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Abstract
The Brazilian Amazon exists at the nexus of rapid agricultural and environmental change. Not only is the Amazon the world's largest tropical rainforest, but it is home to 20% of the world's terrestrial species and helps maintain water supply for South America (May et al., 2013). In the last thirty years, 780 thousand square kilometers, or an area larger than Texas, of the Amazon has been lost in Brazil (INPE, 2020). Numerous public and market-based policies have been implemented to reduce deforestation, and rates declined by 84% between 2003 and 2012 through the combination of these efforts (Assunção et al., 2015). The recent spike in deforestation demonstrates that continued pressure is necessary to maintain this success. Rapid deforestation has also changed the climate; the dry season is becoming longer and more severe in regions with deforestation (Butt et al., 2011; Debortoli et al., 2015; Leite-Filho et al., 2019). From the agricultural perspective, the story of the Amazon is one of success. The region has transformed into an agricultural power house, as its cattle herd expanded by 270% in thirty years (IBGE, 2019), helping Brazil become the world's leading exporter of beef (USDA, 2019). In these papers, I investigate the direct and indirect effects of environmental policy and climate change by studying cattle production in the Amazon.
In the first essay, co-authored with Dr. Fanny Moffette and Dr. Holly Gibbs, we examine potential economic benefits of environmental policies, increased agricultural investment and productivity. Two anti-deforestation policies in the Brazilian Amazon are analyzed: the Priority List, which increases the intensity of fines for deforestation, and the G4 Cattle Agreements, which is a market exclusion mechanism. We compare cattle ranchers' optimal behavior under each policy and extract predictions about their impacts in order to determine which agricultural actors are affected and what the expected combined policy effects might be. A spatial database that covers land-use in Brazil from 2004 - 16 combined with a unique dataset of slaughterhouse locations provide sample comparability since we restrict our analysis to municipalities that ever had an exporting slaughterhouse nearby. We use variations in time and exposure levels of the two policies and find that both increased productivity, while the G4 also increased investment. This research reveals both indirect and unexpected benefits of environmental regulation.
In the second essay, I investigate a novel method of adaptation to climate change: the supply chain. Cattle production in the Brazilian Amazon is largely pasture-based despite the high level of variation in rainfall between summer and winter. Ranchers there have historically coped with the area's monsoon rainfall patterns by allowing their animals to gain and lose weight with the seasons. Deforestation in the region is increasing the length of the dry season, however, increasing the cost of sustaining an animal through the dry season. Livestock mobility allows ranchers to sell their cattle for fattening prior to the onset of the dry season, rather than investing in drought-resistant techniques themselves. I develop a theoretical model to explain how rainfall expectations affect a rancher's decision to sell cattle for fattening before the onset of the dry season, and then use this to draw testable hypotheses. I then test these hypotheses using industry-wide records of cattle movement between 2008 and 2016, and daily records of municipal-level rainfall. I find that in addition to the long term increase in sales for fattening, more animals are sold for fattening in advance of the dry season when the transition between the rainy and dry seasons is drier than normal, or when the onset of the rainy season was delayed two or three years prior. This result is strongest on large volume properties, conversely I find no evidence of adaptation on the smallest properties. These results demonstrate that, although this form of adaptation is theoretically accessible to all ranchers, owners of vulnerable properties are not yet using the market to cope with a lengthening dry season.
The third essay, coauthored with Dr. Holly Gibbs, Dr. Lisa Rausch, Matt Christie, Jacob Munger, Amintas Brandão, Ticiana Amaral, Paulo Barreto, Simon Hall, and Nathalie Walker, quantifies the deforestation that remains in zero-deforestation supply chains and the role of monitoring weaknesses and blind-spots in these Zero-Deforesation Cattle Agreements (CA). While many meatpackers now monitor the farms they buy from directly, they fail to include the large network of indirect supplying farms, such as those where cattle are born and raised in the early parts of the production cycle. Additionally, land ownership is complex in Brazil, with ranchers often owning and managing several properties as a single holding, but current assessments consider only a single property. To better understand these implementation gaps, we use data science techniques to create a novel database based on records from the Animal Transport Guide (GTA) that tracks the movement of cattle between properties and slaughterhouses across the Amazonian states of Mato Grosso and Pará. We used our database to quantify how much deforestation occurs outside of current CA monitoring systems. Altogether, we find more than 963,600 hectares of cleared land that are identifiable and monitorable in CA supply chains, but only 13\% of this occurred within the scope of current monitoring. We find twice as much deforestation by indirect suppliers than direct suppliers; ranchers also deforest twice as much on their unmonitored properties compared to their monitored properties. Our results help explain why the CA have failed to reduce total deforestation, even though slaughterhouses have reduced their purchases from direct suppliers with deforestation (Gibbs et al., 2015; Alix-Garcia and Gibbs, 2017).
