🤖 AI Summary
This study investigates how U.S. farmers’ crop choices reflect environmental adaptation and drive the evolution of regional agro-cultural traits. Leveraging county-level agricultural panel data from 1997 to 2022, it pioneers an integration of cultural evolution theory with empirical agricultural data within a computational social science framework to quantify how environmental returns shape crop portfolio selection. The analysis reveals that counties consistently adopt crop combinations that maximize local environmental fit and productivity, exhibiting clear long-term adaptive trajectories. These findings uncover a mechanism of cumulative cultural selection driven by environmental returns, offering novel evidence for understanding the evolutionary logic of human behavior in ecological adaptation.
📝 Abstract
Agricultural crops are a type of cultural trait and the way farmers of US counties select them can itself result in county-level cultural traits. Using real-world data from 1997 to 2022, we have developed a systematic framework to study the selective mechanisms behind these traits. Our findings indicate that environmental payoff-biased selection has driven counties to adopt traits that maximize their adaptability and yield within their specific environments. These empirical results align with existing theoretical literature [3,16]. Additionally, a clear long-term selective trend is evident, showing that US counties are gradually developing a specific set of more complex combinatorial traits, which provide greater payoffs by enhancing the farmers' environmental adaptability. This study serves as a strong case for empirically modeling the cultural evolutionary processes among US farmers.