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Geophysical Monograph 186

Amazonia and Global ChangeMichael Keller

Mercedes BustamanteJohn Gash

Pedro Silva DiasEditors

American Geophysical UnionWashington, DC

Published under the aegis of the AGU Books Board

Kenneth R. Minschwaner, Chair; Gray E. Bebout, Joseph E. Borovsky, Kenneth H. Brink, Ralf R. Haese, Robert B. Jackson, W. Berry Lyons, Thomas Nicholson, Andrew Nyblade, Nancy N. Rabalais, A. Surjalal Sharma, Darrell Strobel, Chunzai Wang, and Paul David Williams, members.

Library of Congress Cataloging-in-Publication Data

Amazonia and global change / Michael Keller ... [et al.]. p. cm. — (Geophysical monograph ; 186) Includes bibliographical references and index. ISBN 978-0-87590-476-4 (alk. paper) 1. Rain forest ecology—Amazon River Region. 2. Biosphere—Research—Amazon River Region. 3. Climatic changes—Amazon River Region. 4. Amazon RiverRegion—Climate. I. Keller, Michael, 1960-

QH112.A433 2009 577.34¢1409811—dc22

2009040686

ISBN: 978-0-87590-476-4 ISSN: 0065-8448

Cover Photo: The Igarapé Asu in the Instituto Nacional de Pesquisas da Amazônia (INPA) research catchment north of Manaus. Photo courtesy of John Gash.

Copyright 2009 by the American Geophysical Union2000 Florida Avenue, N.W.Washington, DC 20009

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Printed in the United States of America.

CONTENTS

PrefaceJohn Gash, Michael Keller, Mercedes Bustamante, and Pedro Silva Dias ...............................................................ix

Section I: People and Land Change

People and Environment in Amazonia: The LBA Experience and Other PerspectivesM. Batistella, D. S. Alves, E. F. Moran, C. Souza Jr., R. Walker, and S. Walsh .........................................................1

The Changing Rates and Patterns of Deforestation and Land Use in Brazilian AmazoniaDiogenes S. Alves, Douglas C. Morton, Mateus Batistella, Dar A. Roberts, and Carlos Souza Jr. ...........................11

Selective Logging and Its Relation to DeforestationGregory P. Asner, Michael Keller, Marco Lentini, Frank Merry, and Carlos Souza Jr. ............................................25

The Spatial Distribution and Interannual Variability of Fire in AmazoniaWilfrid Schroeder, Ane Alencar, Eugenio Arima, and Alberto Setzer .....................................................................43

The Expansion of Intensive Agriculture and Ranching in Brazilian Amazonia Robert Walker, Ruth DeFries, Maria del Carmen Vera-Diaz, Yosio Shimabukuro, and Adriano Venturieri ............61

Scenarios of Future Amazonian Landscapes: Econometric and Dynamic Simulation ModelsStephen Perz, Joseph P. Messina, Eustaquio Reis, Robert Walker, and Stephen J. Walsh .......................................83

Road Impacts in Brazilian AmazoniaAlexander Pfaff, Alisson Barbieri, Thomas Ludewigs, Frank Merry, Stephen Perz, and Eustaquio Reis .................101

Small Farmers and Deforestation in AmazoniaEduardo S. Brondízio, Anthony Cak, Marcellus M. Caldas, Carlos Mena, Richard Bilsborrow, Celia T. Futemma, Thomas Ludewigs, Emilio F. Moran, and Mateus Batistella ....................................................117

Section II: Atmosphere and Climate

Understanding the Climate of Amazonia: Progress From LBACarlos A. Nobre, José A. Marengo, and Paulo Artaxo .........................................................................................145

Characteristics of Amazonian Climate: Main FeaturesCarlos A. Nobre, Guillermo O. Obregón, José A. Marengo, Rong Fu, and German Poveda ................................149

The Amazonian Boundary Layer and Mesoscale CirculationsA. K. Betts, G. Fisch, C. von Randow, M. A. F. Silva Dias, J. C. P. Cohen, R. da Silva, and D. R. Fitzjarrald ........163

Natural Volatile Organic Compound Emissions From Plants and Their Roles in Oxidant Balance and Particle FormationJürgen Kesselmeier, Alex Guenther, Thorsten Hoffmann, Maria Teresa Piedade, and Jörg Warnke .....................183

Biomass Burning in Amazonia: Emissions, Long-Range Transport of Smoke and Its Regional and Remote ImpactsK. M. Longo, S. R. Freitas, M. O. Andreae, R. Yokelson, and P. Artaxo ...............................................................207

Aerosol Particles in Amazonia: Their Composition, Role in the Radiation Balance, Cloud Formation, and Nutrient CyclesPaulo Artaxo, Luciana V. Rizzo, Melina Paixão, Silvia de Lucca, Paulo H. Oliveira, Luciene L. Lara, Kenia T. Wiedemann, Meinrat O. Andreae, Brent Holben, Joel Schafer, Alexandre L. Correia, and Theotônio M. Pauliquevis ............................................................................................................................233

Modeling the Regional and Remote Climatic Impact of DeforestationM. A. Silva Dias, R. Avissar, and P. Silva Dias ....................................................................................................251

EvapotranspirationHumberto R. da Rocha, Antonio O. Manzi, and Jim Shuttleworth ......................................................................261

Global Warming and Climate Change in Amazonia: Climate-Vegetation Feedback and Impacts on Water ResourcesJosé Marengo, Carlos A. Nobre, Richard A. Betts, Peter M. Cox, Gilvan Sampaio, and Luis Salazar ....................273

Section III: Terrestrial Ecosystems

Biogeochemistry and Ecology of Terrestrial Ecosystems of AmazoniaYadvinder Malhi and Eric A. Davidson ...............................................................................................................293

Nutrient Limitations to Secondary Forest RegrowthEric A. Davidson and Luiz A. Martinelli ..............................................................................................................299

The Maintenance of Soil Fertility in Amazonian Managed SystemsFlávio J. Luizão, Philip M. Fearnside, Carlos E. P. Cerri, and Johannes Lehmann ................................................311

Sources and Sinks of Trace Gases in Amazonia and the CerradoM. M. C. Bustamante, M. Keller, and D. A. Silva ................................................................................................337

The Production, Storage, and Flow of Carbon in Amazonian ForestsYadvinder Malhi, Sassan Saatchi, Cecile Girardin, and Luiz E. O. C. Aragão ......................................................355

Changes in Amazonian Forest Biomass, Dynamics, and Composition, 1980–2002Oliver L. Phillips, Niro Higuchi, Simone Vieira, Timothy R. Baker, Kuo-Jung Chao, and Simon L. Lewis ............373

Ecosystem Carbon Fluxes and Amazonian Forest MetabolismScott Saleska, Humberto da Rocha, Bart Kruijt, and Antonio Nobre ....................................................................389

The Regional Carbon BudgetR. A. Houghton, Manuel Gloor, Jon Lloyd, and Christopher Potter .....................................................................409

The Effects of Drought on Amazonian Rain ForestsP. Meir, P. M. Brando, D. Nepstad, S. Vasconcelos, A. C. L. Costa, E. Davidson, S. Almeida, R. A. Fisher, E. D. Sotta, D. Zarin, and G. Cardinot .............................................................................................429

Soil Carbon DynamicsSusan Trumbore and Plínio Barbosa de Camargo ...............................................................................................451

Ecophysiology of Forest and Savanna VegetationJ. Lloyd, M. L. Goulden, J. P. Ometto, S. Patiño, N. M. Fyllas, and C. A. Quesada ..............................................463

Section IV: Surface Water

Surface Waters in Amazonia: Key Findings and PerspectivesJohn M. Melack, Reynaldo L. Victoria, and Javier Tomasella ..............................................................................485

The Role of Rivers in the Regional Carbon BalanceJeffrey E. Richey, Alex V. Krusche, Mark S. Johnson, Hillandia B. da Cunha, and Maria V. Ballester ...................489

Water and Chemical Budgets at the Catchment Scale Including Nutrient Exports From Intact Forests and Disturbed LandscapesJavier Tomasella, Christopher Neill, Ricardo Figueiredo, and Antonio D. Nobre ................................................505

