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Society & Natural Resources
An International Journal
Volume 35, 2022 - Issue 3
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Perspectives

Why Do we Conserve?: Identifying Mechanisms in Agricultural Conservation Practice Adoption Decisions

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Pages 340-352 | Received 21 Jul 2020, Accepted 30 Nov 2021, Published online: 09 Jan 2022
 

Abstract

Recent reviews of the agricultural conservation adoption literature find few definitive and consistent predictors of adoption across practices. We propose that these inconsistencies may be the result of statistical models failing to account for psychological mechanisms. Such mechanisms can link farm and farmer characteristics to adoption by highlighting not just what is important, but why these characteristics matter. We illustrate a simple, but underutilized strategy exploring mediated explanations of cover crop adoption. Results suggest that when farm or farmer characteristics (e.g., farmer identity) are included with beliefs about practices (e.g., perceived practice feasibility), a mediated arrangement provides a more nuanced and consistent picture of influential motivations and barriers than simple linear models. This focus on belief-based mechanisms provides important insights into why different types of farms or farmers adopt conservation practices with implications for both practical interventions and future research.

Notes

1 There were some small differences for some variables however. Respondents (versus non-respondents) were more likely to have a nutrient management plan for their farm, more likely to think agriculture is not the main driver of algal blooms and less likely to think a good farmer minimized nutrient runoff into waterways suggesting that our sample may be somewhat less conservation minded. Of these only the last is a variable included in our analyses (it is a component of the conservationist ID scale).

2 We also originally included total farm income, however the large quantity of missing data made the planned analysis untenable. The income variable is also significantly correlated with the total farm size variable at around 0.7 suggesting that a considerable degree of the variance from income is likely captured in total farm size.

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