UNIVERSIDADE ESTADUAL DE CAMPINAS SISTEMA DE BIBLIOTECAS DA UNICAMP REPOSITÓRIO DA PRODUÇÃO CIENTIFICA E INTELECTUAL DA UNICAMP

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Cidade Universitária Zeferino Vaz Barão Geraldo CEP 13083-970 – Campinas SP Fone: (19) 3521-6493 http://www.repositorio.unicamp.br Toward a Spatial Understanding of Staple Food and Nonstaple Food Production in Brazil∗

J. Christopher Brown and Lisa Rausch University of Kansas

Veronicaˆ Gronau Luz State University of Campinas

Brazilian agricultural census data at the municipal level are used to develop and map a simple index of staple food versus nonstaple food agriculture for Brazil over time (1996–2006). The results show spatial variation in the direction and degree of the shift toward or away from staple food cropping across Brazil. The index is presented as an important methodological step toward a systematic geographic understanding of crop share changes surrounding food versus fuel and other nonfood crop production. Key Words: biofuels, Brazil, food security, food versus fuel.

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Los datos del censo agropecuario brasileno˜ a nivel municipal se utilizan para desarrollar y cartografiar un ındice´ simple de la agricultura de alimentos esenciales versus la de alimentos no esenciales del Brasil durante un tiempo (1996–2006). Los resultados muestran variacion´ espacial en la direccion´ y grado del cambio hacia cultivos para alimentacion´ esencial, o lo contrario, en Brasil. El ındice´ se presenta como un paso metodologico´ importante hacia un entendimiento geografico´ sistematico´ de cambios hacia un tipo de cosecha compartida que privilegia la produccion´ de alimentos, contra las cosechas para combustibles y otra produccion´ no alimentaria. Palabras clave: biocombustibles, Brasil, seguridad alimentaria, alimentos vs. combustibles.

he market for biofuels is growing for a number of nied by numerous consequences for carbon balance, T reasons, including rapidly rising fossil fuel prices, water use and quality, the survival of small farmers alternative fuel use targets, and national security issues and indigenous groups, and biodiversity, among other (Coyle 2007; Goldemberg 2007; Borras, McMichael, human and environmental consequences (Altieri and and Scoones 2010; Brown 2011). Chakravorty, Bravo 2007; Laurance 2007; Naylor et al. 2007; Chaves Hubert, and Nostbakken (2009) reported that approx- et al. 2008; Fargione et al. 2008; Sawyer 2008; Pimentel imately 1 percent of global cropland is dedicated to et al. 2009; Walker 2011). biofuel production, but this percentage was likely to This article makes a contribution toward the effort grow with increases in biofuel demand (data from to track shifts in agricultural area dedicated to food 2004). Many scholars and policy analysts express con- versus fuel production. We first outline the general dif- cern about the socioeconomic and ecological conse- ficulties in tracking shifts in food versus fuel in world quences of the expected increases in the production agriculture. We then discuss the case of food versus of biofuels around the world. These concerns are ex- fuel more specifically in Brazil, a major agricultural pressed generally in what many refer to as the food producer that finds itself often at the center of debates versus fuel crisis literature. Simply stated, authors in about the food versus fuel crisis. Next, we outline a this literature are concerned that promotion and prac- simple systematic approach to the study of food versus tice of agriculture for biofuel production are occurring fuel production changes in Brazil between 1996 and at the expense of land use leading toward food security; 2006 using municipal-level agricultural census data the world’s push to feed cars and trucks is making it and an index that tracks staple food (hereafter, food) more difficult to feed the world’s growing population, versus not staple food (nonfood) agriculture. Finally, now at 7 billion (Brown 2011). Authors of this litera- we identify regional hot spots where crop area is show- ture claim that threats to food security are accompa- ing major shifts to or away from food crop production.

∗ J. Christopher Brown and Lisa Rausch recognize the support of the College of Liberal Arts and Sciences, University of Kansas; the National Science Foundation under Award No. EPS-0903806; and matching support from the State of Kansas through the Kansas Board of Regents. Veronicaˆ Gronau Luz recognizes the support of the Graduate Scholarship Exchange Program, under Award No. BEX: 2039/10–9, of the CAPES Foundation, an agency of the Ministry of Education of Brazil. Thanks also to the anonymous reviewers for their helpful comments. We are especially grateful for many long discussions with Johannes Feddema that led to our modeling of the food/nonfood index on the climatic moisture index he developed with Cort Wilmott. Any errors remain ours.

