MSc thesis research proposal Department of Geography McGill University Identifying the Role of Crop Production in Land Cover Change in Brazil since 1990
Download 350.04 Kb.
|
- Navigate this page:
- METHODS
|
Source: ESRI, CIAT, IBGE Fig. 4. The Brazilian Major Ecosystem RESEARCH OBJECTIVESThe goal of this project is to examine the role of different crops in the changing land cover of Brazil since 1990. The project will investigate the following research questions: How has the geographic pattern of crops in Brazil changed since 1990? Which crops are driving the change and why? In which physiographic context has this expansion occurred, and which ecosystems are being affected? I will address the above research questions through the following objectives: Analyze the changing spatial distribution of crops in Brazil since 1990 using GIS Analyze crop production and trade data to understand the driving factors behind new crop expansion Examine the physiographic context and ecosystem impacts of the crop expansion Objective 1: Analyze the changing spatial distribution of crops in Brazil since 1990 using GIS In order to identify the spatial distribution of crops in Brazil it is necessary to gather agricultural data such as census and surveys statistics available since 1990 to date. Global databases of agricultural land-use such as AgroMaps15 and FAOSTAT16 contain statistics compiled at national and sub-national levels. Agricultural surveys and censuses commonly include harvested crop area and production by weight and yield. Most countries monitor their agricultural industry through agricultural census data or annual survey data (i.e., IBGE), which are reported at administrative or municipality level. The Brazilian Institute of Geography and Statistics (IBGE17) offers free access to information that includes census data, statistical surveys and data set of agricultural and socioeconomic activities, at municipality and departmental level for the whole of Brazil. Although many environmental and socioeconomic databases related to crop production exist, it is necessary to use GIS tools in order to standardize the diverse dataset to carry out multi-scale analysis, and generate time series map of crop distribution since 1990. Objective 2: Analyze crop production and trade data to understand the driving factors behind new crop expansion I will analyze trade statistics18 to understand the driving forces of crop expansion. Global database like FAOSTAT and USDA provides world agricultural trade data (i.e.: imports and exports) by country over different agricultural crops. Although, trade information for all crops is not available, there are some data collected independently by regional organizations (i.e. UNICA in the case of sugarcane). This information will be analyzed in order to determine what proportion of soy and sugarcane production is for domestic use rather than exports. Objective 3: Examine the physiographic context and ecosystem impacts of the crop expansion I will combine the spatial crop data developed in objective 1 with spatially-explicit data on physiography and ecosystems in Brazil, to analyze the physiographic context of new crop expansion as well as the ecosystem impacts. For this particular objective I will collect spatial datasets such as: soils (FAO/UNESCO; IBGE), climate (TRMM), vegetation (IBGE), agro ecological zones and infrastructure (IBGE; CIAT). METHODSMethods for Objective 1: Geographic information systems (GIS) will be used to examine the changing spatial distribution of crops in Brazil since 1990 to 2005. This will be accomplished through the following activities: Compile sub-national crops statistics from IBGE Combine tabular statistics with administrative boundaries using GIS Perform spatio-temporal analysis of change in crop distribution from 1990 to 2005 The analysis of changing crop distribution will include the following: Changes in the spatial distribution of dominant crops from 1990 to 2005 Absolute and relative changes of different crops during 1990-2005. Spatial analysis of which crops are replacing other crops or expanding into new land. The tabular statistics database from IBGE-SIDRA include information pertaining to planted area, harvested area and the value of production for 31 seasonal crops (subsistence, traditional, and export) reported by each of the 5563 Brazilian municipalities collected from 1990 to 2005. This tabulated data will then be combined with map units corresponding to administrative boundaries using GIS to create a time series map for each period (1990, 1995, 2000, and 2005). The following variables will be created: i) Changes in dominant crops: The harvested area of each crop will be compared in each municipality in order to identify which is the predominating crop, which crops are increased most, and where the changes have been. ii) Changes in distribution of specific crops: Once the crops greatest in area have been identified, it is necessary to carry out different analysis to identify those crops undergoing changes in distribution for 1990, 1995, 2000 and 2005. This analysis include:
absolute change in crop harvested area percentage of change of total harvested area Absolute change in harvested area expressed as a percentage of total harvested area. iii) Analysis of whether soybean and sugarcane are replacing other crops or expanding into new areas. This issue will be analyzed in order to identify whether there are crop changes at the expense of other crops, or if crop changes are causing clearing of forest or other natural ecosystems. For this analysis it is necessary to use variable representing ecosystems as well as natural and planted pastures. Methods for Objective 2: Brazil’s export data from FAOSTAT and UNICA will be compiled for soybean and sugarcane products such as soy oil, soy meal, raw sugar, refined sugar and alcohol for the time period of 1990 to 2005. Available statistical information on bilateral trade will be compiled for different crops and the proportion of crop production, for example soybean and sugarcane, destined for domestic consumption versus exports will be determined. The compiled trade statistics will help us better understand the socioeconomic issues that have triggered the expansion of the agricultural frontier in Brazil. This information contains import and export data from different crops corresponding to the period 1990-2005 per country. The preliminary analysis focused on two of Brazil’s major export crops: soybean and sugarcane. Trade data will be compiled for sugarcane and soybean and each of their products, for example soy oil, soy meal, raw sugar, refined sugar, and alcohol. In most cases, information is only available on the exports and imports of each product per country. If data on the proportion used for domestic consumption are not available for each of these crops, it can be calculated from production data by using the following formula: Domestic consumption = production – exports To make the above calculation, information will be collected to estimate the amount of total crop production required to produce the reported quantity of processed product (e.g., kg of sugarcane production required to produce 1 kg of refined sugar). Methods for Objective 3: Land use has an impact on ecosystems and this impact will be analyzed by building different scenarios that can help identify the main ecosystems affected by crop expansion. This objective involves four activities: (1) Compilation of spatial physiographic data such as climate, soils, topography, ecosystems, vegetation, and infrastructure. (2) Development of a spatial database of agro-ecological zones for Brazil. (3) Spatial analysis to determine the physiographic context and the agro-ecological zones in which the crops have expanded. (4) Spatial analysis to determine the ecosystems that have suffered the greatest impact of crop expansion. Results obtained in preliminary analyses will be combined with physiographic information such as: Soils from FAO/UNESCO with a spatial resolution of 1 X 1 degree lat/long (5 kms), soils from EMBRAPA/IBGE with 2929 map units19 which contain 37 Brazilian soil classification systems. Climate TRMM (Tropical Measuring Mission) with monthly precipitation data at 0.25 degree (30 kms) spatial resolution. Infrastructure from IBGE, CIAT with information about road type characteristics: primary roads, paved, unpaved, railroads and navigable rivers. Vegetation from IBGE of 2004 divided into 12 vegetation classes. Agro ecological zones Spatial data may present different levels of quality and resolution and therefore must be standardized to produce reliable information. This approach allows the generation of new maps that show the spatial distribution, types of change, and ecosystems affected by crop expansion over different periods (1990, 1995, 2000 and 2005). Furthermore, different scenarios can be constructed to identify those ecosystems that would be most affected by this expansion. Download 350.04 Kb. Share with your friends:
|