickly, and the annual loss of forest is high.

Stage 3 – The Late Transition phase is when deforestation rates start to slow down again. At this stage, countries are still losing forest each year, but at a lower rate than before. At the end of this stage, countries are approaching the ‘transition point.’

Stage 4 – The Post-Transition phase is when countries have passed the ‘transition point’ and are now gaining forest again. At the beginning of this phase, the forest area is at its lowest point. But forest cover increases through reforestation. The annual change is now positive.

Why do countries lose and then regain forests?

Many countries have followed this classic U-shaped pattern. What explains this?

There are two reasons that we cut down forests:

• Forest resources: we want the resources that they provide — the wood for fuel, building materials, or paper;
• Land: We want to use the land they occupy for something else, such as farmland to grow crops, pasture to raise livestock or land to build roads and cities.

Our demand for both of these initially increases as populations grow and poor people get richer . We need more fuelwood to cook, more houses to live in, and, importantly, more food to eat.

But, as countries continue to get richer, this demand slows. The rate of population growth tends to slow down. Instead of using wood for fuel, we switch to fossil fuels , or hopefully, more renewables and nuclear energy . Our crop yields improve, so we need less land for agriculture.

This demand for resources and land is not always driven by domestic markets. As I mentioned earlier, 14% of deforestation today is driven by consumers in rich countries.

The Forest Transition, therefore, tends to follow a ‘development’ pathway. 16 As a country achieves economic growth, it moves through each of the four stages. This explains the historical trends we see in countries across the world today. Rich countries — such as the USA, France, and the United Kingdom — have had a long history of deforestation but have now passed the transition point. Most deforestation today occurs in low-to-middle-income countries.

Where are countries in the transition today?

If we look at where countries are in their transition today, we can understand where we expect to lose and gain forest in the coming decades. Most of our future deforestation is going to come from countries in the pre-or early-transition phase.

Several studies have assessed the stage of countries across the world. 17 The most recent analysis to date was published by Florence Pendrill and colleagues (2019), which looked at each country’s stage in the transition, the drivers of deforestation, and the role of international trade. 18 To do this, they used the standard metrics discussed in our theory of forest transitions earlier: the share of land that is forested and the annual change in forest cover.

In the map, we see their assessment of each country’s stage in the transition. Most of today’s richest countries — all of Europe, North America, Japan, and South Korea — have passed the turning point and are now regaining forests. This is also true for major economies such as China and India. The fact that these countries have recently regained forests is also visible in the long-term forest trends above.

Across tropical and sub-tropical countries, we have a mix: many upper-middle-income countries are now in the late transition phase. Brazil, for example, went through a period of very rapid deforestation in the 1980s and 90s (its ‘early transition’ phase), but its losses have slowed, meaning it is now in the late transition. Countries such as Indonesia, Myanmar, and the Democratic Republic of Congo are in the early transition phase and are losing forests quickly. Some of the world’s poorest countries are still in the pre-transition phase. In the coming decades, we might expect to see the most rapid loss of forests unless these countries take action to prevent it and the world supports them in their goal.

Not all forest loss is equal: what is the difference between deforestation and forest degradation?

Fifteen billion trees are cut down every year. 19 The Global Forest Watch project — using satellite imagery — estimates that global tree loss in 2019 was 24 million hectares. That’s an area the size of the United Kingdom.

These are big numbers and important ones to track: forest loss creates a number of negative impacts, ranging from carbon emissions to species extinctions and biodiversity loss. But distilling changes to this single metric — tree or forest loss — comes with its own issues.

The problem is that it treats all forest loss as equal. It assumes the impact of clearing primary rainforest in the Amazon to produce soybeans is the same as logging plantation forests in the UK. The latter will experience short-term environmental impacts but will ultimately regrow. When we cut down primary rainforest, we transform this ecosystem forever.

When we treat these impacts equally, we make it difficult to prioritize our efforts in the fight against deforestation. Decision makers could give as much of our attention to European logging as to the destruction of the Amazon. As we will see later, this would be a distraction from our primary concern: ending tropical deforestation. The other issue that arises is that ‘tree loss’ or ‘forest loss’ data collected by satellite imagery often doesn’t match the official statistics reported by governments in their land use inventories. This is because the latter only captures deforestation — the replacement of forest with another land use (such as cropland). It doesn’t capture trees that are cut down in planted forests; the land is still forested; it’s now just regrowing forests.

In the article, we will look at the reasons we lose forests, how these can be differentiated in a useful way, and what this means for understanding our priorities in tackling forest loss.

Understanding and seeing the drivers of forest loss

‘Forest loss’ or ‘tree loss’ captures two fundamental impacts on forest cover: deforestation and forest degradation .

Deforestation is the complete removal of trees for the conversion of forest to another land use such as agriculture, mining, or towns and cities. It results in a permanent conversion of forest into an alternative land use. The trees are not expected to regrow . Forest degradation measures a thinning of the canopy — a reduction in the density of trees in the area — but without a change in land use. The changes to the forest are often temporary, and it’s expected that they will regrow.

From this understanding, we can define five reasons why we lose forests:

• Commodity-driven deforestation is the long-term, permanent conversion of forests to other land uses such as agriculture (including oil palm and cattle ranching), mining, or energy infrastructure.
• Urbanization is the long-term, permanent conversion of forests to towns, cities, and urban infrastructure such as roads.
• Shifting agriculture is the small- to medium-scale conversion of forest for farming, which is later abandoned so that forests regrow. This is common in local subsistence farming systems where populations will clear forest, use it to grow crops, and then move on to another plot of land.
• Forestry production is the logging of managed, planted forests for products such as timber, paper, and pulp. These forests are logged periodically and allowed to regrow.
• Wildfires destroy forests temporarily. When the land is not converted to a new use, forests can regrow in the following years.

Thanks to satellite imagery, we can get a birds-eye view of what these drivers look like from above. In the figure, we see visual examples from the study of forest loss classification by Philip Curtis et al. (2018), published in Science . 20

Commodity-driven deforestation and urbanization are deforestation : the forested land is completely cleared and converted into another land use — a farm, mining site, or city. The change is permanent. There is little forest left. Forestry production and wildfires usually result in forest degradation — the forest experiences short-term disturbance but, if left alone, is likely to regrow. The change is temporary. This is nearly always true of planted forests in temperate regions — there, planted forests are long-established and do not replace primary existing forests. In the tropics, some forestry production can be classified as deforestation when primary rainforests are cut down to make room for managed tree plantations. 18

'Shifting agriculture’ is usually classified as degradation because the land is often abandoned, and the forests regrow naturally. But it can bridge between deforestation and degradation depending on the timeframe and permanence of these agricultural practices.

One-quarter of forest loss comes from tropical deforestation

We’ve seen the five key drivers of forest loss. Let’s put some numbers on them.

In their analysis of global forest loss, Philip Curtis and colleagues used satellite images to assess where and why the world lost forests between 2001 and 2015. The breakdown of forest loss globally and by region is shown in the chart. 20

Just over one-quarter of global forest loss is driven by deforestation. The remaining 73% came from the three drivers of forest degradation: logging of forestry products from plantations (26%), shifting, local agriculture (24%), and wildfires (23%).

We see massive differences in how important each driver is across the world. 95% of the world’s deforestation occurs in the tropics [we look at this breakdown again later]. In Latin America and Southeast Asia, in particular, commodity-driven deforestation — mainly the clearance of forests to grow crops such as palm oil and soy and pasture for beef production — accounts for almost two-thirds of forest loss.

In contrast, most forest degradation — two-thirds of it — occurs in temperate countries. Centuries ago, it was mainly temperate regions that were driving global deforestation [we take a look at this longer history of deforestation in a related article ] . They cut down their forests and replaced them with agricultural land long ago. But this is no longer the case: forest loss across North America and Europe is now the result of harvesting forestry products from tree plantations or tree loss in wildfires.

Africa is also different here. Forests are mainly cut and burned to make space for local subsistence agriculture or fuelwood for energy. This ‘shifting agriculture’ category can be difficult to allocate between deforestation and degradation: it often requires close monitoring over time to understand how permanent these agricultural practices are.

Africa is also an outlier as a result of how many people still rely on wood as their primary energy source. Noriko Hosonuma et al. (2010) looked at the primary drivers of deforestation and degradation across tropical and subtropical countries specifically. 21  The breakdown of forest degradation drivers is shown in the following chart. Note that in this study, the category of subsistence agriculture was classified as a deforestation driver, so it is not included. In Latin America and Asia, the dominant driver of degradation was logging for products such as timber, paper, and pulp — this accounted for more than 70%. Across Africa, fuelwood and charcoal played a much larger role — it accounted for more than half (52%).

This highlights an important point: around one in five people in sub-Saharan Africa have access to clean fuels for cooking, meaning they still rely on wood and charcoal. With increasing development, urbanization, and access to other energy resources, Africa will shift from local subsistence activities into commercial commodity production — both in agricultural products and timber extraction. This follows the classic ‘forest transition’ model with development, which we look at in more detail in a related article .

Tropical deforestation should be our primary concern

The world loses almost six million hectares of forest each year to deforestation. That’s like losing an area the size of Portugal every two years. 95% of this occurs in the tropics. The breakdown of deforestation by region is shown in the chart. 59% occurs in Latin America, with a further 28% from Southeast Asia. In a related article , we look in much more detail at which agricultural products and which countries are driving this.

As we saw previously, this deforestation accounts for around one-quarter of global forest loss. 27% of forest loss results from ‘commodity-driven deforestation’ — cutting down forests to grow crops such as soy, palm oil, and cocoa, raising livestock on pasture, and mining operations. Urbanization, the other driver of deforestation, accounts for just 0.6%. It’s the foods and products we buy, not where we live, that have the biggest impact on global land use.

It might seem odd to argue that we should focus our efforts on tackling this quarter of forest loss (rather than the other 73%). But there is good reason to make this our primary concern.

Philipp Curtis and colleagues make this point clear. On their Global Forest Watch platform, they were already presenting maps of forest loss across the world. However, they wanted to contribute to a more informed discussion about where to focus forest conservation efforts by understanding why forests were being lost. To quote them, they wanted to prevent “a common misperception that any tree cover loss shown on the map represents deforestation.” And to “identify where deforestation is occurring; perhaps as important, show where forest loss is not deforestation.”

Why should we care most about tropical deforestation? There is a geographical argument (why the tropics?) and an argument for why deforestation is worse than degradation.

Tropical forests are home to some of the richest and most diverse ecosystems on the planet. Over half of the world’s species reside in tropical forests. 22 Endemic species are those which only naturally occur in a single country. Whether we look at the distribution of endemic mammal species , bird species , or amphibian species , the map is the same: tropical and subtropical countries are packed with unique wildlife. Habitat loss is the leading driver of global biodiversity loss. 23 When we cut down rainforests, we are destroying the habitats of many unique species and reshaping these ecosystems permanently. Tropical forests are also large carbon sinks and can store a lot of carbon per unit area. 24

Deforestation also results in larger losses of biodiversity and carbon relative to degradation. Degradation drivers, including logging and especially wildfires, can definitely have major impacts on forest health: animal populations decline, trees can die, and CO 2 is emitted. However, the magnitude of these impacts is often less than the complete conversion of forests. They are smaller and more temporary. When deforestation happens, almost all of the carbon stored in the trees and vegetation — called the ‘aboveground carbon loss’ —  is lost. Estimates vary, but on average, only 10-20% of carbon is lost during logging and 10-30% from fires. 25 In a study of logging practices in the Amazon and Congo, forests retained 76% of their carbon stocks shortly after logging. 26 Logged forests recover their carbon over time, as long as the land is not converted to other uses (which is what happens in the case of deforestation).

Deforestation tends to occur in forests that have been around for centuries if not millennia. Cutting them down disrupts or destroys established, species-rich ecosystems. The biodiversity of managed tree plantations, which are periodically cut, regrown, cut again, and then regrown, is not the same.

That is why we should be focusing on tropical deforestation. Since agriculture is responsible for 60 to 80% of it, what we eat, where it’s sourced from, and how it is produced are our strongest levers to bring deforestation to an end.

Carbon emissions from deforestation: are they driven by domestic demand or international trade?

95% of global deforestation occurs in the tropics. Brazil and Indonesia alone account for almost half. After long periods of forest clearance in the past, most of today’s richest countries are increasing tree cover through afforestation.

This might put the responsibility for ending deforestation solely on tropical countries. But, supply chains are international. What if this deforestation is being driven by consumers elsewhere?

Many consumers are concerned that their food choices are linked to deforestation in some of these hotspots. Since three-quarters of tropical deforestation is driven by agriculture, that’s a valid concern. It feeds into the popular idea that ‘eating local’ is one of the best ways to reduce your carbon footprint. In a previous article , I showed that the types of food you eat matter much more for your carbon footprint than where it comes from — this is because transport usually makes up a small percentage of your food’s emissions, even if it comes from the other side of the world. If you want to reduce your carbon footprint, reducing meat and dairy intake — particularly beef and lamb — has the largest impact.

But understanding the role of deforestation in the products we buy is important. If we can identify the producing and importing countries and the specific products responsible, we can direct our efforts towards interventions that will really make a difference.

Read more about the imported deforestation here:

Do rich countries import deforestation from overseas?

Rich countries import foods produced on deforested land in the tropics. How much deforestation do they import?

One-third of CO 2 emissions from deforestation are embedded in international trade

In a study published in Global Environmental Change , Florence Pendrill and colleagues investigated where tropical deforestation was occurring and what products were driving this. Using global trade models, they traced where these products were going in international supply chains. 27

They found that tropical deforestation — given as the annual average between 2010 and 2014 — was responsible for 2.6 billion tonnes of CO 2 per year. That was 6.5% of global CO 2 emissions. 28

International trade was responsible for around one-third (29%) of these emissions. This is probably less than many people would expect. Most emissions — 71% — came from foods consumed in the country where they were produced. It’s domestic demand, not international trade, that is the main driver of deforestation.

In the chart, we see how emissions from tropical deforestation are distributed through international supply chains. On the left-hand side, we have the countries (grouped by region) where deforestation occurs, and on the right, we have the countries and regions where these products are consumed. The paths between these end boxes indicate where emissions are being traded — the wider the bar, the more emissions are embedded in these products.

Latin America exports around 23% of its emissions; that means more than three-quarters are generated for products that are consumed within domestic markets. The Asia-Pacific region — predominantly Indonesia and Malaysia — exports a higher share: 44%. As we will see later, this is dominated by palm oil exports to Europe, China, India, North America, and the Middle East. Deforestation in Africa is mainly driven by local populations and markets; only 9% of its emissions are exported.

Since international demand is driving one-third of deforestation emissions, we have some opportunity to reduce emissions through global consumers and supply chains. However, most emissions are driven by domestic markets, which means that policies in major producer countries will be key to tackling this problem.

How much deforestation emissions is each country responsible for?

Let’s now focus on the consumers of products driving deforestation. After we adjust for imports and exports, how much CO 2 from deforestation is each country responsible for?

Rather than looking at total figures by country (if you’re interested, we have mapped them here ), we have calculated the per capita footprint. This gives us an indication of the impact of the average person’s diet. Note that this only measures the emissions from tropical deforestation — it doesn’t include any other emissions from agricultural production, such as methane from livestock or rice or the use of fertilizers.

In the chart, we see deforestation emissions per person, measured in tonnes of CO 2 per year. For example, the average German generated half a tonne (510 kilograms) of CO 2 per person from domestic and imported foods.

At the top of the list, we see Brazil and Indonesia, which are some of the major producer countries. The fact that the per capita emissions after trade are very high means that a lot of their food products are consumed by people in Brazil and Indonesia. The diet of the average Brazilian creates 2.7 tonnes of CO 2 from deforestation alone. That’s more than the country’s CO 2 emissions from fossil fuels , which are around 2.2 tonnes per person.

But we also see that some countries which import a lot of food have high emissions. Luxembourg has the largest footprint at nearly three tonnes per person. Imported emissions are also high for Taiwan, Belgium, and the Netherlands at around one tonne.

The average across the EU was 0.3 tonnes of CO 2 per person. To put this in perspective, that would be around one-sixth of the total carbon footprint of the average EU diet. 29

Beef, soybeans, and palm oil are the key drivers of deforestation

We know where deforestation emissions are occurring and where this demand is coming from. But we also need to know what products are driving this. This helps consumers understand what products they should be concerned about and allows us to target specific supply chains.

As we covered in a previous article , 60% of tropical deforestation is driven by beef, soybean, and palm oil production. We should look not only at where these foods are produced but also at where the consumer demand is coming from.

In the chart here, we see the breakdown of deforestation emissions by product for each consumer country. The default is shown for Brazil, but you can explore the data for a range of countries using the “Change country” button.

We see very clearly that the large Brazilian footprint is driven by its domestic demand for beef. In China, the biggest driver is demand for ‘oilseeds’ — which is the combination of soy imported from Latin America and palm oil imported from Indonesia and Malaysia.

Across the US and Europe, the breakdown of products is more varied. But, overall, oilseeds and beef tend to top the list for most countries.

Bringing all of these elements together, we can focus on a few points that should help us prioritize our efforts to end deforestation. Firstly, international trade does play a role in deforestation — it’s responsible for almost one-third of emissions. By combining our earlier Sankey diagram and breakdown of emissions by-product, we can see that we can tackle a large share of these emissions through only a few key trade flows. Most traded emissions are embedded in soy and palm oil exports to China and India, as well as beef, soy, and palm oil exports to Europe. The story of both soy and palm oil is complex — and it’s not obvious that eliminating these products will fix the problem. Therefore, we look at them both individually in more detail to better understand what we can do about it.

However, international markets alone cannot fix this problem. Most tropical deforestation is driven by the demand for products in domestic markets. Brazil’s emissions are high because Brazilians eat a lot of beef. Africa’s emissions are high because people are clearing forests to produce more food. This means interventions at the national level will be key: this can include a range of solutions, including policies such as Brazil’s soy moratorium, the REDD+ Programme to compensate for the opportunity costs of preserving these forests, and improvements in agricultural productivity so countries can continue to produce more food on less land.

FAO. 2020. Global Forest Resources Assessment 2020 – Key findings. Rome. https://doi.org/10.4060/ca8753en

Estimates vary, but most date the end of the last ice age to around 11,700 years ago.

Kump, L. R., Kasting, J. F., & Crane, R. G. (2004). The Earth System (Vol. 432). Upper Saddle River, NJ: Pearson Prentice Hall.

Year-to-year data on forest change comes with several issues: either data at this resolution is not available, or year-to-year changes can be highly variable. For this reason, data sources — including the UN Food and Agriculture Organization — tend to aggregate annual losses as the average over five-year or decadal periods.

Williams, M. (2003). Deforesting the earth: from prehistory to global crisis. University of Chicago Press.

The data for 1990 to 2020 is from the latest assessment: the UN’s Global Forest Resources Assessment 2020.

FAO (2020). Global Forest Resources Assessment 2020: Main report. Rome. https://doi.org/10.4060/ca9825en .

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Mather, A. S., & Needle, C. L. (2000). The relationships of population and forest trends. Geographical Journal, 166(1), 2-13.

It estimated that the net change in forests without plantations was 121 million hectares. With plantations included — as is standard for the UN’s forest assessments — this was 102 million hectares.

