There is a lot of uncertainty about how we pick the best invasive species management strategies to improve the environment, local economy, and human well-being, as invasive species management involves complex and multidimensional challenges. Invasive species management on inhabited islands is especially challenging, often due to perceived socio-political risks and unexpected technical difficulties. Failing to incorporate local knowledge and local perspectives in the early stages of planning can compromise the ability of decision-makers to achieve long-lasting conservation outcomes. Hence, including local knowledge and accounting for subjective stakeholder perceptions is essential for invasive species management, yet this often remains unaddressed. To address this gap, we present an application of invasive species management based on structured decision-making, and the resource allocation tool INFFER, on Minjerribah-North Stradbroke Island (Australia). We assessed the cost-effectiveness of six management scenarios, co-developed with local land managers and community groups, aimed at preserving the environmental and cultural significance of the island by eradicating European red foxes and feral cats. We further conducted a survey eliciting local stakeholders’ perspectives regarding the significance of the Island, their perception of the benefits of the proposed management scenarios, funding requirements, technical feasibility of implementation, and socio-political risk. We found that the best decisions when the budget is low are less cost-effective than when the budget is high. The best strategy focusses on control of European red fox on Minjerribah. However, our results also highlight the need for more research on feral cat management. This work demonstrates how to use a structured decision support tool, like INFFER, to assess contesting management strategies, this is particularly important when stakeholders’ perceptions regarding management outcomes are heterogeneous and uncertain.
Mechanistic invasive species management models and their application in conservation