Secondary Vegetation

Ecological, Social, and Remote Sensing Issues


Report on a workshop organized by the project group for "Measurement and Modeling of the Inter-Annual Dynamics of Deforestation and Regrowth in the Brazilian Amazon." David Skole (Principal Investigator), Robert Walker, William Salas, and Charles Wood.

Edited by Robert Walker, William Salas, Gerald Urquhart, Michael Keller, David Skole, and Marcos Pedlowski.

With contributions from Eduardo Brondizio, Marcellus Caldas, Tatiana Deane de Abreu Sá, Luiz Guilherme de Silva, Rita Mesquita, Paulo Moutinho, Basil Savistky, Andrea Silva, Thomas Stone.

Participating Projects

"Anthropogenic landscape changes and the dynamics of Amazonian forest biomass," William Laurance, Rita Mesquita, and others.

"Biogeochemical cycles in degraded lands," Eric Davidson, Tatiana Deane de Abreu Sá, Ima Guimaraes Vieira, Paulo Moutinho, and others.

"Human and physical dimensions of LUCC in Amazonia: Forest regeneration and landscape structure," Eduardo Brondizio, Emilio Moran, and others.

"Measurement and Modeling of the Inter-Annual Dynamics of Deforestation and Regrowth in the Brazilian Amazon," Marcellus Caldas, Luiz Guilherme Texeira da Silva, Pedro Mourão, Marcos Pedlowski, Bill Salas, David Skole, Robert Walker, William Salas, Charles Wood.


May 16, 1999


Recent results from NASA’s Landsat Pathfinder project indicate that 30% of once cleared land in the Brazilian Amazon is now in secondary regrowth. Such widespread succession clearly impacts carbon flux over the basin, given the sequestration potential of secondary vegetation. Indeed, basin-scale assessments that do not recognize regrowth sequestration miss a key component of the carbon cycle. The balance of atmospheric carbon in Amazonia depends nearly as much on succession in the wake of disturbance as on deforestation.

Despite this centrality, key aspects of successional ecology have been overlooked by the LBA Ecology project For example, there are limited studies addressing critical elements of the disturbance environment associated with logging and fire. Moreover, patterns and processes of vegetation recovery are outcomes of human behavior interacting with the environment, a circumstance calling for interdisciplinary research. For reasons such as these, a workshop was convened at The Florida State University on February 25 and 26, 1999 to identify program-related issues regarding secondary vegetation, to integrate the discussion along ecological, social, and technical dimensions (i.e., measurement via remote-sensing), and, when possible, to state research questions of importance to LBA ecology.

This document, a product of the FSU workshop, is meant to function as a resource for LBA scientists. In particular, we provide brief overviews of pertinent issues that arose in discussion. In order of presentation, these overviews (with appropriate bibliographic materials organized at the end) address (1) terminological issues, (2) measurement from both ecological and remote sensing perspectives, and (3) the human dimensions of regrowth generation, utilization, and abandonment.


The Farmer’s Terminology: Farmers throughout the Amazon basin have different names to indicate different types and stages of secondary growth. Evidently, these terms indicate farmers’ perceptions about differences in structure and species dominance. Terms may be site specific or of common usage throughout the region. In some cases, they reflect actual stages of succession, from shrubby regrowth to more mature stands of successional trees. It is important to keep in mind that farmer terminology is not based on measurement or ecological categories. The following list enumerates a few of the more common terms. Clearly, this list is not an exhaustive one, since terms may be highly specific to place or vegetative complex.

The Ecologist’s Terminology: Ecologists understand secondary vegetation to be the successional plant community that occurs in the wake of disturbance. Such disturbances, both anthropogenic and natural, alter the structure of vegetation and modify microclimate and soil characteristics. Typical anthropogenic disturbances in the tropical forest biome include agriculture, logging, and fire, each of which shows different vegetative impact. Agriculture often eradicates the original species, and post-agricultural regrowth begins with a highly modified set of ecological actors. Logging may leave much of the original vegetation intact, which allows succession to start with a forest community already in place. Fire has variable impacts that range from minor damage to complete obliteration as a function of intensity.

Early stages of post-agricultural secondary succession are usually dominated by grasses (Poaceae), sedges (Cyperaceae), and herbaceous dicots. Over time, pioneer tree species arrive and exclude the early-successional vegetation. In general, key pioneer genera in secondary growth include Vismia (Clusiaceae), Cecropia (Cecropiaceae), Miconia and other Melastomataceae, Piper (Piperaceae), Croton (Euphorbiaceae), and Ochroma (Bombacaceae). Pioneer species typically have short lives (3-15 yrs) and are replaced by heliophiles, sun-loving hardwoods from many different families that appear early during succession. Only after several decades do primary forest tree species become a significant part of the vegetation. The quintessential Amazonia sequence may be summarized as a "forest" dominated by Cecropia progressing to hardwoods as the forest matures. This pattern varies, however, and in certain areas unique species such as the Babassú palm (Attalea racemosa) is a prominent element of secondary growth.


