Carbon farming is a set of land management practices that abate carbon emissions through carbon sequestration and emissions avoidance. The Australian Carbon Credit Unit scheme enables landholders to receive carbon credits for implementing carbon farming projects that use approved methods to reduce emissions relative to baseline practice. The most widely adopted methodology under this scheme is human induced regeneration, whereby a landholder implements land management changes to enable a forest to regrow. Here, we model the spatial diffusion of human induced regeneration projects in Australia between 2014 and 2022 using spatiotemporal data on project registrations and spatial data on the methodology’s economic feasibility. We find that spatial proximity to existing projects is a strong predictor of landholder adoption, conditional on the methodology’s average economic feasibility in the region. We also find that a region’s average economic feasibility is a relatively weak predictor of adoption, after accounting for landholder proximity to existing projects. The spatial dependency of the diffusion process has led to high levels of spatial concentration in Australia’s carbon supply, raising concerns regarding land use efficiency and carbon supply risk. We explore how to design carbon farming schemes to support wider uptake and produce better outcomes.

中文翻译：

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碳农业在澳大利亚的推广


碳农业是一套土地管理实践，通过固碳和避免排放来减少碳排放。澳大利亚碳信用单位计划使土地所有者能够获得碳信用额，以实施碳农业项目，这些项目使用批准的方法相对于基准实践减少排放。该计划中最广泛采用的方法是人为再生，即土地所有者实施土地管理变革以使森林重新生长。在这里，我们使用项目注册的时空数据和该方法的经济可行性的空间数据，对 2014 年至 2022 年间澳大利亚人类诱导再生项目的空间扩散进行了建模。我们发现，与现有项目的空间接近度是土地所有者采用的有力预测因素，这取决于该方法在该地区的平均经济可行性。我们还发现，在考虑了土地所有者与现有项目的接近程度后，一个地区的平均经济可行性对于采用的预测指标相对较弱。扩散过程的空间依赖性导致澳大利亚碳供应的空间高度集中，引发了对土地利用效率和碳供应风险的担忧。我们探索如何设计碳农业计划以支持更广泛的采用并产生更好的成果。