Storing carbon from the atmosphere in terrestrial sinks has been proposed as an important way to mitigate climate change and is a major focus in Australia's climate change policies. Mitigation by changing agricultural practices is seen as a promising way to achieve significant reductions in CO2 concentrations. Several policies therefore aim to stimulate farmers to adopt so-called 'carbon farming' practices. However, there is little information about farmers' ability and willingness to adopt carbon farming. We present a best-worst scaling model to analyse farmers' decisions about adopting climate change mitigating practices. Best-worst scaling data was collected through a survey amongst mixed crop-livestock farmers in Australia, to determine which carbon farming practices farmers would be most and least likely to adopt. Conditional logit models are estimated to assess how socio-demographic factors affect farmers' behaviour. Results suggest that farmers are most likely to adopt stubble retention and no-till cropping practices. Farmers were least likely to adopt biochar applications and tree plantations. Individual decisions were significantly influenced by respondents' opinions about climate change, and familiarity with carbon farming management. The model outcomes provide valuable inputs for future climate change abatement policies, by providing insights into the mitigation decision making process of landholders.
|Title of host publication||Intenational Environmental Modelling and Software Society|
|Place of Publication||United States|
|Publisher||International Environmental Modelling and Software Society|
|Publication status||Published - 2014|
|Event||7th International Congress on Environmental Modelling and Software - San Diego, United States|
Duration: 15 Jun 2014 → 19 Jun 2014
|Conference||7th International Congress on Environmental Modelling and Software|
|Period||15/06/14 → 19/06/14|
Kragt, M., Dumbrell, N., & Gibson, F. (2014). A best-worst scaling model of climate change abatement by Australian farmers. In Intenational Environmental Modelling and Software Society (Vol. 4, pp. 1914-1920). United States: International Environmental Modelling and Software Society.