Ecological Issues and Questions: Summaries of biomass estimates for mature and secondary forests have been provided by Cairns et al. (1997) and Johnson et al. (1999). Cairns et al. (1997) assemble data on biomass and disaggregate it to aboveground and root components. They then explain the magnitude of root biomass in a regression framework using as independent variables the aboveground biomass, age of stand, and a set of dummy variables capturing boreal, temperate, and tropical locations (n=151). Johnson et al. (1999) descriptively address the relationship between above ground biomass and temperature adjusted age (growing-season degree-years), stratified for sandy/non-sandy soils, and for tropical/non-tropical sites (n=283). There is no difference in the relationship for tropical and non-tropical sites, although age is truncated for the tropical sample. The relationship is flatter for sandy than for non-sandy soils, as would be expected with nutrient or water limitation.

Despite worldwide measurements of biomass accumulation, observations for tropical sites are relatively few, which inhibits specification of functional relationships between regrowth rates, age, and environmental conditions. Early work by Uhl and colleagues in the Rio Negro basin provides a well-known account of biomass accumulation in the Amazon region. Uhl (1987) measured regrowth at about 6.77 T/ha in the early stages of succession. Saldarriaga et al. (1988) found a steady increase for older secondary vegetation, but even after eighty years biomass remained substantially less than primary forest. In a similar vein, Brown and Lugo (1990) show the most rapid rate of accumulation occurring during the first thirty years, after which it slows considerably. For sites in northeastern Para, secondary forest appears to recover only thirty five percent of mature forest biomass after twenty years (Vieira 1996).

Many factors contribute to the regeneration of secondary vegetation, and it should come as no surprise that growth rates are highly variable. In some settings, a field abandoned for two years can have woody specimens 4 m tall, while elsewhere a similarly aged plot could still be dominated by grasses and sedges. Soils, nutrients, and mycorrhizal associations play important roles in vegetative regrowth outcomes, as do ecological processes such as decomposition and herbivory (e.g., by ants; see Nepstad et al. 1995). Land use history is critical in this regard (Salomão et al 1996; Moran et al. 1996; Denich and Kanashiro 1998). Long periods of intense use cause the greatest changes to soils and their components, thereby slowing the process of regrowth. Since many secondary forest species reproduce vegetatively, root destruction following mechanized agriculture favors succession by plants such as grasses that reproduce from seeds (Denich and Kanashiro 1998). In abandoned pastures where soil has been compacted and leached, the period of biomass accumulation by secondary vegetation is prolonged. Invasion by woody species is inhibited by root destruction, soil compaction, diminished nutrient stocks, and loss of the mycorrhizal community. Salomão et al. (1996) show that biomass varies as a function of prior land use from 3.5 to 33.4 T/ha for secondary vegetation aged five years, from 22.3 to 62.8 T/ha for vegetation aged ten years, and from 48.1 to 131.5 T/ha for vegetation aged twenty years. The same soil degradation that causes farmers to abandon their land also affects the growth rate of secondary vegetation.

Ecological Research Needs: Although accounts of biomass accumulation exist for sites in the Amazon basin, the sample is insufficient to provide statistical descriptions linking rates of succession to environmental conditions and ecological processes. In addition, research has generally considered the full process stemming from agricultural clearance to restoration of closed, high biomass forest. A notable gap involves disturbances associated with logging and fire. Although previous research has addressed the magnitude of related effects, such as the amount of collateral damage that occurs under selective logging (Uhl et al. 1991), studies aimed at assessing regeneration after logging or fire are limited. Finally, successional studies tend to focus on gross measures of biomass and have paid little attention to nutrient recovery in either biomass or soils, with a few exceptions (e.g., Denich 1991; Hondermann 1995). This linkage is key to understanding the behavior of shifting-cultivators who depend on recycled nutrients. Indeed, social scientists hypothesize that the rate of fertility recovery is a key piece of ecological information assessed by shifting-cultivators in deciding when to slash secondary vegetation (Barret 1991; Walker 1999).

In sum, the following questions are pertinent to the ecology of secondary succession in the basin, and expand upon the LBA Ecology questions elaborated in our Experiment Plan:


Remote Sensing of Secondary Regrowth: Optical remote sensing has been used extensively to map the extent and rates of deforestation in Amazonia (e.g. Tucker et al. 1984, Malingreau and Tucker 1988, and Skole and Tucker 1993). Recently, several studies have mapped the extent and temporal dynamics of secondary vegetation at site level (e.g. Alves and Skole 1996, Mausel et al. 1993, Skole et al. 1994, Adams et al. 1995, Steininger 1996, Foody et al. 1996). Optical remote sensing identifies post-disturbance forest regrowth by analysis of patterns of spectral reflectance, a function of vegetative structure, not biomass. As abandoned pastures develop into young secondary forest stands, reflectance in the visible and mid-infrared regions diminishes with increased canopy density, chlorophyll absorption, and canopy water content; near-infrared reflectance initially increases due to increased mesophyll reflectance of the new green biomass (Mausel et al. 1993, Moran et al. 1994, Steininger 1996, Foody et al. 1996). With continuing maturation, the ratio of visible reflectance in the green and red regions of the spectrum declines, as does near- and mid-infrared reflectance due to inter-canopy shading. Eventually, reflectance characteristics become indistinguishable from those of mature, undisturbed forest (Mausel et al. 1993, Boyd et al. 1996).

Secondary vegetation formation and dynamics can also be monitored using multi-temporal remote sensing. There have been several multi-temporal studies mapping age and dynamics of secondary vegetation in various regions of Amazonia (e.g. Alves and Skole 1996 in Rondonia, Lucas et al. 1993 near Manaus, and Sant’Anna et al. 1995 near Tapajos National Forest). For example, Alves and Skole (1996) used multi-temporal Spot XS imagery for a site in Rondonia, Brazil to show that 42% of the areas in secondary vegetation in 1986 remained in secondary vegetation over the following 6 years and approximately 14% of the total area in secondary vegetation in 1992 was older than 6 years.

