Using management scenarios and a participatory approach to encourage model adoption in managing invasive species

Engaging stakeholders and encouraging community engagement is fundamental for adoption of model results. Engagement benefits from starting from model development and continuing through to model completion and roll-out. This is especially the case when managing invasive species, where a coordinated management strategy between stakeholders works best. We use a participatory approach that combines expert knowledge and spatial data in a Bayesian network to develop risk maps of potential threats. Of particular relevance is the inclusion of management scenarios that can be manipulated to determine the effects of different strategies and combinations of coordinated strategies. Scenarios are built on expert opinion, guided from years of experience in research and management of the invasive species under field conditions. We capture their knowledge and understanding of the study system allowing us to independently validate how the model and scenarios replicate reality. Stakeholders are trained to run scenarios themselves at field days to encourage community engagement. Model results are presented as maps that visualise risk after applying different management scenarios. Maps facilitate interpretation of model results in a spatial context relevant to local communities. Capturing impacts of species invasions by running scenarios specific to targeted community groups, such as land managers, allow for increased adoption when economic incentives are introduced. We demonstrate this with a case study using the European rabbit (Oryctolagus cuniculus), which is a serious agricultural pest in southern Queensland. We model the economic costs and effects of different rabbit management scenarios with the impacts of varying degrees of rabbit damage on different agricultural commodities. Our model allows end-users to choose the management strategies and the desired agricultural commodity, such as broccoli, spatially limited to the areas of suitable growth across the region. Model results show a distribution of costs for each modelled commodity scenario, giving end-users a range of costs unique to each agricultural region. Using ecological knowledge to understand the species' interaction within the environment and economic drivers to capture impact, our scenario modelling allows for immediate relevance to community users and ease of adoption with its participatory approach