Examining Agricultural Land Manager Willingness to Adopt Climate Change Mitigation in the UK

Farmer attitudes towards various mitigation measures for reducing GHG emissions were explored using an online survey hosted on JISC (2023). A range of question types were used, including Likert-scale, multiple choice, and free-text.
Various farmer characteristics were gathered, including farm sector, farm size, tenure status, number of FTEs, age of the participant, and broad location.
The dataset evidence differences in willingness adoption across the farm sector, especially highlighting poor willingness of farmers in livestock sector to adopt GHG mitigation measures. The dataset reflects evidence of limiting work time equivalent as a factor of willingness to adopt GHG mitigation measures. The dataset shows existing polarization in knowledge and adoption of GHG mitigation measures, while some farmers indicated 100% awareness and transition in land use and adoption of GHG mitigation measures, there seem to be farmers who do not know what net zero mitigation practices and its impact.
This work was conducted by the Countryside and Community Research Institute (CCRI, University of Gloucestershire) and Rothamsted Research.

The data were obtained through an online survey hosted on JISC (2023). A range of question types were used, including Likert-scale, multiple choice, and free-text.
The dataset variables are related to the farmer characteristics such as age, farming experience, Education, farmed area, Variables related to the mitigation measures and the farming activity, for example, anaerobic digestion, cropping, livestock, mixed farming.

The data resulting from the survey were critiqued by the research team, with any entries deemed as duplicates or inconsistent removed from the analysis. This resulted in 56 removals, leaving a remaining sample size of 201. The resulting data were largely quantitative as most participants did not enter answers in the optional free-text boxes. Microsoft Excel was used to undertake cross tabulations on the quantitative data, allowing comparisons to be made between farmer characteristics and answers to questions.