About

Dr. Uris Baldos is a faculty member associated with the Department of Agricultural Economics at Purdue University. His research focuses on issues related to farm policy, farmland markets, renewable energy, and rural community resilience. He has contributed to discussions on farmland market dynamics, renewable energy and farmland, and the evolving urban-rural divide, among other topics. Dr. Baldos is involved in the Farm Policy Study Group, where he presents on topics such as macro indicators of urban-rural dynamics and farmland market trends, indicating his active engagement in policy analysis and agricultural economics research.

Research topics

• Ecology
• Environmental science
• Geography
• Natural resource economics
• Computer Science
• Economics
• Environmental resource management
• Environmental economics
• Agronomy
• Agricultural economics

Selected publications

• Updates in assessing soil organic carbon and their implications for evaluating land use change emissions

  Environmental Research Communications · 2026-01-26

  articleOpen access

  Abstract Emissions from land use changes are relevant for environmental policy analysis. Since the late 1990s and early 2000s many of these analyses have examined induced land use changes (ILUC) from biofuel production and policy as well as their associated greenhouse gas (GHG) emissions. These studies have often used the Harmonized World Soil Data (HWSD) to evaluate the corresponding changes in soil organic carbon (SOC) as a part of their assessments. However, those modeling efforts that used this data set have not necessarily implemented its latest version, and therefore, their results may not represent the most recent available SOC data sources. As an example, the AEZ-EF model, which has been frequently used in assessing ILUC emissions, is using the oldest version of this data set. To improve the quality and accuracy of ILUC estimates, this paper creates a new global data set of SOC by combining the latest version of the HWSD (V.2.0) with newly available national soil maps for the USA and Australia. Using this new data set, we then calculate the average SOC for each land cover type (cropland, pasture, and forest) by country and by agro-ecological zones (AEZs). Furthermore, we revised AEZ-EF model to adopt the new SOC data by land types. Finally, the revised AEZ-EF model is used to assess ILUC emissions for a few biofuel pathways to demonstrate the extent to which the new SOC data may affect ILUC emissions. The results of this paper indicate that the newest version of the HWSD represents a lower level of SOC at the global scale compared to its older version. The results also show that the revised AEZ-EF model calculates relatively lower ILUC emissions for the examined pathways compared to its older version.

  PublisherDOI

• Exposure to compound climate hazards transmitted via global agricultural trade networks

  2025-03-14

  preprintOpen access

  Compound climate hazards, such as co-occurring temperature and precipitation extremes, substantially impact people and ecosystems. Internal climate variability combines with the forced global warming response to determine both the magnitude and spatial distribution of these events, and their consequences can propagate from one country to another via many pathways. We examine how exposure to compound climate hazards in one country is transmitted internationally via agricultural trade networks by analyzing a large ensemble of climate model simulations and comprehensive trade data of four crops (i.e. wheat, maize, rice and soya). Combinations of variability-driven climate patterns and existing global agricultural trade give rise to a wide range of possible outcomes in the current climate. In the most extreme simulated year, 20% or more of the caloric supply in nearly one third of the world’s countries are exposed to compound heat and precipitation hazards. Countries with low levels of diversification, both in the number of suppliers and the regional climates of those suppliers, are more likely to import higher fractions of calories (up to 93%) that are exposed to these compound hazards. Understanding how calories exposed to climate hazards are transmitted through agricultural trade networks in the current climate can contribute to improved anticipatory capacity for national governments, international trade policy, and agricultural-sector resilience. We recommend concerted effort be made toward merging cutting-edge seasonal-to-decadal climate prediction with international trade analysis in support of a new era of anticipatory Anthropocene risk management.

  PublisherDOI

• Development of GTAP version 11 Land Use and Land Cover database for years 2004, 2007, 2011, 2014 and 2017

  2025-01-28 · 9 citations

  article1st authorCorresponding

  This memorandum documents the development of the GTAP LULC v.11 database for years 2004, 2007, 2011, 2014 and 2017. In addition to using the GTAP v.11 Data Base (Aguiar et al., 2023) as starting point, the main differences between v.10 and v.11 GTAP LULC data consist of (1) updating the AEZ boundaries given length of growing periods and climate zones from FAO/IIASA GAEZ v.4 (Fischer et al., 2021) and (2) using latest data from FAOSTAT (FAO, 2023) on national land use and land cover. This update heavily relies on the methodology for creating GTAP LULC v.9 and v.10 which downscales national-level land cover crop production and harvested area statistics from FAOSTAT (FAO, 2023).

