Applied Geography 32 (2012) 12e20

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Applied Geography

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The scale of transition: Amazonia and the Atlantic of

Robert Walker

Department of Geography, Michigan State University, USA

abstract

Keywords: This article adapts a general equilibrium model that provides a spatial solution for , labor Forest transition allocation, and product markets in a two good economy. The adaptation, based on von Thünen, considers the multi-regional case, and solves for two regions, one industrial and the other, a newly opened agri- Amazonia cultural frontier. The conceptual framework is considered with reference to Brazil, where forest recovery Globalization Atlantic in the Atlantic Rainforest occurs simultaneously with forest losses in Amazonia. Simulation results of the theoretical model are given, demonstrating the impacts of comparative advantage in regional agriculture on the spatial system. The main theoretical interest of the article, aside from providing a formal spatial statement, is to define a distinction between aggregate forest transition (A-FT), when the area of all forests in a multi-regional system increases with the advent of trade relations, and regional forest transition (R-FT), when forest recovery is spatially constrained, and depends on forest losses elsewhere. Thus, the article addresses the role of scale in defining forest transition, and does so by representing spatial dynamics with a formal model. It also suggests that forest transition privileges one biome at the expense of others, and that a concept of landscape turnaround is more germane from a wildlands conservation perspective. The article closes with a discussion of Brazil, and how its forests in Amazonia and along the Atlantic will fare in the coming years. Ó 2010 Elsevier Ltd. All rights reserved.

Introduction The present paper belongs to the theoretical side of the FT literature. It addresses a basic issue that has arisen in a number of Global forest loss continues to concern the world community, studies regarding scale, and the spatial domain over which FT given the value of forest ecosystems, particularly tropical ones, to manifests. Walker (1993) notes that international trade relations biodiversity maintenance and organic carbon storage. Conse- and population flows, under globalization, play a considerable role quently, a large literature now addresses both the drivers and in determining whether or not a forest transition is likely to occur implications of forest destruction. That said, a number of cases of in specific places. This observation has been corroborated and forest expansion have been observed, in a process referred to as the extended in other studies showing how regions and even entire ‘forest transition,’ the spatial recovery of forest ecosystems after countries can facilitate distant land use change processes by prolonged periods of agricultural land use (Mather, 1992; Walker, allowing people to migrate or by providing the import of agricul- 1993). As with deforestation, a large literature now addresses tural commodities (Robbins & Fraser, 2003). In other word, forest transition, providing both case studies and conceptual a long-settled area can release land to successional processes if frameworks aimed at understanding the social and economic agricultural populations leave, and if locally-consumed produce is processes that generate it (e.g., Barbier, Burgess, & Grainger, 2009; sourced from somewhere else (Meyfroidt & Lambin, 2009; Pfaff & Perz, 2007; Perz & Skole, 2003; Redo, Bass, & Millington, 2009; Walker, 2010). Rudel, Bates, & Machinguiashi, 2002; Walker, 2008). Occurrence The prime goal of the present article is to develop a model that of forest transition (FT) in many parts of the world has raised hopes situates FT within a multi-regional context, thereby enabling that macro-scale forces of economic development will bring about a direct treatment of the scale issue. As such, the model provides a spontaneous solution to the deforestation problem now affecting a theoretical counterpart for studies identifying FT in the presence the tropics (Chomitz, 2006). of inter-regional (and international) trade relations and labor movements. Although the empirical possibility of FT at global scale is not addressed, the article alludes to precisely this outcome. It does so by placing land use change processes in regionally distinct E-mail address: [email protected]. places which, when aggregated, may reveal FT in the aggregate, or