The Professional Geographer, 66(2) 2014, pages 249–259 C Copyright 2014 by Association of American Geographers. Initial submission, April 2012; revised submissions, July and September 2012; final acceptance, September 2012. Published by Taylor & Francis Group, LLC. 250 Volume 66, Number 2, May 2014

Tracking Food Versus Fuel duction to the land tenure rights of both small farmers and indigenous peoples living in the Amazon (Walker If indeed there are shifts in the food versus fuel focus of 2011). Other concerns involve the hydrological issues the world’s agriculture, a number of issues make those related to conversion of land to pastures and fields shifts and their consequences difficult to track. First of (Chaves et al. 2008). Biofuel demand has been shown all, it is necessary to define what is food and what is to be a driver in deforestation, as new lands are incor- fuel. This is not a simple task; take corn, for example. porated into the agricultural landscape to accommo- In the United States, corn ends up in both the human date these increasing demands (Hazell and Evans 2011; food chain, directly or via feed to animals, but it also Walker 2011). Others have raised concerns about the ends up in the ethanol industry for fuel production. high carbon debt of biofuel production, particularly Thus, a rise in corn acreage does not in and of itself when their production involves the conversion of na- mean a shift toward food or fuel. As detailed later, this tive forests and grasslands (Fargione et al. 2008). Brazil problem can be treated by knowing as much as possible has lots of arable land spread across the country, pro- about a given crop’s end uses in the commodity chain. duces most of its own food, has a rapidly growing and Second, even with this issue resolved, we cannot trace changing industrial agriculture sector, and has a pop- how relative acreage changes actually play out spatially ulation that, until recently, maintained relatively tra- in the landscape regarding food versus fuel production. ditional consumption of rice, beans, and manioc as Without a project to map with satellite remote sens- staple foods. Much of the arable land, however, is cov- ing all of the food and fuel production areas of entire ered by biodiverse, carbon-rich forests and grasslands countries or continents, we can never know over large (Aglionby and Minder 2007). Brazil is also a coun- areas whether fuel crop fields are replacing food crop try with large amounts of annual municipal-level agri- fields. Such a shift, however, is not the only way fuel cultural data available online from its Geography and crop production could come at the expense of food Statistics Institute (IBGE). production. With the globalized nature of food and We must consider a number of factors about Brazil- fuel production, increases in fuel production in one ian agriculture, Brazilian diet, and commodity chains area might cause change, affecting food production or to properly identify what are food and fuel crops in having other negative consequences, in areas far away the country. Brazilian dietary concerns are consistent through a number of different mechanisms. For ex- with those of a developed economy—the incidence ample, Laurance (2007) argued that producing corn of obesity and related diseases is now more preva- for ethanol in the United States decreases the global lent than malnutrition (Monteiro, Conde, and Popkin supply of soybeans, perhaps contributing to deforesta- 2002; IBGE 2004, 2010). Brazil grows enough food to tion in distant places such as the Amazon rainforest. be a leading exporter of poultry, beef, orange juice, soy, Many existing quantitative studies that address the re- and sugar (U.S. Department of Agriculture and For- lated issues of food security and changes in crop shares eign Agriculture Service 2011), and it has also been a from food to other uses draw on highly aggregate data leader in the biofuel sector, as evidenced by its success- compiled at a global level or a national scale. Stud- ful and innovative ethanol program (Sachs, Maimom, ies conducted at more local scales are rare (Colbran and Tolmasquim 1987; Goldemberg 2007). Markets and Eide 2008), so the outcomes on the ground, and for soy and corn continue to grow. Food security was possible adaptations of local farming systems to these an important focus of Brazil’s federal government un- global-scale pressures, remain unknown. The scale of der the leadership of President Luiz Inacio´ Lula da analysis of shifts in food versus fuel production must Silva (2003–2010) of the Worker’s Party, even as bio- be flexible to illuminate global to more localized shifts. fuel production and industrial agriculture were actively Despite the difficulties of tracking food versus fuel promoted as well. production spatially, it is essential to develop tools to Heated rhetoric related to the issue of producing do so over large areas in a relatively quick and inexpen- food versus fuel can be used to make persuasive, but sive way. Data sets are readily available at the municipal difficult-to-verify, claims about food security in Brazil or county level that could be used on an annual basis (Birur, Hertel, and Tyner 2007; Ozorio de Almeida to track likely shifts in food versus fuel production in 2009). The complex and sometimes deceptive supply a number of different countries. The challenge is to chains of agricultural products in the modern agro- identify food and fuel crops in a given country and industrial system further complicate this. Consider then develop an index that allows for identification of soybeans. Although used as a food crop in other parts areas shifting from one to another between any years of the world for centuries, relatively little of Brazil’s for which there are data. We take this next step by soy crop ends up directly in the bellies of Brazilians considering the case of food versus fuel in Brazil. (Reenberg and Fenger 2011). Since large-scale culti- vation began in Brazil in the 1970s, most Brazilian soy Food Versus Fuel in Brazil has been destined for industrial uses, first because it was difficult for producers to make soy-derived foods Brazil is an ideal country for which to develop such palatable for Brazilians (Hasse 1996). Soy continued in