  PublisherDOI

• Demographic changes will shape planetary biodiversity

  The Science of The Total Environment · 2025-03-26 · 3 citations

  article
  PublisherDOI

• Exposure to compound climate hazards transmitted via global agricultural trade networks

  Environmental Research Letters · 2025-02-20 · 8 citations

  articleOpen access

  Abstract Compound climate hazards, such as co-occurring temperature and precipitation extremes, substantially impact people and ecosystems. Internal climate variability combines with the forced global warming response to determine both the magnitude and spatial distribution of these events, and their consequences can propagate from one country to another via many pathways. We examine how exposure to compound climate hazards in one country is transmitted internationally via agricultural trade networks by analyzing a large ensemble of climate model simulations and comprehensive trade data of four crops (i.e. wheat, maize, rice and soya). Combinations of variability-driven climate patterns and existing global agricultural trade give rise to a wide range of possible outcomes in the current climate. In the most extreme simulated year, 20% or more of the caloric supply in nearly one third of the world’s countries are exposed to compound heat and precipitation hazards. Countries with low levels of diversification, both in the number of suppliers and the regional climates of those suppliers, are more likely to import higher fractions of calories (up to 93%) that are exposed to these compound hazards. Understanding how calories exposed to climate hazards are transmitted through agricultural trade networks in the current climate can contribute to improved anticipatory capacity for national governments, international trade policy, and agricultural-sector resilience. Our results highlight the need for concerted effort toward merging cutting-edge seasonal-to-decadal climate prediction with international trade analysis in support of a new era of anticipatory Anthropocene risk management.

  PublisherDOI

• Adoption of improved crop varieties limited biodiversity losses, terrestrial carbon emissions, and cropland expansion in the tropics

  Proceedings of the National Academy of Sciences · 2025-02-03 · 12 citations

  articleOpen access1st authorCorresponding

  Research investments in crop improvements, including by national and international agricultural research centers, have made significant contributions to raising yields of staple food crops in developing countries. Although mostly intended to improve food security and rural incomes, innovations in crop production also have major implications for the environment. Building on the latest productivity estimates from historical crop improvements in developing countries and using a gridded (0.25 degrees) equilibrium model of global agriculture, we assess the impacts of improved crop varieties on cropland use, threatened biodiversity, and terrestrial carbon stocks over 1961–2015. We replicate a historical baseline and produce a counterfactual scenario which shows the impact of omitting productivity improvements from these technologies. The results show that higher crop productivity generally lowered commodity prices, which reduced incentives to expand cropland except in those areas where productivity gains outweighed price declines. The net global effect of technology adoption was to limit conversion of natural habitat to agricultural use, although it did cause cropland to expand in some areas. We estimate that adoption of improved crop varieties in developing countries saved on net 16.03 [95% CI, 12.33 to 20.89] million hectares worldwide. With more natural habitat preserved, around 1,043 [95% CI, 616 to 1,503] threatened animal and plant species extinctions were avoided over this period. In addition, net land use savings from the improved crop varieties resulted in avoided terrestrial greenhouse gas (GHG) emissions of around 5.35 [95% CI, 3.75 to 7.22] billion metric tons CO 2 equivalent retained in terrestrial carbon stocks.

  PublisherOA PDFDOI

• Local Groundwater Sustainability Policies and Global Spillovers

  2024-10-28 · 1 citations

  book-chapterOpen access

  Abstract The rapid depletion of US groundwater resources brings attention to the significance of groundwater governance. However, any such restrictions on groundwater withdrawals are likely to generate spillover effects, causing further environmental stresses in other locations and adding to the complexity of sustainability challenges. The goal of this study is to improve our understanding of the implications of growing global food demand for local sustainability stresses and the implications of local sustainability policies for local, regional, and global food production, land use, and prices. We employ Simplified International Model of agricultural Prices, Land use, and the Environment- Gridded version (SIMPLE-G) to disentangle the significance of remote changes in population and income for irrigation and water resources in the United States. Then, we examine the local-to-global impacts of potential US groundwater sustainability policies. We find that developments in international markets are significant, as more than half of US sustainability stresses by 2050 are caused by increased commodity demand from abroad. Furthermore, a US sustainable groundwater policy can cause overseas spillovers, thereby potentially contributing to environmental stresses elsewhere, even as groundwater stress in the United States is alleviated. These unintended consequences could include deforestation due to cropland expansion as well as degradation in water quality due to intensification of production in nontargeted areas.