Hosonuma, N., Herold, M., De Sy, V., De Fries, R. S., Brockhaus, M., Verchot, L., … & Romijn, E. (2012). An assessment of deforestation and forest degradation drivers in developing countries. Environmental Research Letters, 7(4), 044009.

The area of India is around 330 million hectares. The combined losses in the 1990s and 2000s were 309 million hectares. Just 6% less than the size of India.

The area of Spain is around 51 million hectares. Double this area is around 102 million hectares — a little under 110 million hectares.

The UN Food and Agriculture Organization (FAO) Forest Resources Assessment estimates global deforestation, averaged over the five-year period from 2015 to 2020, was 10 million hectares per year.

If we sum countries’ imported deforestation by World Bank income group , we find that high-income countries were responsible for 14% of imported deforestation; upper-middle-income for 52%; lower-middle income for 23%; and low income for 11%.

Mather, A. S. (2004). Forest transition theory and the reforesting of Scotland . Scottish Geographical Journal, 120(1-2), 83-98.

England is similar: in the late 11th century, 15% of the country was forested, and over the following centuries, two-thirds were cut down. By the 19th century, the forest area had been reduced to a third of what it once was. But it was then that England reached its transition point, and since then, forests have doubled in size.

National Inventory of Woodland and Trees, England (2001). Forestry Commission. Available here .

This was first coined by Alexander Mather in the 1990s. Mather, A. S. (1990). Global forest resources . Belhaven Press.

This diagram is adapted from the work of Hosonuma et al. (2012).

Hosonuma, N., Herold, M., De Sy, V., De Fries, R. S., Brockhaus, M., Verchot, L., ... & Romijn, E. (2012). An assessment of deforestation and forest degradation drivers in developing countries . Environmental Research Letters , 7 (4), 044009.

Rudel, T. K. (1998). Is there a forest transition? Deforestation, reforestation, and development . Rural Sociology , 63 (4), 533-552.

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Cuaresma, J. C., Danylo, O., Fritz, S., McCallum, I., Obersteiner, M., See, L., & Walsh, B. (2017). Economic development and forest cover: evidence from satellite data . Scientific Reports , 7 , 40678.

Noriko Hosonuma et al. (2012) looked at this distribution for low-to-middle-income subtropical countries and also studied the many drivers of forest loss.Hosonuma, N., Herold, M., De Sy, V., De Fries, R. S., Brockhaus, M., Verchot, L., ... & Romijn, E. (2012). An assessment of deforestation and forest degradation drivers in developing countries . Environmental Research Letters , 7 (4), 044009.

Pendrill, F., Persson, U. M., Godar, J., & Kastner, T. (2019). Deforestation displaced: trade in forest-risk commodities and the prospects for a global forest transition . Environmental Research Letters , 14 (5), 055003.

Crowther, T. W., Glick, H. B., Covey, K. R., Bettigole, C., Maynard, D. S., Thomas, S. M., ... & Tuanmu, M. N. (2015). Mapping tree density at a global scale . Nature , 525 (7568), 201-205.

Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A., & Hansen, M. C. (2018). Classifying drivers of global forest loss . Science , 361 (6407), 1108-1111.

Hosonuma, N., Herold, M., De Sy, V., De Fries, R. S., Brockhaus, M., Verchot, L., ... & Romijn, E. (2012). An assessment of deforestation and forest degradation drivers in developing countries . Environmental Research Letters , 7(4), 044009.

Hosonuma et al. (2012) gathered this data from a range of sources, including country submissions as part of their REDD+ readiness activities, Center for International Forestry Research (CIFOR) country profiles, UNFCCC national communications, and scientific studies.

Scheffers, B. R., Joppa, L. N., Pimm, S. L., & Laurance, W. F. (2012). What we know and don’t know about Earth's missing biodiversity . Trends in Ecology & Evolution , 27(9), 501-510.

Maxwell, S. L., Fuller, R. A., Brooks, T. M., & Watson, J. E. (2016). Biodiversity: The ravages of guns, nets, and bulldozers . Nature, 536(7615), 143.

Lewis, S. L. (2006). Tropical forests and the changing earth system . Philosophical Transactions of the Royal Society B: Biological Sciences , 361(1465), 195-210.

Tyukavina, A., Hansen, M. C., Potapov, P. V., Stehman, S. V., Smith-Rodriguez, K., Okpa, C., & Aguilar, R. (2017). Types and rates of forest disturbance in Brazilian Legal Amazon, 2000–2013 . Science Advances , 3 (4), e1601047.

Lewis, S. L., Edwards, D. P., & Galbraith, D. (2015). Increasing human dominance of tropical forests . Science , 349 (6250), 827-832.

To do this, they quantified where deforestation was occurring due to the expansion of croplands, pasture, and tree plantations (for logging) and what commodities were produced on this converted land. Then, using a physical trade model across 191 countries and around 400 food and forestry products, they could trace them through to where they are physically consumed, either as food or in industrial processes.

Pendrill, F., Persson, U. M., Godar, J., Kastner, T., Moran, D., Schmidt, S., & Wood, R. (2019). Agricultural and forestry trade drives a large share of tropical deforestation emissions . Global Environmental Change , 56 , 1-10.

In 2012 — the mid-year of this period — global emissions from fossil fuels, industry, and land use change was 40.2 billion tonnes. Deforestation was therefore responsible for [2.6 / 40.2 * 100 = 6.5%].

The carbon footprint of diets across the EU varies from country to country, and estimates vary depending on how much land use change is factored into these figures. Notarnicola et al. (2017) estimate that the average EU diet, excluding deforestation, is responsible for 0.5 tonnes of CO 2 per person. If we add 0.3 tonnes to this figure, deforestation would account for around one-sixth [0.3 / (1.5+0.3) * 100 = 17%].

Notarnicola, B., Tassielli, G., Renzulli, P. A., Castellani, V., & Sala, S. (2017). Environmental impacts of food consumption in Europe . Journal of Cleaner Production , 140 , 753-765.

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Article contents

Deforestation of the brazilian amazon.

• Phillip Fearnside Phillip Fearnside Instituto Nacional de Pesquisas da Amazonia
• https://doi.org/10.1093/acrefore/9780199389414.013.102
• Published online: 26 September 2017

Deforestation in Brazilian Amazonia destroys environmental services that are important for the whole world, and especially for Brazil itself. These services include maintaining biodiversity, avoiding global warming, and recycling water that provides rainfall to Amazonia, to other parts of Brazil, such as São Paulo, and to neighboring countries, such as Argentina. The forest also maintains the human populations and cultures that depend on it. Deforestation rates have gone up and down over the years with major economic cycles. A peak of 27,772 km2/year was reached in 2004, followed by a major decline to 4571 km2/year in 2012, after which the rate trended upward, reaching 7989 km2/year in 2016 (equivalent to about 1.5 hectares per minute). Most (70%) of the decline occurred by 2007, and the slowing in this period is almost entirely explained by declining prices of export commodities such as soy and beef. Government repression measures explain the continued decline from 2008 to 2012, but an important part of the effect of the repression program hinges on a fragile base: a 2008 decision that makes the absence of pending fines a prerequisite for obtaining credit for agriculture and ranching. This could be reversed at the stroke of a pen, and this is a priority for the powerful “ruralist” voting bloc in the National Congress. Massive plans for highways, dams, and other infrastructure in Amazonia, if carried out, will add to forces in the direction of increased deforestation.

Deforestation occurs for a wide variety of reasons that vary in different historical periods, in different locations, and in different phases of the process at any given location. Economic cycles, such as recessions and the ups and downs of commodity markets, are one influence. The traditional economic logic, where people deforest to make a profit by producing products from agriculture and ranching, is important but only a part of the story. Ulterior motives also drive deforestation. Land speculation is critical in many circumstances, where the increase in land values (bid up, for example, as a safe haven to protect money from hyperinflation) can yield much higher returns than anything produced by the land. Even without the hyperinflation that came under control in 1994, highway projects can yield speculative fortunes to those who are lucky or shrewd enough to have holdings along the highway route. The practical way to secure land holdings is to deforest for cattle pasture. This is also critical to obtaining and defending legal title to the land. In the past, it has also been the key to large ranches gaining generous fiscal incentives from the government. Money laundering also makes deforestation attractive, allowing funds from drug trafficking, tax evasion, and corruption to be converted to “legal” money. Deforestation receives impulses from logging, mining, and, especially, road construction. Soybeans and cattle ranching are the main replacements for forest, and recently expanded export markets are giving strength to these drivers. Population growth and household dynamics are important for areas dominated by small farmers. Extreme degradation, where tree mortality from logging and successive droughts and forest fires replace forest with open nonforest vegetation, is increasing as a kind of deforestation, and is likely to increase much more in the future.

Controlling deforestation requires addressing its multiple causes. Repression through fines and other command-and-control measures is essential to avoid a presumption of impunity, but these controls must be part of a broader program that addresses underlying causes. The many forms of government subsidies for deforestation must be removed or redirected, and the various ulterior motives must be combated. Industry agreements restricting commodity purchases from properties with illegal deforestation (or from areas cleared after a specified cutoff) have a place in efforts to contain forest loss, despite some problems. A “soy moratorium” has been in effect since 2006, and a “cattle agreement” since 2009. Creation and defense of protected areas is an important part of deforestation control, including both indigenous lands and a variety of kinds of “conservation units.” Containing infrastructure projects is essential if deforestation is to be held in check: once roads are built, much of what happens is outside the government’s control. The notion that the 2005–2012 deforestation slowdown means that the process is under control and that infrastructure projects can be built at will is extremely dangerous. One must also abandon myths that divert efforts to contain deforestation; these include “sustainable logging” and the use of “green” funds for expensive programs to reforest degraded lands rather than retain areas of remaining natural forests. Finally, one must provide alternatives to support the rural population of small farmers. Large investors, on the other hand, can fend for themselves. Tapping the value of the environmental services of the forest has been proposed as an alternative basis for sustaining both the rural population and the forest. Despite some progress, a variety of challenges remain. One thing is clear: most of Brazil’s Amazonian deforestation is not “development.” Trading the forest for a vast expanse of extensive cattle pasture does little to secure the well-being of the region’s rural population, is not sustainable, and sacrifices Amazonia’s most valuable resources.

• deforestation
• development
• tropical forest
• economic development
• environmental services
• ecosystem services

What Is Deforestation?

“Deforestation” refers to converting forest into nonforest, and the meaning of the term therefore hinges on what is considered to be a “forest.” Semantic distinctions often confuse discussions of deforestation. In official Brazilian data, such as those from Project for Monitoring the Brazilian Amazon Forest by Satellite (PRODES), run by the National Institute for Space Research (Instituto Nacional de Pesquisas Espaciais [INPE]), deforestation refers to the clearing of primary or old-growth forest, not to the clearing of secondary forests. Secondary forests refer to succession in previously clear-cut areas (as distinct from the usage of this term in Southeast Asia to refer to logged forests). The PRODES surveys define forest-based on vegetation types classified by the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística, 2012 ), rather than by percentage cover (Instituto Nacional de Pesquisas Espaciais [INPE], 2013 ). The United Nations Framework Convention on Climate Change (UNFCCC), better known as the “Climate Convention,” defines “forest” as having at least 10% cover (Intergovernmental Panel on Climate Change, 2006 , p. 4.74), allowing many types of cerrado (central Brazilian savanna) to be considered forest, and its clearing as “deforestation.” Note also that the Climate Convention definition, which is based on the definition used by the Food and Agriculture Organization of the United Nations ( 2012 , p. 3), includes “temporarily unstocked” areas that have been completely clear-cut but are intended to be allowed to regenerate, thus opening a loophole by making the definition of forest, and therefore of deforestation, dependent on knowledge of intent rather than being based solely on objective measurements verifiable by satellite.

An important distinction is between net versus gross deforestation (e.g., Brown & Zarin, 2013 ). “Net” deforestation subtracts areas that are regenerating as secondary forests. Some interpretations also include silvicultural plantations, such as of Eucalyptus , as counting toward reducing net deforestation, including Brazil’s 2008 National Plan for Climate Change. This plan promised to end net deforestation by 2015 (Comitê Interministerial sobre Mudança do Clima, 2008 , p. 12), an objective that was not met. A target of zero or reduced “net” deforestation carries a danger, as each hectare of plantation or regenerating trees effectively creates a license to clear a hectare of mature or primary forest elsewhere.

Brazil’s commitment part of the 2015 Paris accords refers to reaching zero “illegal” deforestation by 2030 (Republic of Brazil, 2015 , p. 3). This far from means the end of deforestation, because forest clearing can continue as long it is “legal.” With advance of the Rural Environmental Register, all properties in the country should be registered long before 2030 , making it easy to obtain permission for “legal” deforestation up to the limits specified by Brazil’s Forest Code (20% in Amazonia). But because in the early 21st century , many present and future properties in Amazon forest areas have little clearing, large amounts of “legal” deforestation can continue (Nunes, Gardner, Barlow, Martins, Salomão, & Souza, 2016 ).

Why Is Deforestation Important?

Brazil’s Amazonian deforestation is important to life throughout the world, both human and nonhuman. the impacts of deforestation include losses of environmental services that though they affect whole world, affect Brazil the most (e.g., Fearnside, 1997a , 2008a ). The environmental services of Amazonian forest include its role in storing carbon and thus avoiding global warming (e.g., Fearnside, 2000 , 2016a ; Nogueira, Yanai, Fonseca, & Fearnside, 2015 ), in recycling water provides atmospheric water vapor that is important for rainfall not only in Amazonia but also in non-Amazonian areas such as São Paulo (e.g., Arraut, Nobre, Barbosa, Obregon, & Marengo, 2012 ), and in maintaining biodiversity (e.g., Fearnside, 1999 ). In addition, Amazonian forests provide a variety of material products, such as timber, rubber, and Brazil nuts; these provisioning functions currently support local populations and also represent lost opportunities for sustainable use when areas are deforested.

The vast size of Brazilian Amazonia (Figure 1 ) gives special importance to deforestation processes in this region. In many parts of the world that were originally covered by tropical forests, deforestation has proceeded to the point where only tiny remnants remain. In these areas, the clearing of the last hectares of remaining forest represents a tragedy for biodiversity. In Amazonia, despite the large area of remaining forest, deforestation has a significant impact on biodiversity because the distribution of species is not uniform. The ranges of many species have been restricted to parts of the region where forest has already been reduced to small fragments (e.g., Hubbell, He, Condit, Borda-de-Água, Kellnert, & ter Steege, 2008 ; Michalski & Peres, 2005 ). The disappearance of species that were endemic to heavily deforested areas in eastern and southern Amazonia is already widespread (e.g., Moura, Lees, Aleixo, Barlow, Dantas, Ferreira, et al., 2014 ).

Figure 1. Brazil’s Legal Amazon region and locations mentioned in the text.

The elimination of forest has different implications for biodiversity and for climate. Fighting to save the last remnants of forest in heavily deforested areas is essential for biodiversity, but from the point of view of climate, the dwindling area of remaining forest limits the potential impact of future deforestation. Although the impact on global warming is the same when a hectare of forest is cleared in any part of the world, assuming that forest biomass per hectare and other relevant parameters are the same, the equivalence is restricted to the emission from one year to the next. In the case of Amazonia, in addition to the yearly impact, the vast extent of remaining forest gives additional importance to deforestation processes because they can result in much greater future emissions. In countries where little forest remains, deforestation will diminish and end soon regardless of policy changes, any change in public policies in Brazil has a much greater potential impact, positive or negative, compared to other tropical countries. The various ways that Amazonian forest can be destroyed other than by deliberate human action give the region additional importance for global climate.

How Fast Has Deforestation Occurred?

Brazil’s Amazonian deforestation rates have varied widely the over the decades since construction on the Transamazon Highway (BR-230) began, in 1970 , initiating the “modern” era of deforestation. Between 1978 (the year of images for the first LANDSAT satellite survey) and 1988 (the next complete survey), deforestation averaged 21,050 km 2 /year (Fearnside, 1990 ). Since then, annual coverage figures have been available, with the single exception of 1993 (INPE, 2017a ). A long history of political interference with the monitoring program (Fearnside, 1997d ) has largely been overcome, and the PRODES program currently has much greater transparency. Some discrepancies with other satellite estimates still remain open questions (Fearnside & Barbosa, 2004 ), whereas other LANDSAT estimates are highly consistent (Souza, Siqueira, Sales, Fonseca, Ribeiro, Numata, et al., 2013 ). Deforestation rates have undergone major oscillations (Figure 2 ), mostly as a result of macroeconomic shifts (Fearnside, 2005a ).

Figure 2. Deforestation rates in the originally forested portion of Legal Amazonia. Data from Instituto Nacional de Pesquisas Espaciais ( 2017a ).

PRODES uses Landsat-TM satellite imagery (or the equivalent) with 30-m resolution (INPE, 2017a ). The imagery is freely available on the INPE website, degraded to 60-m resolution. Images are taken in the dry season (August in all but the extreme north of the region), and the “year” of the data refers approximately to the deforestation between August 1 of the previous year and July 31 of the nominal year. The lower limit for detection of clearings is 6.25 ha.

The INPE also has a program called DETER (Detection of Deforestation in Real Time), which produces monthly data from MODIS imagery with maximum resolution of 250 m (Diniz, Souza, Santos, Dias, da Luz, de Moraes et al., 2015 ; INPE, 2017b ). This only detects clearings of 25 ha or larger. A similar MODIS-based monitoring program called SAD (Deforestation Alert Service) is run by the Institute for Man and the Environment in Amazonia (Instituto do Homem e Meio Ambiente da Amazônia [IMAZON]), a nongovernmental organization (NGO). The SAD data are released more quickly than the DETER data and are accompanied by more information on the deforestation processes in course (Instituto do Homem e Meio Ambiente da Amazônia, 2017 ). The results of the DETER program at INPE and the SAD program at IMAZON match well. Care is needed in drawing conclusions from the monthly data. These data are more readily affected by having significant areas covered by clouds than are PRODES data, despite the much more frequent satellite passes by MODIS compared to LANDSAT. More importantly, frequent headlines proclaiming that deforestation in a given month is several hundred percentage points higher or lower than in the same month in the previous year can often be misleading. If the month in question is in the dry season, this can be very significant, but if it is in the wet season, then large variation from a number near zero has little import, and the clearing detected is likely to be an insignificant portion of the annual total deforestation.

An important limitation of deforestation data is that forest degradation, such as by logging and by tree mortality from droughts and fire, is not detected or counted unless the forest has reached the extreme condition of being an open area with only a few scattered trees remaining, thus appearing as cleared on the satellite image. Extreme degradation of this type is counted as deforestation by all the programs mentionedin the preceding paragraph. There has been a long-standing struggle over this issue between the INPE and the state government of Mato Grosso, which insists that these areas are not “deforestation” areas because they were not deliberately clear-cut. This is likely to become even more critical if a proposed law (PL4508/2016) is implemented to allow “sustainable” cattle ranching in legal reserves (Canal Rural, 2017 ). Degradation is monitored by IMAZON (Cardoso, Ribeiro, Salomão, Fonseca, & Souza, 2017 ) and was monitored from 2007 to 2013 by the DEGRAD program at the INPE (INPE, 2014a ).

Why Is Deforestation Happening?

