Mapping Knowledge: GIS as a Tool for Spatial Modeling of Patterns of Warangal Cotton Seed Popularity and Farmer Decision-Making

In the Warangal district of Telangana, India, poor farmer knowledge, rapid seed turnover, and farmer conformist bias have resulted in faddish spikes in GM cotton seed popularity. We analyze space as a variable in 2715 seed choices by 136 farmers in two villages between 2004 and 2014, allowing us to model a decade of changes in farmers’ social learning across the village landscape. GIS analysis in combination with ethnographic research reveals shifting loci of seed certainty, in which different farmers were deemed worthy of emulation in different years. Over the study period, Warangal farmers were far more likely to emulate field neighbors’ cotton choices than they were to replant seeds, regardless of their crop yields. Rapid seed turnover and seed choice conformity was strongest among the comparatively poorer Scheduled Tribe farmers who live on the outskirts of the town proper. When the same farmers plant rice, their choices are more consistent through time and across space, suggesting that farmers learn about these two crops in very different ways.