Data from: User-friendly and evidence-based tool to evaluate probability of eradication of aquatic non-indigenous species
Drolet, David; Locke, Andrea; Lewis, Mark A.; Davidson, Jeff (2015), Data from: User-friendly and evidence-based tool to evaluate probability of eradication of aquatic non-indigenous species, Dryad, Dataset, https://doi.org/10.5061/dryad.1rh77
1. The gap between practitioners and conservation or environmental management science is difficult to bridge. Managers sometimes use limited scientific information in their decision-making process, mainly because they have little time to review primary literature before making a decision. Making data readily available to managers is expected to improve the overall efficiency of management interventions. Here we present an approach to develop user-friendly applications for evidence-based management and illustrate the concept by presenting a simple computer program designed to evaluate the probability of eradication of aquatic non-indigenous species. 2. We conducted a review of case studies that attempted to control aquatic non-indigenous species and used a statistical model to relate the outcome (eradication or non-eradication) to characteristics of the populations and interventions conducted. Based on a few key variables, the model returned accurate probabilities of eradication as evaluated with a Receiver Operating Characteristic curve and jackknife and cross-validation procedures. 3. We packaged the statistical model in a user-friendly computer program that can be used by managers to 1) rapidly calculate the probability of success of a planned intervention with associated uncertainty, 2) compare the success probabilities of different possible interventions, and 3) prioritize what information should be collected to increase the reliability of estimates. 4. Synthesis and applications. Our decision-support tool is easy to implement, statistically flexible, and could be used for any type of conservation or management intervention, given a sufficient number of case studies available in the literature. We recommend that scientists develop such tools whenever they conduct reviews of effectiveness of intervention. This is likely to result in greater use of data by practitioners, increased reliability of cost–benefit analyses, and an overall increase in efficiency in conservation and environmental management.