0143-6228/$ e see front matter Ó 2010 Elsevier Ltd. All rights reserved. doi:10.1016/j.apgeog.2010.10.010 R. Walker / Applied Geography 32 (2012) 12e20 13 among the regional building blocks of the large-scale system. The World System paper’s illustrative application addresses FT within individual regions of a country, and then in the country as a whole on the basis of aggregating the regional land use systems. In principle, aggre- Global North Global South gation could continue to explicitly consider global FT. A secondary goal of the paper is to demonstrate the explanatory power of the spatial model of von Thünen, which has received wide attention by land change science, but primarily in statistical studies of deforestation. Theoretical development and applications to land aggregation abandonment processes are mostly lacking. The Borlaug hypothesis posits an implicit Thunian construct in describing land sparing as a retraction of the agricultural margin (Borlaug, 2007; Rudel et al., Nation 1 Nation N 2009). Similarly, scarcity of timber products raise prices of forest- based products, allowing a Thunian-style forest recovery against retreating agriculture (Barbier et al., 2009). The present paper considers retraction of the agricultural frontier in an explicitly Thunian framework, and does so in a spatially complex manner with multiple regions, and land use aggregation. region 1 region 2 … region n region 1 region 2 … region n The article is organized as follows. The next section opens with a brief discussion of forest transition and terminology, then Fig. 1. Scales from region to the World System. considers the issue of scale in undertaking studies of FT. The paper moves on then to address the case of Brazil, which appears to the predilections of the researcher, a fact that complicates efforts at manifest a complex situation including a regional FT within generalization across different studies. As has been pointed out, a context of national forest loss. A discussion of von Thünen’s social and behavioral processes determining the age of secondary theory, and its suitability to describing land change processes in regrowth in a woodlot are different, in scale and magnitude, from Brazil, follows. This motivates the presentation of a model based on those associated with the recovery of New England’s forests in the the Thunian formulation provided by Nerlove and Sadka (1991), 19th century (Pfaff & Walker, 2010; Walker, 2008). henceforth referred to as NS. The paper implements the model, and That scale of process conditions causal explanation has obvious considers implications of model output for environmental policy in implications for theory. Forest recovery over restricted spatial Brazil and the prospects for forest transition. A brief conclusion realms may be explained by completely different factors that those ends the paper. driving a broad-scale process. Further, the more highly constrained the space, the greater the impact of external factors. An extreme Forest transition and scale version of this latter observation is that deforestation in one place may actually enable FT somewhere else through external relations, Before proceeding to the main points of the section, a discussion such as trade (Pfaff & Walker, 2010; Robbins & Fraser, 2003). This is of terminology is necessary. Specifically, FT refers to spatial of practical significance, given that the policy community views FT recovery of forest lands, due to a variety of factors promoting as a weapon in the fight against tropical deforestation (Chomitz, agricultural abandonment. From the perspective of land “sparing,” 2006). If FT takes place as an endogenous process with no the releasing of land from agriculture with reallocation to natural external impact outside its area of occurrence, then it unambigu- states capable of providing environmental services, FT, restricted by ously promotes expansion of forest-based services and amenities. its very name to forest ecosystems, is conceptually limited. Agri- Alternatively, if FT depends on deforestation somewhere else, we culture encroaches on savannas, prairies, and woodlands, systems are in the conundrum of a zero sum, and policy benefits in one that may have high states of endemism and biodiversity. Recovery place may be offset by policy downsides not immediately apparent. of such ecosystems contributes to the stock of wildlands, and is in Spatial economics suggests that new trade relations enabled by the interest of biodiversity conservation worldwide. Walker (1993) transportation investments enable regional specialization, and the uses the term landscape turnaround in order to represent broad- simultaneous emergence of industrial regions and “breadbaskets” scale land transformations not specific to ecosystem type. Although (Fujita, Krugman, & Venables, 1999). One land cover implication is the present paper maintains FT as a label for the processes under that FT may be observed locally, as industrializing regions begin examination, it recognizes these terminological limitations. This feeding their urbanizing workers with imported farm goods. These becomes particularly important in the Brazilian case, with its highly goods, in turn, are likely to require forest clearing or wildlands productive and biodiverse savannas, or cerrados, which are van- encroachment, particularly if the traded staples come from a newly ishing at an alarming rate, a loss that has yet to gain much attention opened frontier. Whether FT occurs in the scenario as described given public concerns about the Amazonian and Atlantic depends on the scale at which forest dynamics are examined, and (Brown, Koeppe, Coles, & Price, 2005; Jepson, 2005). therefore lies in the eyes of the beholder. If the focus remains on the General characteristics of FT have been well described and need newly industrialized region, with its expanding cities and industrial little discussion. That said, the issue of scale continues to provide an workforce, then FT may be observed, or more appropriately, occasional source of confusion in attempts to discover FTs causal regional FT (R-FT). Alternatively, analysis encompassing both long- drivers. Do processes of FT obtain any time forest succession occurs, settled and frontier regions could fail to identify aggregate-FT or do they reflect long-run forest recovery occurring over regular (A-FT), given rapid change on the frontier, with deforestation domains (Perz, 2007; Walker, 2008)? The early work tended to swamping any forest gains due to industrialization. Complicating address large regions, and posited FT as a process affecting nation this picture from a land sparing perspective is the possibility that states over the course of centuries (Mather, 1992; Walker, 1993). new trade partners possess extensive grasslands, in which case FT More recently, researchers have considered FT at much finer scale, might occur in the aggregate, even with a net loss of wildlands. both spatially and temporally (e.g., Rudel et al., 2002). Identifying These remarks motivate the spatial framework of the analysis to the occurrence of FT, and its scale of operation, are determined by be presented, and the link between forest transition and scale of 14 R. Walker / Applied Geography 32 (2012) 12e20

