Industrial agriculture has extensive environmental and social costs, and efforts to create alternative farming systems are widespread if not yet widely successful. This study explored how a set of grain farmers and rotational graziers in Iowa transitioned to agroecological management practices. Our focus on the resources and strategies that farmers mobilized to develop opportunities for, and overcome barriers to, transitioning to alternative practices allows us to go beyond the existing literature focused on why farmers transition. We attend to both the (...) ecological and socioeconomic context of innovation by comparing processes of technical change in two contrasting regions of Iowa. Farmers cultivated farm-level biodiversity and enterprise diversity, developed new cognitive and psychological competencies, and overcame barriers to innovation by developing external network linkages with peers, knowledge organizations, and federal policies. Our research provides insights into how biophysical, cognitive, structural and market considerations can be integrated into research efforts that aim to make sense of innovation toward sustainable agriculture. (shrink)

A unifying framework for generalized multilevel structural equation modeling is introduced. The models in the framework, called generalized linear latent and mixed models, combine features of generalized linear mixed models and structural equation models and consist of a response model and a structural model for the latent variables. The response model generalizes GLMMs to incorporate factor structures in addition to random intercepts and coefficients. As in GLMMs, the data can have an arbitrary number of levels and can be highly unbalanced (...) with different numbers of lower-level units in the higher-level units and missing data. A wide range of response processes can be modeled including ordered and unordered categorical responses, counts, and responses of mixed types. The structural model is similar to the structural part of a SEM except that it may include latent and observed variables varying at different levels. For example, unit-level latent variables can be regressed on cluster-level latent variables. Special cases of this framework are explored and data from the British Social Attitudes Survey are used for illustration. Maximum likelihood estimation and empirical Bayes latent score prediction within the GLLAMM framework can be performed using adaptive quadrature in gllamm, a freely available program running in Stata. (shrink)

This paper examines structural barriers to the adoption of climate change mitigation practices and the evolution of a climate change ethic among American farmers. It examines how seed corn contracts in Michigan constrain the choices of farmers and allow farmers to rationalize the over-application of fertilizer and associated water pollution and greenhouse gas emissions. Seed corn contracts use a competitive “tournament” system where farmers are rewarded for maximizing yields. Interviews and a focus group were used to understand fertilizer over-application and (...) barriers to participating in a climate change mitigation program. Results indicate that farmers agree that they over-apply fertilizer but would be unlikely to participate in a mitigation program due to their contracts and lack of support from seed corn companies. Because only a few companies control access to the seed corn market, farmers feel they have few choices. Farmers rationalized their practices as their only option given the competitive nature of their contracts and blamed other sources of pollution. Despite increasing efforts to educate farmers about climate change, structural barriers will continue to constrain participation in mitigation efforts and the development of a climate change ethic. (shrink)

Attempts to understand farmer conservation behavior based on quantitative socio-demographic, attitude, and awareness variables have been largely inconclusive. In order to understand fully how farmers are making conservation decisions, 32 in-depth interviews were conducted in the Eagle Creek watershed in central Indiana. Coding for environmental attitudes and practice adoption revealed several dominant themes, representing multi-dimensional aspects of environmental attitudes. Farmers who were motivated by off-farm environmental benefits and those who identified responsibilities to others (stewardship) were most likely to adopt conservation (...) practices. Those farmers who focused on the farm as business and were most concerned about profitability were less likely to adopt practices. The notion of environmental stewardship in particular was found to be much more complex than the way it is traditionally measured in quantitative studies. The interplay between on-farm and off-farm benefits to practice adoption is an issue that quantitative studies largely do not address. This study seeks to increase understanding of farmers’ environmental attitudes and the connections to conservation behavior. (shrink)