Elsevier

Land Use Policy

Volume 92, March 2020, 104491
Land Use Policy

Brazilian policy and agribusiness damage the Amazon rainforest

https://doi.org/10.1016/j.landusepol.2020.104491Get rights and content

Highlights

  • Governmental actions reduce the control of deforestation.

  • A feedback cycle connects politicians, farmers, and the slashing of environmental protection.

  • Agribusiness plays a central role in GHG emissions in Brazil.

Abstract

Since his inauguration on January 1, 2019, Jair Bolsonaro, a declared right-wing candidate nicknamed “Tropical Trump,” has introduced measures to reduce environmental restrictions on livestock farming, the main greenhouse gas (GHG) producing sector in Brazil that is responsible for most of the deforestation in the country. This dangerous relationship between politics and livestock farming in Brazil is detrimental to environmental conservation. Politicians are introducing measures that facilitate the expansion of this type of farming, which in turn provides inputs for the food industry, i.e. agribusiness, which in turn finances politics, thus producing a dangerous cycle in forest conservation.

Introduction

Bolsonaro assumed the Brazilian presidency and, in exchange for political support, mainly of the ruralist group (deputies and senators who are linked to Brazilian agribusiness), he has introduced several measures that encourage the expansion of agriculture and livestock. Among these is a drastic reduction in funds for forest inspection and control agencies (Brasil, 2019a), freer use of agrochemicals and pesticides, a third of which contains at least one substance that is forbidden in the European Union (Brasil, 2019b; Bombardi, 2019; Gortazár, 2019), the loosening of environmental licenses, and the unsuccessful attempt to transfer the demarcation of indigenous lands to the Ministry of Agriculture.

The Amazon has a key role in mitigating global climate change because, if the deforestation situation remains, the temperature in the Amazon can rise up to 6−8 °Celsius above the 1996–2005 average from June to August until 2100. This will not only cause the death of the forest but also harm human life in many ways (Hegerl et al., 2006; Fearnside, 2006). The deforestation of the Amazon contributes significantly to intensifying the greenhouse effect both by releasing carbon from forest biomass and by releasing carbon from the soil, concentrating more than half of the rainforests and a quarter of all plant and animal species on the planet. In fact, land use change and forest are the main source of Brazilian emissions (see Appendix 1). Forest conservation is therefore essential for planet conservation (Fearnside, 2006; Huntingford et al., 2004).

In addition, there is the phenomenon of flying rivers, which are water vapor transport systems from the Amazon rainforest to the Brazilian central and southern regions. These are water vapors that are transported through the atmosphere and originate from the tropical Atlantic Ocean, being processed by the Amazon rainforest and transported to these regions. They play a fundamental role in the Brazilian water system (Marengo, 2006).

Even though Brazilian Greenhouse Gas (GHG) emissions are lower in comparison to Chinese, European or USA emissions (see Appendix 2 to top-20 global polluters), there are many good reasons to conserve the Amazon. These include decreasing agriculture and economic productivity, water availability for human use, river navigation or energy generation, and also increasing the incidence of respiratory diseases (Davidson et al., 2012)1 .

If deforestation continues to rise, reaching about 40 % of the total forest area and causing global temperatures to rise by 4 °Celsius, much of the central, eastern, and southern Amazon will surely become a savannah. This phenomenon is known as the tipping point (Nobre and Borma, 2009). In other studies, this imbalance point would be 20 % of the deforested area (Lovejoy and Nobre, 2018). By August 2018, 19.5 % of the forest had been deforested.

In this context, several studies have dealt with the influence of the Brazilian environmental policy on global sustainability. Fearnside (2016) states that the influence of politics in Brazil threatens the Amazon, mainly supporting large investment projects in the Amazon, such as dams and roads. Similarly, Azevedo-Santos et al. (2017) state that decisions involving the environmental policy in Brazil ignore scientific knowledge, and Rochedo et al. (2018) identified that the Brazilian government signalized landholders to increase deforestation, thus putting the country’s contribution to the Paris Agreement at risk. Abessa, Famá, and Buruaem (2019) emphasize that the dismantling of environmental legislation in Brazil can compromise global sustainability. Pereira et al. (2019a) have identified that cuts in agencies that oversee the Amazon, such as the Brazilian Institute of Environment and Renewable Natural Resources (IBAMA) and the Chico Mendes Institute for Biodiversity Conservation (ICMBio), may cause damage to forest conservation. It seems clear that the government is not seeking a sustainable path for economic development. Thus, the rainforest is at high risk.