Several studies have focused using Landsat TM data to separate age classes of forest regrowth. Results indicate that regrowth stands can be spectrally separated into at most 4-5 spectrally distinct age classes, remaining spectrally distinct until an age of roughly 14 years (Boyd et al. 1996, Foody et al. 1996, and Steininger 1996). Working near Manaus, Foody et al. (1996) have demonstrated that intra-site differences in land use history (short term agriculture versus pasture use) can also have a significant impact on the spectral properties of regrowth stands. A pilot study (Salas and Zarin, unpublished) conducted using Landsat data from Amazonas and Mato Grosso further suggests that the seasonality of precipitation has a significant influence on the rate at which regrowth stands recover mature forest spectral reflectance characteristics in Amazonia.

Over the past few years there have been several studies on the use of synthetic aperture radar (SAR) for mapping deforestation and secondary vegetation in Amazonia. Nevertheless, the absence of a spaceborne multi-frequencey or polarimetric SAR system has limited applications. Studies to date have focused on using single frequency and single polarization spaceborne (e.g. JERS-1 and ERS-1) or mission-based systems of opportunity (e.g. SIR-C; See Rignot et al. 1997, Luckman et al. 1997, Saatchi et al. 1997, and Yanasse et al. 1997).

There has also been considerable research on the use of long wavelength SAR systems for estimating above ground biomass, since changes in radar backscatter are related to biomass. Unfortunately, backscatter data saturates beyond certain biomass levels. Estimates of the saturation point for L-band backscatter from tropical forests vary from 40 tons/ha (Imhoff 1995) to 60 tons/ha (Luckmann et al. 1997). Ranson and Sun (1997) and Rignot et al. (1995) have shown that multipolarization, P-band backscatter can be used to estimate biomass for forest stands ranging from 150 tons/ha (temperate forest ) to 200 tons/ha (tropical forest), respectively, the expected range of biomass for secondary regrowth in the tropics. Yanasse et al. (1997) used C-band and L-band SIR-C data to discriminate secondary forest stand ages up to 6 years old for a site in Amazonia, but Luckman et al. (1997) showed that biomass in secondary forest in central Amazonia is likely to exceed the saturation cutoff for L-band backscatter. Despite the promise of SAR in monitoring land-cover change, a longer wavelength SAR system is needed to systematically map secondary vegetation biomass in the region.

Remote Sensing Research Needs Quantitative estimates of the net biotic flux on a decadal average suffer from lack of quantitative data on pre- and post-disturbance biomass and on the actual fate of disturbed lands which may be logged, dedicated to perennial or annual crops, converted to pasture, or abandoned to fallow. Now that the spatial extent and rates of tropical deforestation are being measured with some degree of accuracy, techniques are needed for measuring rates of secondary vegetation formation, turnover, and accumulation (under a variety of disturbances) in order to more accurately estimate carbon fluxes. In this regard, the following questions are relevant:




The Social Sciences and Secondary Vegetation The social sciences have addressed secondary vegetation from a variety of perspectives, both explicitly and implicitly. Field research, much of it by anthropologists, has long considered the manipulation of fallow and use of associated plants in the household economies of indigenous peoples (Posey 1984; Denevan and Padoch 1987; Irvine 1987; Padoch 1987; Unruh 1988; Unruh 1990). Some of this research explicitly incorporates elements of regrowth and forest structure by addressing links between product type, understood as plants providing some utility to the household or community, and fallow ages (Denevan and Treacy 1987; Unruh and Alcorn 1987; Unruh and Paitan 1987; Balée and Gély 1989). Salick (1989), Salick and Lundberg (1990), and Coomes and Burt (1997) broaden this stream of analysis by attempting to explain characteristics of farming systems (numbers of fields, crop types, associated fallow lengths) in terms of household variables such as size of workforce and wealth position of families or kinship groups. Balée (1989) notes that a large percentage of the Amazonian forest is really an artifact of human use, given the extensive fallow improvements made by pre-colombian inhabitants over hundreds and even thousands of years.

The system of shifting cultivation has also been an object of long term interest to agronomists, anthropologists, and agricultural economists, given its apparently inefficient use of land (Spencer 1966; Ruthenberg 1971; Watters 1971; Peters and Neuenschwander 1988). Shifting cultivation, of course, utilizes secondary vegetation as a means to restore soil fertility; in particular, shifts from swidden fields to newly cleared regrowth occur with declining fertility and weed invasions (Ruthenberg 1971; Peters and Neuenschwander 1988; Unruh 1988). Boserup (1965) provides one of the earliest systematic accounts of shifting cultivation from the perspective of the social sciences, and in so doing elaborates an explicit model of vegetative change. (See Turner et al 1977). According to Boserup (1965), increasing population density explains the historic shift that occurs in land-covers, from old growth forest under long rotations, to younger forms of secondary forest, and ultimately to shrubby regrowth cycled every few years.