Fig. 2. Brazil’s Biomes with Amazonian and Atlantic Forests. observation. Fig. 1 shows an aggregation , from regions on the The present paper seeks to engage the FT literature by reinvigo- lowest tier, to the world system as an integrating whole on top. rating the early emphasis on “large” regions, in order to link FT to Regions are interpreted here as mutually exclusive landscapes that broader structural changes in an economy. As such, FT is assessed in together constitute the land surface of a country. Countries, in turn, a manner consistent with Fig. 1, in which the nation-state Brazil is aggregate to large parts of the earth’s surface, as for example the composed of large regions, two of which drive the theoretical global north and south. This partition is meaningful in the FT development and application presented here, Amazonia and the context, given the suggestion that forest processes differ markedly Atlantic forest (Fig. 2). As the cerrado ecosystem is not forested, the between temperate and tropical countries (Walker, 1993). analysis neglects it while recognizing its importance as a wildland, and the same point holds for Brazil’s other biomes. The case of Brazil The FT research in Brazil, and South America more generally, has tended to focus on relatively small regions. Baptista and Rudel Brazil, an economic powerhouse of the global south, has long (Baptista, 2008; Baptista & Rudel, 2006) address FT in Santa been regarded as a deforesting country, given vertiginous rates of Catarina, a Brazilian State of w95,000 km2, while Rudel et al. deforestation in its Amazonian biome over the past few decades. (2002) assess FT dynamics in an area in the Ecuadorian Amazon Also home to an Atlantic forest of significant extent, Brazil provides w75 km2. This later study covers a ten year period, short for an important case for the explication of forest dynamics, particu- picking up signals of long-term trends in land change drivers, larly FT. A very large cerrado buffer separates these two forest such as associated with FT as originally interpreted. Perz and realms, one that is moist and biodiverse, and has suffered Skole (2003) scale-up in analyzing the potential for FT over rela- tremendous losses (Brown et al., 2005; Jepson, 2005). Despite this tively large sub-regions within the Amazon basin, but they do not ecologic endowment across biomes, almost all research on Brazil- provide an analysis of underlying drivers other than to comment ian land change addresses Amazonian deforestation, and a large on stage of development. Given extensive secondary regrowth in literature has documented its many causes, correlates, and envi- the so-called Bragantine, a long-settled area in the northeastern ronmental impacts (Keller et al., 2004). Amazon, Perz and Skole (2003) conclude FT may occur here More recently, researchers have begun to consider secondary “early” relative to the rest of the basin. Although not explicitly regrowth and FT in parts of Amazonia, as well as in the Atlantic directed at FT, a number of authors have observed abundant forest of Brazil. As will be discussed, these studies call attention to secondary regrowth at farm level in the Amazon, an ecological several of the issues raised thus far, particularly the role of scale. phenomenon that is necessary, if not sufficient, to the occurrence R. Walker / Applied Geography 32 (2012) 12e20 15

Table 1 industrial states in their analysis. Table 2 reproduces and extends the 2 Atlantic rainforest (km ) by state. Pfaff and Walker data for Santa Catarina, recently studied by Baptista Forest Area (2008) and Baptista and Rudel (2006). The table presents summary