Economic cycles and land speculation.

From 1988 to 1991 deforestation declined by half, during a time of a deepening economic recession under president Fernando Collor that culminated with the government ceasing deposits in bank accounts in 1990 , meaning that funds were no longer available for investment in deforestation (among other effects). Deforestation rose in the subsequent years as the economy recovered, reaching a record rate of 29,100 km 2 /year in 1995 , as a consequence of the June 1994 Real Plan, a package of economic reforms that ended hyperinflation. Money that had been invested in the “overnight” (a 24-hour money market that could protect money from inflation) was suddenly available, and it was invested in deforestation, and not, for example, in recuperating degraded pastureland. Deforestation fell dramatically during the next two years, another consequence of the Real Plan. Because the plan had essentially halted inflation, generalized land speculation became unprofitable (though land purchases in areas where roads would be built or upgraded could still yield quick fortunes). Even under the inflation regime that has prevailed since the 1994 Real Plan, with much lower rates than those before this plan, clearing behavior is also frequently explained by speculative returns instead of solely by beef production (Carrero & Fearnside, 2011 ; Razera, 2005 ).

Land speculation is an important force in deforestation because the practical way to secure land holdings is to deforest to create cattle pasture. Under hyperinflation, land values in Amazonia increased faster than the rates inflation, and the increase in land value could yield much more profit than could raising cattle or other activities undertaken while they are in possession (either legally or illegally) of the land (Hecht, 1985 , 1993 ; Hecht, Norgaard, & Possio, 1988 ). Land values in Amazonia and deforestation rates both fell by half after the implementation of Real Plan, an indication of how strong speculation had been as a driver. However, land speculation continues to be an important component in the profitability of extensive ranching (Bowman, Soares-Filho, Merry, Nepstad, Rodrigues, & Almeida, 2012 ). Following the decline after the 1995 peak, deforestation rates increased to a new peak of 27,772 km 2 /year in 2004 , thanks to a strengthening economy and rising commodity prices. Beginning in 2005 , there was a major decline in deforestation rates until 2012 , after which the rate increased (with oscillations), reaching 7989 km 2 /year in 2016 (INPE, 2017a ).

Commodities and Governance

Understanding the causes of the 2005–2012 decline in deforestation rates is essential to the policy lessons that can be derived from this experience. The Brazilian government has repeatedly claimed that the decline was the result of government actions, particularly the increases in inspections and fines for those who deforest illegally. In fact, the decline was brought about by a variety of factors, including governance measures, and it is these other factors that explain most of the decline. The decline occurred in two phases, the first from 2005 to 2007 , and the second from 2008 to 2012 . During the period up to 2007 , deforestation rates tracked the prices of export commodities, such as soybeans and beef, making these the primary drivers during this period (Assunção, Gandour, & Rocha, 2015 ; see also Arima, Barreto, Araujo, & Soares-Filho, 2014 ; Hargrave & Kis-Katos, 2013 ). For the 1995–2007 period, more than 75% of the deforestation is explained by lagged prices of soy and beef (Arima et al., 2014 ). Most (70%) of the total 2005–2012 decline had occurred by 2007 . From 2008 onward, commodity prices recovered, though deforestation continued to decline to 2012 , indicating that something had changed. An event in 2008 that coincides with the change is a resolution of the Brazilian Central Bank (BACEN 3545/ 2008 ), which blocks loans from government banks for agriculture and ranching in properties with fines pending in the environmental agencies (Börner, Kis-Katos, Hargrave & König, 2015 ; Fearnside, 2015e ). The fines themselves have little effect, since they can be appealed almost indefinitely and are rarely paid (e.g., Lima, Capobianco, & Moutinho, 2009 ). In contrast, the block on loans has immediate effect and there is no chance of appeal; it also has its greatest impact on the largest actors. Another key event in 2008 was that the federal environmental agency, the Brazilian Institute for the Environment and Renewable Natural Resources (IBAMA) initiated a blacklist of municipalities with high deforestation. The blacklisted municipalities had a significantly greater reduction in deforestation as compared to non-blacklisted municipalities over the 2009–2011 period (Arima et al., 2014 ), a trend that continued through 2012 (Cisneros, Zhou, & Börner, 2015 ). Blacklisted municipalities had additional requirements for obtaining licenses for legal deforestation, had more inspection effort focused on them by IBAMA, suffered restrictions on agricultural credit, and had additional impetus to hasten implantation of the Rural Environmental Register due to increased assistance from NGOs in registering properties and because of local desire to avoid reputational costs (Cisneros et al., 2015 ).

The strength of governance measures varies with election cycles, and there is a tendency to relax enforcement of environmental regulations prior to major elections, producing a significant relation between deforestation rates and elections (Rodrigues-Filho, Verburg, Bursztyn, Lindoso, Debortoli, & Vilhena, 2015 ). The mere anticipation of such relaxation can stimulate clearing, as was suggested by a dramatic surge in deforestation in Mato Grosso, in 2002 , in the months prior to election of Brazil’s largest soybean producer as governor of the state, thus curtailing the state government’s deforestation control program (e.g., Fearnside, 2005b ).

Fiscal Incentives

In the 1970s and 1980s, fiscal incentives offered by the Brazilian government were a major factor motivating deforestation by large ranchers (Binswanger, 1991 ; Mahar, 1979 ). Incentives included the right to invest in approved Amazonian ranches funds that would otherwise have been paid as taxes on the profits of enterprises elsewhere in the country, generous loans at interest rates far below the rate of inflation, and tax exemptions on the Amazonian income. Clearing forest was primarily a means of gaining access to these subsidies, rather than of earning income from beef production. The effect of incentives continued long after official discourse stressed that the incentive program had been ended. A 1991 decree halted approvals of new projects, but the already approved projects continue to receive the tax incentives (Fearnside, 2005a ). Natural attrition, such as by bankruptcy, has reduced the impact of the incentives by reducing the number of eligible ranches.

Land Tenure

One of the most pervasive motives for deforestation is the establishment and maintenance of land tenure (Fearnside, 1979 , 2001b ). Much of the land in Brazilian Amazonia is in the public domain. Aside from occasional land distributions to small farmers in official settlement programs (such as those on the Transamazon Highway) and to large ranchers in areas that are sold through bidding (such as the Agriculture and Ranching District of the Manaus Free Trade Zone [SUFRAMA]), land enters the private domain by first being illegally invaded either by small squatters or by large grileiros (land thieves or “land grabbers”), and eventually the government recognizes the claims and grants title. The key to gaining title is showing “improvement” ( benfeitoria ) on the land, which means deforesting and planting something, cattle pasture being the cheapest option per hectare. But even if one has title to land, if it is left in forest, the owner can eventually expect to lose it, either through invasion by squatters or grileiros or by expropriation for a government settlement project.

The question of who is deforesting is essential to formulating policies that will be effective in containing the process. Deforestation is done for different reasons and by different actors in different parts of the region and in different historical periods in any given location. For example, land along the Belém-Brasília Highway (BR-010), built in the late 1950s and early 1960s, was first occupied by small squatters, who were later expelled (often violently) and replaced by large ranchers (Foweraker, 1981 ; Valverde & Dias, 1967 ). Similar patterns unfolded in much of southern Pará beginning in the 1970s (Schmink & Wood, 1992 ). The Transamazon Highway (BR-230), built in the early 1970s, was settled through government colonization projects in which small farmers received 100-ha lots (e.g., Moran, 1981 ; Smith, 1982 ). Many of these lots were later acquired by wealthier actors, who then proceed to use them as medium to large ranches (e.g., Fearnside, 1986b ). A similar process took place along the Cuiabá-Porto Velho (BR-364) Highway in Rondônia (Fearnside, 1984 ). In Amazonia as a whole, large (officially defined in Brazilian Amazonia as > 1000 ha) and medium-sized (101–1000 ha) actors have traditionally predominated in deforestation (Fearnside, 1993 , 2008b ); but the relative importance of small (≤ 100 ha) farmers has been increasing, as indicated by the decreasing average size of new clearings (Rosa, Souza, & Ewers, 2012 ), and the deforestation slowdown since 2005 has disproportionately affected the larger actors (Godar, Gardner, Tizado, & Pacheco, 2014 ). However, small farmers have demonstrated greater potential to stabilize their land use in a mosaic of agriculture, pasture, and natural forest, and avoiding the consolidation of small properties into large ranches represents a beneficial measure from the point of view of minimizing deforestation (Campos & Nepstad, 2006 ; Godar, Tizado, & Pokorny, 2012 ).

Money Laundering

Money from such sources as drug trafficking, truck hijacking, government corruption, and income sources not declared to tax authorities can be invested in Amazonian deforestation with minimal risk. If the same funds were invested in the stock market or urban real estate, the inconsistency in declared income would soon be discovered by tax authorities. Illegal money forms a sort of cloud over Amazonia that affects what happens on the ground, often defying traditional economic logic. The terra do meio , an area in Pará the size of Switzerland, has for many years been essentially outside of the control of the Brazilian government (Greenpeace, 2003 ; Taravella, 2008 ). The area has been dominated by drug traffickers, grileiros , and other illegal actors (Escada, Vieira, Amaral, Araújo, da Veiga, Aguiar et al., 2005 ; Fearnside, 2008b ; Greenpeace, 2003 ; Instituto Socioambiental, 2016 ; Schönenberg, 2002 ). In 2005 , following the assassination of Dorothy Stang (a defender of Amazonian social and environmental causes), a group contiguous of protected areas (known in Brazil as a “mosaic”) was created in the terra do meio , but the environmental agencies have yet to establish a physical base in the area, something that has been planned since 2002 . An example of deforestation that is inexplicable by traditional economic logic is provided by a 6239-ha clearing (known as the “revolver” because of its shape) that suddenly appeared, in 2003 , in the terra do meio (Venturieri, Aguiar, Monteiro, Carneiro, Alves, Câmara et al., 2004 ). The location was far from any roads and had been classified as one of the least-promising locations for profitable ranching in all of Amazonia, based on the calculated farm-gate price of beef (Arima, Barreto, & Brito, 2005 , p. 50).

Logging is an important driver of deforestation, though its effect is delayed and hard to show statistically because in areas with active logging there is little deforestation, whereas in those where deforestation is in full swing, timber is no longer available for logging. Logging facilitates deforestation by providing clandestine “endogenous” roads that are subsequently used for entry of deforesters (Arima, Walker, Perz, & Caldas, 2005 ). It also provides much of the money that pays for the felling itself, in the cases of both large actors and small ones (Veríssimo, Uhl, Mattos, Brandino, & Vieira, 2002 ).

Mining is another driver of deforestation. Gold miners ( garimpeiros ), who are attracted to areas with alluvial deposits, can stay on later as squatters or invest proceeds in land or in clearing (MacMillan, 1995 ). Iron mining in the Carajás area justified a major government program to promote agriculture and ranching in the region and also feeds pig-iron smelters who draw wood from the surrounding region for charcoal (Fearnside, 1986a , 1989a ). Bauxite mining, aside from the mine sites themselves, feeds an aluminum smelting industry that drives massive impacts from the hydroelectric dams that are built to supply the smelters (Fearnside, 2016d ). The areas surrounding dams are associated with increased deforestation (Barreto, Brandão, Martins, Silva, Souza, Sales et al., 2011 ; Baretto, Brandão, Silva, & Souza, 2014 ; Fearnside, 2014a , 2014b ).

Roads are the most powerful driver of deforestation (Kirby, Laurance, Albernaz, Schroth, Fearnside, Bergen et al., 2006 ; Laurance, Cochrane, Bergen, Fearnside, Delamônica, Barber et al., 2001 ; Pfaff, 1999 ; Pfaff, Robalino, Walker, Aldrich, Reis, Perz et al., 2007 ; Soares-Filho, Nepstad, Curran, Cerqueira, Garcia, Ramos et al., 2006 ). The construction or upgrading of a road increases migration to the area it accesses; increases the profitability of agriculture and ranching; and greatly increases land values, with consequent speculative deforestation and a turnover of landowners in favor of wealthier actors who deforest faster than the previous owners (Fearnside, 1987a , 1987b ). Deforestation follows roads, and the presence of deforestation has a contagious effect, leading to further acceleration of deforestation along these routes (Rosa, Purves, Carreiras, & Ewers, 2014 ; Rosa, Purves, Souza, & Ewers, 2013 ). Roughly 80% of the forest loss in Brazilian Amazonia has been in the “arc of deforestation,” a crescent-shaped strip along the southern and eastern edges of the forest (Figure 3 ). New highways are bringing deforestation activity into the heart of the Amazon. The most critical case is the planned reconstruction of the abandoned Manaus-Porto Velho (BR-319) Highway, which would connect the arc of deforestation with central Amazonia, bringing the actors and processes from Rondônia to large areas in Amazonas and Roraima that have road access from Manaus, and open the large block of intact forest in the western portion of the state of Amazonas through planned side roads (Fearnside & Graça, 2006 ). The environmental impact statement for this planned highway presented Yellowstone National Park as the expected deforestation scenario, envisioning tourists driving through the area on a “park-highway” without cutting a single tree (see Fearnside, 2015d ; Fearnside & Graça, 2009 ). The unreality of this portrayal of an Amazon frontier would be hard to exaggerate. Unrealistic “governance scenarios” like this are simply excuses that serve to justify the licensing of highways, which imply very real impacts.

Figure 3. Deforestation through 2015 in Legal Amazonia and the Amazonia biome. The “arc of deforestation” is the heavily impacted crescent-shaped area along the eastern and southern edges of the forest (deforestation shown in red). Data from Instituto Nacional de Pesquisas Espaciais ( 2017a ).

Soybeans have been a major force behind deforestation in Mato Grosso, and there have also been advances in some parts of Pará, particularly the Santarém area (Barona, Ramankutty, Hyman, & Coomes, 2010 ; Fearnside, 2001c ; Morton, DeFries, Shimabukuro, Anderson, Arai, del Bon Espirito-Santo et al., 2006 ). Besides the direct conversion of forest for soy, the crop has a very important indirect impact. Soy advance into pasture in the cerrado (as well as into forest areas in northern Mato Grosso) has a prominent role in driving increased investment in clearing for ranches in Amazon rainforest areas in Pará (Arima, Richards, Walker, & Caldas, 2011 ; Richards, Walker, & Arima, 2014 ). The Chinese have played a key role in driving the conversion of forest and cerrado (Fearnside, Figueiredo, & Bonjour, 2013 ). This has primarily been through exports, but it has also been through land purchases and the financing of transport infrastructure. Transport infrastructure is the main limitation on the spread of soybeans from the most profitable areas in Mato Grosso, particularly to the west in Rondônia and Acre, as well as in the portions of northern Mato Grosso still dominated by pasture (Vera-Diaz, Kaufmann, Nepstad, & Schlesinger, 2008 ).

International finance has played a significant role in speeding the advance of soy. In 2002 and 2003 the International Finance Corporation (IFC), the arm of the World Bank that finances private companies, granted Grupo André Maggi (Brazil’s largest soy company) two US$30 million loans. The IFC classified the loans as Category B (low environmental risk), thus not requiring any environmental-impact assessment or subsequent monitoring of impacts. This IFC classification allowed Rabobank (of the Netherlands) to grant Maggi two loans totaling US$330 million (Greenpeace, 2006 , p. 18). Financing from the Brazilian government’s National Bank for Social and Economic Development (BNDES) has also been a major force in the advance of soy (Greenpeace, 2006 ).

It should be noted that gross domestic product (GDP) is not a good predictor of deforestation. Statements associating GDP with clearing give the false impression that deforestation is an inevitable consequence of economic progress. The fraction of Brazil’s economy contributed by new clearing on the Amazon frontier is minimal, although the large areas of soybeans in previously cleared areas are a significant contributor. The questionable nature of a link to GDP is shown by “decoupling” of deforestation rates from agricultural production during the 2005–2012 deforestation slowdown (Lapola, Martinelli, Peres, Ometto, Ferreira, Nobre et al., 2014 ; Nepstad, Irawau, Bezerra, Boyd, Stickler, Shimada et al., 2013 ; Nepstad, McGrath, Stickler, Alencar, Azevedo, Swette et al., 2014 ).

Cattle Ranching

Cattle production (as opposed to ulterior motives) is becoming more prominent in the mix of deforestation motives in Amazonia. This is behavior that following the traditional economic logic, in which actors deforest to earn profits from the sale of products from agriculture and ranching (Faminow, 1998 ; Margulis, 2004 ; Mattos & Uhl, 1994 ; Mertens, Poccard-Chapuis, Piketty, Laques, & Venturieri, 2002 ). Forest conservation ultimately requires addressing the “underpinnings of the cattle economy itself” (Walker, Moran, & Anselin, 2000 ). Cattle ranching is even accelerating in the extractive reserves, created to maintain forests by supporting traditional populations of rubber tappers and Brazil-nut gatherers; ranching has proliferated in these areas and is replacing the economy based on nontimber forest products (Salisbury & Schmink, 2007 ). Rubber extraction is not economically viable without subsidies (Jaramillo-Giraldo, Soares Filho, Ribeiro, & Gonçalves, 2017 ).

Export in general has become a more prominent predictor of deforestation at the municipality (county) level (Faria & Almeida, 2016 ). The increase in beef exports is especially significant because of the great potential for expansion (McAlpine, Etter, Fearnside, Seabrook, & Laurance, 2009 ). Brazilian exports of frozen beef were barred from virtually all international markets because of the presence of foot-and-mouth disease (Fearnside, 1987a ). Brazilian Amazonia was thereby protected from the “hamburger connection” (Myers, 1981 ) that has driven much of the deforestation in Central America, an area that is free of the disease. Beginning in 1998 , states in Brazil were successively certified as free of foot-and-mouth disease, starting with the non-Amazonian states in the south (Kaimowitz, Mertens, Wunder, & Pacheco, 2004 ). This had an indirect impact on Amazonia in that beef produced in southern Brazil could be exported; whereas people in São Paulo, for example, could eat beef from Pará. All nine states in Brazilian Amazonia have, since 2015 , been classified as having, at most, a medium risk, in addition to being without clinical cases of the disease; but Amazonas, Roraima, and Amapá have not been classified as “disease free,” which would allow direct exports from these states (Pithan e Silva, 2016 ). Brazil is the world’s largest exporter of beef, some of which is even exported as live cattle. In 2015 and 2016 , accords with Russia, the United States, and China opened these markets to Brazilian beef. The full opening of the Chinese market is particularly significant, since its potential scale is essentially infinite from the perspective of Brazilian producers. In addition to dominating beef exports to China, Brazil is also China’s main supplier of leather. China is the world’s largest manufacturer of shoes. In 2008 , the value of Brazil’s leather exports totaled US$1.9 billion, as compared to US$5.1 billion for beef (Greenpeace, 2009 , p. 61).

The Brazilian government’s generous subsidies for ranching in the 1970s and 1980s came during the “economic miracle” period, and their later curtailment was coincident with a severe recession. As in the case of soybeans, international finance has contributed to speeding up of the current “modern” period of livestock production and processing. In March 2007 , the IFC made a US$90 million loan to Bertin (Brazil’s largest slaughterhouse company at the time), which supplied beef to Burger King, among many other outlets (Greenpeace, 2009 ; Rich, 2013 ). Brazilian government financing from BNDES has also been important in advancing the modern livestock industry in Amazonia.