Recently, economists and geographers have extended the explanation of shifting cultivation beyond the demographic factors identified by Boserup (1965). One aspect of the literature addresses farmer control over soil loss (McConnell 1983) and develops a modeling frame based on pulsing models from the renewable resource literature (Lewis and Schmalensee 1977 and 1979). Krautkraemer (1994) argues that shifting cultivation may be understood as a sequence of farming episodes broken into intervals of soil fertility recuperation during which farming ceases. In this framework, the farmer controls the rate of soil loss (or fertility decline) to maximize net benefits. The approach by Barrett (1991) is similar in that a periodic sequence of farming and fallow is determined to be optimal for the farmer. The farmer’s behavior is fundamentally different, however, in that no control over soil loss is exercised. Instead, the farmer chooses fallow and farming periods that will provide the most income over the planning horizon. Walker (1999) develops a model in keeping with the subsistence requirement of shifting cultivators, who must insure a yearly supply of food from their own farming systems in the absence of capital markets for borrowing. Walker’s approach predicts the fallow times of secondary regrowth as well as the areas of regrowth associated with each regrowth cohort, as a function of family size (Walker 1999).

Social Science Needs The importance of secondary vegetation has been well-elaborated for indigenous groups, but not for colonists, the majority population in the forest frontiers of Amazonia. In particular, little is know about how these farmers actually utilize secondary regrowth in their farming systems. In addition, the existing model frameworks suggest that vegetative fallow provides natural re-fertilization and soil protection, but the work remains abstract, with little empirical grounding in the knowledge base of ecology. This shortcoming inhibits behavior-based models of carbon flux, given that regrowth sequesters carbon and is a function of farming activity. Finally, logging and fire disturbances in the tropical forest biome have not been systematically addressed by social sciences, excepting cost-benefit analyses of harvesting programs and plantation forestry for the case of logging. Thus, questions that remain to be answered include:





Secondary vegetation is a form of land-cover, but it is also a conceptual focal point that unites information from the ecological, physical, and social sciences. As such, it is an inherently interdisciplinary concept. Ecologists describe the structure of secondary vegetation, its rate of biomass accumulation, and the environmental conditions, including those of human origin, that impact its trajectory of change. Remote sensors measure the areal extent of succession, while social scientists explain why people find it advantageous to manage fallows, to slash their regrowth, and to abandon fields to natural processes of nutrient recovery. Consequently, the dynamics of secondary succession cannot be comprehended without interdisciplinary effort. For the purposes of modeling, this effort must be placed in a conceptual framework that allows for integration across disciplines.

In particular, a composite regrowth function needs to be developed in which biomass accumulation is explained by age, on the basis of both environmental and land-use controls. This function, in turn, must be linked to the land management actions of shifting-cultivators, who assess ecological information regarding nutrient recovery and prospects for weed invasions in taking their decisions. The exogenous effects of logging and fire must also be introduced into the model formulation, because these affect both successional and decision-making processes. And finally, upon integration, such a model must be stated with sufficient empirical detail that remote-sensing can be used to test, calibrate, and extend its predictions to regional and basin scale. Only in this way can carbon flux be predicted in a manner sensitive to both the natural and human dimensions of land-cover change.




Adams, J.B., Sabol, D.E., Kapos, V., Filho, Roberts, D.A., Smith, M.O., and Gillespie, A.R. 1995. Classification of multispectral images based on fractions of end members: Application to land-cover change in the Brazilian Amazon. Remote Sensing of Environment 52:137-154.

Aide, T. M., Zimmerman, J. K., Herrera, L., Rosario, M., and Serrano, M. 1995. Forest recovery in abandoned tropical pastures in Puerto Rico. Forest Ecology and Management 77: 77-86.

Aide, T. M., Zimmerman, J. K., Rosario, M., and Marcano, H. 1996. Forest recovery in abandoned cattle pastures along an elevational gradient in northeastern Puerto Rico. Biotropica 28:537-548.

Alcorn, J. B. 1989. Process as Resource: The Traditional Agriculture Ideology of Bora and Huastec Resource Manager and its Implications for Research. Advances in Economic Botany 7:63-77.

Allan, William. 1965. The African Husbandman. New York: Barnes and Noble, Inc.

Alves, D.S., Soares, J.V., Amaral, S., Mello, E.M.K., Almeida, S.A.S., DaSilva, O.F., Silveira, A.M. 1997. Biomass of primary and secondary vegetation in Rondonia, Western Brazilian Amazon. Global Change Biology 3(5):451-461.

Alves, S. D. and Skole, D. 1996. Characterizing land cover dynamics using multi-temporal imagery. International Journal of Remote Sensing 17(4):835-839.

Atran, S. 1993. Itza Maya Tropical Agro-Forestry. Current Anthropology 34(5):633-700.

Balée, W. 1989. The Culture of Amazonian Forests. Advances in Economic Botany 7:1-21.

Balée, W. and Gély, A. 1989. Managed Forest Succession in Amazonia: The Ka’apor Case. Advances in Economic Botany 7:129-158.

Barrett, S. 1991. Optimal soil conservation and the reform of agricultural pricing policies. Journal of Development Economies 36:167-187.

Beckerman, S. 1983. Does the Swidden Ape the Jungle? Human Ecology 11(1):1-12.

Bergman, R. W. 1980. Amazon Economics: The Simplicity of Shipibo Indian Wealth. Syracuse University: University Microfilms International.