Floodplain Ecosystem ProcessesJohn M. Melack, Evlyn M. L. M. Novo, Bruce R. Forsberg, Maria T. F. Piedade, and Laurence Maurice .............525

Effects of Climatic Variability and Deforestation on Surface Water RegimesMarcos Heil Costa, Michael T. Coe, and Jean Loup Guyot .................................................................................543

Section V: Conclusions and Vision for the Future

Results From LBA and a Vision for Future Amazonian ResearchM. Batistella, P. Artaxo, C. Nobre, M. Bustamante, and F. Luizão .......................................................................555

Index...................................................................................................................................................................565

Amazonia and Global ChangeGeophysical Monograph Series 186Copyright 2009 by the American Geophysical Union.10.1029/2009GM000883

PREFACE

ix

Writing about Amazonia demands superlatives: the world’s most extensive area of tropical forest, the world’s greatest river, the world’s most species-diverse ecosystem, the world’s largest store of aboveground carbon; the list goes on. We add one more: Amazonia, subject of the largest, coordinated, sci-entific study into a specific region of the world’s land sur-face. That study, an international experiment led by Brazil, is the Large-Scale Biosphere-Atmosphere Experiment in Ama-zonia, also known as LBA. The ambitious objective of LBA was to understand how Amazonia functions as an entity, as a whole ecosystem. This task was made all the more urgent, yet equally all the more difficult, by the fact that Amazonia is in a state of flux. Climate change, combined with land cover change in the form of deforestation, has created a three-dimensional moving picture of interacting causes and effects. To capture this dynamic situation, LBA adopted the design philosophy that the big picture would only emerge from an understand-ing of the component pieces and the interactions between them, building up regional-scale understanding from local measurements. This book synthesizes the results of that LBA research, bringing together the most important new scientific results and the new understanding that has resulted. The sta-tistics on LBA are impressive: nearly 2000 scientists (includ-ing over 500 Ph.D. and masters students) producing at least 1300 scientific papers. Reviewing all of this research in a single book is a daunting task and a process that inevitably reflects the personal perspectives of the editors and authors. Nevertheless, we hope to have covered the whole spectrum of research: the human dimensions, the meteorology and at-mospheric chemistry, the ecology and biogeochemistry of the land surface, and the hydrology. Despite the integration of research within LBA, there is a continuing need to improve communications between disciplines and for individual sci-entists to see their own research in the context of the overall

effort to understand the Amazonian ecosystem. Recognizing this need, the Scientific Steering Committee of LBA asked us to edit this book, to bring all this research together within one cover. An important legacy of LBA has been the training of a new generation of young environmental scientists who are now responsible for continuing the next phase of LBA. We envision that this book will be a resource to underpin that future research.

LBA is a special program of the Brazilian Ministry of Science and Technology (MCT), and we acknowledge their continuing support in the planning and implementation of this research. Funds have been provided by a number of Brazilian national and state agencies and funding agencies in the United States, the European Union, and elsewhere. In particular, we acknowledge major funding from MCT, NASA, and the European Commission. We acknowledge a debt to Carlos Nobre and Diane Wickland for their vision and leadership, particularly in the early stages of the design of LBA. Our personal thanks also go to Lorena Brewster for coordinating the editing of this volume.

John GashCentre for Ecology and Hydrology

Michael KellerInternational Institute of Tropical Forestry,

USDA Forest ServiceNEON, Inc.

Mercedes BustamanteUniversity of Brasília

Pedro Silva Dias

University of São Paulo

�

Amazonia and Global ChangeGeophysical Monograph Series �86Copyright 2009 by the American Geophysical Union.�0.�029/2009GM000902

People and Environment in Amazonia: The LBA Experience and Other Perspectives

M. Batistella,� D. S. Alves,2 E. F. Moran,3 C. Souza Jr.,4 R. Walker,5 and S. J. Walsh6

Amazonia is the arena for an ongoing extraordinary transformation of nature and society. This process of change can be depicted in many ways and by various disciplines, with emphasis on the biosphere or the atmosphere, as demonstrated by the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA). However, the human factors behind environmental change should not be neglected. This chapter introduces the section on people and environment in the region proposing an examination of the human dimensions of land use and land cover change from the LBA experience and other perspectives. As a basis for this approach, we provide a brief review on related topics and insights about opportunities for integrative research. Selected findings produced by LBA projects are highlighted and a synthetic view on research gaps, analytical gaps, data gaps, and policy implications of human dimension research in Amazonia is presented.

�Embrapa Satellite Monitoring, Campinas, Brazil.2Instituto Nacional de Pesquisas Espaciais, São José dos Cam-

pos, Brazil.3Department of Anthropology and Anthropological Center for

Training and Research on Global Environmental Change, Indiana University, Bloomington, Indiana, USA.

4Instituto do Homem e Meio Ambiente da Amazônia, Belém, Brazil.

5Department of Geography, Michigan State University, East Lansing, Michigan, USA.

6Department of Geography, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.

�. MOTIvATIONS

The chapters in this section of the book examine a variety of human impacts on ecosystems, landscapes, and regions as a consequence of different processes occurring in Amazo-nia, for example, deforestation and land use change [Alves et al., this volume; Brondizio et al., this volume], selective log-

ging [Asner et al., this volume], fire occurrences [Schroeder et al., this volume], the expansion of intensive agriculture and ranching [Walker et al., this volume], road building, and development [Pfaff et al., this volume]. Scenarios of future Amazonian landscapes built with simulation models are also discussed [Perz et al., this volume]. Assuming the current transformation of nature and society in Amazonia as an inter-active process, this chapter proposes a broad examination of the human dimensions of land use and land cover change from the Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) and other perspectives. One way to ap-proach this theme is to take the major scientific questions posed by LBA and identify situations where the human per-spective is implicated, for example, when human agents are responsible, directly or indirectly, for changes in land use and land cover. Another way might be to examine the epis-temology behind LBA to understand the role of science, and scientists, in formulating the mix of articulated disciplines and questions. A third way could be to examine biophysical dimensions, the climate change drivers, and their impacts on human society.

Our goals are not to enumerate all these options but to present how a human-centered perspective came to be part of LBA and what insights we have gained to date from that perspective. The next section will focus on the major

2 PEOPLE AND ENvIRONMENT IN AMAZONIA

questions proposed for LBA and why a human dimension was inherent, and indeed necessary, given how these ques-tions were formulated. Our focus is on the human dimen-sions of land use and land cover change because it was under this topic that the substantive work on human dimensions was originally developed within LBA science.

2. AN OvERvIEW ON THE HUMAN DIMENSION RESEARCH IN LBA

Taking the two fundamental questions of LBA, to under-stand how Amazonia functions as a regional system and how changes in land use, land cover, and climate might affect its functioning, it is evident that one could not answer these two questions by examining only the biophysical systems. At the center of change in Amazonia is the fact that the region is experiencing migration and settlement, high rates of defor-estation and logging, the development of roads and urban centers, and land use intensification. These changes in land use and land cover will have an impact on Amazonia’s long-term functioning. People are the agents of change, the agents that disturb the system, and also the ones that will suffer the consequences of such disturbance. LBA has learned to address how human-driven land use change affected land cover and how climate variability has been influenced by human changes in land cover and ecosystem functioning.

People are a major force in the biosphere (and the atmosphere), but human actions are mediated by human institu-tions at a variety of scales, from local, to regional, to national, and international. It is not simply individuals or households, which act upon the environment of Amazonia; it is also gov-ernment, nongovernmental organizations, and other forms of organized groups. These groups do not always work in concert. They differ in their goals, and how these conflicting goals play out is part of human dimension research.