Population Growth

Increasing population has a significant effect on Brazil’s Amazonian deforestation (Laurance, Albernaz, Schroth, Fearnside, Bergen, Venticinque et al,, 2002 ). However, interpreting the relationship is more complicated than might be thought. Studies that look at political units, such as countries, states, or municipalities, or at arbitrary geographic units, such as grid cells, will find results on population change and deforestation rate that go in both directions and will conclude that there is no relationship between these two variables. The first step to make sense of such data is removing the urban population from the analysis. While the urban population has an effect, it is very distinct from the effect of the direct deforestation actors. Then, there must be a breakdown by the different rural actors who are present before and after the land-use transformation under study, such as deforestation in a given period. These data do not exist for Brazil. The only solution is to obtain detailed information from case studies in specific locations. It is important that the locations chosen be “typical” of large areas of deforestation. The places being converted to cattle pastures in Brazilian Amazonia represent an obvious priority.

Two key questions affecting the relationship of population and deforestation are (a) who are the actors, such as ranchers versus small farmers, and (b) what population and land use is being replaced. If the situation is one of small farmers replacing “unoccupied” forest, then a greater population (of small farmers) translates into more deforestation. If it is ranchers who are replacing “unoccupied” forest, then the same relationship applies, although the number of people will be lower and the amount of deforestation per capita will be much greater. If the situation is one of ranchers replacing small farmers, then the human population will decrease and the rate of deforestation per capita will increase, resulting in a negative relationship between population change and deforestation rate.

One theory regarding population is that increasing rural-urban migration will result in the abandonment of large areas that are currently used for agriculture and ranching, leading to the establishment of secondary forests and a recovery of biodiversity (Wright & Muller-Landau, 2006 ). Unfortunately, other than existence of significant rural-urban migration (Parry, Day, Amaral, & Peres, 2010 ), this theory bears little resemblance to events in Amazonia (Fearnside, 2008c ). Those who migrate to cities are usually riverside inhabitants, who do very little deforestation. Were larger actors to give up their operations and move to cities, their land would be sold to others who would continue to use the cleared areas (sometimes with intervals under secondary succession). Cattle pasture requires very little labor once established, and a small population can occupy a very large area.

Household Dynamics

Household processes among small farmers can result in deforestation that is independent of the profit-seeking motive, which can be used as a lever by incentive programs to change clearing behavior. These include household demographic changes and the economic circumstances of each family (Caldas, Walker, Arima, Perz, Aldrich, & Simmons, 2007 ). At the stage in the household life cycle when both labor capability and the demand for consumption to support dependents are at a maximum, deforestation advances at maximum speed and is unlikely to be influenced by outside policy interventions. Minimizing risks takes precedence over maximizing profits (Walker, Perz, Caldas, & Silva, 2002 ).

Extreme Degradation

Forest can be converted to nonforest (i.e., deforested) by extreme degradation rather than by clear-cutting. Degradation is becoming increasingly prevalent in Brazilian Amazonia and has not been affected by the forces that shifted deforestation rates to a lower plateau after 2004 (Souza et al., 2013 ). Logging is a major factor that even prior to the deforestation “slowdown” affected a larger area each year than the annual clear-cut (Asner, Knapp, Broadbent, Oliveira, Keller, & Silva, 2005 ). Logging has increased since the slowdown began, rather than decreasing in parallel with the deforestation (e.g., Silvestrini, Soares-Filho, Nepstad, Coe, Rodrigues, & Assunção, 2011 ), making the post-slowdown area that is subjected to logging each year far greater than the area that is deforested outright. Logging makes forests more susceptible to entry of fire because it leaves slash and unintentionally killed trees in the forest that can act as fuel, and also opens canopy gaps that allow sunlight and wind to enter, hastening the drying of the fuel bed (Cochrane, Alencar, Schulze, Souza, Nepstad, Lefebvre et al., 1999 ; Nepstad, Verissimo, Alencar, Nobre, Lima, Lefebvre et al., 1999 ; Uhl & Buschbacher, 1985 ). This sets in motion a positive-feedback process that successively degrades the forest by the repeated entry of fire (Barlow & Peres, 2006 ; Nepstad, Carvalho, Barros, Alencar, Capobianco, Bishop et al., 2001 ). Droughts are major factors in facilitating Amazonian forest fires, with or without logging (Alencar, Nepstad, & Diaz, 2006 ; Aragão & Shimabukuro, 2010 ; Barbosa & Fearnside, 1999 ; Barlow & Peres, 2008 ; Barlow, Peres, Lagan, & Haugaasen, 2003 ; Berenguer, Ferreira, Gardner, Aragão, de Camargo, Cerri et al., 2014 ; Vasconcelos, Fearnside, Graça, Nogueira, de Oliveira, & Figueiredo, 2013 ). Droughts also degrade forest by killing trees for lack of water, even in the absence of fire (Lewis et al., 2011 ; Nepstad, Tohver, Ray, Moutinho, & Cardinot, 2007 ; Phillips, Aragão, Fisher, Lloyd, Lopez-Gonzalez et al., 2009 ). Severe droughts are becoming more frequent in Amazonia, for various reasons (Marengo & Espinoza, 2016 ), and climate-change projections indicate the likelihood of substantial future increases in these events (e.g., Malhi, Roberts, Betts, Killeen, Li, & Nobre, 2008 ). Loss of biodiversity caused by anthropogenic disturbances may even double the losses caused by the deforestation itself, as shown by study in Pará that found median losses from perturbation to be larger than those from deforestation in three of the five areas of endemism in this state (Barlow, Lennox, Ferreira, Berenguer, Lees, MacNally et al., 2016 ). In addition to degradation from logging and fire, hunting threatens wildlife (Antunes, Fewster, Venticinque, Peres, Levi, Rohe et al., 2016 ) and removes animals essential for the reproduction and dispersal of trees (Peres, Emilio, Schietti, Desmoulière, & Levi, 2016 ).

The Post-slowdown Deforestation Surge

Following the 27,772-km 2 /year peak of deforestation in 2004 , rates fell by 84% to 4571 km 2 /year in 2012 . This engendered a dangerous illusion in Brasília that deforestation was under control and that the government could therefore build roads, dams, and other infrastructure without putting the forest at risk. Unfortunately, this was never the case. Deforestation rates have trended upward since 2012 , and jumped by 29% in 2016 . The underlying forces behind deforestation have increased each year, with ever more population, investment, and roads that give deforesters access to the forest. More international markets were opening for Brazilian beef during this period, and exports were expanding. The reversal of the deforestation decline in 2012 coincided with the enactment of a major weakening of Brazil’s Forest Code, reducing restrictions on clearing near rivers and on steep hillsides and pardoning vast areas of illegal clearing done by 2008 , with significant environmental and social consequences (Metzger, Lewinsohn, Joly, Verdade, & Rodrigues, 2010 ; Soares-Filho, Rajão, Macedo, Carneiro, Costa, Coe et al., 2014 ). Most importantly, this demonstrated the extraordinary influence of the “ruralist” bloc (representatives of large landholders) and created an anticipation of future “amnesties.”

The 1965 Forest Code (Law 4771/ 1965 ), a package of regulations governing deforestation, was replaced by Law 12,651/ 2012 . In 2011 , the initial vote in the House of Deputies, where representation is proportional to population, approved the revision by a ratio of 7:1. Since 85% of Brazil’s population is urban, the vast majority of the electorate has no financial stake in being allowed to deforest more, especially in risk-prone locations. Opinion polls showed 80% of Brazil’s population opposing any changes in the Forest Code (Lopes, 2011 ). The power of money from soy and other agribusiness interests is believed to be the most logical explanation for the outcome (Fearnside & Figueiredo, 2016 ).

The most noteworthy at the time of the deforestation surge in 2016 was the political uncertainty during and after the trial of president Dilma Rousseff, who was forced to step aside when her trial began in March 2016 , culminating in her formal impeachment in August 2016 . The uncertainty in 2016 offered an opportunity for the rapid advancement of legislative initiatives to remove environmental restrictions, and this continued following the formal transfer of presidential powers (Fearnside, 2016b ). Other factors may have contributed. The value of the Brazilian real relative to the US dollar decreased by 12% from January to May 2016 (the period when decisions regarding deforestation are usually made), increasing the attractiveness of exporting soy and beef. Beef prices rose by 5%, and soy prices rose by 12.5%. The May 2016 soy price was 18% above the May average for the preceding five years. These economic factors would have contributed to the 2016 surge, but the magnitude of the surge suggests that it also had roots in the spectacular rise in the political power of the ruralists, which had begun well before the end of the previous presidential administration (Fearnside, 2017d ).

The similarities and differences in the changes in deforestation rates among the nine states in Legal Amazonia are revealing. Deforestation rates increased in all states except Amapá and Mato Grosso. Amapá is insignificant, since the state only accounted for 0.3% of the total deforestation in 2016 . Deforestation in Mato Grosso in 2016 was 1508 km 2 , though this was 5.8% less than in the preceding year. Mato Grosso has a substantial influence from soybeans, whereas in the other states the vast majority of clearing is for pasture. The importance of Mato Grosso relative to other Amazonian states has been decreasing, from 43.1% of the total deforestation in 2004 to 18.9% in 2016 , reflecting the dwindling areas of remaining forest in places that are topographically favorable for mechanized agriculture. Other factors leading to decreased clearing in Mato Grosso include the predominance of large properties in this state; these properties are more sensitive to repression measures than are smaller ones (Godar et al., 2014 ). The distribution of the 2016 surge among Amazonian states suggests a continuation of trends to increased prominence of ranching relative to direct deforestation for soybeans, and of greater importance of smaller properties relative to larger ones.

How Can Deforestation Be Controlled?

Inspection and the punishment of illegal deforestation is an important part of any effort to control the process, because the lack of this form of action fosters an assumption of impunity, with far-reaching consequences. Monitoring capabilities are important to these efforts, and the advent of the DETER program, in 2004 , provided an essential tool to allow reaction within a meaningful time period (Assunção, Gandour, & Rocha, 2013 ). Since 2003 , Brazil’s command-and-control program is administered under the Plan of Action for Prevention and Control of Deforestation in Legal Amazonia (PPCDAm) (Ministério do Meio Ambiente, 2013 ). The program has had measurable effects (Arima et al., 2014 ).

Amazonian deforestation can be controlled, but the unfounded notion that it is under control and that therefore new roads, dams, and other infrastructure projects can be built without increasing deforestation is very dangerous. The official government interpretation—that the 2005–2012 decline proves that deforestation is under control—has been repeated countless times. However, falling commodity prices (rather than governance measures) account for nearly all the decrease in deforestation rates between 2005 and 2007 , which represents 70% of the total through 2012 , when the downward trend ended. Deforestation rates did not continue to decline after 2012 , despite frequent official statements implying that the decline continued.

The effect of the repression program since 2008 rests on a fragile foundation: the 2008 Central Bank resolution linking government bank loans to an absence of pending fines (Fearnside, 2015e ). This is because the ruralist bloc has enormous influence in the national legislature, and revoking the Central Bank resolution is one of its priorities. The effectiveness of the repression program could literally be removed at the stroke of a pen.

An example of the potential for the repression of deforestation to have an effect on clearing rates is provided by a state government program, from 1999 to 2001 , in Mato Grosso (Fearnside, 2003b ). At a time when deforestation was increasing in Amazonia as a whole, the trends in Mato Grosso turned from increases to decreases in municipalities in which significant amounts forest were still available for clearing (deforestation will tend to zero independent of any repression program in municipalities with little left to clear). However, after the election of Brazil’s largest soy entrepreneur as governor, in 2002 , the program was gutted and entered a phase of “institutional subversion” (Rajão, Azevedo, & Stabile, 2012 ).

It is important that direct deforestation control measures, such as fining property owners who clear without the required licensing and restricting credit in municipalities (counties) that have been blacklisted for illegal deforestation, can have a significant effect (Tasker & Arima, 2016 ). The Brazilian foreign ministry’s long opposition to any form of international payment for avoiding deforestation was based on the belief of key individuals that controlling deforestation was impossible (Fearnside, 2012a ). Indeed, the succession of “packages” of control measures implemented after each rise in clearing rates seemed to have no effect. Brazil changed its position in 2007 , after the “slowdown” in deforestation was well underway.

Remove or Redirect Subsidies

Subsides take many forms besides the notorious fiscal incentives that massively subsidized large cattle ranches in the 1970s and 1980s. Low-interest loans are provided for actors of various sizes, including small farmers. A large subsidy, which often goes unrecognized, results from periodic “amnesties,” forgiving debts for farmers, both large and small, whose crops have failed because of weather events or other general misfortunes, thus transferring the risk of these agricultural activities to the taxpayers (e.g., Fearnside, 2001b ). Of course, a wide array of other government expenditures provides transport infrastructure and other services in remote locations, generally with only a minimal return to the government in the form of taxes. In the case of small farmers, the fact that a substantial fraction of the economically disadvantaged portions of Brazil’s rural population depends on government bolsas (stipends), such as the family stipend ( bolsa família ), and on rural retirement benefits for elderly family members, represents a substantial subsidy that maintains families in agricultural activities even when they are unprofitable in their own right. Although they are closely tied to electoral politics, these income-redistribution programs are based on poverty-reduction objectives that apply to both rural and urban residents throughout the country as a matter of social justice. Government stipends maintain important deforestation actors, such as sem terras (organized landless workers). These actors have a key role in settlement establishment and deforestation (Simmons, Walker, Perz, Aldrich, Caldas, Pereira et al., 2010 ). Government settlement projects are heavily subsidized (Peres & Schneider, 2012 ). Even at the low levels of deforestation by small farmers, rural residents emit far more greenhouse gases than do urban residents, and the impact of the larger actors is very much greater (Fearnside, 2001a ). Preventing rural-urban migration is seen as socially desirable, both by rural people who want to stay where they are and by urban residents who fear the social impact of burgeoning cities. However, municipality-level data in Amazonia indicate a positive effect of urbanization on well-being as measured by the human development index (HDI) (Caviglia-Harris, Sills, Bell, Harris, Mullan, & Roberts, 2016 ). The questions of how much rural subsidy is appropriate and of what types are extremely delicate ones.

Remove Ulterior Motives

Land speculation is a motive for deforestation that has essentially no benefit for the country and leads to substantial environmental damage. It needs to be stopped by government actions such as taxes and fines.

The present system of land-tenure establishment, which is based on deforestation, must end. Brazil has yet to make the transition from the centuries-old custom of the “regularization” of de facto possession of illegal land claims to one in which the population assumes as a matter of course that illegal occupation of land will not eventually result in a land title. A significant setback occurred in 2009 , with Provisional Measure (MP) 158 (Law No. 11,952) creating the terra legal (legal land) program that legalizes claims up to 1500 ha (which can hardly be considered a small farm). Large illegal claims are often subdivided among the various members of an extended family to gain legal title within the limits of the program. The amount of land potentially to be legalized totals 67 million ha, or half the size of the state of Pará (Fearnside, 2013a ). Most pernicious, the program leads to the logical assumption by present and future grileiros and squatters throughout the region that their claims will eventually be legalized by subsequent regularization programs. Achieving the goal of Amazonia becoming a landscape with defined and secure land tenure is essential for many reasons, including encouraging more sustainable behavior by landholders and assuring the rights of exclusion that must underlie any program for payment for environmental services, but a path to reaching this goal without provoking the perverse assumption of an eternally moving “line in the sand” has yet to be found. The “closing of the frontier” in 1890 in the western United States (Turner, 1893 ) has yet to have its parallel in Brazilian Amazonia, and a way must be found to achieve this by means other than simply running out of land (Fearnside & Graça, 2006 ).

Land-tenure establishment is handled by the National Institute for Colonization and Agrarian Reform (INCRA), which in recent years has acted almost entirely reactively, resettling squatters and sem terras (members of organized landless movements) in official settlement areas (Fearnside, 2001b ). Settlements represented 13.5% of all deforestation up to 2011 in the 1911 settlements included in a study by Schneider and Peres ( 2015 ). In a study by Yanai, Nogueira, Graça, and Fearnside ( 2017 ) covering 3325 settlements, the settlements accounted for of 21% of the deforestation up to 2013 . This process has no natural stopping point because the number of landless farmers in the country exceeds the capacity of the entire Amazon region if distributed in settlement areas (Fearnside, 1985 ). Caldas, Simmons, Walker, Perz, Aldrich, Pereira et al. ( 2010 ) expressed the implications most eloquently, “It is time to recognize past mistakes and adapt the land policy to the new reality in the Amazon that takes into consideration the environmental problems that current laws are causing. If we do not act now, the future of the poor in the region will not change; and the same cyclic processes of land occupation and degradation will occur until no forest will remain to support life in the region.”

Soy Moratorium

On July 24, 2006 , three months after the release of the Greenpeace ( 2006 ) report “Eating Up the Amazon,” Cargill and other major soy exporters of were convinced to sign a “soy moratorium” that committed them to not buy soy grown in the Amazon on land deforested after 2006 (a cutoff that was relaxed to 2008 in 2013 ). The moratorium was successively renewed, and in 2016 it was made permanent. It has had a measurable effect in reducing new forest clearing for soy (Adario, 2016 ; Gibbs, Rausch, Munger, Schelly, Morton, Noojipady et al., 2015 ). However, the soy moratorium cannot be credited with the overall decline in deforestation rates in Amazonia (the “slowdown”), as has sometimes been implied. The departure of overall deforestation rates from what is explained by commodity prices only began in 2008 , not in 2006 . The direct conversions affected by the moratorium are only a portion of the impact of soy. The moratorium does not include the cerrado , where soy expansion continues unfettered. The displaced deforestation from pastures converted to soy (either in the cerrado or in the Amazon forest) causes increasing clearing of Amazon forest for pasture, not only by means of the invisible hand of the economy, as ranchers respond to price signals, but also directly by the migration of ranchers themselves to rainforest areas. When an area becomes more profitable to use as soy than as pasture, as happened, for example, in Mato Grosso, ranchers do not switch to become soy planters. Instead, the ranchers (who represent a distinct cultural group in Amazonia; see Hoelle, 2015 ) will sell their land to a buyer with a soy-planting background (often arriving from non-Amazonian states such as Rio Grande do Sul), and the rancher will use the proceeds of the sale to buy a much larger area of cheap land in Pará on which to establish a new ranch.

Another limitation is that significant markets exist outside the exporting companies that participate in the soy moratorium. Since 2013 the main destination for Brazilian soy has been China, where purchases are little influenced by environmental impacts in other parts of the world. There are also domestic markets, including the market for soy oil in Brazil’s biodiesel program (Fearnside, 2009b ).

