Lawson Connor Source Confirmed
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Assistant Professor
University of Arkansas at Fayetteville
faculty
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Biography and Research Information
OverviewAI-generated summary
Lawson Connor's research investigates the economic and policy drivers of agricultural practices, with a particular focus on soil health and crop insurance. He has published work examining the relationship between crop insurance participation and the adoption of cover crops, utilizing county-level data. Connor has also explored remote sensing methodologies for identifying cover crops and analyzing crop rotations, contributing to the rapid generation of data in agricultural studies. His work has also addressed the actuarial implications of prevented planting coverage and the economic effects of crop insurance on agricultural loan delinquencies. Additionally, Connor has investigated the influence of local cultural climate on minority farmer and rancher delinquency rates, drawing on Farm Service Agency data. He has collaborated with researchers from the University of Arkansas at Fayetteville, including Michael P. Popp, Zobaer Ahmed, and Lawton Lanier Nalley, as well as V. Steven Green from Arkansas State University.
Metrics
- h-index: 5
- Publications: 28
- Citations: 129
Selected Publications
- Satellite Remote Sensing Reveals Voluntary Cover-Crop Adoption and Crop-Rotation Hotspots in the Mississippi Alluvial Plain (2025) DOI
- Climate-driven doubling of U.S. maize loss probability: Interactive simulation with neural network Monte Carlo (2025) DOI
- Economic and Policy Drivers of Climate-Smart Soil Health Practices in the United States (2025) DOI
- Determinants of Market Participation among Milk Producers in Kyrgyzstan (2025) DOI
- Actuarial implications of prevented planting coverage (2024) DOI
- Diversified crop rotations mitigate agricultural losses from dry weather. (2024) DOI
- Winter-time cover crop identification: A remote sensing-based methodological framework for new and rapid data generation (2023) DOI
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