Soon after its inception, LBA leading investigators recog-nized the need to develop a human dimension research agenda within the program. As with the International Geosphere- Biosphere Programme (IGBP), which realized in �988 that it needed to invite social scientists to help understand the hu-man drivers of global change, LBA became concerned early with the impact of environmental changes on people and of people on the environment. To explore this required social science, the challenge was how to include this human di-mension expertise in an effective way, given that the original LBA questions were not conceived with this perspective in mind and were drawn up without social scientists’ participa-tion. The original formulation involved climatologists, bio-geochemists, hydrologists, ecologists, and other biophysical scientists. As the LBA research progressed, the need for understanding the human dimensions of change in Amazo-

nia became so evident that even sensitivities to the theme by the Brazilian government, related to policy issues, were overcome, leading to recognized progress in articulating the natural and the social sciences [Batistella et al., 2008].

Four strategies were adopted to develop the human di-mension component of LBA. First, efforts were made to find ad hoc partnerships to jointly formulate scientific ques-tions reflecting the social processes behind land use and land cover change and the impacts of environmental change upon human health. Second, efforts were made to examine the policy implications of LBA for human resources, education, and training, particularly with regard to how it might affect the sustainable development of the region and the role of the state in such development. Third, LBA sought to strengthen the bridges with the social sciences, by inviting social scien-tists to join its Scientific Steering Committee and later devel-oping programmatic initiatives that were inclusive of social science questions [see Lahsen, 2002; Alves et al., 2004; Schor, 2005; Alves, 2007a, 2007b, 2008; Egler and Ibañez, 2007]. Finally, in the context of the transition to the second phase of LBA, a number of initiatives were taken to bring decision makers and stakeholders to present and discuss sci-entific findings and new integrative questions.

Among the relevant results was a bibliographic study to review the scientific production during the 1990s in the re-gion, with a focus on four major themes: populations, eth-nic and cultural representations; agropastoral and extractive activities; industrial activities; and urban networks [Becker, 2007a]. The search found a reasonable amount of work in the social sciences, both in regional institutions, and out-side the region. It revealed considerable depth in research on sociopolitical issues, particularly on modernization and social change, the expansion of the agropastoral frontier in the period �960–�985, the impact of the current frontier expansion, and of new dynamics of regional change. The greatest amount of debate in the literature focused on land use, particularly the use of forest resources, the impacts of cattle ranching, extractivism, and the different ways, some of them predatory, of land appropriation dominating the region. Other areas of considerable debate in the literature deal with deforestation, logging, and forest management and, more recently, urban development in the region as an alternative to rural living. The study identified some major topics for future research: the need for more attention to intraregional migration, the potential and limitations of various forms of production, and the role of cities and networks promoting regional development and change.

Another key initiative to foster the integration of social sciences in LBA was the workshop “The Human Dimen-sions of Environmental Change and LBA,” held in May 2004. It was a singular opportunity to address three main

BATISTELLA ET AL. 3

concerns about the importance of social sciences to LBA: (�) human dimensions of environmental change in Amazo-nia, including the identification of research gaps and analyti-cal tools to conduct such research; (2) data availability and quality; and (3) policy making. The workshop represented a rare chance for articulation among LBA and social sci-entists, allowing the formulation of research questions, not addressed in the original LBA scientific plan. A collection of selected papers produced by this workshop can be found in the work of Costa et al. [2007]. The workshop empha-sized knowledge gaps and the need for new analytical data and tools of interest to LBA, particularly related to issues

of sustainability. Table � synthesizes the outcomes of the workshop. Far from being a complete picture, it offers a pos-sible path for future initiatives integrating social and natural sciences in Amazonia.

3. HUMAN AND BIOPHySICAL DIMENSIONS OF LAND USE AND LAND COvER CHANGE

IN AMAZONIA: SELECTED FINDINGS AND OTHER PERSPECTIvES

A variety of relevant topics were posed by LBA scien-tists and contributors to the discussion of human dimensions

Table 1. Research Gaps, Analytical Gaps, Data Gaps, and Policy Implications of Human Dimension Research in Amazonia

TopicsInstitutions and

Governance

Logistics and Regional

DevelopmentProduction

SystemsPopulational

Mobility UrbanizationLand Use/Cover Changes (LUCC)

Research gaps

Role and weight of institutions;

Public/private relations;

Links between markets and the State

Differentiation of territorial units;

Links with institutions

Urban and rural linkages

Inter-regional/intraregional patterns;

Linkages with all other topics (e.g., LUCC)

Urban typology;Linkages

between urban infrastructure and all other topics (e.g., LUCC)

Regional patterns for deforestation and abandonment dynamics;

Linkages between agricultural production and LUCC (e.g., intensification, degradation);

New occupation fronts

Analytical gaps

Sociology of action

Network analysis Environmental valuation;

Regional accounting;

Production functions;

Data integration

Spatially explicit models

Tools for characterization of urban areas

Multiscale analysisassessments of land

use expansion and concentration;

Intra-annual classification of crops and pastures;

Analysis based on land parcels and agrarian structure

Data gaps Case studies Land zoning data;Census data

(including census-tract level)

Environmental, social, and economic variables;

Census data (including census-tract level)

Intramunicipal data (mostly from field work)

Data for periods between censuses

Deforestation data from the �970s;

Intra-annual remote sensing data;

Agricultural production data;

Land tenure data

Implications for policy making

Assessment of institutional lack and efficiency

Infrastructure and urban planning;

Land zoning

Land zoning;Institutional

building

Job creation;Infrastructure and

urban planning

Infrastructure and urban planning

Land zoning and planning;

Deforestation control


of Amazonian environmental changes. The economic ques-tions, for example, their relation with deforestation and other social and environmental dimensions, have revealed multitiered processes and highlighted the limitations of data gaps, analytical gaps, and incomplete knowledge [Perz et al., this volume]. The main challenges still reflect the need to balance economic development and nature conservation, including the difficulties of ensuring sustainability through market integration. In addition to these difficulties, the agrarian situation represents distinct opportunities and limi-tations for actors [Costa, 2007a; Walker et al., this volume; Brondizio et al., this volume]. As a consequence, some areas show emerging production systems, while others maintain their business as usual [Costa, 2007b].

The contrast between macroeconomic approaches and case studies at local scales remains an important source of discus-sion. This emerges from the research about land use patterns and processes at various scales and from the challenge of mul-tiscale integration, as revealed by the chapters of this section of the book. Two different problems can be recognized: (�) un-derstanding the system functioning as a regional entity, a well-known challenge of scale integration within LBA [LBA, �996; Nobre et al., 200�] and (2) identifying and comparing different locations, looking for understanding of social processes with higher or lower chances of environmental and economic sus-tainability [Batistella and Moran, 2005].

Logistics and regional development are closely related with the economic system, but one can also find connections with other dimensions, particularly with geopolitics and policy making. Becker [2007b] emphasizes the singular dy-namics referring to the soybean phenomenon in Amazonian frontiers, its production chains, its impact on the organization of actors, mainly due to the different roles of smallholders and largeholders, and policies related to infrastructure de-velopment. Walker et al. [this volume] discuss policies that created the preconditions for modern Amazonian agriculture as well as describing cattle ranching and soybean market set-tings and trajectories of expansion.

The role of roads and networks to provide access to re-sources and markets has also been highlighted [Pfaff et al., this volume]. These artificial landscape corridors should be considered in territorial planning, land zoning, and geo-politics. However, the differentiation of land units and insti-tutional arrangements is far from being achieved.

Moreover, understanding population mobility and strate-gies of occupation through the region will expose complex trajectories [Hogan et al., 2008]. In recent years, the popula-tion in Amazonia has grown increasingly urbanized, but the consequences of patterns and processes of urbanization to land use and land cover change remain a research topic to be developed.

The questions addressing land use and land cover change in Amazonia are central to LBA as they articulate with most of the research components of the experiment (Figure �). However, some scientific gaps remain. For example, knowl-edge is still incomplete about the regional patterns of de-forestation and land abandonment, the identification and quantification of land use intensification and land degrada-tion processes, and the immediate tracking of new fronts of occupation [Alves, 200�].

Data gaps include deforestation assessments for dates be-fore the �970s, remote sensing seasonal data, regional and local data about the agrarian structure and agropastoral pro-duction. Without these inputs, it is virtually impossible to carry out comprehensive multiscale analyses, intra-annual classifications of agricultural and pasture lands, as well as studies based on land parcels. These issues have clear policy implications, particularly for land zoning and deforestation monitoring.

