Predicting the cost of eradication for 41 Class 1 declared weeds in Queensland

The feasibility of state-wide eradication of 41 invasive plant taxa currently listed as ‘Class 1 declared pests’ under the Queensland Land Protection (Pest and Stock Route Management) Act 2002 was assessed using the predictive model ‘WeedSearch’. Results indicated that all but one species (Alternanthera philoxeroides) could be eradicated, provided sufficient funding and labour were available. Slightly less than one quarter (24.4%) (n = 10) of Class 1 weed taxa could be eradicated for less than $100 000 per taxon. An additional 43.9% (n = 18) could be eradicated for between $100 000 and $1M per taxon. Hence, 68.3% of Class 1 weed taxa (n = 28) could be eradicated for less than $1M per taxon. Eradication of 29.3% (n = 12) is predicted to cost more than $1M per taxon. Comparison of these WeedSearch outputs with either empirical analysis or results from a previous application of the model suggests that these costs may, in fact, be underestimates. Considering the likelihood that each weed will cost the state many millions of dollars in long-term losses (e.g. losses to primary production, environmental impacts and control costs), eradication seems a wise investment. Even where predicted costs are over $1M, eradication can still offer highly favourable benefit:cost ratios. The total (cumulative) cost of eradication of all 41 weed taxa is substantial; for all taxa, the estimated cost of eradication in the first year alone is $8 618 000. This study provides important information for policy makers, who must decide where to invest public funding.

Potential Distribution and Risk Assessment of an Invasive Plant Species: A Case Study of Hymenachne amplexicaulis in Australia

Given the limited resources available for weed management, a strategic approach is required to give the best bang for your buck. The current study incorporates: (1) a model ensemble approach to identify areas of uncertainty and commonality regarding a species invasive potential, (2) current distribution of the invaded species, and (3) connectivity of systems to identify target regions and focus efforts for more effective management. Uncertainty in the prediction of suitable habitat for H. amplexicaulis (study species) in Australia was addressed in an ensemble-forecasting approach to compare distributional scenarios from four models (CLIMATCH; CLIMEX; boosted regression trees [BRT]; maximum entropy [Maxent]). Models were built using subsets of occurrence and environmental data. Catchment risk was determined through incorporating habitat suitability, the current abundance and distribution of H. amplexicaulis, and catchment connectivity. Our results indicate geographic differences between predictions of different approaches. Despite these differences a number of catchments in northern, central, and southern Australia were identified as high risk of invasion or further spread by all models suggesting they should be given priority for the management of H. amplexicaulis. The study also highlighted the utility of ensemble approaches in indentifying areas of uncertainty and commonality regarding the species invasive potential.