Binswanger, H. P. and Pingali, P. L. 1984. The Evolution of Farming Systems and Agricultural Technology in Sub-Saharan Africa. Discussion Paper. Research Unit, Agricultural and Rural Development Department, Operational Policy Staff, World Bank.

Binswanger, H. P. and McIntire, J. 1987. Behavioral and Material Determinants of Production Relations in Land-abundant Tropical Agriculture. Economic Development and Cultural Change 36(1):73-99.

Bohlman, S.A., Adams, J.B., Smith, R.O., and Peterson, D.L. 1998. Seasonal foliage change in the eastern Amazon detected from Landsat TM Satellite images. Biotropica 30(3):376-391.

Boserup, E. 1965. The conditions of agricultural growth. London: Allen and Unwin.

Boyd, D. S., Foody, G. M., Curran, P. J., Lucas, R. M., and Honza, M. 1996. An assessment of radiance in Landsat TM middle and thermal infrared wavebands for the detection of tropical forest regeneration. International Journal of Remote Sensing 17(2):249-261.

Brown, S. and Lugo, A. 1990. Tropical secondary forests. Journal of Tropical Ecology 6:1-32.

Budowksi, 1965. Distribution of tropical rainforest species in the light of successional process. Turrialba 15:40-42.

Cairns, M.A., Brown, S., Helmer, E.H., and Baumgardner, G.A. 1997. Root biomass allocation in the world's upland forests. Oecologia 111(1):1-11.

Centro Agro-Ambiental do Tocantins (CAT). 1992. Elementos de análise do funcionamento dos estabelecimentos familiares da região de Marabá & Pesquisa-Formação-Desenvolvimento no programa CAT. Marabá, Brazil: CAT.

CIFOR, CATIE, EBRAPA-CPATU, UCA, UNALM and local communities and organizations involved in natural resource management. 1998. Farmer Management of Secondary Forest in Tropical America: Sustaining natural resources by generating benefits from secondary forest for rural communities. Unpublished manuscript. Belém: EMBRAPA/CPATU.

Cochrane, M. 1998. Forest Fires in the Amazon Basin, Conservation Biology 12(5):948-950.

Cochrane, M A. and Souza, C.M., submitted. Linear Mixture Model Classification of Burned Forest in Eastern Amazonia.

Coomes, O. T. and Burt, G. J. 1997. Indigenous market-oriented agroforestry: dissecting local diversity in western Amazonia. Agroforestry Systems 37:27-44.

de Moraes, J.F.L., Seyler, F., Cerri, C.C., and Volkoff, B. 1998. Land cover mapping and carbon pools estimates in Rondonia, Brazil. International Journal of Remote Sensing 29(5):921-934.

Denevan, William, M. 1992b. Stone Vs. Metal Axes: The Ambiguity of Shifting Cultivation in Prehistoric Amazonia. Journal of the Steward Anthropological Society 20: 153-165.

Denevan, W. M. and Padoch, C. (eds). 1987. Swidden-Fallow Agroforestry in the Peruvian Amazon. Advances in Economic Botany 5:1-107.

Denevan, W. M. and Treacy, J. M. 1987. Young Managed Fallows at Brillo Nuevo. Advances in Economic Botany 5:8-46.

Denich, M. 1991. Estudo da importância de uma vegetação secundária nova para o incremento da produtividade do sistema de produção na Amazônia Oriental Brasileira. EMBRAPA/CPATU-GTZ, Eschborn, 284 pp.

Denich, M. and Kanashiro, M. 1998. Potential Land-Use and Management of Altered and Abandoned Areas in the Brazilian Amazon Region. Studies of Human Impact on Forests and Floodplains in the Tropics (SHIFT). Brasilia: CNPq.

Dove, M.R. 1986. The Ideology of Agricultural Development in Indonesia. In Central Government and Local Development in Indonesia. ed.: C. MacAndrews, pp. 221-247. Singapore: Oxford University Press.

Dvorak, K. A. 1992. Resource Management by West African Farmers and the Economics of Shifting Cultivation. American Agricultural Economics Association 74(3):809-815.

Ellsworth, D. S. and Reich, P. B. 1996. Photosynthesis and leaf nitrogen in five Amazonian tree species during early secondary succession. Ecology 77: 581-594.

Finegan, B. 1996. Pattern and process in neotropical secondary rain forests: the first 100 years of succession. TREE 11(3):119-124.

Foin, T. C. and Davis, W. G. Equilibrium and Nonequilibrium Models in Ecological Anthropology: An Evaluation of "Stability" in Maring Ecosystems in New Guinea. American Anthropologist 89(1):9-31.

Foody, G., Palubinskas, G., Lucas, R., Curran, P.J. and Honzak, M. 1996. Identifying Terrestrial Carbon Sinks: Classification of Successional Stages in Regenerating Tropical Forest from Landsat TM Data. Remote Sensing of the Environment 55:205-2126.

Foody, G.M., Green, R.M., Lucas, R.M., Curran, P.J., Honzak, M., and DoAmaral, I. 1997. Observations on the relationship between SIR-C backscatter and the biomass of regenerating tropical forests. International Journal of Remote Sensing 18(3):687-694.

Frohn, R.C., McGwire, K.C., Dale, V.H., and Estes, J.E. 1996. Using satellite remote sensing analysis to evaluate an socio-economic and ecological model of deforestation in Rondonia Brazil. International Journal of Remote Sensing 17(16):3233-3255.