Several initiatives within LBA addressed changes in land use and land cover. Considering only LBA-Ecology, a NASA-funded program on terrestrial ecology, there were 38 projects under this research component (Figure 1). These projects used a variety of perspectives, as illustrated by Fig-ure 2. On the other hand, only five projects addressed human dimensions of Amazonian change (Figure 3).

In general, progress was made in understanding the rela-tionship between certain types of land use and forest conver-sion, in particular, with regard to logging, cattle ranching, and small agriculture. Also of late, there has been progress in understanding the dynamics of conversion to mechanized soybean production, the transformation of land from forest matrices to agropastoral production centered landscapes, and the dynamics of fire in their relation to altered regions through selective logging and other land uses. The expansion of intensive agriculture, the impact of roads and networks on deforestation, and scenario developments also produced rel-evant results through LBA. Chapters in this section present findings and considerations on these matters.

Some aspects deserve special attention when examining the biophysical and human dimensions of land use and land cover change in Amazonia. Differences in soil quality, for example, explain much of the variance in the rates of sec-ondary succession, in crop choices, and persistence of farm-ers on the rural properties [Moran et al., 2000]. This finding highlights that we cannot overlook soil quality assessment as a key variable that makes a real difference in social and en-vironmental outcomes. Farmers with high quality soils were able to persist on their properties despite ups and downs of the economy over a 30-year period. When these soils were located favorably to markets, this advantage further multi-plies. These differences in soil quality are particularly no-

BATISTELLA ET AL. 5

table when we compare results across regions [Tucker et al., �998]. In interregional comparisons, biophysical factors are often more explanatory than human factors, and broad differences in agricultural potential are more likely to be considered by policy makers, thereby further enhancing the natural effect of biophysical differences.

However, the use and management of land better explains the differences in the rate of secondary succession and agri-culture intensification when we compare locations within a region [Moran and Brondizio, �998]. This is not surprising, as the detailed knowledge of a given property allows dif-ferences in management to be used in explanation. These

Figure 2. Research themes for projects under the component “Land Use and Land Cover” of LBAECO.

Figure 1. Number of projects by research component of LBAECO (the projects funded during the phase of synthesis and integration are in parentheses).


differences are commonly left out in aggregate analyses, where farmers may at best be treated as small or large, rather than having inherent different qualities in their stewardship of the land.

Monitoring land cover change in Amazonia has evolved significantly during the last decade. Stages of secondary succession can now be associated with spatial and spectral patterns that can be captured via analysis of remote sensed images, and further, can be used to estimate biomass and carbon, as well as to infer cycles of production [Moran et al., �994; Lu et al., 2005]. Spectral mixture analysis and classifi-ers using spatial, spectral, and textural information are better able to capture the heterogeneity of landscapes with greater accuracy [Lu et al., 2004].

Classification of successional forest stages remains a challenging task because of the lack of sharp distinctions between adjacent stages and confusion between early suc-cessional forest stages with degraded pasture and advanced successional forest stages with perennial plantations and agroforestry. Accurate classification of these land covers and associated biomass estimation has become a significant factor in reducing the uncertainty of carbon emission and sequestration [Zarin et al., 2005; Neeff et al., 2006].

Integration of remote sensing and geographic informa-tion systems allows the evaluation and mapping of soil ero-sion risk in a large area. When high-quality topographic and climate data are not available, a surface cover index based purely on remote-sensing data is useful to evaluate and map

the potential land degradation risks caused by deforestation and associated soil erosion in Brazilian Amazonia [Lu et al., 2007].

vegetation change detection has long been regarded as a challenge, especially in the moist tropical regions. Hybrid approaches combining image differencing and postclassi-fication comparison are promising in detecting vegetation change trajectories, especially for vegetation gain and loss [Lu et al., 2008].

The search for quantitative methods to analyze and de-scribe the structure of landscapes has also become a high priority. Land use and land cover issues are at the core of this perspective, due to their intricate dynamics and con-sequences in landscape structure and function. Landscape fragmentation is the process whereby a landscape matrix is progressively subdivided into smaller and more isolated patches, mainly as a result of human land use activities. The design of Amazonian settlements affects the structure of landscapes and the processes of fragmentation. Orthogonal settlement structure (such as the classic fishbone patterns found in Rondônia) produce greater forest fragmentation, have lesser spatial complexity, and less interspersion between landscape classes than settlements designed as a function of topographic variability. The design based on topography plays an important role in maintaining or increasing forest interior habitat relative to the entire landscape area, lower-ing the impact of forest fragmentation on the occurrence and distribution of organisms. The maintenance of large patches

Figure 3. Research themes for projects under the component “Human Dimensions” of LBAECO.

BATISTELLA ET AL. 7

of forest reserves also play an important role in maintain-ing lower levels of fragmentation [Batistella et al., 2003; Batistella and Brondizio, 2004].

The policy implications of such considerations are crucial for further initiatives regarding settlement implementation. Development and conservation strategies can be informed by the results achieved, but regional dynamics and local con-text should be taken into account to avoid political failures. The path for a reasonable conceptual approach explaining the heterogeneous processes of colonization in Amazonia is far from achieved, but analyses of landscape structure and function can provide a unique way to understand the spatial characteristics of Amazonian land change.

Land tenure, type of settlement, the developmental cycles, period and cohort effects also affect patterns of land use and land cover [McCracken et al., �999]. The cohort effect, for example, persists despite period effects, i.e., events such as tight credit, hyperinflation, and other macroeconomic forces affect the magnitude but not the overall trajectory of defor-estation [Evans et al., 200�]. On the other hand, the con-servation of relatively large areas of forest within human settlements is more effective if dependent on institutions’ self-organization relative to the needs of the population and to demarcating areas of reserve with rights given to local people vested in its protection [Batistella, 200�].

The understanding of human and environment interac-tions, in particular, the role of cohort, age, period effects, external capital, and household processes upon land cover trajectories in colonization areas, has progressed [Walker et al., 2000; Brondizio et al., 2002]. Among other initiatives, agent-based models incorporate household demographics and labor arrangements, land cover and allocation, soil qual-ity and crop productivity, and spatial features of the farm lot [Deadman et al., 2004].

However, the role of social variables to understand the dy-namics of land use and land cover in Amazonia is still poorly explored. Social studies rarely investigate the outcomes in terms of land change, and land use/land cover assessments rarely include the social dimensions of land change [Turner et al., 2004]. This research gap reveals an opportunity for future studies about the human-environment interactions in the region.

4. CONCLUDING REMARkS

The following seven chapters discuss human and bio-physical dimensions of land use and land cover change in Amazonia assuming that the understanding of changes in Amazonian landscapes and regions depend on documenta-tion of alterations in land cover and trajectories of land use. These land changes are intriguing processes to investigate,

as they produce relevant environmental outcomes and social feedbacks, such as land appropriation and conflicts, agricul-tural production systems, and human-dominated landscapes. The spatial nature of human-environment interactions in Amazonia brings up issues of scale and levels of analyses, providing opportunities for the study of spatially explicit processes, such as tropical deforestation and its impacts from region to household. The chapters in this section of the book provide a general picture about the accomplishments and limitations of this integrative research and also indicate promising grounds for future studies.

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BATISTELLA ET AL. 9

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M. Batistella, Embrapa Satellite Monitoring, Avenida Soldado Passarinho 303, Fazenda Chapadão, CEP �3070-��5, Campinas, SP, Brazil. ([email protected])

E. F. Moran, Department of Anthropology and Anthropologi-cal Center for Training and Research on Global Environmental Change, Indiana University, Bloomington, IN 47405, USA.

C. Souza Jr., Instituto do Homem e Meio Ambiente da Amazô-nia (Imazon), Rua Domingos Marreiros 2020, CEP 66060-�60, Belém, PA, Brazil.