Cattle Agreement

In June 2009 Greenpeace released a report entitled “Slaughtering the Amazon” (Greenpeace, 2009 ), and four months later, the “cattle agreement” was signed by major slaughterhouses: JBS (Friboi), Bertin, Minerva, and Marfrig. There were actually two agreements: in July 2009 , a term of adjustment of conduct was signed; and in October 2009 , a zero deforestation agreement (G4). The agreements have been found to have had an effect in reducing deforestation despite problems with “laundering” cattle (Gibbs, Munger, L’Roe, Barreto, Pereira, Christie et al., 2016 ). “Laundering” cattle occurs when a nonparticipating ranch moves its cattle to a participating ranch, from which the cattle are sold to one of the signatory slaughterhouses. Improbably high cattle production per hectare of pasture is a sign that ranches are acting as intermediaries. This is a “common and accepted practice” and is not prohibited by the cattle agreement (Gibbs et al., 2016 , p. 8). The monitoring system tracks only properties, not individual cows (which would need to be identified by ear tags, for example). The cattle agreement is most relevant for beef being exported to other countries, although the adherence of Brazil’s largest supermarket chain (Pão de Açucar) in 2016 is an important milestone in the domestic market (Charoux, 2016 ). Earlier, 35 Brazilian supermarket chains had discontinued beef purchases from offending slaughterhouses, and similar commitments had been made by some leather buyers (Arima et al., 2014 , p. 467). As with soybeans, the fact that China is the major destination for beef undermines any possibility of pressure from consumers there affecting adherence.

An example of the problems with the cattle agreement is provided by JBS (which gets its name from the initials of its founder, João Batista Sobrinho), which, including the fusion of Friboi and Bertin, which it acquired on October 27, 2009 , is the world’s largest processer of cattle products. Shortly before the cattle agreement, Greenpeace reported a large number of cattle purchases by Bertin from ranches that had been embargoed (Greenpeace, 2009 ). After the cattle agreement, the federal prosecutor’s office found a similar pattern of violation by JBS (Greenpeace, 2011 ); in 2012 , JBS recommitted to the cattle agreement.

Protected Areas

Creating and defending protected areas is an important component of any strategy for containing deforestation. Protected areas in Brazil include both indigenous lands, which are under the National Foundation of the Indian (FUNAI), and “conservation units,” which are under the Ministry of the Environment (Ministério do Meio Ambiente [MMA]) if federal, or under equivalent state-level agencies if created by the state governments. Since advent of the National System of Conservation Units (SNUC), in 2000 , conservation units are classified into categories as “integral protection” and “sustainable use” (Ministério do Meio Ambiente, 2015 ). The integral protection category is for various kinds of parks and reserves that exclude human residents; the sustainable use category includes forests for timber management, “extractive reserves” for rubber tappers and other collectors of nontimber forest products, and “sustainable development reserves” with riverside dwellers and other traditional residents. Overlap sometimes occurs between indigenous territories and conservation units, leading to conflicts among government agencies and between the resident populations and the agencies. A case in point is a national forest (for timber management) that was created on the Tapajós River without considering the needs of the Munduruku indigenous residents, who are struggling to have the area declared as an indigenous land (Fearnside, 2015b ).

Protected areas have a significant effect on preventing deforestation (Ferreira, Venticinque, & de Almeida, 2005 ; Ricketts, Soares-Filho, da Fonseca, Nepstad, Petsonk, Anderson et al., 2010 ; Veríssimo, Rolla, Vedoveto, & Futada, 2011 ; Walker, Moore, Arima, Perz, Simmons, Caldas et al., 2009 ). Location with respect to the arc of deforestation is important in this effect (Nolte, Agrawal, Silvius, & Soares-Filho, 2013 ), and the defensibility of the sites chosen should be an essential criterion in selecting areas (Peres & Terborgh, 1995 ). The category of the protected area, together with its administration at the state or federal level, affects reserve effectiveness in preventing deforestation (Vitel, Fearnside, & Graça, 2009 ). Locational effects and political pressures can obscure these differences (Pfaff, Robalino, Sandoval, & Herrera, 2015 ). Indigenous lands have the best record in excluding deforestation (Nepstad, Schwartzman, Bamberger, Santilli, Ray, Schlesinger et al., 2006 ). In the case of the Amazon Protected Areas Program (ARPA), which beginning in 2002 created and fortified a series of conservation units to meet an objective of protecting 600,000 km 2 of Amazonian forest, the reserves have been shown to imply a reduction in deforestation (Nepstad et al., 2006 ; Soares-Filho, Moutinho, Nepstad, Anderson, Rodrigues, Garcia et al., 2010 ).

Sites can be selected to create barriers in order to block the advance of deforestation. For example, in 2004 , a 30,000 km 2 “mosaic” of protected areas was created by the state of Amazonas to block entry of deforestation from Mato Grosso. Another example is the “armored zone” ( zona blindada ) along the proposed BR-319 (Manaus-Porto Velho) Highway. This is supposed to act, in a way similar to the armor on a tank, to prevent deforestation from perforating the barrier of reserves that are parallel to the highway. Although the reserves themselves may resist deforestation, planned side roads cutting through them would simply take deforesters into unprotected areas beyond the line of “armor” (Fearnside, Graça, Keizer, Maldonado, Barbosa, & Nogueira, 2009 ). Reserves are needed in the large area that would be exposed to this migration to the west of the Purus River (Graça, dos Santos M. A., Jr., Rocha, Fearnside, Emilio, Menger et al., 2014 ). Similarly, new reserves are needed in Roraima in areas that would receive migrants from the arc of deforestation as a result of opening the BR-319 (Barni, Fearnside, & Graça, 2015 ).

The creation of protected areas is, in many cases, a question of now or never. Once population moves into and claims an area, it becomes politically impossible to create protected areas. One of the choices that must always be made is whether to prioritize the creation of areas in the integral-protection category or in the sustainable-use category. Because it is much easier to obtain political and local support for creating sustainable-use areas, these often best serve the objective of obtaining large areas of protected forest within a time frame that avoids losing the option to create a protected area altogether (Fearnside, 2011 ). Depending on circumstances, creating integral-protection protected areas can also result in social injustices. However, it is also possible to go too far in the direction of reduced protection in order to garner support. The SNUC includes as one of its protected area types the “environmental protection area” (APA). There are almost no restrictions on APAs, in practice, including in urban areas. Creating APAs may result in maps with large areas colored in green, but it does little to actually protect the forest. Instead, it offers an easy escape for interest groups intent on averting protected-area restrictions because they can always demand that a proposed protected area be an APA instead of one of the types with more real protection (e.g., Câmara, 2000 ; Pádua, 2011 ).

Protected areas are not as protected as is often assumed (Table 1 ). Deforestation takes place within these areas, including indigenous areas (Fearnside, 2005b ; Nogueira, Yanai, Vasconcelos, Graça, & Fearnside, 2017 ). There is also a tendency for the government to downgrade or downsize existing reserves, or even to revoke them completely (Bernard, Penna, & Araújo, 2014 ; de Marques & Peres, 2015 ). An example is provided by the protected areas that would be affected by planned dams in the Tapajós River basin (Fearnside, 2015a ). Another is a proposed law by legislators from the state of Amazonas to revoke protection from 10,000 km 2 of the “mosaic” of conservation units in the deforestation hotspot in the southern part of the state (Instituto Socioambiental, 2017a , 2017b ).

Table 1. Protected Areas in Legal Amazonia (a)

a Values summed from Nogueira et al. ( 2017 ), which includes area and carbon data for each protected area.

b All original vegetation, including nonforest vegetation, such as cerrado (savanna).

Since both the human and financial resources for protected areas are always very limited, one of the perennial dilemmas is whether to give priority to creating new areas or to invest in staffing and defending existing areas. So long as Brazilian Amazonia continues to have large areas of unprotected forest on government land, the better option is to maximize the creation of new areas, even if they are “paper parks” with only a token government presence. This is needed to obtain larger areas before the opportunities to do so are foreclosed. Even “paper parks” have a significant effect in inhibiting deforestation because their legal status makes it far less likely that potential invaders will be successful in gaining title to the land in the future, as compared to their invading forest in an area that is not legally protected.

Depending on whether a protected area is near or far from the deforestation frontier, its effect on deforestation will either be immediate or delayed. The priority for reserve creation will depend on the objectives that motivate the decision. It is often said that those who are primarily concerned with maintaining biodiversity and those who are primarily concerned with avoiding climate change share a natural alliance in that protecting tropical forest achieves both goals. However, this identity of interests can break down when choices must be made. If the priority is protecting biodiversity, the objective is likely to be seen in terms of a measure such as the number of species that will be maintained over a long time—theoretically permanently—making the creation of large, inexpensive reserves far from the frontier the best choice (Fearnside, 2003a ; Fearnside & Ferraz, 1995 ). In terms of climate change, the priority is likely to be measured in terms of reduced emissions over a short time period, making reserves nearer to the frontier the best choice. The financial costs and other obstacles at each distance from the frontier will determine the ideal location, which is likely not to be at either extreme in terms of distance from the frontier. In practice, the type of protected area is associated with distance from the frontier, and sustainable-use areas are more likely to be closer to the frontier than are integral-protection areas, giving the former a greater short-term effect in avoiding deforestation (Pfaff, Robalino, Lima, Sandoval, & Herrera, 2014 ).

The 2015 Paris accords have fundamentally changed the criteria for choices based on climate benefits: the objective is expressed as keeping mean global temperature from rising above a value “well below” the benchmark of 2 °C over the preindustrial average, whereas the objective was previously expressed in terms of Article 2 of the Climate Convention, which specifies “stabilization” of greenhouse-gas concentrations at a level to avoid “dangerous interference with the global climate system.” Because stabilization can take many years, even centuries, this is an entirely different time scale. Assuming that diplomats and decision-makers are serious about complying with the Paris accords, what counts is what happens in the next 20 years. In terms of protected areas, relevant benefits will be from those near the frontier. The fact that many protected areas are far from the frontier means that their climatic benefit is decreased by the Paris accord relative to other forms of mitigation that yield quicker returns. Another factor decreasing the importance of protected areas is the effect of “leakage,” or the displacement of impacts, in this case deforestation, to locations beyond the boundaries of a mitigation project. Leakage from reserve creation is of two types: “in-to-out” leakage, in which deforesters leave the area to continue clearing forest elsewhere, and “out-to-out” leakage, in which potential squatters and grileiros choose areas elsewhere in the forest to invade because the reserve decreases their chances of gaining title. Deforestation that has been displaced by leakage will continue until the available forest is exhausted in the landscape outside the reserve, after which the climatic benefit that was lost through leakage will be recovered assuming that the reserve is effective in excluding deforesters (Fearnside, 2009a ). The impact of leakage on decreasing the climatic value of a reserve increases with increasing value attributed to time, as through a discount rate. Reserves as a mitigation option therefore decrease in value with the Paris accords. By contrast, other options substantially increase in value, such as refraining from building hydroelectric dams, which are an energy source that has very high initial emissions and that emits methane, a short-lived gas with high impact while it remains in the atmosphere (Fearnside, 2015c , 2017c ).

Contain Infrastructure Projects

An essential part of any plan to contain deforestation in Amazonia is to limit new infrastructure projects, such as roads and dams. This often goes unmentioned in plans for limiting deforestation, such as Brazil’s PPCDAm (Ministério do Meio Ambiente, 2013 ) and National Plan for Climate Change (Comitê Interministerial sobre Mudança do Clima, 2008 ). Vast plans for new infrastructure imply more, not less, deforestation—one cannot expect deforestation to decrease if new projects go ahead regardless of impacts. The pattern of assuming that unrealistic governance scenarios will play out in practice is a formula for environmental disaster (Fearnside, 2007 ; Fearnside & Graça, 2009 ).

Decisions on new infrastructure represent a key element that is in the control of the government. The decision to build a road, for example, is made by a handful of government authorities, as contrasted with the individual decisions of the thousands of actors who will determine the deforestation consequences once the road is built. The decision-making process for infrastructure projects is therefore critical. Decision-making is distinct from licensing, although licensing is also important. At present, the role of environmental licensing in Brazil is largely limited to suggesting minor changes in project design or compensation measures, not to comment on the existence or not of the infrastructure project in question. This system need to reformed to ensure that environmental and social costs and benefits are transparently assessed and democratically debated before the actual decision to build a project is made (e.g., Fearnside, 2014a ). Among the changes needed to create a more rational decision-making system is to remove the underlying causes of the current bias in favor large, expensive projects regardless of their impacts. This requires making changes in the regulation of political campaign contributions (Fearnside, 2016d ). It also requires revocation of the “security-suspension” laws stemming from Brazil’s military dictatorship period that allow any judicial decision to be overturned in the interests of the “public economy” (Fearnside, 2015c ). Despite its problems, Brazil’s environmental licensing system is far better than the practices that were used before this system was implemented, in 1986 ; however, environmental licensing faces a series of immediate threats that could result in its being effectively abolished by the National Congress (Fearnside, 2016b ; Ferreira et al., 2014 ).

Abandon Myths That Divert Efforts to Contain Deforestation

A variety of myths tend to divert efforts to control forest loss in directions that fail to achieve this objective or that are counterproductive. One is the idea that “sustainable logging,” or “sustainable forest management,” will motivate long-term maintenance of the forest. It is simply assumed that what is called “sustainable forest management” is really sustainable (e.g., Ministério do Meio Ambiente & Ministério de Ciência, Tecnologia e Inovação, 2014 ). However, fundamental contradictions result in the behavior of the managers not being sustainable, no matter what their discourse or promises may be (Fearnside, 1989d , 2003a ). This is because trees in tropical forests grow at rates that are limited by biology and have no relation to the rates at which money can be made in alternative investments. In practice, the trees are in competition with a wide range of other possible investments (including first-cycle forest-management projects elsewhere), and it is more profitable for the manager to exploit the potentially renewable resource as quickly as possible and then to invest the proceeds in an option with a faster return elsewhere (e.g., Clark, 1973 , 1976 ). The first cycle, which is what is in course in virtually all forest-management projects in Brazilian Amazonia, is inherently more profitable than subsequent cycles because the large forest trees that have been growing for centuries at no cost to the manager are there for the harvesting; whereas the situation will change in a future equilibrium when the manager can only harvest what grows while the management area is being defended and maintained. In addition, based on the population biology of the trees, the current rules for management projects are unlikely to maintain forest indefinitely even if they are followed as is theoretically envisioned (Kageyama, 2000 ). Furthermore, the theoretical 30-year cycle in terra firme (unflooded upland) forests has been subverted by the inclusion of loopholes that imply a virtual zero probability of continuation after the first cycle. An example is provided by a project in Acre managing 12,000 ha (Fearnside, 2015f ). Instead of dividing the area into 30 plots, one to be harvested in each year of the cycle, the manager was allowed to harvest the entire area in only six years. Theoretically, the land would have then sat unused for 24 years until the second cycle began. The chance of this happening was obviously slim, even less so given that the area was later sold for a settlement project. The chances are even lower in the case of small management projects (up to 100 ha under management) in the state of Amazonas, which allow the entire area to be harvested in the first year, to theoretically be followed by a 29-year wait for the start of another cycle.

Another myth that diverts efforts to contain deforestation is the notion that intensification of agriculture and ranching will cause actors to stop deforesting. There are good reasons for intensification, but land sparing is not one of them. The subsidies and marketing advantages that can be garnered from this discourse represent attractions for endorsing this path, which nevertheless goes against economic logic. The idea that people’s ambitions are limited by a “full-stomach” effect, when one stops expanding production once minimal requirements are met, does not apply to individuals who are integrated into modern economies, as are almost all actors in Amazonian deforestation. A number of authors have proposed land sparing through intensification by (Sánchez, Bandy, Villachica, & Nicholaides, 1982 ; Strassburg, Latawiec, Barioni, Nobre, da Silva, V.P., Valentim et al., 2014 ; Zarin, Harris, Baccini, Aksenov, Hansen, Azevedo-Ramos et al., 2016 ), but the prospects that this strategy will have the desired environmental result are poor (Fearnside, 1987c ). Unfortunately, there is no evidence that the response to a productivity increase would be to restore forest. If pasture were to produce more, then the ranchers would simply export the excess—not keep the total production of their properties constant and reduce pasture areas. In fact, since the more highly productive pastures would presumably be more profitable than the present ones, the tendency would be to do just the opposite—expand the area of pasture by clearing more (Fearnside, 2002 ; Kaimowitz & Angelsen, 2008 ). Pasture area in Brazil is not restrained, either by a limited desire of ranchers to make more money or by global markets for beef.

Another diversion of efforts to contain Amazonian deforestation is investment in subsidizing what is known in Brazil as “recuperation of degraded areas,” that is, restoring tree cover in nonproductive areas that have already been deforested. This should not be a current priority because, under current conditions in Amazonia, it is much more expensive to recuperate a hectare of forest than to avoid a hectare of deforestation, and the benefits in terms of both carbon and biodiversity are much less (Fearnside, 2003a ). Severe limits restrict the recuperation of degraded lands through sustainable uses such as agroforestry (Fearnside, 1995 ). One is the difference in scale between the extent of degraded pastures in Amazonia and the capacity of markets and input sources to support agroforestry. Another is the logic from the viewpoint of a farmer making decisions on agroforestry: if a hectare is planted in a degraded pasture, it will produce very little compared to what it would produce if another hectare of forest is cleared and planted.

Provide Alternatives

It is not enough to prohibit deforestation and punish violations—alternatives must be offered for supporting the small farmers who sustain themselves by clearing forest, for both subsistence and commercial production. However, there is no need to provide such alternatives for investors (Fearnside, 1989b ). These larger operators can fend for themselves very well by switching to other types of investment without a need for subsidies with funds intended for environmental purposes.

The current economy of rural Amazonia is almost entirely based on destruction of the forest: selling timber and replacing forest with crops or pasture. Tapping the value of the environmental services of the forest as an alternative basis for the rural economy. Even though the environmental services, such as avoiding global warming, recycling water, and maintaining biodiversity, are worth much more to human society than the money gained from destroying the forest, the institutional mechanisms needed to transform these services into a monetary flow and to use this flow to support the rural population without provoking perverse social effects are lacking. Some progress has been made toward the goal of obtaining monetary flows through international negotiations under the Climate Convention, but the social side of this mechanism—how money would be used once obtained—is completely unresolved. Payment for environmental services (PES) is viewed as the most direct way of providing conservation incentives and avoiding perverse effects on equity (Börner, Wunder, Wertz-Kanounnikoff, Tito, Pereira, & Nascimento, 2010 ; Ferraro & Kiss, 2002 ). Land-tenure regularization is an unavoidable prerequisite for PES to function (Wunder, Börner, Tito, & Pereira, 2009 ), which creates both dangers and new opportunities to induce environmental compliance (Duchelle, Cromberg, Gebara, Guerra, Melo, Larson et al., 2014 ). In terms of cost effectiveness, command and control is still the cheapest option for reducing deforestation in Brazilian Amazonia, but PES, if directed to small actors, offers a way of reducing or avoiding negative social impacts (Börner, Marinho, & Wunder, 2015 ).

One cannot simply pay people for doing nothing or distribute money and goods to local communities without creating conflicts and destroying cultures. The recent disastrous case of compensation distributions to indigenous communities affected by the Belo Monte Dam offers a concrete example (Fearnside, 2017a , 2017b ; Heurich, 2013 ). Subsidizing purchases of nontimber forest products from extractive reserves has been suggested as one possible support mechanism (Fearnside, 1989c ). Current discussions of REDD+ (Reducing Emissions from Deforestation and Degradation) involve a series of controversies, including questions of how accounting for carbon benefits is done at both the proposal stage and later stages for verification and payment (Fearnside, 2012a , 2012b ; Vitel, Carrero, Cenamo, Leroy, Graça, & Fearnside, 2013 ; Yanai, Fearnside, Graça, & Nogueira, 2012 ). Resolution of the various open questions regarding the quantification and institutional mechanisms for rewarding the environmental services of Amazonian forests, including their carbon benefits, remains a top priority for creating an alternative to deforestation on the scale and within the time frame that this alternative is needed (Fearnside, 2013b ).