Hardwick, K., Healey, J., Elliott, S., Garwood, N., and Anusarnsunthorn, V. 1997. Understanding and assisting natural regeneration processes in degraded seasonal evergreen forests in northern Thailand. Forest Ecology and Management 99(1-2):203-214.

Hondermann, J.B.N. 1995. Fitomassa e estoque de bioelementos das diversas fases da vegetação secundária, provenientes de diferentes sistemas de uso da terra no nordeste paraense, Brasil. Tese Mestrado. Belém, Brasil: UFPA.

Houghton, R. A. 1997. Terrestrial carbon storage: Global lessons for Amazonian research. Environmental Impact 49(1/2):58-72.

Imhoff, M.L. 1995. Radar backscatter and biomass saturation: ramification for global biomass inventory. IEEE Trans. Geosci. & Remote Sensing. 33:511-518.

Irvine, D. 1989. Succession Management and Resource Distribution in an Amazonian Rain Forest. Advances in Economic Botany 7:223-237.

Johns, A. D. 1988. Effects of "Selective" Timber Extraction on Rain Forest Structures and Composition and Some Consequences for Frugivores and Folivores. Biotropica 20(1):31-37.

Johns, J., Barreto, P., and Uhl, C. 1996. Logging damage during planned and unplanned logging operations in the eastern Amazon. Forest Ecology And Management 89(1-3):59-77.

Johnson, C.M., Zarin, D.J., and Johnson, A.H. 1999. Post-disturbance aboveground biomass accumulation in global secondary forests: climate, soil texture, and forest-type effects. Unpublished manuscript.

Jones, D. W. and O’Neill, R. V. 1993a. Human-environmental influences and interactions in shifting agriculture when farmers form expectations rationally. Environment and Planning A 25(1):121-136.

Jones, D. W. and O’Neill, R. V. 1993b. Human-Environmental Influences and Interactions in Shifting Agriculture. Structure and Change in the Space Economy by Lakshmanan, T. R. and Nijkamp, P. (eds), pp. 297-309. Springer-Verlag: New York.

Kauffman, J.B., Cummings, D.L., Ward, D.E., and Babbitt, R. 1995. Fire in the Brazilian Amazon: 1. Biomass, nutrient pools, and losses in slashed primary Forests. Oecologia 104(4):397-408.

Kimes, D.S. 1998. Accuracies in mapping secondary tropical forest age from sequential satellite imagery. Remote Sensing of Environment 65:112-120.

Krautkraemer, J. A. 1994. Population growth, soil fertility, and agricultural intensification. Journal of Development Economics 44:403-428.

Lewis, T. R. and Schmalensee, R. 1977. Nonconvexity and Optimal Exhaustion of Renewable Resources. International Economic Review 18(3):535-552.

Lewis, T. R. and Schmalensee, R. 1979. Non-convexity and optimal harvesting strategies for renewable resources. Canadian Journal of Economics 4:677-691.

Li, Y. et al. 1994. Discrimination between Advanced Secondary Succession and Mature Moist Forest Near Altamira, Brazil Using Landsat TM. ASPRS/ACSM, proceedings(?) pp 350-364.

López, R. and Niklitschek, M. 1991. Dual economic growth in poor tropical areas. Journal of Development Economics 36:189-211.

Lucas, R. M., Honzak, M., Foody, G. M., Curran, P. J., and Corves, C. 1993. Characterizing tropical secondary forests using multi-temporal Landsat sensor imagery. International Journal of Remote Sensing 14(16):3061-3067.

Luckman, A., Baker, J., Kuplich, T.M., Yanasse, C.C.F., Frery, A.C. 1997. A study of the relationship between radar backscatter and regenerating tropical forest biomass for spaceborne SAR instruments. Remote Sensing of Environment. 60-1-13.

Malingreau, J.P. and Tucker, C.J. 1988. Large-scale deforestation in the southeastern Amazon basin of Brazil. Ambio 17:49-55.

Mausel, P., Wu, Y., Li, Y., Moran, E.F., and Brondizio, E.S. 1993. Spectral identification of successional stages following deforestation in the Amazon. Geocarto International 4:61-71.

McConnell, K. E. 1983. An Economic Model of Soil Conservation. American Agricultural Economics Association 65(1):83-89.

McKane, R. B., Rastetter, E. B., Melillo, J. M., Shaver, G. R., Hopkinson, C. S., Fernandes, D. N., Skole, D. L., and Chomentowski, W. H. 1995. Effects of global change on carbon storage in tropical forests of South America. Global Biogeochemical Cycle 9(3):329-350.

Metzger, J. P. No Date. Dinâmica da paisagem, tempo de pousio e estrutura espacial da vegetação secundária numa área de agricultura de corete e queima. Unpublished manuscript.

Moran, E.F., Brondizio, E., Mausel, P., and Wu, Y. 1994. Integrating Amazonain vegetation, land-use, and satellite data. Bioscience 44:329-338.

Moran, E.F., Packer, A., Brondizio, E., and Tucker, J. 1996. Restoration of Vegetation Cover in the Eastern Amazon. Ecological Economics 18: 41-54.

Nelson, B. et al. 1998? Allometric regression for improved estimates of secondary forest biomass in the Central Amazon. Forest Ecology and Management

Nepstad, D., Jipp, P., Moutinho, P., Negreiros, G., and Vieira, S. 1995. Forest recovery following pasture abandonment in Amazonia: Canopy seasonality, fire resistance and ants. In Evaluating and Monitoring the Health of large-scale Ecosystems (eds.: D.J. Rapport, C.L. Gaudet, and P. Calow. Pp. 333-349. Berlin: Springer-Verlag.)