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11

The Changing Rates and Patterns of Deforestation and Land Use in Brazilian Amazonia

Diogenes S. Alves,1 Douglas C. Morton,2 Mateus Batistella,3 Dar A. Roberts,4 and Carlos Souza Jr.5

Investigating the rates and patterns of land cover and land use change (LCLUC) in Amazonia is a central issue for Large-Scale Biosphere-Atmosphere Experiment in Amazonia (LBA) research. LCLUC, along with climatic changes, affects the biological, chemical, and physical functions of Amazonia, thereby linking environmental change at the local, regional, and global scales. Considerable research has focused on estimating rates of forest conversion in Amazonia, mainly through the use of satellite remote sensing, and evaluating factors that influence these rates. Beyond the rates of forest loss, LCLUC research in Amazonia has also considered the variety of agricultural uses that replace forest cover, forest degradation from logging and fire, and secondary vegetation on previously cleared lands.

1Instituto Nacional de Pesquisas Espaciais, São José dos Cam-pos, Brazil.

2Goddard Space Flight Center, Greenbelt, Maryland, USA.3Embrapa Satellite Monitoring, Campinas, Brazil.4Department of Geography, University of California, Santa Bar-

bara, California, USA.5Instituto do Homem e Meio Ambiente da Amazônia, Belém,

Brazil.

1. INTRoDUCTIoN

Investigating the rates and patterns of land cover and land use change (LCLUC) in Amazonia is a central issue for Large-Scale Biosphere-Atmosphere (LBA) Experiment in Amazonia research [Keller et al., 2004] (see the LBA Extended Science Plan at http://lba.cptec.inpe.br/lba/site/?p=plano_cientifico_estendido&t=1). LCLUC, along with climatic changes, affects the biological, chemical, and phys-ical functions of Amazonia, thereby linking environmental change at the local, regional, and global scales [Keller et al.,

2004] (LBA Extended Science Plan at http://lba.cptec.inpe.br/lba/site/?p=plano_cientifico_estendido&t=1). Consider-able research has focused on estimating rates of forest con-version in Amazonia, mainly through the use of satellite remote sensing and evaluating factors that influence these rates [e.g., Tardin et al., 1980; Fearnside et al., 1990; Fearn-side, 1990; Skole and Tucker, 1993; Alves, 2002; Margulis, 2004; Chambers et al., 2007]. Beyond the rates of forest loss, LCLUC research in Amazonia has also considered the variety of agricultural uses that replace forest cover, forest degradation from logging and fire, and secondary vegetation on previously cleared lands. LCLUC in Brazilian Amazonia is highly heterogeneous, both spatially and temporally, as are the varieties of agricultural uses that replace forest cover [e.g., Becker, 1997; Machado, 1998; Faminow, 1998; Alves, 2002, 2007a; Morton et al., 2006]. To capture this hetero-geneity, we develop a framework in which deforestation is one transition stage in a continuum of land use and land cover changes and their associated impacts on ecosystems and landscapes of Amazonia. We refer to the sequence of land cover changes, from mature forests to agricultural uses and abandonment, as a land use trajectory. Individual events within a trajectory are described as transitions.

The current Amazonian landscape is an integrated measure of the disturbance history from different development phases over the past 50 years. Numerous studies have provided

Amazonia and Global ChangeGeophysical Monograph Series 186Copyright 2009 by the American Geophysical Union.10.1029/2008GM000722

12 DEFoRESTATIoN AND LAND USE IN BRAZILIAN AMAZoNIA

a multifaceted history of the driving forces behind fron-tier expansion and deforestation in the region [e.g., Velho, 1976; Sawyer, 1984; Schmink and Wood, 1992; Machado, 1998; Margulis, 2004], and we will not duplicate those ef-forts here. Historically, variations in forest clearing rates were generally linked with changes in access to the region; thus, road building and migration were critical precursors to forest losses. During the 1980s and 1990s, large-scale colonization projects, credit incentives, and steady invest-ment in the region led to annual forest losses of 1–3 million ha [INPE, 2001, 2007] (Figure 1). More recently, economic forces within and beyond Amazonia have exerted stronger controls over deforestation rates and postclearing land uses, including domestic and global demand for beef, soybeans, and wood products [Faminow, 1998; Andersen et al., 2002; Margulis, 2004; Veiga et al., 2004; Morton et al., 2006].

LBA contributed to the development of remote sensing methods to map land cover and land use in Amazonia [Rob-erts et al., 2002; Hess et al., 2003; Lu et al., 2004; Anderson et al., 2005; Morton et al., 2006] and to greater understand-ing of the patterns and processes of deforestation and the overall dynamics of LCLUC through field, remote sensing, modeling, and related studies [e.g., Alves, 2002; Asner et al., 2005; Soares Filho et al., 2004; Alves, 2007a]. LCLUC plays a central role in many elements of LBA research, since the

sum of recent LCLUC defines the spatial patterns of land cover and the relative proportion of mature forest, secondary growth, or degraded forest of varying structural characteris-tics, wetlands, natural and planted pastures, and croplands in any Amazonian landscape.

In this chapter, we summarize recent LBA research fo-cused on regional-scale patterns and processes of forest modification, conversion, postclearing land use, and the fate of deforested land over time. Rates and patterns of defor-estation are influenced by a range of economic, social, and political factors, and where possible, we describe linkages between these controls and deforestation activity. We con-centrate on the large-scale dynamics that link a variety of LCLUC processes; specific transitions such as logging, fire, and individual agricultural uses will also be addressed in more detail in the following chapters. We begin with a sum-mary of deforestation mapping and monitoring approaches of both forest loss and postclearing land use. Basin-wide dy-namics of forest loss, agricultural land uses, and rates of land abandonment are subsequently described to discuss recent spatial and temporal trends in LCLUC. Finally, we examine the deforestation and postclearing land use of Mato Grosso state in greater detail to highlight rapid changes over the past decade in this region and the development of grain produc-tion capacity.

Figure 1. Interannual deforestation rates in Amazonia from Instituto Nacional de Pesquisas Espaciais (INPE) deforesta-tion surveys [INPE, 2001, 2007; Alves, 2007b]. (1) Average annual rates for the 1978–1988 period; estimates for 1978 were produced after partial reanalysis of black-and-white Landsat MSS 1:500,000-scale images and maps by Tardin et al. [1980] to address inconsistencies between this study and later INPE surveys [Fearnside et al., 1990]; (2) Average annual rates for the 1992–1994 period. Statistics for the 1987–2000 period are based on visual interpretation of color compos-ites of Landsat TM red, near-infrared and mid-infrared channels at the 1:250,000-scale. Later statistics are derived from digital processing of Landsat TM images mapping forest clearings of 6.25 and larger.

ALvES ET AL. 13

2. CHARACTERIZING SPATIAL AND TEMPoRAL vARIATIoNS oF LAND CovER AND USE

Mapping or monitoring land cover changes in Amazonia is challenging. The region is very large, rapidly changing, and often covered by clouds. The study of deforestation and subsequent LCLUC has therefore relied on satellite remote sensing and periodic agricultural censuses to construct the spatial and temporal variations in deforestation and post-clearing land uses. Satellite remote sensing has also been an integral part of investigations of the forest modification by logging and fire that often precedes deforestation and to the characterization of the spatial and temporal distribution of anthropogenic fires in Amazonia.

Given the vast geographic extent of inundated forests and other wetlands, tropical forest, and savannas (Plate 1), meth-odological approaches to map or monitor LCLUC often re-quire trade-offs in spatial or temporal resolution [Chambers et al., 2007]. Thus, deforestation mapping based on high-resolution satellite data can only be completed once per year, since cloud-free satellite coverage is most reliable during the dry season months [Fearnside, 1990; Asner, 2001]. Moni-toring changes in land management across Amazonia may only be possible at 5- or 10-year intervals from agricultural census data, given the amount of effort required to survey

farmers across the basin. The required spatial and tempo-ral resolution of any application will therefore influence the choice of a specific satellite sensor or data product.

