| Selecting which trees to retain and which to remove during thinning is one of the most crucial decisions in managing a production forest. This decision can directly impact the long-term success of a forest investment, affecting both yield potential and forest health. Whether the task is done with a chainsaw, chemically or with a mechanised machine, developing decision-making skills and supporting personnel to optimise yield potential are key skills that need to be developed by forest managers and workers alike. To support this, scientists at the Bioeconomy Science Institute | Scion have conducted research for the Forest Growers Research (FGR) Precision Silviculture Programme (PSP) to map the critical decisions undertaken in a thinning operation. These findings are now being applied to another PSP innovation, Scion’s virtual reality (VR) thinning training tool, offering a unique approach to developing crop tree selection and other critical thinning tasks in a fully immersive, virtual environment. |
Analysing real-world decision-making and integrating it into VR enables workers to effectively learn crop tree selection and other key tasks in a safe, controlled realistic virtual environment before applying them in the field.
The study identified enhancement opportunities for the VR platform to address other practical challenges, such as navigating dense regeneration, canopy variability and felling direction planning, while reinforcing safe practices and engaging thinning workers during early training.
The research team employed a variety of methods, including expert interviews and a focus group, followed by a thematic template analysis and a hierarchical task analysis, to identify the decision points, motor-manual thinning work and other tasks that define a typical day for a silvicultural thinner. The entire thinning sequence was mapped to pinpoint where experience and environmental uncertainty intersect.
Insights from expert thinners emphasised the dynamic nature of field-based judgment and highlighted the limitations of traditional training methods, which often fail to replicate the complexity and unpredictability of real-world thinning operations. The gamified nature of the VR training has been shown to not only to enhance engagement but reinforce safe practices, ultimately reducing the time needed for trainees to reach proficiency in high-risk roles. This approach represents a significant leap toward safer and more effective thinning operations. By embedding these insights into digital training tools, the forestry industry can improve both decision quality and operational efficiency, leading to better outcomes in precision silviculture.