  PublisherOA PDFDOI

• Model Validation: Comparing Gridded and Regional Simulations to Observations

  2024-10-28 · 1 citations

  book-chapterOpen accessSenior author

  Abstract Model validation is a critical step in ensuring the accuracy and reliability of model results and is challenging for emerging multi-scale geospatial models. This chapter focuses on the validation of the SIMPLE-G model, which involves economic decisions about land use and water withdrawals at the grid-cell level that are connected to global agricultural markets. The model must simulate complex processes to represent the complexities in observed changes in land-use patterns, which are the result of many mutually interconnected local, regional, and global drivers. Unfortunately, only a few of these models are validated, and validation techniques have been slower to advance than new model developments. In this chapter, we validate the SIMPLE-G model using various methods. We use benchmark replication, backcasting, sensitivity analysis, and uncertainty quantification. These methods help ensure that the model can replicate a base reference condition accurately, model structural processes correctly, identify important parameters, and determine sources of uncertainty in the results.

  PublisherOA PDFDOI

• Benchmark Data: Integrating Biophysical and Economic Information in a Consistent Geospatial Dataset

  2024-10-28

  book-chapterOpen accessSenior author

  Abstract A multiscale economic analysis requires global, regional, and local data and parameters. This chapter introduces the benchmark data required to describe the current status of human and environmental systems. The behavioral parameters that describe how the system responds to changes and shocks are described in Chap. 7 . The benchmark data include geospatial information on input usage and agricultural production as well as regional information about exports, imports, and food consumption in the reference year. After running a SIMPLE-G simulation, these values are expected to change in response to new economic conditions. We obtain these data from a variety of sources (e.g., international databases, satellite imagery, climate and hydrological simulations, and national censuses). These data are then processed and made consistent to produce gridded data that can be used within the model. This consistent, multiscale dataset allows researchers to better understand and predict the impact of certain changes on the human and environmental systems.

  PublisherOA PDFDOI

• Tackling Policy Leakage and Targeting Hot Spots Could Be Key to Addressing the “Wicked” Challenge of Nutrient Pollution from Corn Production in the United States

  2024-10-28

  book-chapterOpen access

  Abstract Reducing nutrient loss from agriculture to improve water quality requires a combination of management practices. However, it has been unclear what pattern of mitigation is likely to emerge from different policies, individually and combined, and what are the impacts on land use and farm returns at both local and national levels. We address this research gap by developing an integrated multiscale framework that evaluates alternative nitrogen loss management policies for corn production in the United States. This approach combines site- and practice-specific agroecosystem processes with a grid-resolving economic model to identify locations that can be prioritized to increase the economic efficiency of the policies. We find that regional measures, while effective at reducing nitrogen loss locally, may inadvertently displace corn production to areas where nitrogen fertilizer productivity is lower and nutrient loss rates are higher, thereby offsetting the overall effectiveness of the nutrient management strategy. This spatial spillover effect can, however, be mitigated by combining regional measures with broader nationwide policies. For instance, the combination of wetland restoration, split fertilizer application and a nitrogen loss tax could reduce nitrate nitrogen loading in the Mississippi River by 30%, with only a modest increase in corn prices (less than 2%).

  PublisherOA PDFDOI

Frequent coauthors

• Thomas W. Hertel

  96 shared

• Frances C. Moore

  University of California, Davis

  14 shared

• Iman Haqiqi

  Purdue University West Lafayette

  13 shared

• Keith O. Fuglie

  Economic Research Service

  12 shared

• Jing Liu

  Guangdong Ocean University

  11 shared

• L. C. Bowling

  10 shared

• Justin A. Johnson

  University of Minnesota

  10 shared

• Sadia Jame

  Purdue University West Lafayette

  7 shared

Education

• Doctorate, Agricultural Economics

  Purdue University

  2014

• Master of Science, Agricultural Economics

  Purdue University

  2009

• Bachelor of Science, Economics

  University of the Philippines Los Baños

  2005

Awards & honors

• James C. Snyder Memorial Lecture
• Purdue Ag Alumni Association AGEC Distinguished Ag Alumni