Abstract

Adoption of temperate agroforestry practices generally remains limited despite considerable advances in basic science. This study builds on temperate agroforestry adoption research by empirically testing a statistical model of interest in native fruit and nut tree riparian buffers using technology and agroforestry adoption theory. Data were collected in three watersheds in Virginia’s ridge and valley region and used to test hypothesized predictors of interest in planting these buffers. Confirmatory factor analysis was used to verify independence of underlying latent measures. Multiple linear regression was used to model interest using the Universal Theory of Acceptance and Use of Technology (UTAUT). A second model that added agroforestry-specific predictors from Pattanayak et al. (Agrofor Syst 57:173–186, 2003) to UTAUT was tested and compared with the first. The first model was robust (Adj R 2 = 0.49) but was improved by adding agroforestry specific predictors (Adj R 2 = 0.57). Model generalizability was confirmed using double cross validation and normality indices. Social influence, risk expectancy, planting experience, performance expectancy, parcel size, and the interaction of gender and risk were significant in the final model. In addition, socioeconomic variables were used to characterize landowners according to their level of interest. Respondents with greater interest were newer owners that have higher incomes and are less active in farming. The result implies that future agroforesters may in large part consist of owners that have recently acquired land and manage their property more extensively with higher discretionary income and multiple objectives in mind.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.