an index. It is a country that is often at the center of its industrial role in Brazil because of the development debates in the food versus fuel literature. Researchers of processing methods for the derivation of chemicals have investigated the threat of increasing biofuel pro- for a multitude of manufacturing uses, including food Staple Food and Nonstaple Food Production in Brazil 251 additives. Soybeans have also become an important in- production. This allows for addressing more compre- gredient in animal feed mixes. hensively the alternative uses of some crops (corn, soy, The same can be said for corn consumption, which and sugar) for biofuel production as well as for other has actually declined in the population’s diet since the industrial uses and for the production of animal feed. 1970s, even though the amount of corn being grown From an energy flow standpoint, food security is in- in Brazil has remained relatively steady (Companhia creased when land is put into production for staple Nacional de Abastecimento 2010). Over 65 percent crops that are directly consumed by humans. Under of national corn production in the 2000s was used as this framework, an increase in acreage of crops to feed animal feed, seeds, and exports, whereas less than 10 to animals, which are then consumed by humans, does percent went for human consumption (Duarte 2000, not count as increasing food security, because there 2007; Pinazza 2007). Thus, both corn and soybeans is an enormous loss of energy through trophic lev- are predominantly used as a basic ingredient in an- els. Therefore, crops destined for use in livestock feed imal food and biofuels (biodiesel), not as foodstuffs may be considered nonfood products, again as regards (IBGE 2008), and so their increased cultivation should questions of food security (Magdoff 2008). The same not be considered an increase in food production per is true for crops that are highly processed into deriva- se. Moreover, the very same soybean can be used to tives that might end up in packaged foods or in any produce oil (for human consumption or biodiesel cre- number of nonconsumable industrial products. Even ation) as well as meal (for livestock consumption). In though some portion of these crops might end up other words, food and nonfood are not mutually ex- on Brazilian tables for direct consumption, this por- clusive (Associac¸ao˜ Brasileira das Industrias´ de Oleos´ tion is miniscule in comparison to the amount of the Vegetais 2012), making it extremely difficult to accu- crop directed toward nonfood ends. Moreover, despite rately determine at the beginning of the production Brazil’s recent economic boom, many industrialized chain whether food or something else is ultimately be- products remain out of the reach of the country’s poor- ing produced. est people, those who are most affected by rises in food Historically, much of Brazil’s population has not prices and are least likely to eat a varied diet. Thus, been able to meet its minimum nutritional needs. Since our conception of food for the purposes of our analy- the 1970s, though, average total calories available for sis is restricted to the country’s three main staple crops each Brazilian has been increasing steadily (2,408 in that can be produced successfully throughout most of 1970 to 3,094 in 2005; Monteiro, Conde, and Popkin Brazil’s territory: rice, beans, and manioc. This has the 2002), although food security has remained an ongo- dual purpose of simplifying our study and making our ing issue for many in Brazil due to inflation, income point that when production of other crops comes at disparity, and the physical distribution of foodstuffs the expense of these crops, Brazil’s most vulnerable (Coelho 2005). In the last four decades, concurrent might suffer. with the so-called soy boom and general expansion of For our analysis we used data from IBGE for the industrial-scale monoculture, Brazil has been experi- amount of area planted with a certain crop in each of encing an important nutritional transition, featuring Brazil’s roughly 5,500 municipalities (IBGE 2012).1 a shift toward obesity and away from malnutrition. Table 1 shows those crops considered food and those Whereas malnutrition in children and adults has been considered nonfood for the purposes of this study. declining, the prevalence of overweight and obese indi- Food crops are those for which the majority of the viduals has increased steadily (Batista Filho and Rissin total national yield is consumed by Brazilians in whole 2003). The country has seen an overall increase in fatty or minimally processed form and can be considered foods (especially in saturated and trans fats), sugar, staples of the Brazilian diet. Because we are using data soda, and processed foods in the diet of its entire pop- that are national in extent, we have only used those ulation. Animal protein foods like beef, milk, and their crops that are grown in most of the country or at least derivatives are being consumed more frequently by grown in large quantities in significantly large areas the higher income population when compared with of the country. Nonfood crops are those for which the low-income population, but an overall increase has yield (a majority) goes toward indirect or nonhuman occurred in both classes all the same (Levy Costa et al. consumption as previously discussed. Our categoriza- 2005). Consumption habits are also changing with re- tions correspond closely with those previously cited by gard to foods traditionally considered to be staples on Ozorio de Almeida (2009). the Brazilian table. For example, the population as a whole is consuming less rice and beans than they did Ta b l e 1 Classification of major crops in Brazil a decade ago, although consumption is still highest in the low-income population (Levy Costa et al. 2005; Food crops Nonfood crops Instituto de Economia Agrıcola´ 2009). Rice Sugarcane With these issues in mind, for the purposes of our Beans Soybeans study, we have refined the food–fuel terminology. The Manioc Eucalyptus heart of our concern is ultimately food security, so as Wheat Cotton Corn food security relates to the food versus fuel debate, Pasture we should really be referring to food versus nonfood 252 Volume 66, Number 2, May 2014