Satellite remote sensing analyses have mapped the spatial extent of deforestation [e.g., Fearnside et al., 1990; Fearn-side, 1990; INPE, 2001; Alves, 2007b], selective logging [e.g., Asner et al., 2005; Souza et al., 2005], secondary for-est [e.g., Roberts et al., 2002; Alves et al., 2003], and land use following clearing [e.g., Moran and Brondízio, 1998; Morton et al., 2006; Lu et al., 2008]. Region-wide deforesta-tion in Brazilian Amazonia has been mapped with satellite data since the 1970s [e.g., Tardin et al., 1980; Fearnside et al., 1990; Fearnside, 1990; Skole and Tucker, 1993; Shimabu-kuro et al., 2007; Alves, 2007b]. Annual Landsat-based sur-veys estimate total deforested area in Brazilian Amazonia to have reached nearly 70 million ha by 2005 [INPE, 2001, 2007] (Plate 1).

Information regarding the timing of forest clearing activi-ties has emerged recently with the launch of new moderate resolution sensors SPoT-vEGETATIoN (1998, 1.1 km) and Moderate Resolution Imaging Spectroradiometer (MoDIS; 2000, 2003, 250 m to 1 km). Near-daily coverage from these instruments can be combined to provide cloud-free data at weekly to monthly intervals to map land cover change [e.g., Carreiras et al., 2002; Souza et al., 2003; Anderson et al.,

Plate 1. Brazilian Amazonia showing the areas of closed forest (58%), Cerrado woodland-savannas (14%), wetlands and water bodies (9%), and deforestation to 2005 (13%). Unobserved areas correspond to 2005 cloud cover (6%) or areas outside the limits of Brazilian Amazonia. Data sources: closed forest, woodland-savannas, and deforestation [INPE, 2007]; wetlands and water bodies [Hess et al., 2003].


that deforestation timing differed markedly between 2005 and 2006. In 2005, forest clearing in Mato Grosso was al-most equally split between September and April (47%) and May and August (53%), suggesting a strong wet season clearing component (November and April, 31%). In 2006, less than 20% of all clearing between was identified before May. Less wet season clearing in 2006 is consistent with reductions in large, mechanized clearing activities compared to other recent years.

Agricultural census data are a rich archive of regional in-formation on agricultural production, land management de-cisions, and related ecosystem and economic impacts. For 1970–1985, censuses were carried out every 5 years; after this period, a single survey was conducted (1995/1996), and a new census was underway in 2007. Census data are generally available at the municipal scale; however, due to frequent subdivisions of large municipalities, establishing a consistent unit of analysis to track changes over the entire 1970–1996 period would require very large, heterogeneous units, which, in some cases, would include entire states (see, for example, http://www.ipeadata.gov.br). Also, method-

Plate 2. (a) Regions of predominance of forest clearings of various sizes during 1991–1997 [after Alves, 2002]. Categories represent the clearing size that accounted for 50% or more of the total cleared area in the period; area depicted comprises the ¼° cells that accu-mulated the first 95% in the Lorenz curve shown in Figure 3 [after Alves, 2002]. (b) Same as Plate 2a but for 2000–2005.

2005; Morton et al., 2005; Lu et al., 2008]. Moderate resolu-tion data are not ideal for quantifying fine-scale land cover changes; deforestation monitoring algorithms only consider forest losses larger than several moderate resolution pixels, or approximately 25 ha [Morton et al., 2005; Shimabukuro et al., 2007]. MoDIS-based deforestation monitoring pro-vided the first regional understanding of the timing of for-est clearing activities [Anderson et al., 2005; Kay, 2005; Shimabukuro et al., 2007]. For recent deforestation in Mato Grosso state, clearing activity began in 93% of deforested areas prior to the onset of dry season conditions [Kay, 2005]. Clearings initiated in the wet season averaged three to five times the size of those areas cleared during the dry season, indicating that mechanized clearing may be less dependent on climate conditions than previously thought [Kay, 2005]. Data from DETER, an operational deforestation monitoring system developed by Instituto Nacional de Pesquisas Espa-ciais, Sao Paulo, Brazil [Shimabukuro et al., 2007], show

Plate 3. Contrasting patterns of forest fragmentation and land cover in two regions of Rondônia. old secondary forest appears to be abundant in an area of the northwestern part of the state. Within a region of old settlement near the town of Jaru, deforestation elimi-nates most forest cover between 1986 and 2003. Each scene is 21 km across.

ALvES ET AL. 15

ological issues from changes in the categories of data or the period of data collection, and difficulties related to the logistics of data collection in Amazonia further complicate comparisons between censuses. Despite these drawbacks, agricultural censuses constitute the most complete survey of agricultural production, including the area under different land use categories, crop production, and agricultural inputs, allowing for detailed analyses of social, economic, and en-vironmental aspects of agriculture in Amazonia and com-parison of the region with other parts of Brazil. During LBA, research based on data from the agricultural censuses evalu-ated the suite of positive and negative effects of deforesta-tion in Amazonia [Andersen et al., 2002] and the dynamics of land abandonment and land use intensification during this period [Alves, 2007a]. Methodological advances in fusing satellite and census data captured the corresponding spatial detail and management information in both data types for studies of land cover change and future landscape scenarios [Cardille and Foley, 2003; Morton et al., 2009].

3. LAND CovER AND LAND USE CHANGE: PATTERNS AND TRAJECToRIES IN AMAZoNIA

The same LCLUC trajectory can result from different suites of transitions, depending on the type of initial forest disturbance and the number of preceding land uses (Figure 2). For example, the forest to pasture trajectory can occur di-rectly, if mature forest is clear-cut to plant grasses, or in-

directly if pastures are established following logging or crop cultivation. The likely transition pathway from forest to other land uses depends on the stage of frontier occu-pation and the site conditions, such as distance to existing settlements and roads [Alves, 2002], soils and topography [e.g., Machado, 1998], land tenure, household assets, and market conditions for specific forest or agricultural products [Batistella et al., 2003; Batistella and Moran, 2005]. These factors influence the probabilities for individual transitions within this diagram at a variety of spatial scales; the spatial extent of logging and deforestation were nearly equivalent during 2000–2002, yet logged forest within 25 km of major roads had a higher probability of being deforested than un-logged forest [Asner et al., 2006].

Census data from 1970 to 1995 show several key trends in LCLUC trajectories during the expansion of the agricul-tural frontier. During this period, the majority of deforested land was converted to pasture for cattle ranching. The rela-tive importance of temporary crops was relatively stable across much of Amazonia except Mato Grosso (Table 1). The contribution of Amazonian cattle to the total Brazilian herd increased from 8% to 23%, driven by both an increase in pasture area and a doubling of the average stocking rates per hectare.

The long-term land use trajectories in a given region may be linked to different land use processes and socioeconomic factors. For example, cycles of land abandonment can be linked to shifting cultivation or land rotation in established

Figure 2. (a) Diagram showing the most common transitions among land cover/use classes studied during LBA. Initial forest disturbances occur through clear-cutting (solid), fire (dashed), and logging (dotted). Subsequent transitions among pasture, cropland, secondary forest, and degraded forest cover types show the diversity of pathways that are possible for any land use trajectory. (b) Transition probabilities for postclearing land uses in Mato Grosso state during 2000–2005 for forest, secondary forest, and cerradão woodland clearings >25 ha. Small deforestation events (<25 ha, not shown) in Mato Grosso account for 15% of all deforestation. Percentages refer to the fraction of cleared area converted to specific land uses [Morton et al., 2006, 2007a].


farms; cropland can rotate with pasture when grain prices are low. Although not shown in Figure 2, agroforestry, re-forestation, urban expansion, and other types of land use can also replace pastures or croplands. In addition, some land use trajectories can be influenced by a combination of fac-tors, such as forest degradation from selective logging and fire [Nepstad et al., 1999], which fundamentally alter forest structure and land value.

Particular LCLUC transitions generate unique patterns of forest loss. Different agrarian regimes, including farm size, the architecture of settlement projects, and different pro-duction and land management strategies can lead to diverse expressions of the same trajectory in landscape patterns. The composition and configuration of the landscapes pro-duced have important consequences for the functioning of the biophysical systems in Amazonia and may help inform discussions of plausible development scenarios for the re-gion. Within many older agricultural frontiers, concentrated deforestation activity in the vicinity of major roads and colo-nization projects [Machado, 1998; Alves, 2002] has led to landscapes dominated by pastures and cropland. The mag-nitude of forest clearing for agriculture in these areas often exceeds the limits prescribed by the Brazilian Forest Code [Alves et al., 2003; Alvez, 2007b].