State Original 1990 2005 Forest Gain calculations to show imbalances for land-based sectors, a regional Area (km2) (km2) (km2) between specialization of agricultural regions and frontiers. For example, 1990-2005(%) sector-specific exports from Amazonia far exceed those from Santa AL 14,607 718.11 1,486.33 106.98 Catarina to Amazonia. For agricultural products, every unit of value BA 203,379 12,631.75 15,845.72 25.44 traveling from Santa Catarina north is compensated by 6.8 units CE 4,863 865.98 606.16 -30.00 going in the opposite direction. The imbalance is not so great for ES 46,166 4,097.41 4,766.87 16.34 GO 12,116 71.19 443.55 523.05 processed food and beverages, with a disproportion of 1.7; however, MS 63,404 437.52 3,452.70 689.15 for furniture and products, the flow from Amazonia is nearly MG 289,396 12,140.59 27,838.85 129.30 14 times greater than what Santa Catarina sends back in return. The PB 6,791 462.80 687.64 48.58 trade flows reflected by the table are consistent with land change PE 17,934 906.67 2,221.62 145.03 dynamics within these two regions, with Amazonia losing forest, PI 22,918 ––– PR 195,174 18,151.57 19,343.91 6.57 and the Atlantic Forest, gaining ground. RJ 43,835 10,692.30 8,155.38 -23.73 RN 3,321 478.33 329.33 -31.15 Modelling forest transition: considerations RS 133,527 5,352.55 9,842.80 83.89 SC 95,655 17,291.60 21,898.83 26.64 SE 7,932 885.41 730.50 -17.50 Brazil possesses multiple landscape processes within its SP 205,292 18,589.59 24,870.15 33.79 boundaries. The paper now turns to a theoretical formulation that Total 1,366,310 accommodates this empirical setting, and also allows for a simul- Total w/o PI 1,343,392 103,773.37 142,520.34 37.34 taneous representation of regional- and aggregate-FT (R-FT and A- Total w/o Northeast 86,824.32 120,613.04 38.92 FT). Thus, thinking of Brazil once again, the model is meant to reflect the complex case in which R-FTs are underway in a context of aggregate deforestation. Before proceeding, it is necessary to of FT (Moran, Brondizio, Mausel, & Wu, 1994; Perz & Walker consider the classical version of the von Thünen model, sometimes 2002). characterized as dictating a highly localized pattern of concentric As indicated, this paper pursues an explicitly spatial approach to land use rings, emanating from a unique and isolated urban market. FT regarding scale. In this regard, it isolates Brazil’s Amazonian Obviously, the Amazonian and Atlantic forest biomes are much Biome and the Atlantic forest as its regions of interest. Aggregate more expansive than the “isolated state” of von Thünen’s original land cover dynamics in Amazonia are well known and need no formulation, and their land uses do not evidence precise patterns elaboration, other than to point out that consistently high rates of based on concentric circles. Nevertheless, the bid rent concept that deforestation have come down to less than 40 percent their historic underlies von Thünen’s theory and its link to transportation costs levels, probably due to new vigor in Brazil’s enforcement actions have accommodated a wide range of application at many different and to global recession (Nepstad et al., 2009). The Atlantic forest, scales. Moreover, theoretical statements explaining deforestation less studied than Amazonia, presents a cloudier picture, although in terms of the impact of transportation costs on prices for agri- research has demonstrated recovery in specific places (Baptista, cultural inputs and outputs refer explicitly to von Thünen, and do 2008; Baptista & Rudel, 2006). At biome scale, the empirical ques- not prescribe the scale of their formulations (Nelson, Harris, & tion remains, even as aggregate statistics suggest a widespread FT Stone, 2001; Walker, 2004). Von Thünen is often invoked to along the entire Brazilian coast. Table 1 presents data gleaned from represent very broad patterns of land use, as well as frontier recent reports showing the extent of the Atlantic forest by state dynamics (e.g., Cronon, 1991; Katzman, 1977; Walker et al., 2009). (Fundação SOS Mata Atlantica and INPE, various years; 1990 data for Besides the scale issue, Thunian applications invite commentary Northeastern States (AL, BA, CE, PB, PE, RN, SG) from Conservation on the geometry of the model ’s predictions, as well as its spatial International, Fundação Biodiversitas e Sociedade Nordestina de assumptions. Considering Amazonian deforestation again, the Ecologia). Although the 2005 forest (w143,000 km2) is only a small Thunian impulse to clear land given bid rent opportunities is not fraction (11 percent) of its pre-colonial size (1,343,392 km2), the transmitted in a radial line from a market center because (1) data indicate a recovery of w40,000 km2, or nearly 40 percent since transportation costs do not vary this way given the road system, 1990. This is a strong recovery in such a short time span, and and because (2) the “market” is diffuse, spread out over two suggests that Brazil continued on its path of industrial dimensions. Consequently, distance from roads themselves is in the wake of monetary reform and recovery from the long- a more robust indicator of the Thunian phenomenon, with defor- standing recession that plagued its economy for nearly a decade estation occurring in more readily accessible areas than remote after democratization in 1985. ones. Presumably, land abandonment associated with FT would A key point of the paper, and the model to be developed, is that behave similarly, with less accessible locations given over to forest spatial relations between regions account, at least in part, for the succession sooner than more accessible ones. As a consequence, the land cover dynamics within them. Pfaff and Walker (2010) have pattern of land use, at least its aggregated form into agriculture and suggested region-scale linkages within Brazil that invite an analysis forest, reflects the road network, and is not organized into the of interdependencies of land cover changes between the Atlantic abstract concentric geometry so often interpreted as the von Thü- forest and Amazonia. Although their analysis is not conclusive nen model. For his part, Von Thünen was well aware that trans- empirically, they argue that FT in the Atlantic forest biome, which portation systems introduce distortions, producing actually covers a large part of Brazil’s industrial heartland in São Paulo state, observed patterns (von Thünen, 1966). has been enabled, in part, by expanding agricultural production in the Amazonian biome. They present data showing a significant trade Model application imbalance between the Brazilian North and South, with relatively high volumes of resource-based products flowing from Amazonia to The model used in this paper, and fully presented in the consumers in São Paulo and Santa Catarina, the two southern and appendix, generalizes a formulation developed by Nerlove and 16 R. Walker / Applied Geography 32 (2012) 12e20

Table 2 inter-regional trade imbalance, 1999 Amazonia and Santa Catarina (SC).

Amazônia is Amazonas, Mato Grosso, Pará, and Rondônia, the largest trade partners with the rest of Brazil.

