Where money grows on trees: a socio-ecological assessment of land use change in an agricultural frontier

Integrating social or cultural data into ecological models is critical for understanding complex social-ecological systems. In this study, we used an interdisciplinary approach to identify, assess, and contextualize possible drivers of farmer decisions to use land for cannabis production and development shortly after adult use of cannabis was legalized in Josephine County, Oregon. First, we interviewed 14 cannabis farmers about their relationship with the land, their land use decision-making process, and reflections on the local industry. Second, we identified recurring responses in farmer interviews that highlighted perceived social and geographic drivers of cannabis land use distribution and change. Finally, we quantified these drivers as spatial covariates and evaluated their value as predictors in three models: 1) Logistic regression of cannabis land use distribution post-legalization (2016); 2) Logistic regression of cannabis development from pre- to post-legalization (2013/2014 to..., These datasets were generated from spatial data on cannabis agriculture in Josephine County, Oregon in 2013, 2014, and 2016, and spatial drivers identified based on interviews with cannabis farmers. Due to the sensitivity of the subject matter, spatial identifiers have been removed. These data are therefore only the code and csv files necessary to run the land use models associated with the paper entitled \"Where money grows on trees: a socio-ecological assessment of land use change in an agricultural frontier\" by Parker-Shames et al. 2023, R or R Studio (created in version 2021.09.1+372)