Our objective is not to map all possible crops typi- After the index was calculated, duplicate cases and cally grown on small holdings. Displacement of horti- incomplete cases (cases for which there were no data culture and other crops grown primarily on relatively available for either total food crops or total nonfood small land-holdings is not yet seen as a major threat in crops) were removed from the data set. Because the in- Brazil and, in any case, would require data with even dex is scaled from −1to+1, no outliers were present finer detail than those available for this study. Thus, in this variable after these no-data cases were removed. we have limited this analysis to those crops that meet To compare index values for the 2 years, a third value our relatively restrictive criteria, recognizing that this was calculated for each municipality: the difference be- study is only meant to be a starting point for a method tween index values from 1996 to 2006 (Delta96–06 = to track food versus nonfood production. i1996–i2006). Delta96–06 values fall on a scale of −2to +2, with +2 being an extreme move from total non- Methods food to total food and −2 as an extreme move from total food to total nonfood. Brazil has more than 5,500 municipalities (analogous For the spatial analysis, the index data were dis- to counties in the United States), most of which con- played in ArcGIS (Environmental Systems Research tain some kind of agricultural activity. Area planted Institute [ESRI] 2011, version 10). Municipal redis- in hectares for each food and nonfood crop was tricting was addressed using the method developed by downloaded from the IBGE (see http://www.sidra. Brown, Brown, and Desposato (2002). Because we are ibge.gov.br/) for the years 1996 through 2006, which primarily interested in changes in cropping patterns are the years of the most recent complete agricultural or shifts toward or away from food crops over time, censuses conducted at the municipal level by the IBGE. we focused on the patterns revealed by visualizing the The data were organized at the municipal level, the Delta96–06 variable. Choropleth maps of Brazil with smallest spatial resolution available. A food–nonfood the index calculated at the municipal level were gener- index was created using the crop area data. The index ated. This index is meant to be a tool for systematically is based on the same structure as the moisture index selecting areas of interest for further investigation and developed by Willmott and Feddema (1992), chosen field work, so our initial interest in this exploratory for its simplicity in normalizing data around a value of project is in locating possible extreme areas of change 0. The following equations were used to calculate the toward or away from food production. We set the bins index: for displaying the Delta96–06 values to highlight ar- eas with this goal in mind to enable visual detection of If NF = F, Index = 0 areas of extreme shifts.   Spatial pattern analysis was also conducted using F ∗ If NF > F, Index = 1 − Getis-Ord Gi statistic, which helps to identify hot and NF cold spots in spatial data or, in other words, clusters   of points with higher or lower (higher in magnitude) NF If F > NF, Index = − 1 values than would be expected in a random distribu- F tion of values. (ESRI 2011). These statistics were used to identify potential areas of interest that experienced where NF is the nonfood planted area (ha) and F is the especially strong shifts toward or away from food pro- food-planted area (ha). duction in Brazil during the period from 1996 to 2006. The index is a modified ratio of total area planted in food and nonfood crops, based on the total number of hectares planted in rice, beans, manioc, and wheat Results (the major food crops for domestic consumption in The study revealed considerable spatial variation in Brazil) as the food crops and the total hectares planted shifts toward or away from food production, using in sugarcane, soybeans, eucalyptus, cotton, corn, and our index. Figure 1 shows the spatial distribution of pasture (major commercial crops and land uses) that change in Food/Non-Food Index values from 1996 to do not lead to direct domestic food consumption as 2006 (Delta96–06). Significant clusters of high and low the nonfood crops. The index was calculated for each values were found in the Amazon, along the northern year and an index value calculated for each municipal- coast, and the south (Figure 1). A standard Getis-Ord ity in Brazil. The values of the index range from −1 ∗ Gi statistic was calculated for each data point (munic- to +1. An index value of +1 would mean that the mu- ipality); these statistics and their p values were mapped nicipality was planted entirely in nonfood crops and to enable the visual detection of hot and cold spots in a value of −1 would mean that the municipality was the distribution of Delta96–06 (Figure 2). planted entirely in food crops. The majority of the values, then, will fall somewhere between −1and+1 because few municipalities are devoted entirely to one Discussion kind of agriculture or the other. The equation for the index is inverted if the amount of food area is larger This analysis shows that variation exists in both the than the nonfood area to maintain the possible values direction (toward or away from planting food crops) for the index between −1and+1 for easy comparison and degree of cropping shifts across Brazil. The food/ across years. nonfood index presented in this study is an important Staple Food and Nonstaple Food Production in Brazil 253