Sadka (1991), henceforth referred to as NS. The NS statement the opening of the Belém-Brasília Highway in 1960 (Walker et al., presents spatial equilibrium in population and extent of agricul- 2009). tural production for the case of a single city and region. This paper’s Illustrative simulation results are given in Fig. 3. As discussed in objective is to extend NS to multiple regions linked to one another the preceding section, a Thunian formulation does not require by trade. The multi-region system of interest has an industrial base perfectly symmetric geometry. As the goal of the paper is the in one of the regions, where a manufactured good is produced in implementation of an initial theoretical model, and the presenta- a city, given spatially as a single point, and agriculture is practiced tion of illustrative simulation results, the development in the in a ring out to a fixed distance from the center. For the agricultural appendix opts for an analytical development that does not depend regions, production organizes spatially the same way, but around entirely on a numerical solution. Thus, the theoretical treatment a central transshipment point. The multi-region model implements yields a radius in keeping with the tradition of spatial economics; the NS notation, as well as assumptions (Nerlove & Sadka 1991,101) this is immediately interpretable as area of cleared, or deforested, regarding the homogeneity of land quality and production tech- land, with a large radius indicating a reduced extent of forest, or nologies. As in NS, total workforce (population), L,isfixed, and the wildlands as the case may be. The figure shows two curves; the model allocates labor across sectors. The meaningful departure of low-lying one represents agricultural land for Region I, while the the paper from NS involves allocation of labor and farm production one above it gives agricultural area summed for both regions, in a multi-regional space. the Atlantic Forest and Amazonia. The “x” axis measures produc- The NS model is used to investigate extents of agricultural tivity of agriculture in Region A, or Amazonia, relative to Region I. hinterland and labor allocation, given ensembles of parameter Graph values have been normalized so that 1 is interpretable as values, with a focus on transportation costs (Nerlove & Sadka, 1,000,000 km2, taken as the maximum level of agriculture, or 1991, 117). The present model, in contrast, considers comparative deforestation, in the Atlantic Forest. As the relative productivity of advantage across regions, and develops an application that agriculture in the frontier increases from left to right, the amount of addresses agricultural extents for two regions (cf. Amazonia and agricultural land in Region I decreases. Since 1,000,000 km2 Atlantic Forest biomes). The goal is not to replicate FTs empirically represents the land cleared in the absence of trade, the lower curve for specific places, or to undertake sensitivity analyses given shows R-FT the moment the Amazonian frontier opens, indicated uncertainty about parameter values in general. Thus, the model by reduced agricultural area. R-FT increases in magnitude as uses the functional forms and settings found in NS, adding only a function of the frontier’s agricultural potential. one, the characteristic that establishes comparative advantage in As for FT in the aggregate, or A-FT, this is assessed with the up- agriculture, namely quality of resource base, which may or may lying curve, giving the sum of the agricultural areas in both regions. not be linked to regionally-specific technological adaptation. As This always lies above the 1 value, which indicates that A-FT never per the theoretical development, Region I is industrialized, and occurs, although the strength of the deforestation process, or the Region A, an agricultural hinterland newly accessible due to amount of land needed in Region A, does vary. The amount of land dramatic reductions in costs of inter-regional transport. Although provided by Region A, which is the difference between to the two such costs always persist empirically, the present model takes curves, rises continuously with relative productivity, although the them as effectively zero to simplify the exposition. For the case of greatest increase takes place where productivities are evenly Brazil, and in particular the two regions of interest, transportation matched, near the value 1. Ultimately, all agriculture shifts to the costs between Amazonia and the rest of the country, notably São frontier, and farmland in Region I is entirely abandoned. At a rela- Paulo which is an Atlantic Forest state, have dropped sharply since tive productivity value of just above 1.5, R-FT in Region I, the R. Walker / Applied Geography 32 (2012) 12e20 17

1.4 Agricultural Area: Amazon (Region A) + Atlantic (Region I) Forest Regions 1.2

1

0.8 Agriculture 0.6 106 Km2 0.4 Agricultural Area: 0.2 Atlantic (Region I) Forest Region 0 0 0.5 1 1.5 2

Relative Productivity

Fig. 3. Simulation output.