There is a range of methods and data available to assess the risks to the Amazon rainforest. It should be highlighted that complex networks have contributed to the economy by proposing new methods, techniques, and properties (Schweitzer et al., 2009; Pereira et al., 2017). Generally speaking, networks are vertices or nodes connected by edges. The structure of a network is represented as a graph by a set R, which, in the case of networks that do not have weights in their connections, is defined by R(v,ε), where v=(v1,v2,v3,,vn,) are the vertices and ε=(ε1,ε2,ε3,,εn,) are the edges that connect pairs of vertices; and the number of elements in v and ε is N and M, respectively. Networks have been used in several areas such as transportation, sociology, biology, medicine, and economics, among others (Newman, 2018; Pereira et al., 2019a, 2019b).

Ecological networks have been consolidated as a method to evaluate how the diverse exchanges involving regional or global economic sectors affect the emission of greenhouse gases. Thus, Kagawa et al. (2015) analyzed the effects of global transactions on CO2 emissions, noting the existence of two large emitting communities, with emphasis on the civil construction sector in China. Hanaka et al. (2017) used network properties to calculate which sectors have a central role in CO2 emissions. There are applications in the global consumption of water (Fang and Chen, 2015), CO2 emissions embedded in the Chinese trade (Wang et al., 2017), and in energy consumption (Chen and Chen, 2015). We evaluated the sectorial emission relationships in the Brazilian economy using the network theory and found that the sectors that emit most greenhouse gases are related to livestock, agriculture, and the food industry, all of which are a part of the ruralist group.

This paper shows that the nexus between the government and the ruralist group contributes to the increase in GHG emissions. Presently, the environmental policy facilitates the expansion of livestock production in the Amazon region. This, in turn, provides cattle for the food industry that finances the politics, which is a dangerous cycle for forest conservation.

Section snippets

Ten months of Bolsonaro’s presidency

Among the most controversial measures introduced is the cut to the budget of the Ministry of the Environment, which is responsible for the agencies that directly supervise the Amazon forest, such as the Brazilian Institute of Environment and Renewable Natural Resources (IBAMA) and the Chico Mendes Institute for Biodiversity Conservation (ICMBio).

The government cut 95 % of the National Policy on Climate Change budget, 26 % of the Federal Conservation Management and Implementation Program budget,

Methods and database

The input-output model represents the trade relations between the economic sector and components of final demand in a given period. The model’s solution can be specified, according to Miller and Blair (2009), as x=Ly, where x is the sectorial output vector, L is the Leontief Inverse Matrix, that is, L=I-A-1 and y is the final demand vector. A is defined as the Technological matrix, i.e., A=aij=zijxj, where zij is the trade relationship between sectors i and j. The main difference between the

Agribusiness and GHG emissions in Brazil

The deforestation process in the Brazilian Amazon region is complex. Hoefle (2013) argues that smallholders often do the hard work of forest felling then sell out or are pushed out by landgrabbing ranchers, selling them and move on much like the smallholders do into primary forest. According to this author, ranchers accounted for 66 % of deforestation in Brazilian Amazon against 23 % caused by smallholders between 2000 and 2005.

Walker (2012) also shows that the expansion of ethanol in the

Discussion and conclusion

One way to reduce further deforestation is to return to the Soy Moratorium, an environmental pact established between 2006 and 2016 among environmentalists, farmers, and nongovernmental organizations. The moratorium sought to reconcile economic development with responsible and sustainable use of natural resources. During this period, the Brazilian Association of Vegetable Oil Industries and the Brazilian Association of Cereal Exporters and their respective associates pledged not to market

CRediT authorship contribution statement

Eder Johnson de Area Leão Pereira: Conceptualization, Methodology, Software, Visualization, Investigation, Software, Validation, Project administration, Formal analysis, Writing - original draft. Luiz Carlos de Santana Ribeiro: Data curation, Writing - original draft, Visualization, Investigation, Writing - review & editing, Formal analysis, Supervision, Validation, Writing - original draft. Lúcio Flávio da Silva Freitas: Data curation, Writing - original draft, Formal analysis, Software.

Acknowledgment

The authors gratefully acknowledge the financial support from Fundação de Amparo e Pesquisa do Estado da Bahia - FAPESB (Grant Number BOL 0261/2017).

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