Figure 1 Changes in food/nonfood index from 1996 through 2006 (Delta 96–06). F/NF = food/nonfood. Source: IBGE. (Color figure available online.)

tool toward developing a spatial understanding of these spot analysis of the distribution of low or high index changes and focusing efforts to uncover mechanisms values can also help researchers identify areas for fu- driving these changes at local and regional levels. ture case studies. Once particular hot spots have been Predictably, there appear to be clusters of munici- identified using index values or, as we present in this palities shifting their croplands to nonfood production analysis, the size of the change in index values over in the northern and western Amazon, where ranching a particular time period, additional studies with the (pasture) and, to a lesser extent, soybean farming are goal of determining the specific land change dynamics prominent and expanding activities (Figure 3). In the involved in wide index value shifts can follow. Such southern Amazon and cerrado (savanna) region, where studies could include high-spatial-resolution satellite significant growth in Brazil’s large-scale agricultural remote sensing to determine precise land-use/land- production has occurred, there appears to have been cover changes. These could then be coupled with land very little change in the ratio of food planting to non- manager and other interviews or surveys to help de- food planting. In this area, either food production is termine the human drivers of land change. keeping pace with expansion of plantings of soybeans, Consider the hot spot of low index change values corn, and pasture or else the majority of the expansion identified with the Gi∗ statistic in Figure 4. This is to new lands for these crops already occurred before a group of forty-five municipalities in western Santa 1996. Shifts toward nonfood in the south of Brazil Catarina (SC). During the study period, there was a might be due to expansion of sugarcane production. decline in land area planted in beans of 80 percent Perhaps most surprising are the number and distri- from 1996 to 2006. This is consistent with a steady bution of municipalities showing moderate or strong decline in SC and the country of Brazil as a whole over shifts toward food production between 1996 and 2006. this time period, although the decline in the hot spot Some of these municipalities are in the Amazon, but zone appears to have been steeper. In SC overall, the many of these are along the northern coast (Figure 2), decline in area dedicated to beans was only 50.9 per- in the northeast, and in the south and appear to be in- cent over the time period and in Brazil as a whole, the terspersed with municipalities showing moderate shifts decline was only 5.7 percent over the time period. In toward nonfood production. Future work should fo- the hot spot municipalities of SC, rice planting area cus in on these regions of interest to look for drivers also declined by 33 percent, and wheat declined by of shifts toward or away from food production and the 57 percent. Manioc area dropped 18 percent. Regard- impacts of these shifts on local and regional levels. Hot ing nonfood crop production, sugarcane area increased 254 Volume 66, Number 2, May 2014

