New publication: Carbon farming diffusion in Australia

Recently published CSIRO research explores the dynamics of how knowledge is shared using carbon farming in Australia as a case study

Carbon farming is a set of land management practices that sequester carbon in vegetation and soils or avoid emissions – reducing greenhouse gas emissions and improving the resilience and productivity of agricultural systems.

Through the Australian Carbon Credit Unit (ACCU) scheme, landholders who implement carbon farming projects using approved methods can receive carbon credits. The most widely adopted methodology under this scheme is human-induced regeneration, which requires landholder to implement land management changes that enable a forest to regrow.

Using publicly available spatio-temporal data, a research team from CSIRO’s Valuing Sustainability Future Science Platform (VS FSP) has modelled the spatial diffusion of human-induced regeneration (HIR) projects in Australia between 2014 and 2022. The resulting paper was published in Global Environmental Change.

“We wanted to explore how knowledge and information around carbon farming is shared among farmers,” explains Dr Bernardo Cantone, a Postdoctoral Fellow with the VS FSP who works on the Knowledge Commons for Sustainability project.

“By improving our understanding of how this knowledge is shared, it means CSIRO can help work out how to extend that to a broader audience for more impact.”

High levels of spatial concentration

Project register data from the Clean Energy Regulator, which details the geographical locations of HIR projects across Australia (Figure1), reveals that that registered projects occur in highly concentrated clusters.

“The driver for this research was that we wanted to understand why the projects are occurring in such clusters,” says Dr Cantone.

“Having a situation where the projects are highly spatially concentrated might not be desirable. Very highly concentrated areas of carbon farming leave the projects vulnerable to the risk of large-scale losses – whether that’s through fire, drought, climate change, tree diseases or a range of natural causes.”

While several previous studies have identified potential drivers of carbon farming adoption, there has been less work done on the relative effects of these drivers on the diffusion process.

Improving our understanding of the mechanisms driving the diffusion of carbon farming practices can inform the design of these programs to achieve desired outcomes – including their adoption across broader, more dispersed locations.

Predictors of landholder adoption of HIR: the impact of knowing adopters

Based on the literature on landholder uptake of carbon farming, the research team identified a number of variables as predictors to include in their modelling.

These were:

• Private economic benefit
• Knowing adopters
• Farm size
• Farmer demographics

Using the available data to model the diffusion process, the researchers found – as expected – that landholder adoption of HIR projects has tended to occur in land areas where it is economically feasible to participate in these projects.

But they also found that the registration of new HIR projects tends to be concentrated around the locations of existing HIR projects. In technical terms, spatial proximity to registered carbon farming projects has a large positive effect on a landholder’s participation in the registered carbon market.

This suggests that social learning and knowledge transfer from local peers is a key mechanism that drives market participation and adoption of carbon farming practices.

“We knew that social factors would be important, but we weren’t expecting them to be the main driver of adoption,” says Dr Cantone. “The analysis shows that proximity to other adopters is much more impactful than every other factor we looked at – even economic feasibility.”

Implications and future work

The research team did not have access to data that reveals what the specific social mechanisms are that allow the flow of knowledge between farmers.

However, knowing that spatial proximity to other adopters is the strongest driver of carbon farming adoption and diffusion is enormously valuable, and an important starting point for future research.

This new understanding can help decision makers to design carbon farming schemes in a way that supports wider uptake and produces better outcomes.

“We provide a number of suggestions in the paper for mechanisms to drive wider adoption of sustainable practices,” explains Dr Cantone. “That might include establishing local communities of practice for early adopters to share their experience, setting up demonstration farms, or making digital tools available to simplify the application process for landholders.”

“While carbon farming is the case study we have used in this paper, it is only one of many settings in Australia where we need to consider how knowledge is created and diffused,” continues Dr Cantone. “I think the study also makes a bigger contribution to the literature on technological adoption and new environmental practices – helping us understand how knowledge for sustainable practices is generated and shared.”

Author – Ruth Dawkins