Atlantic Forest, is effectively complete, and 1,000,000 km2 of forest Thus, the two region model of Thunian land use is able to have been cleared in Region A, Amazonia. represent complex within-country landscape dynamics, and to discriminate between regional- and aggregate-FT, a useful distinction on both theoretical and practical grounds. Meaningful Discussion extensions would involve detailed parameterization to the actual case in question, a spatial reformulation sensitive to the geometry Amazonia enjoys high relative productivity, following techno- of road networks, and the inclusion of time in order to reflect logical adaptations strategically targeting the region. Genetic dynamic adjustments. Also important would be to “open” the improvements in source materials enable Amazonian soy farmers model to international trade, given it only accounts for domestic to produce 3 ton ha1, which is 30 percent above the national exchanges within the confines of a national economy. To fully average (Almeida et al., 1999; Kiihl, Almeida, & Dall’agnol, 1985; address the impact of globalization on Brazilian forest dynamics, Souza et al., 2000). Ranching also possesses advantages, thanks the present structure would have to be nested within a broader partly to the adaptation of forages from Africa, which flourish in the market framework. Key to this would be incorporating trans- moisture regime and sunlight. Productivity for calving and portation costs, which are presently missing. Although the present fattening operations is 10 percent higher than outside the region, structure is adequate for addressing Brazilian biomic landscape and for integrated operations, 11 percent (Arima, Barreto, & Brito, dynamics through the mid 1990s, exports literally exploded later 2005). Amazonia’s insolation, rainfall, and frost free climate have that decade with currency devaluation in the wake of monetary made agriculture productive here, which is good for the Atlantic reform (Walker et al., 2009). Demand beyond the borders of Brazil but not the Amazonian forests, by the implications of the model. provides one possible explanation for why the model under- Unfortunately, the “good” enjoyed by the Atlantic forests never predicts total Brazilian forest loss. comes with A-FT for Brazil as a while, a rather gloomy forecast. Globalization of Brazilian agriculture has raised alarms about That said, any interpretation of model results in empirical impacts on the Amazonian biome, in particular, inspiring efforts to context must remain highly speculative given the abstract nature of project implications for forest land cover. Evidently, another the theoretical statement, which is really more a point of departure w400,000 km2 of Amazonian land could convert to farmland and for future work than a definitive statement about actual landscape pasture by 2020, which would involve yearly rates of forest loss in dynamics in Brazil. To date, over 700,000 km2 of the Amazon forest considerable excess of historic levels (Lapola et al., 2010; Walker, has been cleared. Combined with deforestation along the Atlantic, DeFries et al., 2009). Obviously, Amazonian deforestation of this Brazil has lost about 2,000,000 km2 of forest, which tops the magnitude weakens prospects for A-FT in Brazil, even with strong numbers discussed for Fig. 3. It must also be pointed out that much forest recovery elsewhere in the country. Table 1 indicates the cerrado has also been converted, an ecological dynamic completely Atlantic biome could contribute just over w1,000,000 km2 to the neglected by the framework presented. That said, the model extent of national , but this would require a 100 percent structure sheds some light on the land change dynamics arising R-FT, which is extremely unlikely. On the other hand, a sharp from landscape connectivity, particularly the zero sum nature of FT reduction in Amazonian deforestation rates, contrary to projections, and its relationship to comparative advantages across regions. It could trigger A-FT by bringing Amazonian deforestation rates below also provides a suggestive explanation for complex migration flows rates of forest recovery in the Atlantic forest biome. Of course, A-FT in countries undergoing urbanization with industrial growth. To would only ensue if the Atlantic forest continues its recovery, by no the far right in Fig. 3, with complete R-FT in Region I, workers have means a foregone conclusion, since globalization involves emerging concentrated in the urban core, presumably via an intra-regional, demands for the biofuel, ethanol. For Brazil, this means expanding rural-to-urban migration flow. At the same time, inter-regional sugarcane production, which is now concentrated in the south of the redistribution has occurred to the frontiers of Region A, with country, and in São Paulo State in particular (UNICA, 2010). a counter flow of migration to rural areas, originating in the Significant reduction in Amazonian deforestation is not an idle industrial heartland. fantasy for a variety of reasons, not the least of which is Brazil’s 18 R. Walker / Applied Geography 32 (2012) 12e20 commitment in 2008 to do so under the U.N. climate treaty protocol Landscapes and Land-Climate Interactions” and from NSF project (Nepstad et al., 2009). This would be accomplished, in part, by (BCS-0620384) “Collaborative Research: Globalization, Defores- defending its protected areas, which are extensive and include tation, and the Livestock Sector in the Brazilian Amazon.” The a large portion of Amazonia’s remaining forest cover (Walker, views expressed are those of the author, and do not necessarily Moore, et al., 2009). Such an eventuality effectively introduces reflect those of the supporting agencies. I would like to thank a spatial constraint to the model as presented, a limit to the area Ritaumaria Pereira for assistance in accessing data for the Atlantic convertible to agriculture. If supply expands under such conditions Forests, and Eugenio Arima, Alex Pfaff, and Eustaquio Reis for to meet projected demands, it can only do so by intensifying stimulating discussions about the Brazilian “space economy.” production. This outcome is consistent with the observation that Comments by anonymous reviewers significantly improved the land sparing has been observed only where countries take flow of the manuscript and the relevance of its arguments. I am a proactive stance with conservation of natural areas (Rudel et al., indebted to Rinku Roy Chowdhury for the invitation to present on 2009). In such a situation, intensification is not an autonomous forest transition at the 2009 IHDP Open Meetings in Bonn, factor that produces the land sparing outcome, but the conse- Germany. quence of government interventions to restrict the use of land. This fundamentally alters the application of a Thunian construct to Appendix explain evolving landscape structure, as the R’s are no longer free to adjust to changing trade relations, or differentials in comparative Multi-regional formulation advantages across regions. In other words, bid-rents no longer determine spatial structure, but the other way around. At this point, Production of the manufactured good is given as Q0 ¼ f0L0, land cover dynamics, at least the component involving the incor- where L0 is urban labor dedicated to . Agricultural poration of wildlands into a system of human land use, give way to i i i production, normalized to unit land, is q1 (r) ¼ f1 [l1(r)], for regions the dynamics of rent structure, the emergence of a property i i ¼ 0, .., n, where f1 is the agricultural production function, and distribution, and the spatial organization of crop areas. Forest i l1(r), the labor allocation per unit land. Without loss of generality, transition becomes a story of development history, at least within let the industrial region be superscripted by 0. Total agricultural the multi-regional space in question. output for the multi-regional system is:

ZRi Conclusions Xn i ; Q1 ¼ 2p q1ðrÞdr The paper has used a Thunian model to describe in broad i 0 ¼ 0 strokes the landscape dynamics of a national land use system. The formulation is capable of depicting countervailing processes of with the extensive margin of agriculture given by Ri. Assume land cover change at different scales, and provides a way to production cannot be undertaken beyond some minimal labor explain FT in the face of aggregate forest loss. As such, the model application per unit area, in which case: reflects, if imperfectly, the empirical situation of Brazil, where the i i : Atlantic forest is recovering, but less quickly than its Amazonian l1 R ¼ m forest is giving ground. In developing its application, the paper emphasizes scale as a critical factor in identifying FT, and in Total labor in agriculture is: isolating its drivers. FT may be enabled by the export of devel- ZRi opment externalities on distal landscapes, which is to say it should Xn i ; not be judged environmentally restorative in the absence of L1 ¼ 2p l1ðrÞdr i 0 complete spatial analysis. ¼ 0 Although the model is not parameterized for the Brazilian case, P n i and labor force across the regions is: L ¼ L0 þ L , where deforestation there provides its motivation. The emerging global R i i ¼ 1 1 Li 2p R li r dr. Let w(r) represent wage rate at distance r from scope of Brazilian agriculture points to the next step needed in 1 ¼ 0 1ð Þ extending the model in a useful fashion. Specifically, the multi- a regional center, and p0(r) and p1(r), prices for the manufactured regional structure reflecting national land use must be nested and farm good, respectively, also at distance r. Since wages equal within a global market system. Such a formulation would likely the value of marginal product, the city center for the industrial show how Brazil now runs the risk of becoming the world’s “Region region yields w(0) ¼ p0(0)f0 ¼ f0, with the manufactured good taken as numeraire. Further, w r p r f i0 li r , where the wage rate is A,” in the symbolic language of the model. Without government ð Þ¼ 1ð Þ 1 ½ 1ð Þ 0 intervention to stop the advancing agricultural frontier, the model always the same at equidistance from the regional center (where f would probably predict a continuing green hemorrhage of Ama- is the derivative in l). Land rents at distance r are: zonia, and a stymied R-FT in the Atlantic forest. n h i h io i i i i i0 i ; In conclusion, the paper calls on all concerned parties to help y1ðrÞ¼p1ðrÞ f1 l1ðrÞ l1f1 l1ðrÞ

Brazil fulfill the promise of its protected areas programs. If not, P R i and aggregate rent is Y 2p n R yi r dr. Prices for the Thunian dynamics under globalization will permanently transform ¼ i ¼ 0 0 1ð Þ manufactured and agricultural goods vary over space according to much of the Amazonian and Atlantic forests into fields and the ice-berg technology assumption, which accounts for trans- pastures. In fact, the time has come to fix the spatial limits of portation costs (Nerlove & Sadka, 1991). This leads to lower agri- Brazilian agriculture in all its biomes, so as to ensure some measure cultural prices with distance from the center, and higher of conservation of their magnificent native landscapes. manufactured goods prices. Consequently,

Acknowledgements a1r a0r p1ðrÞ¼p1ð0Þe and p0ðrÞ¼p0ðrÞe ;

I would like to acknowledge support from NASA project where a0, a1 > 0. Locational equilibrium requires the same (NNG06GD96A) “Spatially Explicit Land Cover Econometrics and utility, u, be achieved at all locations. Thus, the farm surplus at Integration with Climate Prediction: Scenarios of Future every distance r in the multi-regional systems is given as: R. Walker / Applied Geography 32 (2012) 12e20 19