Is Brazil’s Amazonian Deforestation “Development”?

The term “development” implies a change with an effect that increases human well-being. This is not to be confused with “growth,” which refers to an increase in the throughput of matter and energy in a human society and may or may not benefit well-being (Daly, 1996 ). Fortunately, development does not necessarily require growth, which is subject to sever planetary limits (Steffen, Richardson, Rockstrom, Cornell, Fetzer, Bennett et al., 2015 ). Limiting factors within Amazonia restrain many types of use (Fearnside, 1986b , 1997c ; Fearnside & Leal Filho, 2001 ). To be considered sustainable development, the productive systems must continue to yield their benefits for a very long time, theoretically indefinitely, the Brundtland Commission’s ( 1987 ) caveat regarding nonrenewable resources notwithstanding. Many of the most common land uses, such as extensive cattle pasture, are unsustainable (Fearnside, 1983 ). In the case of cattle pasture, which dominates deforested areas in most of Brazilian Amazonia (Fearnside, 1996 ; INPE, 2014b ), the human population supported per unit area of deforestation is minimal: the productivity and financial benefit are small, and there is even less of a local benefit (Fearnside, 2005a , 2013a , 2016c ). The question of who benefits is, of course, critical to defining what is development; this author has argued that the people living in Amazonia must be benefited in order for undertakings in the region to be considered “development” (Fearnside, 1997b ).

The sequence of changes in human well-being as Amazon deforestation progresses has been characterized as a boom-and-bust pattern, in which indicators of well-being increase in the early phase of deforestation, followed by a decline after the frontier stage has passed so that the median HDI by municipality (county) returns to a low level, similar to that before the deforestation boom (Rodrigues et al., 2009 ). This conclusion was based on a cross-sectional study of statistics by the United Nations Development Programme (UNDP) for 286 municipalities from 1991 to 2000 . Celentano, Sills, Sales, and Verissimo ( 2012 ), using the same data source, reached a similar conclusion based on 399 municipalities (that also went up to 2000 ), although these authors also found that HDI could rise again after the crash in a second turning point. The boom-and-bust pattern has been contested by Weinhold, Reis, and Vale ( 2015 ), who found that the pattern in the cross-sectional data is explained by spatial correlation, because the pre-frontier phase is largely represented by poor municipalities with abundant forest in the western part of the state of Amazonas, while the postdeforestation “bust” is largely represented by heavily deforested areas in the state of Maranhão, where the persistent poverty of northeastern Brazil explains the low HDI rather than the assumed sequence based on municipalities elsewhere. The boom-bust effect disappears without these municipalities in the analysis, and extending the analysis to 2010 also eliminates the effect. Weinhold et al. ( 2015 ) also emphasize that none of the five existing longitudinal studies of specific cases shows a boom-and-bust pattern. Caviglia-Harris et al. ( 2016 ) also analyzed these municipal data for 1991 , 2000 , and 2010 , finding that cross-sectional analysis shows a boom-and-bust but that a panel analysis indicates instead a “decoupling” of HDI from deforestation.

An important aspect of municipal-level HDI data is that only the population that is present at the time of each census is considered. There are both winners and losers with the arrival and with the passage of the deforestation frontier. Many of the transformations involve a substitution of the resident population, with one set of residents being either expelled or bought out by the next. For example, small farmers may be replaced by cattle ranchers, who may at a later phase sell their land to soybean planters from other parts of the country, as has occurred in many areas in Mato Grosso. The municipalities dominated by soybeans in Mato Grosso have some of the highest HDI values in Brazil, but the initial population of these areas is no longer present and is not among the beneficiaries: only the winners remain (Fearnside & Figueiredo, 2016 ).

Both extensive cattle ranching and soybeans occupy vast areas but support few people as compared to family agriculture. However, in the approximately 3,000 settlements that have been established to support small farmers (Yanai et al., 2017 ) the sequence of developments is not so different in environmental terms. The vast majority of the land that the settlers deforest soon becomes cattle pasture, even if it is first planted a time or two in annual food crops (e.g., Diniz, Hoogstra-Klein, Kok, & Arts, 2013 ; Fearnside, 1986b , 1989e ). Altering this pattern will require changing the way land tenure is established, eliminating the tradition of legalizing invasions whether by small squatters or large grileiros (Fearnside, 1979 , 2001b ). It will also require an end to using Amazonia as a dumping ground for the country’s social problems, such as the presence of millions of poor, landless farmers. Brazil’s Amazon forest was originally the size of Western Europe, and the 784,666 km 2 that had been deforested by 2016 is the size of France and the United Kingdom combined. This alone is more than sufficient to feed the Brazilian population. Brazil is the world’s largest exporter of beef, and one of the top exporters of soybeans, meaning that the production of these products already far exceeds the amounts needed to feed the country’s population, and every hectare that is now being deforested for pasture and soy is for export. This means that deforestation can be reduced without affecting Brazil’s food supply. In other words, “zero deforestation” is possible.

Acknowledgments

The author’s research is supported by the National Council for Scientific and Technological Development (CNPq: Proc. 304020/2010-9; 573810/2008-7), the Foundation for Support of Research in Amazonas (FAPEAM: Proc. 708565), the National Institute for Research in Amazonia (INPA: PRJ15.125) and the Brazilian Research Network on Climate Change (RedeClima; FINEP: 01.13.0353-00). No funds are received from corporate sources, such as those for soy, beef, or timber. Reviewer and editor comments were helpful.

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Brazil: Amazon sees worst deforestation levels in 15 years

Deforestation in Brazil's Amazon rainforest has hit its highest level in over 15 years, official data shows.

A report by Brazil's space research agency (Inpe) found that deforestation increased by 22% in a year.

Brazil was among a number of nations who promised to end and reverse deforestation by 2030 during the COP26 climate summit.

The Amazon is home to about three million species of plants and animals, and one million indigenous people.

It is a vital carbon store that slows down the pace of global warming.

According to the latest data, some 13,235 sq km (5110 sq miles) was lost during the 2020-21 period, the highest amount since 2006.

Environment Minister Joaquim Leite said the data represents a "challenge" and said: "We have to be more forceful in relation to these crimes."

He added that the data "does not exactly reflect the situation in the last few months".

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Deforestation of the Amazon has increased under President Jair Bolsonaro. who has encouraged agriculture and mining activities in the rainforest.

He has also clashed with Inpe in the past over its deforestation, accusing the agency in 2019 of smearing Brazil's reputation.

But at November's climate conference in Glasgow, Brazil was among a number of nations who signed a major deal to end and reverse the practice.

The pledge included almost £14bn ($19.2bn) of public and private funds. Some of that will go to developing countries to restore damaged land, tackle wildfires and support indigenous communities.

Close links have previously been uncovered between the deforestation of the Amazon and international supply chains.

Last year, a Greenpeace investigation discovered links between the mass deforestation of the region and food sold in British supermarkets and restaurants.

The investigation found that Tesco, Asda, Lidl, Nando's and McDonalds were selling meat, sourced from a UK supplier, which had been fed on soy grown on farms built in deforested areas.

Just this week, Jair Bolsonaro, on tour in Dubai, told investors that attacks towards Brazil on deforestation were "unfair".

"We want people to know the real Brazil," he said, adding that 90% of the forest is still preserved.

Well, these latest figures reveal the real Brazil - a country whose government has from the very beginning talked up the opportunities in developing the Amazon and at the same time, belittled environmental concerns.

Not only that, these figures were actually dated 27 October - it appears they were held until after COP26.

Jair Bolsonaro didn't turn up to COP26, but his delegation wanted to go to Glasgow and convince the world that people were wrong about Brazil - it even said it would move forward its commitment to ending deforestation by 2028.

But with numbers like these, who can believe Jair Bolsonaro now?

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Amazon's record drought driven by climate change

• Published 24 January

One of our planet's most vital defences against global warming is itself being ravaged by climate change.

It was the main driver of the Amazon rainforest's worst drought in at least half a century, according to a new study.

Often described as the "lungs of the planet", the Amazon plays a key role in removing warming carbon dioxide from the atmosphere.

But rapid deforestation has left it more vulnerable to weather extremes.

While droughts in the Amazon are not uncommon, last year's event was "exceptional", the researchers say.

In October, the Rio Negro - one of the world's largest rivers - reached its lowest recorded level near Manaus in Brazil, surpassing marks going back over 100 years.

As well as being a buffer against climate change, the Amazon is a rich source of biodiversity, containing around 10% of the world's species - with many more yet to be discovered.

The drought has disrupted ecosystems and has directly impacted millions of people who rely on rivers for transport, food and income, with the most vulnerable hit hardest.

One trigger for these dry conditions is El Niño - a natural weather system where sea surface temperatures increase in the East Pacific Ocean. This affects global rainfall patterns, particularly in South America.

But human-caused climate change was the main driver of the extreme drought, according to the World Weather Attribution group, reducing the amount of water in the soil in two main ways.

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Firstly, the Amazon is typically receiving less rainfall than it used to between June and November - the drier part of the year - as the climate warms.

Secondly, hotter temperatures mean there's more evaporation from the plants and soils, so they lose more water.

The researchers used weather data and computer simulations to compare drought conditions in two scenarios: one with human-caused warming, and one without.

In a world where humans hadn't heated up the planet by around 1.2C, such an intense 'agricultural drought' - where a lack of rainfall and high evaporation dry out the soils - may only have happened around once every 1,500 years, the study suggests.

Climate change has made a drought of this severity around 30 times more likely, according to the researchers, and one is now expected to happen every 50 years under current conditions.

"This really is something quite exceptional," says Dr Ben Clarke, a researcher with the World Weather Attribution group.

As the map below shows, drought hit almost all of the Amazon basin. This scale - and intensity - makes it different to previous droughts, Dr Clarke told BBC News.

And if warming continues, such extreme droughts could become even more common.

"If we continue burning oil, gas and coal, very soon, we'll reach 2C of warming and we'll see similar Amazon droughts about once every 13 years," says Dr Friederike Otto, a senior lecturer in climate science at Imperial College London.

More frequent and intense droughts test the Amazon's resilience. That has already been stretched by deforestation - around one-fifth of the rainforest has been lost over the last 50 years.

Trees help the area retain and release moisture, fuelling their own clouds, and they also help to cool temperatures.

While the effect of deforestation was not directly tested in this latest study, previous research has shown it increases the vulnerability of the rainforest to drought.

Lungs of the planet

The world's largest rainforest is seen as crucial in the battle to limit global warming.

"The Amazon could make or break our fight against climate change," says Regina Rodrigues, a professor of physical oceanography and climate at the Federal University of Santa Catarina in Brazil.

In a healthy state, it takes up more carbon dioxide (CO2) than it releases.

This limits CO2 increases in the atmosphere from human activities, keeping a lid on temperatures.

But there is evidence that this may be changing, as trees die back due to drought, wildfires and deliberate clearance to make room for agriculture.

There is concern that if climate change and deforestation continue at their current pace, the Amazon could soon reach a "tipping point".

If crossed, this could lead to the rapid and irreversible dieback of the whole rainforest - potentially leading to the region becoming a significant source of CO2 emissions.

It's not known exactly where such a threshold might sit.

"I don't think that [tipping point] is what we are seeing [yet], at least in all but the driest part of the Amazon forest," says Yadvinder Malhi, a professor of ecosystem science at the University of Oxford, who was not involved in the latest study.

Despite the latest record drought, there has been some encouraging progress.

The rate of deforestation fell in 2023 compared with the year before, according to the Brazilian space agency, with President Luiz Inácio Lula da Silva pledging to halt it completely by 2030.

This - alongside urgent action to slash the greenhouse gas emissions that are fuelling global warming - can still help to protect what's left of the Amazon, researchers say.

"The loss of the Amazon forest is far from inevitable in the short-term," as long as fire and deforestation can be controlled, Prof Malhi told BBC News.

"But we do need to get to grips with stabilising global climate, as the risk increases with every fraction of a degree the planet warms."

Graphics by Erwan Rivault

Related topics

• Deforestation of the Amazon rainforest
• Amazon rainforest
• Deforestation

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Deforestation of Brazil’s Amazon Has Reached a Record High. What’s Being Done?

By Diana Roy

Last updated August 24, 2022 2:30 pm (EST)

Scientists say the rain forest is approaching a critical tipping point at which the damage is irreversible.

Deforestation of the Amazon Rainforest is threatening to accelerate past a point of no return. Countries and international organizations have called on Brazilian President Jair Bolsonaro to strengthen environmental protections and Indigenous land rights that he has weakened since taking office.

What is the current state of the Amazon Rainforest?

Scientists warn that the world’s largest rain forest is approaching a critical tipping point past which there could be severe, irreversible consequences for the planet. 

Deforestation

New data from Brazil’s National Institute for Space Research shows that more than 3,980 square kilometers of the Amazon—an area five times the size of New York City—were cleared in the first six months of 2022, the highest figure in at least six years. Continued deforestation of the rain forest is contributing to a loss in resilience , or the forest’s ability to recover from droughts, fires, and landslides . If this continues, it could cause the Amazon’s traditionally wet, tropical climate to dry out, a phenomenon known as “dieback.” It’s estimated that between 17 and 20 percent of the Amazon has been destroyed over the past fifty years, and some scientists believe that the tipping point for dieback is between 20 and 25 percent deforestation .

International demand for beef and soy incentivizes ranchers to clear the land for cattle ranching and soybean production. Brazil is currently the world’s top exporter of beef and soy, exporting more than $35 billion worth of those products in 2020.

Why does it matter?

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The Amazon plays a critical role in climate regulation. Often referred to as “the lungs of the Earth,” it produces between 6 and 9 percent of the world’s total oxygen and long functioned as a carbon sink , absorbing more carbon dioxide than it emitted. However, scientists say parts of the Amazon now emit more carbon dioxide than they absorb. This puts the Amazon’s rich biodiversity at risk: frequent fires, hotter temperatures, and changing rain patterns damage the habitats of the forest’s more than three million species, thousands of which are endangered. 

Also under threat are nearly four hundred Indigenous tribes. Deforestation has displaced several of them, inspiring Indigenous-led protest movements across Brazil. In 2021, there were 305 cases of illegal occupation of Indigenous land, which human rights groups have attributed to Bolsonaro’s continued efforts to dismantle protections for Indigenous communities. In August 2021, a coalition of Brazilian Indigenous rights groups petitioned the International Criminal Court to investigate Bolsonaro for alleged crimes against humanity and genocide. 

How did we get here?

Large-scale deforestation of the Amazon began in the 1960s, but it has accelerated under Bolsonaro, reaching a fifteen-year high in 2021. Since taking office in 2019, his government has scaled back the enforcement of environmental laws and pushed to open Indigenous lands to commercial exploitation . When widespread fires broke out in 2019, Bosonaro rejected millions of dollars in aid from the Group of Seven (G7), claiming the G7 sought to infringe on Brazilian sovereignty.

His administration has also weakened existing environmental protections. In addition to approving a 24 percent cut to the 2021 environment budget, Brazil’s Congress passed several measures that reduced citizen representation on environmental policy counsels and replaced environmental policymakers with military officials. Other efforts, including bills that would legitimize illegal squatting and erode protections for Indigenous territories, are still being deliberated.

Still, Bolsonaro has taken some steps to protect the Amazon. In January 2020, he announced the creation of an Amazon Council, consisting of fourteen cabinet members but no governors from Amazonian states, to oversee sustainable development efforts. And in May of that year, he tasked the country’s armed forces with responding to environmental crimes committed in the forest. His administration has also begun to increase the fines issued for environmental crimes. However, critics say the reliance on the military to enforce environmental protections has often undercut the work of federal environmental agencies and failed to achieve significant results.

What are the options going forward?

Bolsonaro faces growing international pressure to address deforestation. During U.S. President Joe Biden’s 2021 Leaders Summit on Climate, Bolsonaro promised to end illegal deforestation by 2030 and achieve carbon neutrality by 2050. At the United Nations’ twenty-sixth Conference of the Parties (COP26) in Glasgow later that year, he made a more ambitious pledge to end deforestation by 2028.

The president could also see financial pressure ramp up ahead of his bid for reelection in October 2022. Germany and Norway gave billions of dollars to Brazil’s Amazon Fund, created in 2008 to promote sustainable use of the rain forest, but those countries have frozen that support. Likewise, Brasilia and Washington have been negotiating a proposed $20 billion U.S. donation to help conservation efforts, but talks have stalled over Bolsonaro’s policies. Deforestation has also played a role in the European Union’s delay in ratifying a comprehensive trade agreement with the Mercosur trade bloc , of which Brazil is a member.

Michael Bricknell and Will Merrow created the graphic for this article.

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Mapping the Effect of Deforestation on Rainfall: a Case Study from the State of Mato Grosso

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Rainfall and the Role of the Amazon Forest

The Amazon Forest provides many crucial ecological services in Brazil and beyond, including serving as a carbon sink and regulating air quality. Without these benefits, Brazil and other countries would lose a primary support to their development and existence. Often in climate discussions, the forest is reduced to a carbon sink and forest loss is only used to account for emissions, but one important ecological service worthy of greater consideration is the forest’s ability to control rainfall at a continental scale, which affects agricultural production, energy generation, and urban water supply.

In this insight, Climate Policy Initiative/Pontifical Catholic University of Rio de Janeiro (CPI/PUC-Rio) show that Amazon deforestation affects rainfall in the state of Mato Grosso – one of the most important agricultural hubs in the world, home to more than three million people, and 8 hydroelectric power plants. As a case study, CPI/PUC-Rio shows that the deforestation of the Xingu River region could lead to a decrease of 7% of the annual historical average precipitation in the state of Mato Grosso. This impact varies greatly across the state and throughout the seasons. The estimated decrease in the wet season due to deforestation could reach 8% of the historical seasonal rainfall average, with the center and north of the state being the most affected. During the dry season, the estimated impact of deforestation could result in a 15% decrease of the historical seasonal average, with the center and the northwest regions being the most affected.

Table 1. Impact of Deforestation on Rainfall Reduction in Mato Grosso

Source: CPI/PUC-Rio, 2021

Continental precipitation starts in the ocean where the sun’s energy converts salt water to water vapor that is then transported through atmospheric circulation to continental lands. In doing so, each air parcel travels over different types of terrain, including densely populated areas, huge monoculture landscapes of soybeans, and dense tropical forest areas. Each type of terrain sustains and provides humidity to each air parcel differently. Forest areas, among all types, maintain and provide the most humidity to the air. The implication of this process is straightforward: air that travels over forest delivers more rainfall. As a result, deforestation reduces rainfall.

Figure 1. Rainfall Trajectory

Significantly, this rainfall process takes place over large areas covering thousands of kilometers, which means the Amazon’s deforestation affects rainfall not only in Brazil but also in Argentina and other South American countries. 

