Management feasibility of established invasive plant species in Queensland, Australia: A stakeholders' perspective.

Managing and monitoring invasive alien species (IAS) is costly, and because resources are limited, prioritization decisions are required for planning and management. We present findings on plant pest prioritization for 63 established invader species of natural and grazing ecosystems of Queensland, Australia. We used an expert elicitation approach to assess risk (species occurrence, spread, and impact) and feasibility of control for each IAS. We elicit semi-quantitative responses from diverse expert stakeholders to score IAS on three management approaches (biocontrol, chemical and mechanical) in relation to cost, effectiveness and practicality, and incorporate uncertainty in expert inputs and model outputs. In the process, we look for promising management opportunities as well as seek general trends across species' ecological groups and management methods. Stakeholders were cautiously optimistic about the feasibility of managing IAS. Taking into consideration all factors, the overall feasibility of control was uncorrelated with the stakeholders' level of confidence. However, within individual management criterion, positive trend was observed for the same bivariate traits for chemical control, and negative trends for biocontrol and mechanical controls. Utility and confidence in IAS management options were in the order: chemical > biocontrol = mechanical, with practicality and effectiveness being the main driver components. Management feasibility differed significantly between IAS life forms but not between habitats invaded. Lastly, we combined IAS risk assessment and management feasibility scores to create a risk matrix to guide policy goals (i.e. eradication, spread containment, protection of sensitive sites, targeted control, site management, monitoring, and limited action). The matrix identifies promising species to target for each of these policy outcomes. Overall, our general approach illustrates (i) the importance of understanding the feasibility of IAS control actions and the factors that drive it, and (ii) demonstrates how quantifying management feasibility can be used to enhance traditional risk assessment rankings to improve policy outcomes.

Modelling seasonal habitat suitability for wide-ranging species: Invasive wild pigs in northern Australia.

Invasive wildlife often causes serious damage to the economy and agriculture as well as environmental, human and animal health. Habitat models can fill knowledge gaps about species distributions and assist planning to mitigate impacts. Yet, model accuracy and utility may be compromised by small study areas and limited integration of species ecology or temporal variability. Here we modelled seasonal habitat suitability for wild pigs, a widespread and harmful invader, in northern Australia. We developed a resource-based, spatially-explicit and regional-scale approach using Bayesian networks and spatial pattern suitability analysis. We integrated important ecological factors such as variability in environmental conditions, breeding requirements and home range movements. The habitat model was parameterized during a structured, iterative expert elicitation process and applied to a wet season and a dry season scenario. Model performance and uncertainty was evaluated against independent distributional data sets. Validation results showed that an expert-averaged model accurately predicted empirical wild pig presences in northern Australia for both seasonal scenarios. Model uncertainty was largely associated with different expert assumptions about wild pigs' resource-seeking home range movements. Habitat suitability varied considerably between seasons, retracting to resource-abundant rainforest, wetland and agricultural refuge areas during the dry season and expanding widely into surrounding grassland floodplains, savanna woodlands and coastal shrubs during the wet season. Overall, our model suggested that suitable wild pig habitat is less widely available in northern Australia than previously thought. Mapped results may be used to quantify impacts, assess risks, justify management investments and target control activities. Our methods are applicable to other wide-ranging species, especially in data-poor situations.