Figure 2 Getis-Ord Gi∗ for change in index 1996 through 2006 and associated p values for municipalities in Brazil. F/NF = food/nonfood. (Color figure available online.)

only about 1 percent. Area for corn planting declined tion of staple food crops declined significantly, from 10 percent, soybean area increased 120 percent, and 129,974 ha in 1996 to 36,537 ha in 2006, a loss of pasture area increased by 54 percent (Table 2). Be- 93,437 ha or a decline of 72 percent. Major non- sides beans, the changes in the areas of the other crops food crop acreage only increased by 78,877 ha, leaving planted in the municipalities in this hot spot appear to 14,560 ha of cropland unaccounted for in this hot spot be consistent with the changes happening in SC and area. Future studies involving satellite remote sens- Brazil as a whole. Cotton and eucalyptus production ing could potentially determine how this land is be- were negligible in this region. ing used, whether abandoned or converted for other The increase in soybean, sugarcane, and pasture uses. Moreover, the sharp decline in food crops ap- planting alone, though, does not adequately account parently occurring in this hot spot does not appear to for the massive decrease in food crops being planted in be consistent with changes in SC as a whole or Brazil. these municipalities. Total acreage devoted to produc- Acreage devoted to staple food crops has remained Staple Food and Nonstaple Food Production in Brazil 255

Figure 3 Changes in food/nonfood index from 1996 through 2006 (Delta 96–06), with states of the Legal Amazon and the south region of Brazil highlighted. F/NF = food/nonfood. (Color figure available online.)

quite even throughout the study period in both SC literature on this question. Many researchers have state and Brazil. When comparing food versus non- focused on government policies, including subsidies food production at different scales, different patterns for biofuel production, mandatory blending require- are likely to emerge that can lead to formulation of ments, and tariffs that might incentivize planting novel hypotheses that can be tested with additional so- biofuel crops instead of staple food crops (Birur, cioeconomic data provided by IBGE at the municipal Hertel, and Tyner 2007; Cassman and Liska 2007; scale. Clancy 2008; Tenenbaum 2008; Pimentel et al. 2009). It is beyond the scope of this study to investigate Other studies focus on the social dynamics of food se- the particular mechanisms at work in SC, Brazil, curity, highlighting ways that the land tenure changes and globally that have led to such a decrease in food related to biofuel expansion push out small-scale and production and the possibility of creating a region subsistence farmers who are important food producers with decreased food security. We do, however, want in many areas (Altieri and Bravo 2007; Fargione et al. to identify some of the major varied forces in the 2008; Tenenbaum 2008). Changes in diet such as

Ta b l e 2 Percentage change in crop area in Santa Catarina hot spot

Percentage change from 1996 Percentage change from 1996 Food crops through 2006 Nonfood crops through 2006

Beans −80 Sugarcane +1 Rice −33 Soybeans +120 Manioc −18 Eucalyptus — Wheat −57 Cotton — Corn −10 Pasture +54 Change in total crop acreage, 1996–2006 Total food crop acreage −93,437 ha Total nonfood crop acreage +78,877 ha Balance −14,560 ha 256 Volume 66, Number 2, May 2014

