My da|ra Login

Detailed view

metadata language: English

Land Use, Agropastoral Production, Family Composition, and Household Economy in Santarem, Para, Brazil, June-August 2003

Resource Type
Dataset : administrative records data, census/enumeration data, survey data
  • Moran, Emilio (Indiana University. Anthropological Center for Training and Research on Global Environmental Change (ACT))
Other Title
  • Version 1 (Subtitle)
Publication Date
Funding Reference
  • United States Department of Health and Human Services. National Institutes of Health. Eunice Kennedy Shriver National Institute of Child Health and Human Development
  • National Aeronautics and Space Administration
  • National Oceanic and Atmospheric Administration
Free Keywords
agricultural productivity; agriculture; birth control; crop income; crop value; deforestation; fertility; household composition; household income; immigration; land ownership; livestock; livestock income; population characteristics; property values; rural population
  • Abstract

    The 2003 Santarem dataset consists of 8 interconnected datasets and 1 linking file. The primary unit of analysis is the rural property or lot. Each lot in the sample contains a minimum of 1 household with a mean of 1.33 households per lot in the final sample. Within households, data were collected on subsets of individuals as well as additional properties used by the households in the study. These 2003 Santarem data come from interviews with farm families in an agricultural zone south of the city of Santarem in the Brazilian state of Para. Santarem is a relatively old settlement within the Brazilian Amazon that has experienced waves of regional settlement in the 1930s, mid-century, and the 1970s. The study region is adjacent to the confluence of the Amazon and Tapajos Rivers and the northern terminus of the BR-163 (the Cuiaba-Santarem Highway). BR-163 links intensive agropastoral production (particularly mechanized soybean farming) in the state of Mato Grosso to Santarem, where the multinational corporation Cargill runs a deepwater port (opened in 2003) for loading soybeans onto oceangoing ships. The opening of this port has accelerated the process of urbanization and led to a transformation from a landscape of small family farming to a landscape of mechanized agriculture (description adapted from VanWey, Leah K., and Kara B. Cebulko, 2007, Journal of Marriage and the Family 69: 1257-1270). The discourse on deforestation has focused on the alarming rates of deforestation in the Amazon Basin to the neglect of the dynamic and reciprocal influences between the human population and the environment. Deforestation is a process mediated by human intervention, from the act of clearing to how such a clearing is used and managed over time. It would be helpful to know whether observable rates of forest removal represent a stage in the developmental cycle of households or represents the simple and direct impact of increasing population in these environments. From the point of view of theory and method, it is necessary to develop new approaches that effectively link demographic process to the interactive relationship of population to specific aspects of an environmental matrix. This project addressed multiple scales, from household dynamics to landscape dynamics and has developed methods by which to scale between them. We hypothesize that as households occupy frontier areas past the first generation, they move from a strategy of managing their land under the constraints of available household labor to a strategy that gives greater recognition of the constraints posed by land quality and of the risks to their farm operation coming from external socioeconomic forces and biophysical constraints. In the first generation, the labor available to a household is determined by the size of the household making the initial trip to the frontier (primarily young couples is common in frontier regions) and later by the fertility of these initial migrants. As these initial migrants age and their children enter adulthood (thereby becoming the second generation), labor supply is determined by the reproductive and land use choices of these children. Given the precipitous decline in female fertility, other factors gain salience in the second generation: the suitability of the land for various uses, the availability of off-farm employment and educational opportunities (both locally and those requiring migration), and macroeconomic factors affecting the economic viability of farming. These decisions then directly determine the entries into and exits from the household. This study investigated five basic questions: (1) Does the changing availability of household labor over the household life cycle affect the trajectory of deforestation and land use change in the same way for later generations of Amazonian farmers as for first generation in-migrants? (2) What are the determinants of changing household labor supply? Specifically, what are the biophysical and socioeconomic determinants of entries into and exits from the household through fertility, migration, and marriage? (3) How are the decisions of households regarding land use and labor allocation constrained by soil quality, access to water supplies, interannual drought events (e.g. El Nino type events), and other resource scarcities? (4) Are there notable differences in land use choices made by landholders who live in an urban area (away from the piece of land owned in the rural area) in contrast to the decisions made by those who live on their rural properties? (5) What are the bases for the precipitous decline in female fertility in these frontier regions, especially the use of sterilization after two pregnancies? Households will be surveyed in the Santarem region, in the Lower Tapajos Basin, Brazilian Amazon to collect detailed demographic, land-use histories, and economic data. The sampling of households for inclusion in the study will be based on a stratified random sample by period of occupation in Santarem, to capture intergenerational processes that preceded the availability of satellite images. Based on the particular combination of methodologies used in this investigation (traditional household surveys, satellite image analysis, and GIS, and the scaling up and down from households to landscape), future environmental changes were projected for the regional landscape under various scenarios of continued settlement, household life cycles, combinations of credit, and changing environmental conditions.
  • Methods