Nepstad, D., Verssimo, A., Alencar, A., Nobre, C., Lefebvre, P., Schlesinger, P., Potter, C., Moutinho, P., Lima, E., Cochrane, M., and Brooks, V. In press, b. Large-scale impoverishment of Amazonian forests by logging and fire. Nature.

Nepstad, D. C., de Carvalho, C.R., Davidson, E.A., Jipp, P., Lefebvre, P., Negreiros, G.H., da Silva, E.D., Stone, T., Trumbore, S., and Vieira, S. 1994. The role of deep roots in the hydrological and carbon cycles of Amazonia forests and pastures. Nature 372:666-669.

Nepstad, D. C., Uhl, C. and Serrao, E. A. S. 1991. Recuperation of a Degraded Amazonian Landscape: Forest Recovery and Agricultural Restoration. Ambio 20(6):248-255.

Nerlove, M. 1997. In and Out of Africa, July 27-August 23, 1996: A personal journal.

Nykvist, N. 1996. Regrowth of secondary vegetation after the 'Borneo fire' of 1982-1983. Journal of Tropical Ecology 12:307-312.

Padoch, C. 1987. The Economic Importance and Marketing of Forest and Fallow Products in the Iquitos Region. Advances in Economic Botany 5:74-107.

Peters, W. J. and Neuenschwander. 1988. Slash and Burn: Farming in the Third World Forest. University of Idaho Press: Moscow, Idaho.

Petriceks, J. 1968. Shifting Cultivation in Venezuela. Master’s Thesis. Syracuse University.

Posey, D. A. 1984. A Preliminary Report on Diversified Management of Tropical Forest by the Kayapó Indians of the Brazilian Amazon. Advances in Economic Botany 1:112-126.

Ranson, K.J., and Sun, G. 1994. Mapping forest biomass of a northern forest using multifrequency SAR data. IEEE Transactions on Geoscience and Remote Sensing, 32(2):388-396.

Rignot, E., Salas, W. A., and Skole, D. L. 1997. Mapping Deforestation and Secondary Growth in Rondonia, Brazil, Using Image Radar and Thematic Mapper Data. 1997. Remote Sensing of Environment 59:167-179.

Rignot, E.J., Zimmermann, R., van Zyl, J.J. 1995. Spaceborne application of P Band imaging radars for measuring biomass. IEEE Trans. Geosci. and Remote Sensing. 33:1162-1169.

Ruddle, K. 1974. The Yukpa Cultivation System: A Study of Shifting Cultivation in Colombia and Venezuela. University of California Press: Berkeley.

Ruthenberg, H. 1971. Farming Systems in the Tropics. Clarendon Press: Oxford.

Saatchi, S.S., Soares, J.V., Alves, D.S. 1997. Mapping deforestation and land use in Amazon rainforest using SIR-C imagery. Remote Sensing of Environment, 59:191-202.

Sader, S. A., Waide, R. B., Lawrence, W. T., and Joyce, A. T. 1989. Tropical forest biomass and successional age class relationships to a vegetational index derived from Landsat TM data. Remote Sensing of Environment 28:143-156.

Saldarriaga, J. G. and Uhl, C. 1990. Recovery of Forest Vegetation Following Slash-and-Burn Agriculture in the Upper Rio Negro. Rain Forest Regeneration and Management 6(18):303-312.

Saldarriaga, J. G., West, D. C., Tharp, M. L., and Uhl, C. 1988. Long-Term Chronosequence of Forest Succession in the Upper Rio Negro of Colombia and Venezuela. Journal of Ecology 76:938-958.

Salick, J. 1989. Ecological Basis of Amuesha Agriculture, Peruvian Upper Amazon. Advances in Economic Botany 7:189-212.

Salick, J. and Lundberg, M. 1990. Variation and Change in Amuesha Agriculture, Peruvian Upper Amazon. Advances in Economic Botany 8:199-223.

Salomão, R., Nepstad, D., and Vieira, I. C. Biomassa de florestas tropicais e efeito estufa. Ciência Hoje 21(123).

Sampaio, S.M.N., and de Silva, L.G. 1998. Dynamics of the Vegetation and Land Use in relation to Agro-ecological and Socio-economic Factors in Rural Communities of Northeastern Pará.

Sant'Anna, S.J., Yanasse, C. F., Filho, P.H., Kuplich, T.M., Dutra, L.V., Frery, A.C., and P.P. Santos. 1995. IGARSS'95, pp 323-325.

Scatena, F., Walker, R.T., Homma, A., de Conto, A.J., Ferreira, C.A.P., Carvalho, R., Neves da Rocha, A.C.P., Moreira dos Santos, A.I., and Mourao de Oliveira, P. 1996. Cropping and Fallowing Sequences of Small Farms in the "Terra Firme" Landscape of the Brazilian Amazon: A Case Study from Santarem, Para. Ecological Economics 18: 29-40.

Skole, D. L., Moore III, B. and Chomentowski, W. H. 1994. Spatial Analysis of Land-Cover Change and Carbon Flux Associated with Biomass Burning in Brazil, 1970-1980. Climate Biosphere Interaction: Biogenic Emissions and Environmental Effects of Climate Change.