The following sections review advances in understanding the evolution of landscape patterns and the dominant long-term LCLUC trajectories in Amazonia.

3.1. Landscape Patterns of Forest Conversion

Deforestation in Amazonia has replaced the forest with a fragmented landscape of pasture and agricultural areas, leav-ing few forest remnants where deforestation has been most concentrated. The total extent of deforestation in Amazonia until 2005, depicted in Plate 1, provides a first approxima-tion of important regional patterns in forest loss. Major road and river networks are buffered by the outlines of historic deforestation and older frontier areas of eastern Pará, Mato Grosso, and Rondônia states have greater forest loss than newer frontiers in central Pará, Acre, or Amazonas states. Specific site conditions, including soil quality or topogra-phy, further influence both the location of forest clearing and the postclearing land uses, such that patterns of deforestation and land use may be locally consistent.

The spatial patterns resulting from forest conversion may differ substantially across the basin as a function of clear-ing size (Plate 2). Deforestation between 1991 and 1997 oc-curred in very large clearings in central Mato Grosso and

Table 1. Evolution of Aggregate Land Use Statistics According to Brazilian Agricultural Censusa

1970 1975 1980 1985 1995

Land Category, % Total Farm AreaPasture 37.9 35.5 35.2 36.8 42.4Crops, temporary 2.6 3.3 4.1 4.4 3.9Crops, permanent 0.3 0.4 0.7 0.8 0.8Forest 37.3 43.0 42.4 40.4 41.3Abandoned landb 15.5 13.1 9.8 8.9 5.7All otherc 6.4 4.7 7.8 8.7 5.9

Temporary Crops in MT and in All Other States, % Total Farm Area

Mato Grosso state 1.4 2.1 4.1 5.3 5.6All other states 3.0 3.8 4.0 4.0 2.8

Cattle Head in Amazonia as a Fraction of National Herd, %8.2 9.0 12.7 14.7 23.3

Average Stocking Rate, head/ha0.30 0.30 0.40 0.40 0.70

aAggregate data for the nine states belonging to Legal Amazonia: Acre, Amapá, Ama-zonas, Maranhão, Mato Grosso, Pará, Rondônia, Roraima, and Tocantins. Source: http://www.ipeadata.gov.br.

bAbandoned land is defined as land unused for more than 4 years.cAll other includes land in rotation, planted forest, and other categories like swamps.

ALvES ET AL. 17

eastern Pará states and in smaller clearings in regions with higher densities of settlement projects in Pará and Rondô-nia. overall, large clearings on larger farms contributed the greatest fraction of total deforestation (Figure 3) [Alves, 2002]. During 2000–2005, the patterns in deforestation size show a bimodal distribution, with regions either dominated by very large (>1000 ha, 25% of cells) or very small (<50 ha, 51% of cells) clearing sizes. very large clearings in central Pará, southern Amazonas, and central Roraima states sug-gest that these regions were recently exposed to the same degree of capital and technology that was previously found only in older frontier areas.

Landscape patterns of forest conversion at the local scale reflect additional heterogeneity beyond clearing size (Plate 3). In 1986, central Rondônia near Jaru was already highly disturbed, consisting of nearly equal proportions of primary forest and pasture, with pasture concentrated along planned roads at 4-km intervals. By 2003, linear strips of forest from 1986 had been reduced to small forest fragments, many of which were less than 1 km across. Small patches of secondary forest mapped in 2003 occur exclusively along the margins of forest fragments that have never been cleared, suggesting that forest edges are taking on the spectral sig-nature of secondary forest in the absence of any clearing. Patterns in a region of the nearby municipio of Ariquemes differ markedly with extensive tracts of mature forest in both 1986 and 2003, no “fishbone” pattern from evenly spaced roads, and some large patches of secondary forest as much as 18 years old. Differences in fragmentation patterns reflect differences in the architecture of settlement and colonization

projects, whereas the persistence of secondary forest in the northwest is likely due to higher rainfall and poorer soils in this region.

3.2. Forest Degradation From Logging

Selective logging is one of the most important drivers of forest degradation and land cover change in Amazonia. Logging is rarely practiced in a sustainable fashion. In fact, only 1248 ha of mature forests were harvested following the Forest Stewardship Council (FSC) standards in Amazonia in 2003 [Lentini et al., 2005].

The extensive network of secondary roads built by log-gers and capital obtained by land owners selling timber help to accelerate the deforestation process near sawmill centers [Uhl et al., 1991; Verissimo et al., 1992]. Unmanaged log-ging practices lead to forest degradation through damage to forest structure and altered species composition [see Asner et al., this volume]. Using remote sensing techniques, As-ner et al. [2005] estimated that the annual area affected by logging was 12,000–19,000 km2 between 2000 and 2002, equivalent to the average annual deforestation rate during this period of 18,000 ± 2900 km [INPE, 2007]. Logging and deforestation are not mutually exclusive; an average of 16% of logged forests are clear-cut in the first year following log-ging operations, with 33% deforested within 4 years of log-ging [Asner et al., 2006]. Canopy damage and slash from logging operations increase the likelihood of fire damage in logged forests [Nepstad et al., 1999], although the extent of logged and burned forest has not been estimated for the en-tire Amazon region.

3.3. Forest Conversion to Pasture

According to census data, pasture has been the most com-mon land use in Amazonia (Table 1). Typical processes of pasture establishment in Amazonia include the direct con-version of forest to pasture or a longer conversion trajec-tory beginning with an initial phase of annual crops before pasture establishment after a number of years [e.g., Millikan, 1992]. After establishment, pasture productivity typically remains high for 5 to 7 years before declining due to changes in soil fertility and pH, resulting in a progressive decrease in forage quality and increased weed invasion [Buschbacher, 1986; Serrão and Toledo, 1990].

As pasture quality degrades, pastures can either be re- invigorated through repeated cycles of burning, reformed via fertilizer application and reseeding, or abandoned to second-ary succession. The length of time a pasture remains produc-tive is highly dependent on pasture management practices, local climate, and soil quality [Serrão and Toledo, 1990;

Figure 3. Lorenz curve of the 1991–1997 deforestation rate calcu-lated for ¼° cells and accompanying cumulative curves of the area of forest clearings of two different sizes in the same period [after Alves, 2002].


Moran, 1993; Dias Filho et al., 2000; Numata et al., 2007]. For example, pastures established on Alfisols or Ultisols in Rondônia that receive moderate levels of precipitation can remain productive for well over 20 years, whereas pastures established on oxisols or in more humid or arid conditions show earlier evidence of degradation and higher rates of abandonment [Numata et al., 2007].

Cattle ranching remains the dominant land use in Amazo-nia (Table 1), following important changes during the last decades. Faminow [1998] argues that a fundamental cause for the growth of the cattle herd was the considerable ex-pansion of regional demand associated with urban growth. Andersen et al. [2002] and Margulis [2004] reviewed the many motivations for cattle ranching and intensification of pasture use, concluding that ranching became profitable in-dependent of subsidies due to the growth of urban demand and increased productivity. Veiga et al. [2004] observed a variety of market chains stimulated by local demands and markets outside Amazonia. Higher stocking rates are more commonly found in the most deforested areas, suggesting a transition to pasture use intensification [Alves, 2007a]. Taken together, these factors help to explain the continued predominance of pastures in land use trajectories in Amazo-nian landscapes.

3.4. Forest Conversion to Cropland

In the context of LCLUC, we classify forest conversion to cropland according to the most common land use trajectories in recent decades. Cropland may directly follow deforesta-tion or arise as part of a rotation cycle with secondary forest or pasture. Direct conversion of forest to cropland occurs for both small-scale [e.g., Moran and Brondizio, 1998] and large-scale crop production [Morton et al., 2006]. In addi-tion to subsistence crops, small farmers may also invest in other crops for local or national markets [Moran and Bron-dizio, 1998; Costa, 2007]. Forest conversion for soybean, maize, or other grain production follows the recent develop-ment of crop varieties specifically adapted to the soils and climate of some Amazon regions [Warnken, 1999; Jepson, 2006]. The dynamics of forest conversion for mechanized crop production in Mato Grosso is discussed in more detail in section 4.1.

