Nelson B. Villoria

Green Revolution research saved an estimated 18 to 27 million hectares from being brought into agricultural production

New estimates of the impacts of germplasm improvement in the major staple crops between 1965 and 2004 on global land-cover change are presented, based on simulations carried out using a global economic model (Global Trade Analysis Project Agro-Ecological Zone), a multicommodity, multiregional computable general equilibrium model linked to a global spatially explicit database on land use. We estimate the impact of removing the gains in cereal productivity attributed to the widespread adoption of improved varieties in developing countries. Here, several different effects—higher yields, lower prices, higher land rents, and trade effects—have been incorporated in a single model of the impact of Green Revolution research (and subsequent advances in yields from crop germplasm improvement) on land-cover change. Our results generally support the Borlaug hypothesis that increases in cereal yields as a result of widespread adoption of improved crop germplasm have saved natural ecosystems from being converted to agriculture. However, this relationship is complex, and the net effect is of a much smaller magnitude than Borlaug proposed. We estimate that the total crop area in 2004 would have been between 17.9 and 26.7 million hectares larger in a world that had not benefited from crop germplasm improvement since 1965. Of these hectares, 12.0–17.7 million would have been in developing countries, displacing pastures and resulting in an estimated 2 million hectares of additional deforestation. However, the negative impacts of higher food prices on poverty and hunger under this scenario would likely have dwarfed the welfare effects of agricultural expansion.

Geography Matters: International Trade Patterns and the Indirect Land Use Effects of Biofuels

This article investigates the relationship between international trade patterns and the global distribution of coarse grain production responses to market developments in the United States. Our null hypothesis is that world markets are fully integrated, rendering the geographic persistence of bilateral trade flows irrelevant in the global production response to a change in U.S. prices. The alternative hypothesis allows price transmission to vary along with the intensity of competition among countries in specific markets. Using data from 1975 to 2002, we reject the null hypothesis. Our work has direct implications for the analysis of the global land use impacts of biofuel mandates. Copyright 2011, Oxford University Press.

GTAP-HET: Introducing Firm Heterogeneity into the GTAP Model

Computable General Equilibrium (CGE) models incorporating firm heterogeneity can overcome the shortcomings of traditional Armington-based models in explaining changes in productivity and variety in the wake of reduced trade costs. In this paper, we present a new modeling framework where the firm heterogeneity theory of Melitz is introduced into the Global Trade Analysis Project (GTAP) model and calibrated to the GTAP 8 Data Base. The new mechanisms in the model are demonstrated in a stylized scenario with 3 regions (USA, Japan and the Rest of the World) and 2 sectors (manufacturing and non-manufacturing) where the elimination of tariffs levied by Japan on the import of US manufacturing goods is examined. Results are compared with those under monopolistic competition motivated by Krugman and under perfect competition motivated by Armington. The firm heterogeneity model incorporates endogenous variety, scale, productivity, and fixed cost effects into welfare change in addition to the traditional allocative efficiency and terms of trade effects. We observe that these effects are significant sources of welfare change. GTAP-HET presents the first GTAP implementation of firm heterogeneity. It is a powerful tool for policy analysis with improved abilities in tracing out productivity changes and entry/exit of firms following trade liberalization scenarios.

iData: a community geospatial data sharing environment to support data-driven science

With the advent of XSEDE, the national cyberinfrastructure has evolved from a set of traditional HPC resources to a broader range of digital services. Science gateways, which serve as portals to scientific applications, have also evolved as researchers are dealing with rapidly expanding scientific datasets and the increasingly complex workflows. More and more gateways are being developed to support integrated services for running data-driven applications on HPC resources such as those on XSEDE. To facilitate this type of workflow, there is a pressing need for web-based data management systems that are easy to use, support data upload, sharing, access and management, and can be integrated with advanced computation and storage resources. More importantly such systems need to be accessible by users from the broad research and education communities. In this paper, we describe the design and implementation of iData, a web-based community data publishing and sharing system. iData supports both generic file-based data collections and several commonly used environmental data collection formats including time series, GIS vector and raster data. Integrated data processing, visualization and filtering capabilities are provided for these data formats. Currently iData can be downloaded and deployed in a HUBzero-based gateway, and we plan to make it available for non-HUBzero platforms in the future. We present two examples in which iData has been successfully used to support research collaboration in driNET and GEOSHARE projects.

Bring integrated GIS data and modeling capabilities into HUBzero platform

The rapid advancement in the collection of environmental data, geospatial analysis and modeling software calls for new GIS-enabled cyberinfrastructure (CI) capable of support large scale integrated data and modeling activities. Although the HUBzero platform is gaining popularity as a portal development framework for many science and engineering communities, it has limited success in earth and environmental science domains, mainly due to its lack of native support for large geospatial data management and GIS functionalities in the Rappture toolkit. In this paper, we describe our initial work on bringing integrated GIS data and modeling capabilities into the HUBzero platform. We describe the overall architecture of our CI solution which is scalable, extensible and portable to other gateway framework as well. Two prototype applications are presented as a proof-of-concept. Coupling the scalable GIS capabilities with a wealth of tools for user participation and community building on the HUBzero platform, we hope to help new science communities in utilizing this platform.

Downscaling of national crop area statistics using drivers of cropland productivity measured at fine resolutions

Despite substantial research and policy interest in pixel level cropland allocation data, few sources are available that span a large geographic area. The data used for much of this research are derived from complex modeling techniques that may include model simulation and other data processing. We develop a transparent econometric framework that uses pixel level biophysical measurements and aggregate cropland statistics to develop pixel level cropland allocation predictions. Such pixel level land use data can be used to investigate the impact of human activities on the environment. Validation exercises show that our approach is effective at downscaling cropland allocation to multiple levels of resolution.

R Meets GEMPACK for a Monte Carlo Walk

This paper discusses two R functions for reading the output of GEMPACK-based CGE models into R. We highlight the potential of coupling GEMPACK and R by conducting systematic sensitivity analysis of model results using Monte Carlo experiments. We also show how R can enhance the analysis of CGE results by allowing for formal hypothesis testing of the effects of policies which outcome depends on stochastic shocks.