Skole, D.S. and Tucker, C.J. 1993. Tropical deforestation and habitat fragmentation in the Amazon: Satellite data from 1978 to 1988. Science 260:1905-1910.

Smith, J., van de Kop, P., Reategui, K., Ignacio, L., Sabogal, C. and Diaz, A. 19 __. Dynamics of secondary forests in slash-and-burn farming: interactions among land use types in the Peruvian Amazon.

Souza Jr., C. and Barreto, P. in press. An Alternative Approach for Detecting and Monitoring Selectively Logged Forests in the Amazon. International Journal of Remote Sensing.

Spencer, J.E. 1966. Shifting Cultivation in Southeastern Asia. University Publications In Geography 19. Berkeley: University of California Press.

Staver, C. 1991. The role of weeds in the productivity of Amazonian bush fallow agriculture. Experimental Agriculture 27(3):287-304.

Steininger, M. K. 1996. Tropical secondary forest regrowth in the Amazon: age, area, and change estimation with Thematic Mapper data. International Journal of Remote Sensing 17:9-27.

Stone, T. A and Lefebvre, P. 1998. Using Multi-Temporal Satellite Data to Evaluate Selective Logging in Para, Brazil. International Journal of Remote Sensing 19(13):2517-2526.

Szott, L. T., Palm, C. A., and Davey, C. B. 1994. Biomass and litter accumulation under managed and natural tropical fallows. Forest Ecology and Management 67(1-3):177-190.

Thomlinson, J. R., Serrano, M. I., Lobez, T. M., Aide, T. M., and Zimmerman, J. K. Land-use dynamics in a post-agricultural Puerto Rican landscape (1936-1988). Biotropica 28:525-536.

Tian, H., Melillo, J. M., Kicklighter, D. W., McGuire, A. D., Helfrich, J.V.K. III, Moore, Berrien III, and Vörösmarty, C. J. 1998. Effect of interannual climate variability on carbon storage in Amazonian ecosystems. Nature 396:664-667.

Tucker, C.J., Holben, B.N., and Goff, T.E. 1984. Intensive forest clearing in Rondonia, Brazil as detected by satellite remote sensing. Remote Sensing of Environment 15:255-261.

Tucker, J. M, Brondizio, E. S., and Moran, E. F. 1998. Rates of Forest Regrowth in Eastern Amazônia: A Comparison of Altamira and Bragantina Regions, Pará State, Brazil. Interscienca 23(2).

Turner II, B.L., Hanham, R.Q., and Portararo, A.V. 1977. Population Pressure and Agricultural Intensity. Annals of the Association of American Geographers 67: 384-396.

Turner, I.M., Wong, Y.K., Chew, P.T., and BinIbrahim, A. 1996. Rapid assessment of Tropical Rain forest successional stages using aerial photographs. Biological Conservation 77(2-3):177-183.

Uhl, C. and Murphy, P. 1981. Composition, Structure, and Regeneration of a Tierra Firme Forest in the Amazon Basin of Venezuela. Tropical Ecology 22(2):219-237.

Uhl, C., Buschbacher, R. and Serrão, E. A. S. 1988. Abandoned Pastures in Eastern Amazonia. I. Patterns of Plant Succession. Journal of Ecology 76:663-681.

Uhl, C., Verissimo, A., Mattos, M.M., Brandino, Z., and Vieria, I.C.G. 1991. Social, economic, and ecological consequences of selective logging in an Amazon frontier: the case of Tailândia. Forest Ecology and Management 46:243-273.

Unruh, J. D. 1988. Ecological aspects of site recovery under swidden-fallow management in the Peruvian Amazon. Agroforestry Systems 7:161-184.

Unruh, J. D. 1990. Interative increase of economic tree species in managed swidden-fallows of the Amazon. Agroforestry Systems 11:175-197.

Unruh, J. and Alcorn, J. B. 1987. Relative Dominance of the Useful Component in Young Managed Fallows at Brillo Nuevo. Advances in Economic Botany 5.

Unruh, J. and Paitán, S. F. 1987. Relative Abundance of the Useful Component in Old Managed Fallows at Brillo Nuevo. Advances in Economic Botany 5:67-73.

Vickers, W. T. 1976. Cultural Adaptation to Amazonian Habitats: The Sione-Secoya of Eastern Ecuador. Ph.D. Dissertation. University of Florida.

Vieira, I., Salomão, R., Rosa, N., Nepstad, D., and Roma J. 1996. O Resascimento da Floresta no Rastro da Agricultura. Ciência Hoje 20(119).

Walker, R. 1999. The structure of uncultivated wilderness: Land use beyond the extensive margin. Journal of Regional Science 33:387-410.

Watrim, O.S. 1994. Estudo da dinámica na paisagem da Amazônia Oriental através de técnicas de geoprocessamento. Curso de pós-graduação do INPE, São José dos Campos. 153 pp.

Watters, R. F. 1971. Shifting Cultivation in Latin America. FAO Forestry Development Paper No. 17.

Yanasse, C.D.F., SantAnna, S.J.S., Frery, A.C., Renno, C.D., Soares, J.V., and Luckman, A.J. 1997. Exploratory Study of the relationship between Tropical Forest Regeneration Stages and SIR-C L and C data. Remote Sensing of the Environment 59(2):180-190.