This insight summarizes findings using atmospheric transport model to connect deforestation in the Amazon to rainfall in the state of Mato Grosso. Furthermore, it provides a general framework that can be adapted as a tool to analyze the effects of deforestation on rainfall in different settings . [1]

How Deforestation Affects Rainfall: Case Study in Mato Grosso

Rainfall levels in the state of Mato Grosso are already on decline and deforestation may further reduce them. Figure 2a shows a slight drop in overall annual mean precipitation over the 35-year period between 1985 and 2020. However, the results of this study illustrate how precipitation may decline even further if deforestation increases. Also, the marked gap between wet and dry seasons (Figure 2b) may widen even more.   

Figure 2. Rainfall in Mato Grosso, 1985-2015

These figures show the average annual precipitation (Figure 2a) and monthly average precipitation (Figure 2b) for each municipality in the state of Mato Grosso. Figure 2a shows a slight decline trend, particularly between 1985 and 2005, while Figure 2b illustrates the markedly difference between the dry season (May to August) and the wet season (September to April).

Source: CPI/PUC-Rio with data from ERA5, 2021

To further investigate this phenomenon, the author considered what would happen if deforestation expanded over the Indigenous territories located in the Xingu River Basin (Figure 3). This Basin comprises eleven Indigenous territories that cover 140,000 km 2 . Apart from the northern region, the surroundings of this area have been completely deforested, due to expanded soybean planting and cattle pastures.

Figure 3. Indigenous Territories in Xingu’s River Basin

This figure shows the location of the Indigenous Territories of the Xingu River Basin. This is the region that, in the counterfactual scenario, is totally deforested.

Source: CPI/PUC-Rio with data from FUNAI and MapBiomas, 2021

How much rainfall do the territories located in the Xingu River Basin provide to the state of Mato Grosso? Which regions of the state benefit the most from this ecological service? To answer these questions, it is necessary to build a counterfactual scenario where the entirety of the Xingu’s Indigenous Territories is deforested. This counterfactual exercise shows an average decrease of 7% of the annual historical average precipitation in the state of Mato Grosso.

Figure 4 shows the rainfall decrease resulting from the Xingu’s deforestation for wet and dry seasons, as a proportion of the historical average. In the wet season, rainfall level is expected to decline up to 8% of the historical average. The effect is much more pronounced in the dry season, where the level of rainfall can decrease up to 15% of the historical average. The center of the state, where the most productive agricultural producers are, is strongly affected in both seasons. The north of the state, where the Teles Pires hydroelectric power plant is located, is one of the most affected areas in the wet season. However, due to wind patterns, rainfall in the eastern part of the state remains almost unaffected.

Figure 4. Counterfactual Variation in Rainfall due to Xingu’s River Basin Deforestation

These maps show the impact of the Xingu region deforestation on rainfall, as a proportion of the historical average. Higher values (yellow) mean a higher impact of the deforestation on rainfall. For the dry season (Figure 4a), the Xingu region deforestation may decrease rainfall up to 14% of the historical average. For the wet season, the Xingu region deforestation may decrease rainfall up to 8% of the historical average.

Source: CPI/PUC-Rio with data from ERA5, FUNAI, and MapBiomas, 2021

This exercise highlights a range of important results. First, the results show the significance of protected areas for providing dependability of rainfall and all the economic activities it helps sustain. Second, the impact of deforestation on reducing rainfall is sizeable. An 8% decrease in rainfall levels in the wet season and a 15% decrease in the dry season will affect agricultural productivity, urban water supply, and reservoirs of hydroelectric plants. Third, it is important to note that these effects are not the same throughout Mato Grosso and throughout the year. In general, agriculture, energy, and urban water supply in Mato Grosso benefit from more rainfall but, the month that each sector benefits the most from more rain is different. These variations in effects thus generate substantial differences in exposure to deforestation-induced rainfall changes not only across different regions, but also across different sectors. Potential winners and losers from deforestation are decided by a complex but predictable system of atmospheric transport. For example, the expansion of pastureland into the Xingu’s region can benefit local ranchers, at the expense of decreasing rainfall in the growing season for soybeans producers in the center of the state.

CPI/PUC-Rio also detailed the effect of the Xingu’s region deforestation on precipitation, month by month. In Figure 5, the effect for the months of the wet season is displayed. It is interesting to note that not only does the magnitude of the effects vary across months, but so does the spatial distribution. Across the wet season the biggest effects move from west to east, as the wind patterns change. Figure 6 shows a different pattern for the dry season, with the center of the state being the most affected throughout the months. This is important because sectors benefit differently from more rainfall in each month. For example, soybean producers benefit most from rain in the growing season (October to December), while a run-of-the-river dam has the greatest benefits from rain in the seasonal peak demand for energy (February to March).

Figure 5. Counterfactual Variation in Rainfall due to Xingu River Basin Deforestation Month by Month in the Wet Season

These maps show the impact of the Xingu region deforestation on rainfall for the wet season, as a proportion of the historical average. Higher values (yellow) mean a higher impact of the deforestation on rainfall. Each map shows the deforestation effect on rainfall for that month. For example, the Xingu Region deforestation may decrease rainfall in December up to 7% of the historical average of that month.

Figure 6. Counterfactual Variation in Rainfall due to Xingu’s River Basin Deforestation Month by Month in the Dry Season

These maps show the impact of the Xingu region deforestation on rainfall for the dry season, as a proportion of the historical average. Higher values (yellow) mean a higher impact of the deforestation on rainfall. Each map shows the deforestation effect on rainfall for that month. For example, the Xingu Region deforestation may decrease rainfall in April up to 12% of the historical average of that month.

Source: CPI/PUC-Rio with data from ERA5, FUNAI and MapBiomas, 2021

Finally, it is important to acknowledge that every study has its caveats. This study does not compound the synergies of climate change and other regions’ deforestation to the effect of the Xingu’s deforestation. Also, hydrological effects of deforestation on Xingu River itself are not considered, even though they are likely to further contribute to the decrease of precipitation and water supply in general. Taken together, this counterfactual exercise offers a lower bound effect of deforestation on rainfall.

Tropical forests provide a range of ecological services that are crucial to socioeconomical activities. This study by CPI/PUC-Rio provides a framework to analyze the effects of deforestation on the rainfall of regions located hundreds or thousands of kilometers away from the deforestation. This tool can give power to local governments and local populations to advocate for stronger conservation efforts in specific policies that are known to generate deforestation. The tool can also be adapted to other regions, both in Brazil and across South America.

The deforestation of the Xingu River Basin is a case that illustrates the broad range of stakeholders who would be impacted by failing to protect the region and the subsequent widespread variation in rainfall and droughts that would occur. Identifying and quantifying the gains and losses associated with deforestation is a necessary step to increase transparency and accountability of public policies in the Amazon Forest.

Methodology: A climate model to measure the Relationship between Deforestation and Rainfall

The same way that one can follow a river upstream to find its source, one can follow the wind direction to find its path from the ocean. This path is called a back trajectory of atmospheric transport. Atmospheric transport models reconstruct the back trajectory of an air parcel that is over a location at the given moment of rainfall. The author used averaged monthly wind speed and direction from ERA5 to build back trajectories for every month from 1985 to 2020.

Figure 7 shows a set of five-day back trajectories from the state of Mato Grosso for two different selected months from 2002 to illustrate what the back trajectories look like. They identify a distinctive pattern across months in the year, with the rainy season receiving winds from the Amazon (north to south) while the dry season receives winds from outside the Amazon (east to west). Each blue line represents a wind trajectory ending in a point in Mato Grosso, with the wind covering different types of terrain. The main explanatory variable of the model is a count of how many pixels (locations) with forest cover the wind has covered. The higher this variable is, the more likely it is that the air parcel can maintain and increase its humidity.

Figure 7. Back Trajectories of Atmospheric Transport, 2002

These maps illustrate the back trajectories of atmospheric transport for two specific months (February 2002 and July 2002). A blue line represents the trajectory of the wind from the ocean to a location in the state of Mato Grosso. Note that the trajectories directions are very distinctive for the two months. This is a general pattern, with the wet season being characterized by trajectories moving north to south, and the dry season by trajectories from east to west.  

In addition to the natural variability of the count of forest pixels across months in a year, the average count along the years has seen a steady decline, due to deforestation, as shown in Figure 8a, where the deviations from the average count of forest pixel per year is shown for each municipality of the state of Mato Grosso. This steady decline results in a drop of average rainfall, year after year.

To count forest pixels across paths, CPI/PUC-Rio uses data from the Pan-Amazon MapBiomas from 1985 to 2018. This data classifies land use for the entire Amazon territory using satellite data. Originally in 30 meters resolution, the data are converted to 0.25 degrees, where each pixel stores the proportion of 30 meters pixels classified as forest.

To formally estimate the effect of forest count on rainfall, a fixed effects estimator is employed, as described in Equation 1:

𝒓 𝒍𝒎𝒚 = 𝛼 + 𝜷 𝒎 𝒄 𝒍𝒎𝒚 + 𝛄 𝒍𝒎 + 𝛄 𝒚 + 𝛄𝜲 𝒍𝒎𝒚 + 𝝐 𝒍𝒎𝒚

The parameters of interest are 𝜷 𝒎 , which give the effect of forest count (𝒄 𝒍𝒎𝒚 ) on rainfall (𝒓 𝒍𝒎𝒚 ) for each month of the year. Additional variables, such as total distance traveled (𝜲 𝒍𝒎𝒚 ) and fixed effects of location-month and year (𝛄 𝒍𝒎, 𝛄 𝒚 ) control for a range of potential confounding variables that could offer alternatives explanations for the observed relationship between rainfall and forest count.  The main result of this regression is shown in Figure 8b. Each coefficient 𝜷 𝒎  shows the effect of an increase of one standard deviation in the forest count variable on rainfall, measured as mm equivalent per day. The standard errors show that, given the model, the uncertainty around the effect is low.

Figure 8. Forest Count and Precipitation, 1985 – 2015

Figure 8a shows evolution of the forest count variable (as deviations from the mean) throughout the years for each municipality of the state of Mato Grosso. Values below zero mean that the forest count is below the historical average. Note the steady decline for all series, due to the increasing deforestation. Figure 8b shows the estimated coefficients of the empirical climate model described in Equation 1. Each month (m) shows the estimated coefficient 𝜷 𝒎 . The small vertical lines show the estimated standard deviation of the estimative. The magnitude of the effect is stronger in the months of the wet season, even though, proportionally, this effect is stronger for the months of the dry season.

Source: CPI/PUC-Rio with data from ERA5 and MapBiomas, 2021

There are two main differences between the model in Equation 1 and the models that are currently found in the literature. First, the forest count variable (𝒄 𝒍𝒎𝒚 ) could be replaced with a Leaf Area Index (LAI) variable. This would require LAI to be input in counterfactual scenarios of deforestation, a task that is not straightforward, given the variability of LAI across different land uses and times of the year. Second, back trajectories are computed with monthly averaged wind data instead of hourly data. This restriction greatly simplifies data management and computation necessity. The case study for the state of Mato Grosso, for example, can be run on a personal computer. Formally, these two differences may include measurement error in our explanatory variable of forest count. Such measurement error can down bias the estimates, generating a lower bound for the effect of deforestation on rainfall.

The next step is to use this model combined with a counterfactual deforestation scenario to understand the impact of localized deforestation on rainfall. In this study, the author considered a scenario where the entirety of the Xingu’s Indigenous Territories is deforested. This deforestation will impact the forest count variable and, consequently, rainfall. Which locations will be impacted depends on the back trajectories. Even though there is substantial variation across time in the paths of each trajectory, the average path is informative of atmospheric circulation patterns. Therefore, the average effect gives an expected impact of deforestation on rainfall.

The author would like to thank Jennifer Roche, Natalie Hoover El Rashidy, and Giovanna de Miranda for the editing and revision of the text and Meyrele Nascimento and Nina Oswald Vieira for formatting and graphic design.

[1] Spracklen, Dominick, et al. “The Effects of Tropical Vegetation on Rainfall”. Annual Review of Environment and Resources 43 (2018): 193-218. bit.ly/3zPtaXF .

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• Published: 06 May 2020

Deforestation and world population sustainability: a quantitative analysis

• Mauro Bologna 1   na1 &
• Gerardo Aquino 2 , 3 , 4   na1  

Scientific Reports volume  10 , Article number:  7631 ( 2020 ) Cite this article

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• Applied mathematics
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• Population dynamics
• Statistical physics, thermodynamics and nonlinear dynamics

In this paper we afford a quantitative analysis of the sustainability of current world population growth in relation to the parallel deforestation process adopting a statistical point of view. We consider a simplified model based on a stochastic growth process driven by a continuous time random walk, which depicts the technological evolution of human kind, in conjunction with a deterministic generalised logistic model for humans-forest interaction and we evaluate the probability of avoiding the self-destruction of our civilisation. Based on the current resource consumption rates and best estimate of technological rate growth our study shows that we have very low probability, less than 10% in most optimistic estimate, to survive without facing a catastrophic collapse.

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Introduction.

In the last few decades, the debate on climate change has assumed global importance with consequences on national and global policies. Many factors due to human activity are considered as possible responsible of the observed changes: among these water and air contamination (mostly greenhouse effect) and deforestation are the mostly cited. While the extent of human contribution to the greenhouse effect and temperature changes is still a matter of discussion, the deforestation is an undeniable fact. Indeed before the development of human civilisations, our planet was covered by 60 million square kilometres of forest 1 . As a result of deforestation, less than 40 million square kilometres currently remain 2 . In this paper, we focus on the consequence of indiscriminate deforestation.

Trees’ services to our planet range from carbon storage, oxygen production to soil conservation and water cycle regulation. They support natural and human food systems and provide homes for countless species, including us, through building materials. Trees and forests are our best atmosphere cleaners and, due to the key role they play in the terrestrial ecosystem, it is highly unlikely to imagine the survival of many species, including ours, on Earth without them. In this sense, the debate on climate change will be almost obsolete in case of a global deforestation of the planet. Starting from this almost obvious observation, we investigate the problem of the survival of humanity from a statistical point of view. We model the interaction between forests and humans based on a deterministic logistic-like dynamics, while we assume a stochastic model for the technological development of the human civilisation. The former model has already been applied in similar contexts 3 , 4 while the latter is based on data and model of global energy consumption 5 , 6 used as a proxy for the technological development of a society. This gives solidity to our discussion and we show that, keeping the current rate of deforestation, statistically the probability to survive without facing a catastrophic collapse, is very low. We connect such probability to survive to the capability of humankind to spread and exploit the resources of the full solar system. According to Kardashev scale 7 , 8 , which measures a civilisation’s level of technological advancement based on the amount of energy they are able to use, in order to spread through the solar system we need to be able to harness the energy radiated by the Sun at a rate of ≈4 × 10 26 Watt. Our current energy consumption rate is estimated in ≈10 13 Watt 9 . As showed in the subsections “Statistical Model of technological development” and “Numerical results” of the following section, a successful outcome has a well defined threshold and we conclude that the probability of avoiding a catastrophic collapse is very low, less than 10% in the most optimistic estimate.

Model and Results

Deforestation.

The deforestation of the planet is a fact 2 . Between 2000 and 2012, 2.3 million Km 2 of forests around the world were cut down 10 which amounts to 2 × 10 5 Km 2 per year. At this rate all the forests would disappear approximatively in 100–200 years. Clearly it is unrealistic to imagine that the human society would start to be affected by the deforestation only when the last tree would be cut down. The progressive degradation of the environment due to deforestation would heavily affect human society and consequently the human collapse would start much earlier.

Curiously enough, the current situation of our planet has a lot in common with the deforestation of Easter Island as described in 3 . We therefore use the model introduced in that reference to roughly describe the humans-forest interaction. Admittedly, we are not aiming here for an exact exhaustive model. It is probably impossible to build such a model. What we propose and illustrate in the following sections, is a simplified model which nonetheless allows us to extrapolate the time scales of the processes involved: i.e. the deterministic process describing human population and resource (forest) consumption and the stochastic process defining the economic and technological growth of societies. Adopting the model in 3 (see also 11 ) we have for the humans-forest dynamics

where N represent the world population and R the Earth surface covered by forest. β is a positive constant related to the carrying capacity of the planet for human population, r is the growth rate for humans (estimated as r  ~ 0.01 years −1 ) 12 , a 0 may be identified as the technological parameter measuring the rate at which humans can extract the resources from the environment, as a consequence of their reached technological level. r ’ is the renewability parameter representing the capability of the resources to regenerate, (estimated as r ’ ~ 0.001 years −1 ) 13 , R c the resources carrying capacity that in our case may be identified with the initial 60 million square kilometres of forest. A closer look at this simplified model and at the analogy with Easter Island on which is based, shows nonetheless, strong similarities with our current situation. Like the old inhabitants of Easter Island we too, at least for few more decades, cannot leave the planet. The consumption of the natural resources, in particular the forests, is in competition with our technological level. Higher technological level leads to growing population and higher forest consumption (larger a 0 ) but also to a more effective use of resources. With higher technological level we can in principle develop technical solutions to avoid/prevent the ecological collapse of our planet or, as last chance, to rebuild a civilisation in the extraterrestrial space (see section on the Fermi paradox). The dynamics of our model for humans-forest interaction in Eqs. ( 1 , 2 ), is typically characterised by a growing human population until a maximum is reached after which a rapid disastrous collapse in population occurs before eventually reaching a low population steady state or total extinction. We will use this maximum as a reference for reaching a disastrous condition. We call this point in time the “no-return point” because if the deforestation rate is not changed before this time the human population will not be able to sustain itself and a disastrous collapse or even extinction will occur. As a first approximation 3 , since the capability of the resources to regenerate, r ′, is an order of magnitude smaller than the growing rate for humans, r , we may neglect the first term in the right hand-side of Eq. ( 2 ). Therefore, working in a regime of the exploitation of the resources governed essentially by the deforestation, from Eq. ( 2 ) we can derive the rate of tree extinction as

The actual population of the Earth is N  ~ 7.5 × 10 9 inhabitants with a maximum carrying capacity estimated 14 of N c  ~ 10 10 inhabitants. The forest carrying capacity may be taken as 1 R c  ~ 6 × 10 7 Km 2 while the actual surface of forest is \(R\lesssim 4\times {10}^{7}\) Km 2 . Assuming that β is constant, we may estimate this parameter evaluating the equality N c ( t ) =  βR ( t ) at the time when the forests were intact. Here N c ( t ) is the instantaneous human carrying capacity given by Eq. ( 1 ). We obtain β  ~  N c / R c  ~ 170.

In alternative we may evaluate β using actual data of the population growth 15 and inserting it in Eq. ( 1 ). In this case we obtain a range \(700\lesssim \beta \lesssim 900\) that gives a slightly favourable scenario for the human kind (see below and Fig.  4 ). We stress anyway that this second scenario depends on many factors not least the fact that the period examined in 15 is relatively short. On the contrary β  ~ 170 is based on the accepted value for the maximum human carrying capacity. With respect to the value of parameter a 0 , adopting the data relative to years 2000–2012 of ref. 10 ,we have

The time evolution of system ( 1 ) and ( 2 ) is plotted in Figs.  1 and 2 . We note that in Fig.  1 the numerical value of the maximum of the function N ( t ) is N M  ~ 10 10 estimated as the carrying capacity for the Earth population 14 . Again we have to stress that it is unrealistic to think that the decline of the population in a situation of strong environmental degradation would be a non-chaotic and well-ordered decline, that is also way we take the maximum in population and the time at which occurs as the point of reference for the occurrence of an irreversible catastrophic collapse, namely a ‘no-return’ point.

