Soy in Uruguay from 1961-2016: how the adoption of soy has influenced agricultural production systems and land-use

Author: Ingrid Tejada

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Tejada, Ingrid, 2019 Soy in Uruguay from 1961-2016: how the adoption of soy has influenced agricultural production systems and land-use, Flinders University, College of Science and Engineering

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Abstract

The focus of the research reported in this thesis is on the consequences of the significant growth in soy production in Uruguay since the 1990s and its impact on agricultural production systems and land use in the country. To the author’s knowledge, it fills a lacuna in the research literature on soy in South America, particularly in the context of land systems science.

The thesis comprises eight chapters. The first chapter introduces the contexts for the research, it introduces the research themes and provides important background material on Uruguay.

The second chapter, which reviews relevant research literature, is written in the form of an essay on the evolution of soybean from a regionally important crop in northeast Asia to one of the world’s major traded commodities. Emphasis is placed on its expansion into South America and in particular Uruguay, and its roles in stimulating land-use change.

The third chapter introduces the research project design, sampling and methods used in interviews and land-use surveys.

In the fourth chapter time-series of economic data are modelled to explain the growth of soy from a minor crop to the most important export crop in Uruguay. The time-series data include macroeconomic data, export and imports, and soy production and areas from 1961-2016 for the main soy exporting and importing nations. The modelling technique used is Temporal Causal Modelling (TCM), which was released in SPSS in 2016. It is a form of time-series modelling based on Granger causality. This chapter introduces Granger causality, reviews the data used in the modelling (and the decisions behind the model choice and data inputs), explains how TCM operates in SPSS and presents the results. To the author’s knowledge, this is the first application of the SPSS model to agricultural economic data and the first application of any Granger causality model in land systems science.

Significant soy production models in Uruguay between 1961 and 2016 from TCM are discussed in Chapter 5, along with the main reasons behind the arable land-use regime shift that occurred in the 1990s. The main reasons being the outbreak of a fungal disease that devastated the sunflower crop, the influx and capital and technical knowledge from Argentina during its 1990’s economic crisis, increasing demand for soy from China and the EU, and the role of MERCOSUR.

The introduction of soy-based rotation systems is described in Chapter 6, along with a discussion of the development of the actors, processes and infrastructure that make the contemporary soy supply-chain from farm to export market in Uruguay.

Predicted land area under soy in Uruguay between 1961 and 2016 are analysed and discussed in Chapter 7. As was the case with Chapter 5, this uses data acquired from government departments and semi-structured interviews key stakeholders in Uruguay. In addition, a land-use survey of summer crops in the main soy growing provinces was carried out in February 2016. This chapter also analyses how the growth of soy in Uruguay from the 1960s to the 1990s replaced other crops, and how, since then expansion and later contraction of the area under soy has impacted pastures used for beef and dairy production in the country.

The final chapter reviews the findings and presents a conceptual model of soy-pasture dynamics for Uruguay. Limitations and their potential impacts on the research are discussed. Finally, contributions to knowledge in three areas are outlined: the agricultural geography of Uruguay, land systems science, and the application of TCM to land-use change studies.

Keywords: Soy, Land-use change, Land-use science, Pasture, Commodity, Indirect and Direct Land-use, Uruguay, South America, Teleconnections

Subject: Biological Sciences thesis

Thesis type: Doctor of Philosophy
Completed: 2019
School: College of Science and Engineering
Supervisor: Professor Andrew Millington