    Weights are not employed in any of the data sets included here.
  • Methods

    ICPSR data undergo a confidentiality review and are altered when necessary to limit the risk of disclosure. ICPSR also routinely creates ready-to-go data files along with setups in the major statistical software formats as well as standard codebooks to accompany the data. In addition to these procedures, ICPSR performed the following processing steps for this data collection: Created variable labels and/or value labels.; Standardized missing values.; Checked for undocumented or out-of-range codes..
  • Methods

    Response Rates: Of 488 household heads on 300 lots that were sampled for an attempted interview, 401 provided data that appear in the final sample for an overall response rate of 82.2 percent. These households occupied 244 of the original 300 properties sampled for a property-level response rate of 81.3 percent.
  • Table of Contents


    • DS0: Study-Level Files
    • DS1: Household Characteristics Data
    • DS2: Household Roster Data
    • DS3: Contraceptive Use Data
    • DS4: Children Data
    • DS5: Former Household Member Data
    • DS6: Female Household Head Life History Data
    • DS7: Land Use History Data
    • DS8: Land Use Data
Temporal Coverage
  • Time period: 2003
  • Collection date: 2003
Geographic Coverage
  • Brazil
  • Global
  • Santarem
Sampled Universe
Households and household members dwelling on properties within the sampled study area (Santarem and Belterra municipios) during the summer months of 2003. Smallest Geographic Unit: Property or lot
The sample is a 4-stage cluster sample with stratification at the first stage. During stage 1, a grid of 3x3 km cells was superimposed on the study area using a Geographic Information System. The region was spatially subdivided into four sub-regions of roughly equal size, corresponding to four major roadways of different ages that transect the region, effectively stratifying by the age of the settlements. From each sub-region, approximately 12 3x3 km grids were selected. Using existing government property records, targeted properties were enumerated into a sampling frame. A spatial sampling algorithm was utilized during stage 2 sampling to ensure spatial clustering of the sampled properties for logistical and cost reasons. In each 3x3 km quadrant sampled, 5 targeted properties were identified and 4 backups in the event that one or more of the initial 5 properties was invalid. In the third and fourth stages of sampling, all households (census) and household members (census) past and present were identified and data were collected on various sub-populations.
Collection Mode
  • face-to-face interview

    The data and documentation (codebook and SAS, SPSS and Stata setup files) for this collection contain characters with diacritical marks used in the Spanish language.

Funding insitution(s): United States Department of Health and Human Services. National Institutes of Health. Eunice Kennedy Shriver National Institute of Child Health and Human Development (HD35811-08). National Aeronautics and Space Administration (LBA-ECO LC-09). National Oceanic and Atmospheric Administration (NA06GP0344).
This study is freely available to ICPSR member institutions via web download.
Alternative Identifiers
  • 34347 (Type: ICPSR Study Number)

Update Metadata: 2015-08-05 | Issue Number: 6 | Registration Date: 2015-06-16

Moran, Emilio (2013): Land Use, Agropastoral Production, Family Composition, and Household Economy in Santarem, Para, Brazil, June-August 2003. Version 1. Version: v1. ICPSR - Interuniversity Consortium for Political and Social Research. Dataset.