Figure 4 Hot spot visualization of food/nonfood index changes, Santa Catarina region. F/NF = food/nonfood. (Color figure available online.)

increased global demand for livestock products and Tenenbaum (2008) has found that the net economic increased industrial use for certain crops like soybeans impact of increased biofuel production might be posi- might also encourage farmers to plant oilseeds for tive on producers but negative on consumers. Review- feed rather than food staples (Hazell and Evans ing several model-based studies, Chakravorty, Hubert, 2011). and Nostbakken (2009) have found that policies that Much of the debate, though, comes down to the encourage the production of land-based or crop-based ways in which increases in biofuels affect food security biofuels will likely increase deforestation and carbon- by first affecting food prices (Rosegrant et al. 2006; release rates and cause food prices to rise for the next Cassman and Liska 2007). Ugarte and He (2007) have few decades but that technological improvements in shown that crops for biofuels will threaten food secu- crop yields, development of second-generation biofu- rity by driving up grain prices and taking up cropland if els, and protectionist policies for biofuel markets in biofuels continue to increase at current rates. Increased developed countries will mitigate these effects. production of biofuels in the United States paradoxi- These existing studies have yet to be comple- cally requires massive petroleum inputs in the form of mented by studies that help identify the sociopolitical, fuel for machinery operations and fertilizer, threaten- environmental, and socioeconomic processes that de- ing food security throughout the world by driving up termine changes in the relative proportions of food the cost of these inputs (Pimentel and Patzek 2007). and nonfood production in particular areas like our Staple Food and Nonstaple Food Production in Brazil 257 case study of western SC, Brazil. Food, like other Our presentation of this in the Brazilian context basic necessities such as shelter, employment, and showed tremendous spatial variability, allowing for education, is not distributed evenly throughout the identification of major shifts away or toward food pro- population of any given country (Streeten 1994). duction in particular municipalities and spatial clus- Moreover, rising prices for agricultural commodities ters of municipalities. Changes in the index values as a result of biofuel production could have contra- themselves do not help resolve the human and en- dictory effects on farmers in poor regions, who might vironmental mechanisms at play in those changes. By benefit from high prices for their crops but also would identifying these sites empirically, however, it is our be negatively influenced by rising food prices because hope that future studies might focus where the spe- these farmers are known to spend a sizable portion of cific mechanisms producing food security or insecu- their wages on food (Birur, Hertel, and Tyner 2007). rity could be most easily observed. Our study brings The net effect of these opposing trends is unclear and us methodologically a step closer to understanding ex- would be dependent on a variety of economic, social, actly where changes in crop shares, and hence food and environmental factors (Ugarte 2006). Technolog- security, might be occurring.  ical investment, politics at various scales, transporta- tion networks, and social norms are among the factors Note that play important roles in determining food secu- rity within national borders (Rosegrant et al. 2006). 1 These data are not entirely straightforward, though, due in In other words, food insecurity is a global problem large part to the issue of double- and triple-cropping. Be- with global causes and global effects, but it is also a cause much of Brazil is tropical, and so not subject to freezes, problem that is responsive to mechanisms operating many fields are planted year-round. This issue means that in some cases, a change in the amount of area planted as at national and smaller scales. Moreover, in a country one crop might be misleading; a certain crop like soy might like Brazil, with a large agricultural sector that pro- appear to be expanding in terms of area planted, but it is duces most of its own food, domestic changes in crop- not “replacing” any other crop at all—it might simply be land use could have much larger impacts than global being planted on a corn field during a season that the land shifts. These mechanisms are still poorly understood was previously left fallow and would not have been planted in spite of widespread concern about the effects on with any of the main food crops in any case, for example. food security of increased biofuel production and the Unfortunately, without actually visiting farms or analyzing upsurge of other industrial uses of agricultural prod- remote sensing data from various time periods throughout ucts. Systematic, empirical studies are needed to begin a given year, it is impossible to know where this is the case to identify and explain these mechanisms and explain and where it is not. Thus, for simplicity’s sake and because this is only a preliminary analysis, we have assumed that all how their influences vary from one part of a country to changes in area planted as a certain crop could have been another. planted as any other crop. Other challenges in using this data set are consistent with most large, highly detailed agri- cultural data sets but should be noted anyway; these are Conclusion primarily related to suspected inconsistency in data collec- tion methods in different regions and rounding issues when In sum, we argue for a shift to more systematic as- crops are planted in patches smaller than the unit of mea- sessments of cropping changes in the food versus fuel surement, in this case, 1 ha. literature, especially at subnational scales. Tracking shifts in food versus fuel production and associated human and environmental impacts is difficult, espe- Literature Cited cially with aggregate acreage statistics. It is not always clear what is a food crop and what is a fuel crop; it is Aglionby, J., and R. Minder. 2007. Fuel crops cultivate also not always clear that a change in relative acreages hopes and fears. (World News). The Financial Times 23 in food versus fuel crops means that one type of pro- November. http://www.ft.com/cms/s/0/6eb02a7e-9952- 11dc-bb45-0000779fd2ac.html#axzz2O6vbLzwM (last ac- duction is occurring at the expense of another (one cessed 20 March 2013). type replacing another); finally, the globalized nature Altieri, M. A., and E. Bravo. 2007. 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A transic¸ao˜ nutri- cional no Brasil: Tendenciasˆ regionais e temporais [The literature is fuel production at the expense of food nutritional transition in Brazil: Regional and temporal and food security. A careful selection of food versus trends]. Caderno de Sa´ude P´ublica 12 (Suppl. 1): S181– nonfood crop area statistics then follows, and relative S191. changes in their proportion can be examined as change Birur, D. K., T. W. Hertel, and W. E. Tyner. 2007. The in an index. biofuels boom: Implications for world food markets. Paper 258 Volume 66, Number 2, May 2014