On the left: plot of the solution of Eq. ( 1 ) with the initial condition N 0  = 6 × 10 9 at initial time t  = 2000 A.C. On the right: plot of the solution of Eq. ( 2 ) with the initial condition R 0  = 4 × 10 7 . Here β  = 700 and a 0  = 10 −12 .

On the left: plot of the solution of Eq. ( 1 ) with the initial condition N 0  = 6 × 10 9 at initial time t  = 2000 A.C. On the right: plot of the solution of Eq. ( 2 ) with the initial condition R 0  = 4 × 10 7 . Here β  = 170 and a 0  = 10 −12 .

Statistical model of technological development

According to Kardashev scale 7 , 8 , in order to be able to spread through the solar system, a civilisation must be capable to build a Dyson sphere 16 , i.e. a maximal technological exploitation of most the energy from its local star, which in the case of the Earth with the Sun would correspond to an energy consumption of E D  ≈ 4 × 10 26 Watts, we call this value Dyson limit. Our actual energy consumption is estimated in E c  ≈ 10 13 Watts (Statistical Review of World Energy source) 9 . To describe our technological evolution, we may roughly schematise the development as a dichotomous random process

where T is the level of technological development of human civilisation that we can also identify with the energy consumption. α is a constant parameter describing the technological growth rate (i.e. of T ) and ξ ( t ) a random variable with values 0, 1. We consider therefore, based on data of global energy consumption 5 , 6 an exponential growth with fluctuations mainly reflecting changes in global economy. We therefore consider a modulated exponential growth process where the fluctuations in the growth rate are captured by the variable ξ ( t ). This variable switches between values 0, 1 with waiting times between switches distributed with density ψ ( t ). When ξ ( t ) = 0 the growth stops and resumes when ξ switches to ξ ( t ) = 1. If we consider T more strictly as describing the technological development, ξ ( t ) reflects the fact that investments in research can have interruptions as a consequence of alternation of periods of economic growth and crisis. With the following transformation,

differentiating both sides respect to t and using Eq. ( 5 ), we obtain for the transformed variable W

where \(\bar{\xi }(t)=2[\xi (t)-\langle \xi \rangle ]\) and 〈ξ 〉 is the average of ξ ( t ) so that \(\bar{\xi }(t)\) takes the values ±1.

The above equation has been intensively studied, and a general solution for the probability distribution P ( W , t ) generated by a generic waiting time distribution can be found in literature 17 . Knowing the distribution we may evaluate the first passage time distribution in reaching the necessary level of technology to e.g. live in the extraterrestrial space or develop any other way to sustain population of the planet. This characteristic time has to be compared with the time that it will take to reach the no-return point. Knowing the first passage time distribution 18 we will be able to evaluate the probability to survive for our civilisation.

If the dichotomous process is a Poissonian process with rate γ then the correlation function is an exponential, i.e.

and Eq. ( 7 ) generates for the probability density the well known telegrapher’s equation

We note that the approach that we are following is based on the assumption that at random times, exponentially distributed with rate γ , the dichotomous variable \(\bar{\xi }\) changes its value. With this assumption the solution to Eq. ( 9 ) is

where I n ( z ) are the modified Bessel function of the first kind. Transforming back to the variable T we have

where for sake of compactness we set

In Laplace transform we have

The first passage time distribution, in laplace transform, is evaluated as 19

Inverting the Laplace transform we obtain

which is confirmed (see Fig.  3 ) by numerical simulations. The time average to get the point x for the first time is given by

which interestingly is double the time it would take if a pure exponential growth occurred, depends on the ratio between final and initial value of T and is independent of γ . We also stress that this result depends on parameters directly related to the stage of development of the considered civilisation, namely the starting value T 1 , that we assume to be the energy consumption E c of the fully industrialised stage of the civilisation evolution and the final value T , that we assume to be the Dyson limit E D , and the technological growth rate α . For the latter we may, rather optimistically, choose the value α  = 0.345, following the Moore Law 20 (see next section). Using the data above, relative to our planet’s scenario, we obtain the estimate of 〈 t 〉 ≈ 180 years. From Figs.  1 and 2 we see that the estimate for the no-return time are 130 and 22 years for β  = 700 and β  = 170 respectively, with the latter being the most realistic value. In either case, these estimates based on average values, being less than 180 years, already portend not a favourable outcome for avoiding a catastrophic collapse. Nonetheless, in order to estimate the actual probability for avoiding collapse we cannot rely on average values, but we need to evaluate the single trajectories, and count the ones that manage to reach the Dyson limit before the ‘no-return point’. We implement this numerically as explained in the following.

(Left) Comparison between theoretical prediction of Eq. ( 15 ) (black curve) and numerical simulation of Eq. ( 3 ) (cyan curve) for γ  = 4 (arbitrary units). (Right) Comparison between theoretical prediction of Eq. ( 15 ) (red curve) and numerical simulation of Eq. ( 3 ) (black curve) for γ  = 1/4 (arbitrary units).

(Left panel) Probability p suc of reaching Dyson value before reaching “no-return” point as function of α and a for β  = 170. Parameter a is expressed in Km 2 ys −1 . (Right panel) 2D plot of p suc for a  = 1.5 × 10 −4 Km 2 ys −1 as a function of α . Red line is p suc for β  = 170. Black continuous lines (indistinguishable) are p suc for β  = 300 and 700 respectively (see also Fig.  6 ). Green dashed line indicates the value of α corresponding to Moore’s law.

Numerical results

We run simulations of Eqs. ( 1 ), ( 2 ) and ( 5 ) simultaneously for different values of of parameters a 0 and α for fixed β and we count the number of trajectories that reach Dyson limit before the population level reaches the “no-return point” after which rapid collapse occurs. More precisely, the evolution of T is stochastic due to the dichotomous random process ξ ( t ), so we generate the T ( t ) trajectories and at the same time we follow the evolution of the population and forest density dictated by the dynamics of Eqs. ( 1 ), ( 2 ) 3 until the latter dynamics reaches the no-return point (maximum in population followed by collapse). When this happens, if the trajectory in T ( t ) has reached the Dyson limit we count it as a success, otherwise as failure. This way we determine the probabilities and relative mean times in Figs.  5 , 6 and 7 . Adopting a weak sustainability point of view our model does not specify the technological mechanism by which the successful trajectories are able to find an alternative to forests and avoid collapse, we leave this undefined and link it exclusively and probabilistically to the attainment of the Dyson limit. It is important to notice that we link the technological growth process described by Eq. ( 5 ) to the economic growth and therefore we consider, for both economic and technological growth, a random sequence of growth and stagnation cycles, with mean periods of about 1 and 4 years in accordance with estimates for the driving world economy, i.e. the United States according to the National Bureau of Economic Research 21 .

Average time τ (in years) to reach Dyson value before hitting “no-return” point (success, left) and without meeting Dyson value (failure, right) as function of α and a for β  = 170. Plateau region (left panel) where τ  ≥ 50 corresponds to diverging τ , i.e. Dyson value not being reached before hitting “no-return” point and therefore failure. Plateau region at τ  = 0 (right panel), corresponds to failure not occurring, i.e. success. Parameter a is expressed in Km 2 ys −1 .

Probability p suc of reaching Dyson value before hitting “no-return” point as function of α and a for β  = 300 (left) and 700 (right). Parameter a is expressed in Km 2 ys −1 .

Probability of reaching Dyson value p suc before reaching “no-return” point as function of β and α for a  = 1.5 × 10 −4 Km 2 ys −1 .

In Eq. ( 1 , 2 ) we redefine the variables as N ′ =  N / R W and R ′ =  R / R W with \({R}_{W}\simeq 150\times {10}^{6}\,K{m}^{2}\) the total continental area, and replace parameter a 0 accordingly with a  =  a 0  ×  R W  = 1.5 × 10 −4 Km 2 ys −1 . We run simulations accordingly starting from values \({R{\prime} }_{0}\) and \({N{\prime} }_{0}\) , based respectively on the current forest surface and human population. We take values of a from 10 −5 to 3 × 10 −4 Km 2 ys −1 and for α from 0.01 ys −1 to 4.4 ys −1 . Results are shown in Figs.  4 and 6 . Figure  4 shows a threshold value for the parameter α , the technological growth rate, above which there is a non-zero probability of success. This threshold value increases with the value of the other parameter a . As shown in Fig.  7 this values depends as well on the value of β and higher values of β correspond to a more favourable scenario where the transition to a non-zero probability of success occurs for smaller α , i.e. for smaller, more accessible values, of technological growth rate. More specifically, left panel of Fig.  4 shows that, for the more realistic value β  = 170, a region of parameter values with non-zero probability of avoiding collapse corresponds to values of α larger than 0.5. Even assuming that the technological growth rate be comparable to the value α  = log(2)/2 = 0.345 ys −1 , given by the Moore Law (corresponding to a doubling in size every two years), therefore, it is unlikely in this regime to avoid reaching the the catastrophic ‘no-return point’. When the realistic value of a  = 1.5 × 10 4 Km 2 ys −1 estimated from Eq. ( 4 ), is adopted, in fact, a probability less than 10% is obtained for avoiding collapse with a Moore growth rate, even when adopting the more optimistic scenario corresponding to β  = 700 (black curve in right panel of Fig.  4 ). While an α larger than 1.5 is needed to have a non-zero probability of avoiding collapse when β  = 170 (red curve, same panel). As far as time scales are concerned, right panel of Fig.  5 shows for β  = 170 that even in the range α  > 0.5, corresponding to a non-zero probability of avoiding collapse, collapse is still possible, and when this occurs, the average time to the ‘no-return point’ ranges from 20 to 40 years. Left panel in same figure, shows for the same parameters, that in order to avoid catastrophe, our society has to reach the Dyson’s limit in the same average amount of time of 20–40 years.

In Fig.  7 we show the dependence of the model on the parameter β for a  = 1.5 × 10 −4 .

We run simulations of Eqs. ( 1 ), ( 2 ) and ( 5 ) simultaneously for different values of of parameters a 0 and α depending on β as explained in Methods and Results to generate Figs.  5 , 6 and 7 . Equations ( 1 ), ( 2 ) are integrated via standard Euler method. Eq. ( 5 ) is integrated as well via standard Euler method between the random changes of the variable ξ . The stochastic dichotomous process ξ is generated numerically in the following way: using the random number generator from gsl library we generate the times intervals between the changes of the dichotomous variable ξ  = 0, 1, with an exponential distribution(with mean values of 1 and 4 years respectively), we therefore obtain a time series of 0 and 1 for each trajectory. We then integrate Eq. ( 5 ) in time using this time series and we average over N  = 10000 trajectories. The latter procedure is used to carry out simulations in Figs.  3 and 4 as well in order to evaluate the first passage time probabilities. All simulations are implemented in C++.

Fermi paradox

In this section we briefly discuss a few considerations about the so called Fermi paradox that can be drawn from our model. We may in fact relate the Fermi paradox to the problem of resource consumption and self destruction of a civilisation. The origin of Fermi paradox dates back to a casual conversation about extraterrestrial life that Enrico Fermi had with E. Konopinski, E. Teller and H. York in 1950, during which Fermi asked the famous question: “where is everybody?”, since then become eponymous for the paradox. Starting from the closely related Drake equation 22 , 23 , used to estimate the number of extraterrestrial civilisations in the Milky Way, the debate around this topic has been particularly intense in the past (for a more comprehensive covering we refer to Hart 24 , Freitas 25 and reference therein). Hart’s conclusion is that there are no other advanced or ‘technological’ civilisations in our galaxy as also supported recently by 26 based on a careful reexamination of Drake’s equation. In other words the terrestrial civilisation should be the only one living in the Milk Way. Such conclusions are still debated, but many of Hart’s arguments are undoubtedly still valid while some of them need to be rediscussed or updated. For example, there is also the possibility that avoiding communication might actually be an ‘intelligent’ choice and a possible explanation of the paradox. On several public occasions, in fact, Professor Stephen Hawking suggested human kind should be very cautious about making contact with extraterrestrial life. More precisely when questioned about planet Gliese 832c’s potential for alien life he once said: “One day, we might receive a signal from a planet like this, but we should be wary of answering back”. Human history has in fact been punctuated by clashes between different civilisations and cultures which should serve as caveat. From the relatively soft replacement between Neanderthals and Homo Sapiens (Kolodny 27 ) up to the violent confrontation between native Americans and Europeans, the historical examples of clashes and extinctions of cultures and civilisations have been quite numerous. Looking at human history Hawking’s suggestion appears as a wise warning and we cannot role out the possibility that extraterrestrial societies are following similar advice coming from their best minds.

With the help of new technologies capable of observing extrasolar planetary systems, searching and contacting alien life is becoming a concrete possibility (see for example Grimaldi 28 for a study on the chance of detecting extraterrestrial intelligence), therefore a discussion on the probability of this occurring is an important opportunity to assess also our current situation as a civilisation. Among Hart’s arguments, the self-destruction hypothesis especially needs to be rediscussed at a deeper level. Self-destruction following environmental degradation is becoming more and more an alarming possibility. While violent events, such as global war or natural catastrophic events, are of immediate concern to everyone, a relatively slow consumption of the planetary resources may be not perceived as strongly as a mortal danger for the human civilisation. Modern societies are in fact driven by Economy, and, without giving here a well detailed definition of “economical society”, we may agree that such a kind of society privileges the interest of its components with less or no concern for the whole ecosystem that hosts them (for more details see 29 for a review on Ecological Economics and its criticisms to mainstream Economics). Clear examples of the consequences of this type of societies are the international agreements about Climate Change. The Paris climate agreement 30 , 31 is in fact, just the last example of a weak agreement due to its strong subordination to the economic interests of the single individual countries. In contraposition to this type of society we may have to redefine a different model of society, a “cultural society”, that in some way privileges the interest of the ecosystem above the individual interest of its components, but eventually in accordance with the overall communal interest. This consideration suggests a statistical explanation of Fermi paradox: even if intelligent life forms were very common (in agreement with the mediocrity principle in one of its version 32 : “there is nothing special about the solar system and the planet Earth”) only very few civilisations would be able to reach a sufficient technological level so as to spread in their own solar system before collapsing due to resource consumption.

We are aware that several objections can be raised against this argument and we discuss below the one that we believe to be the most important. The main objection is that we do not know anything about extraterrestrial life. Consequently, we do not know the role that a hypothetical intelligence plays in the ecosystem of the planet. For example not necessarily the planet needs trees (or the equivalent of trees) for its ecosystem. Furthermore the intelligent form of life could be itself the analogous of our trees, so avoiding the problem of the “deforestation” (or its analogous). But if we assume that we are not an exception (mediocrity principle) then independently of the structure of the alien ecosystem, the intelligent life form would exploit every kind of resources, from rocks to organic resources (animal/vegetal/etc), evolving towards a critical situation. Even if we are at the beginning of the extrasolar planetology, we have strong indications that Earth-like planets have the volume magnitude of the order of our planet. In other words, the resources that alien civilisations have at their disposal are, as order of magnitude, the same for all of them, including ourselves. Furthermore the mean time to reach the Dyson limit as derived in Eq.  6 depends only on the ratio between final and initial value of T and therefore would be independent of the size of the planet, if we assume as a proxy for T energy consumption (which scales with the size of the planet), producing a rather general result which can be extended to other civilisations. Along this line of thinking, if we are an exception in the Universe we have a high probability to collapse or become extinct, while if we assume the mediocrity principle we are led to conclude that very few civilisations are able to reach a sufficient technological level so as to spread in their own solar system before the consumption of their planet’s resources triggers a catastrophic population collapse. The mediocrity principle has been questioned (see for example Kukla 33 for a critical discussion about it) but on the other hand the idea that the humankind is in some way “special” in the universe has historically been challenged several times. Starting with the idea of the Earth at the centre of the universe (geocentrism), then of the solar system as centre of the universe (Heliocentrism) and finally our galaxy as centre of the universe. All these beliefs have been denied by the facts. Our discussion, being focused on the resource consumption, shows that whether we assume the mediocrity principle or our “uniqueness” as an intelligent species in the universe, the conclusion does not change. Giving a very broad meaning to the concept of cultural civilisation as a civilisation not strongly ruled by economy, we suggest for avoiding collapse 34 that only civilisations capable of such a switch from an economical society to a sort of “cultural” society in a timely manner, may survive. This discussion leads us to the conclusion that, even assuming the mediocrity principle, the answer to “Where is everybody?” could be a lugubrious “(almost) everyone is dead”.

Conclusions

In conclusion our model shows that a catastrophic collapse in human population, due to resource consumption, is the most likely scenario of the dynamical evolution based on current parameters. Adopting a combined deterministic and stochastic model we conclude from a statistical point of view that the probability that our civilisation survives itself is less than 10% in the most optimistic scenario. Calculations show that, maintaining the actual rate of population growth and resource consumption, in particular forest consumption, we have a few decades left before an irreversible collapse of our civilisation (see Fig.  5 ). Making the situation even worse, we stress once again that it is unrealistic to think that the decline of the population in a situation of strong environmental degradation would be a non-chaotic and well-ordered decline. This consideration leads to an even shorter remaining time. Admittedly, in our analysis, we assume parameters such as population growth and deforestation rate in our model as constant. This is a rough approximation which allows us to predict future scenarios based on current conditions. Nonetheless the resulting mean-times for a catastrophic outcome to occur, which are of the order of 2–4 decades (see Fig.  5 ), make this approximation acceptable, as it is hard to imagine, in absence of very strong collective efforts, big changes of these parameters to occur in such time scale. This interval of time seems to be out of our reach and incompatible with the actual rate of the resource consumption on Earth, although some fluctuations around this trend are possible 35 not only due to unforeseen effects of climate change but also to desirable human-driven reforestation. This scenario offers as well a plausible additional explanation to the fact that no signals from other civilisations are detected. In fact according to Eq. ( 16 ) the mean time to reach Dyson sphere depends on the ratio of the technological level T and therefore, assuming energy consumption (which scales with the size of the planet) as a proxy for T , such ratio is approximately independent of the size of the planet. Based on this observation and on the mediocrity principle, one could extend the results shown in this paper, and conclude that a generic civilisation has approximatively two centuries starting from its fully developed industrial age to reach the capability to spread through its own solar system. In fact, giving a very broad meaning to the concept of cultural civilisation as a civilisation not strongly ruled by economy, we suggest that only civilisations capable of a switch from an economical society to a sort of “cultural” society in a timely manner, may survive.

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Acknowledgements

M.B. and G.A. acknowledge Phy. C.A. for logistical support.

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These authors contributed equally: Mauro Bologna and Gerardo Aquino.

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Departamento de Ingeniería Eléctrica-Electrónica, Universidad de Tarapacá, Arica, Chile

Mauro Bologna

The Alan Turing Institute, London, UK

Gerardo Aquino

University of Surrey, Guildford, UK

Goldsmiths, University of London, London, UK

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M.B. and G.A. equally contributed and reviewed the manuscript.

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Bologna, M., Aquino, G. Deforestation and world population sustainability: a quantitative analysis. Sci Rep 10 , 7631 (2020). https://doi.org/10.1038/s41598-020-63657-6

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