Factors affecting farmers' crop diversity decisions: an integrated approach

Sustainable cropping systems use crop diversity as a foundation to reduce the environmental impacts of agrichemicals and risks of pest and disease outbreaks. Although greater diversity in the agricultural landscape is an important goal, the decisions of individual farmers determine the diversity of crops used in each farming system. Therefore, it is essential to gain an understanding of important factors in farmers' decisions as part of any proposed solution to low crop diversity. Our objective was to develop and test an integrated socioeconomic model of farmers' decisions on crop rotations as an indicator of overall crop diversity. The model incorporated measures of farmers' attitudes, net household income, control over decisions, social norms, and regional location to address the social, economic, and environmental factors of crop diversity. Mail survey responses from 197 farmers from a western Corn Belt county in 1998 supplied the data for the analysis. Location had the strongest influence on crop diversity in the model, on the basis of a standardized beta statistic of 0.46 in the ordinary least squares regression analysis. Farmers in the region with the highest degree of sloping land had significantly higher crop diversity than farmers in the most productive, relatively flat area. Lower household net income and positive attitudes toward crop rotations were also associated with higher crop diversity. We believe social norms and control would exert more influence in uncertain decisions. The results of this study suggest that, to maintain and possibly expand crop diversity in the future, targeting farmers in sloping landscapes with positive attitudes toward rotations would be the best approach to focus economic incentives for diverse crop rotations and technical support from Extension. In any effort to support crop diversity greater than a typical corn-soybean rotation, it is also critical to preserve integrated forage/crop/livestock systems. Further adaptation and application of our behavioral model in other settings would help to better evaluate, understand, and target the integrated decisions people make relative to crop diversity.