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Sachs, I., D. Maimom, and M. T. Tolmasquim. 1987. The Willmott, C. J., and J. J. Feddema. 1992. A more rational social and ecological impact of pro-acool. Institute of Devel- climatic moisture index. The Professional Geographer 44 (1): opment Studies Bulletin 18 (1): 39–45. 84–88. Sawyer, D. 2008. Climate change, biofuels and eco-social impacts in the Brazilian Amazon and Cerrado. Philosophical Transactions of the Royal Society B 363 (1498): 1747–52. J. CHRISTOPHER BROWN is Associate Professor of Streeten, P. 1994. Human development: Means and ends. The Geography and the Environmental Studies Program at American Economic Review 84 (2): 232–37. the University of Kansas, Lawrence, KS 66045. E-mail: Tenenbaum, D. J. 2008. Food vs. fuel: Diversion of crops [email protected]. His research focuses on the human and could cause more hunger. Environmental Health Perspectives environmental dynamics of land change in the rapidly chang- 116 (6): A254–A257. ing agricultural landscapes of the Brazilian Amazon. Ugarte, D. D. 2006. Developing bioenergy: Economic and social issues. In Bioenergy and agriculture: Promises and LISA RAUSCH is a doctoral candidate in the Department challenges, ed. P. B. R. Hazell and R. K. Pachauri, 5–6. of Geography at the University of Kansas, Lawrence, KS Washington, DC: International Food Policy Research 66045. E-mail: [email protected]. Her research interests Institute. include changing patterns of environmental governance in Ugarte, D. D., and L. He. 2007. Is the expansion of biofuels the context of agricultural development and land use change at odds with the food security of developing countries? in the Brazilian Amazon. Biofuels, Bioproducts, and Biorefining 1:92–102. U.S. Department of Agriculture and Foreign Agriculture Ser- VERONICAˆ GRONAU LUZ is a nutritionist and a doc- vice. 2011. Production, supply and distribution online.Wash- torate student in the Department of Public Health at ington, DC: U.S. Department of Agriculture. State University of Campinas (UNICAMP), Brazil. E-mail: Walker, R. 2011. The impact of Brazilian biofuel production [email protected]. Her research interests include food on Amazonia.ˆ Annals of the Association of American Geogra- security and nutrition and occupational health in people from phers 101 (4): 929–38. rural areas.