n h i o Xn ; ; aY ; ; i i ; ; ; D0ðp0ð0Þ p1ð0Þ YÞ¼ ¼ aY and D1ðp0ð0Þ p1ð0Þ YÞ 2pr f1 l1ðrÞ H1ðp0ðrÞ p1ðrÞ uÞl1ðrÞ dr p0ð0Þ i ¼ 1 ¼ð1 aÞY=p1ð0Þ where H1 is Hicksian demand for the agricultural product. with p (0) as numeraire. Since a and (1 a) are budget shares of Hicksian demand prescribes quantities consumed holding utility 0 the manufactured and farm good, respectively, the wage rate is (NS, constant, in order to neutralize the income effects of changing p. 109): prices. Constant utility for the workforce is necessary in order to achieve their locational equilibrium. That is, they must all be wðrÞ¼f expfða a a ð1 aÞÞrg: indifferent about possible locations for work and residence, 0 0 1 whether in the city or hinterland. Because transportation costs This is also equal to the marginal value of farm production: impact prices for both goods, the worker substitutes agricultural b1 b1 produce for manufactured products with distance from the city 1 a1r I A a1r A ; wðrÞ¼g bp1ð0Þe l1ðrÞ ¼ g bp1ð0Þe l1ðrÞ center. For equilibrium to prevail, he or she must face identical i utility across all possible locations. The market clearing equation for in which case the l1 (r) functions may be solved: the farm good is:

1 b ZRi f0expfða0a þ a1aÞrg 1 X n h i o lI r ; lA r 1ð Þ¼ I 1ð Þ n i i ; ; i a1r g bp1ð0Þ 2p i ¼ 1 r f1 l1ðrÞ H1ðp0ðrÞ p1ðrÞ uÞl1ðrÞ e dr 1 b 0 f0expfða0a þ a1aÞrg 1 ¼ A ¼ L0H1ðp0ðrÞ; p1ðrÞ; uÞþD1ðp0ð0Þ; p1ð0Þ; YÞ; g bp1ð0Þ

where D1 is Marshallian demand, with rent-based income, Given the minimal labor application condition, these can be Y. The landowner, who receives all rents, does not require the rewritten as: Hicksian assumption, as he or she is not an agricultural worker, and 2 3 1 2 3 1 therefore remains spatially unconstrained. The market clearing b1 b1 f expfða a þ a aÞRIg f expfða a þ a aÞRAg equation for the manufactured good is: m 4 0 0 1 5 4 0 0 1 5 ¼ I ¼ A 8 9 g bp1ð0Þ g bp1ð0Þ > ZRi > < Xn = 2p H ðp ðrÞ; p ðrÞ; uÞli ðrÞgea0rrdr :> 0 0 1 1 ;> Solution i 1 ¼ 0 The solution in NS involves the statement of market clearing þ L0H0ðp0ðrÞ; p1ðrÞ; uÞþD1ðp0ð0Þ; p1ð0Þ; YÞ equations for the manufactured good and labor. These contain two : ¼ Q0 endogenous variables, distance to extensive margin, R, and work- force allocated to manufacturing. With values for these variables, Finally, locational equilibrium is given by E(p0(r), p1(r),u)¼ w(r), where E is expenditure. Thus, worker expenditures at every loca- the rest of the system can be solved, although NS maintains focus tion must equal the wage rate, and must everywhere yield the same on labor allocation and agricultural extent (Nerlove & Sadka, 1991). utility, u. The present paper is interested primarily in agricultural extent, given it defines distance to wildlands like primary forest. This, by Specification for two regions implication, yields areas under cultivation and left in natural cover. Thus, a solution similar to NS is sought, with values for RI and RA. The model is now solved for the case of two regions. Specifically, This is accomplished by stating three equations in three unknowns, I A I investigate impacts on the agricultural hinterland in an industri- including L0 in addition to R and R . Given algebraic complexity, alized region, I, given the availability of a newly opened region, A,to computational methods are implemented to solve the equations. migration and agricultural activity. Thus, A produces crops, but no The equations utilized are the market clearing equations and the manufactured goods, which I supplies for both regions. The ques- extensive margins conditions. The two region market equations for I the manufactured good and for labor are: tion is, what happens to R as farming expands in Region A? 2 ZRI As in NS, assume a Cobb-Douglas production technology in farming, with technological coefficient b: 16 a 2apmb 4exp d2R expðd1rÞrdr h i b 0 3 f i li ðrÞ ¼ gi li ; ZRA 1 1 1 7 b 5 I ; þexp d2R expðd1rÞrdr ¼ð1 aÞL0 and with productivity potentially higher in the agricultural 0 region than the manufacturing one, gA > gI. For Brazil, this might cause question prima facie, given the widespread belief that Ama- and zonia possesses low agricultural productivity. In fact, productivity 2 here is higher here for the rest of the country for important crops, ZRI 6 as well as for cattle pasture, as discussed in the text. With Cobb- I 4 I L ¼ L0 þ 2pm exp d2R expðd2rÞrdr Douglas preferences, the Hicksian demand functions are: 0 3 ; ; a1 1a ; ; ZRA H0ðp0 p1 uÞ¼ap0 p1 u and H1ðp0 p1 uÞ A 7 a a þ exp d2R expðd2rÞrdr5 ¼ð1 aÞp0p1 u 0 As in NS, the landowners’ demand functions are given by: 20 R. Walker / Applied Geography 32 (2012) 12e20

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