The nature of rotation systems between cropland and forest or pasture depend on both farm size and market conditions. For small farms, crop areas may be used until soil nutrients are depleted and then abandoned for several years to allow forest vegetation to accumulate nutrients. The length of fal-low rotations in a “slash-and-burn” or “chop-and-mulch” system depends on the rate of forest recovery and farm size [Denich et al., 2004]. on larger farms, market conditions

for beef or grains may determine the interannual patterns of pasture and cropland use or the frequency of fallow cycles.

Cropland can be both a precursor to land consolidation for cattle ranching or an endpoint itself, independent of farm size. Census data suggest that in Amazonia, croplands es-tablished in the original phases of colonization were largely replaced by cattle ranching as more forest was converted [Alves, 2007a]. However, recent expansion of mechanized crop production was generated through new deforestation, savanna clearing, and transitions from pasture to cropland [Morton et al., 2006]. The diversity of transition pathways, crop types, and farm sizes in Amazonia highlights the spatial and temporal variability of cropland on the landscape.

Deforestation dynamics in Mato Grosso state represents one case of particular interest because of specific sociodemo-graphic, economic, and bioclimatic conditions, suggesting the establishment of a new land use system differing from those dominating in other parts of Amazonia. Mato Grosso had the highest deforestation rate during 1995–2005, ac-counting for 33–43% of the annual deforestation increment in the Brazilian Amazon [INPE, 2007]. High rates of forest loss were driven by large clearing sizes [Alves, 2002; Mor-ton et al., 2006; Ferreira et al., 2007] (Plate 2 and Figure 3); large landholders (≥1000 ha) owned an estimated 84% and 82% of all land in private property statewide according to the 1985 and 1996 agricultural censuses, respectively [IBGE, 1996]. Although deforestation is associated with a variety of influences, economic factors have been largely linked with credit and economic opportunities for extensive cattle ranch-ing operations and crop production such as soybeans, and with inter-regional differences in land prices [Fearnside, 2001; Andersen et al., 2002; Margulis, 2004; Morton et al., 2006].

Deforestation in Mato Grosso is highly mechanized in comparison with other states. Two tractors, linked by a strong chain, are used to pull down trees in the transitional forests. Even in taller-stature forests, heavy machinery is used to manage manually felled trees. Piling and re-burn-ing forest vegetation can reduce standing forest to bare soil in a matter of months. Unlike previous estimates of carbon losses from deforestation, where 20% of biomass is com-busted, and the remainder decomposes over 10–30 years [Fearnside et al., 1993; Houghton et al., 2000], mechanized forest clearing practices may result in near-complete com-bustion of aboveground woody biomass and woody roots [Morton et al., 2008]. Mechanization has thereby increased the potential size of forest clearings and decreased the dura-tion of the deforestation process.

Combined advances in deforestation mapping and track-ing the fate of cleared land provide spatial and temporal de-tails regarding land cover transitions statewide. vegetation

ALvES ET AL. 19

phenology, derived from time series of MoDIS data, has proven useful for separating land cover types and following changes in land management over time [Ratana et al., 2005; Morton et al., 2006; Brown et al., 2007]. Figure 2b high-lights the dynamics of 2000–2005 transitions among major cover types in Mato Grosso state, showing the proportion of new deforestation, woodland savanna, and secondary forest conversions >25 ha as a function of postclearing land use. The main driver of forest loss in Mato Grosso is large-scale cattle production, yet direct conversion of forest to cropland contributed substantially to the number of large deforestation events and to woodland and secondary forest losses during this period [Morton et al., 2006, 2007a, 2007b]. Secondary forest is not a large component of the landscape in Mato Grosso compared with estimates for other regions, compris-ing only 11–14% of historic deforestation [Carreiras et al., 2006; Morton et al., 2007a]. Detailed analysis of the source of secondary and degraded forests in Mato Grosso from aban-donment, logging, and burning remains a research challenge.

Expansion of soybeans and other mechanized crop vari-eties in Amazonia has renewed the debate over extensive versus intensive land uses, and about the social and envi-ronmental outcomes of agricultural expansion. Climate, soils, and topography are suitable for soybean cultivation in forested regions of northern Mato Grosso and surrounding areas [Jasinski et al., 2005], and some authors have argued that soybean cultivation can be a competitive, intensive agri-culture alternative over extensive and low-productive cattle ranching [e.g., Andersen et al., 2002; Margulis, 2004]. How-ever, soybean production can contribute to pushing cattle ranching into new deforestation frontiers, as seen following its introduction in southern and west-central Brazil [Ander-sen et al., 2002], even if a detailed assessment of the role of soybeans in concentration of land tenure and income, rural outmigration, and loss of biodiversity has not yet been com-pleted [Fearnside, 2001].

3.5. Land Abandonment and Secondary Vegetation Growth

Considerable research has focused on mapping second-ary forest at local and regional scales [Lucas et al., 1993; Moran et al., 1994; Roberts et al., 2002; Alves et al., 2003; Carreiras et al., 2006]. Secondary forests are a potential carbon sink and can help recover hydrological and biogeo-chemical functioning after forest clearing [e.g., Brown and Lugo, 1990; Moran et al., 1994]. Secondary succession can develop following different pathways, including land rota-tion during shifting cultivation and land abandonment after pasture degradation or immediately following forest clear-ing; species composition, vegetation structure, and rates of carbon uptake in secondary forests are highly dependent

upon soil type and prior land use [Alves et al., 1997; Moran et al., 2000; Lucas et al., 2002; Zarin et al., 2005].

Census data and remote sensing analyses raise important questions about the long-term dynamics of secondary veg-etation in Amazonia. The proportion of cleared land that was unused for more than 4 years as a percentage of farm area declined steadily, from 15.5% to 5.7%, during 1970–1995 (Table 1). This evidence is consistent with findings that rates of land abandonment were higher in newly established frontiers, while secondary vegetation tended to be re-cleared concurrently with the elimination of mature forest remnants in older settlement areas [Alves et al., 2003; Alves, 2007a]. Time series of satellite data show that secondary forest is a dynamic component of the landscape in the Ariquemes and Ji-Paraná regions of Rondônia (Figure 4). In both regions, steady increases in pasture area resulted from more rapid re-clearing of secondary forest than pasture abandonment. overall, the contribution of secondary forest remained sta-ble or declined during 1986–2003, never exceeding 10% of the landscape. Declining rates of land abandonment in more intensively deforested areas indicate that over the long term, secondary forests may offset only a small fraction of the ini-tial carbon emissions from deforestation [Alves et al., 1997; Alves, 2007a].

4. CoNCLUSIoNS AND oUTLook

Brazilian Amazonia is one of most active regions of ag-ricultural expansion in the world. Clearing tropical forest is the primary means to increase the area of cattle pasture and crops, while related processes such as logging, fire for land clearing and management, land abandonment, and land use intensification are also key elements of the LCLUC dynam-ics. The conceptual model of transitions between multiple land cover and use states illustrates the heterogeneity of LCLUC trajectories and their expression in landscape pat-terns across Amazonia. Characterizing the spatial patterns created by such processes represents an important methodo-logical success in Amazonia, based on multiple data sources and a variety of analysis techniques, from which to investi-gate the role of LCLUC on the biophysical system.

Agriculture in the region is becoming increasingly in-tensive, conducted by large-scale operators with sufficient access to capital. These shifts in the spatial and temporal dynamics of LCLUC are present in both census data and satellite remote sensing as a decrease in secondary forests, increase in pasture stocking rates, and rapid expansion of the area under mechanized agriculture. The rise of intensive production and the influence of both national and interna-tional market forces on land use have led to the development of new ecologically oriented certification schemes for beef

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