Inferring invasive species abundance using removal data from management actions

摘要: Evaluation of the progress management programs for invasive species is crucial demonstrating impacts to stakeholders and strategic planning resource allocation. Estimates abundance before after activities can serve as a useful metric population programs. However, many methods estimating size are too labor intensive costly implement, posing restrictive levels burden on operational Removal models reliable method using data from removal exclusively, thus requiring no work in addition management. We developed Bayesian hierarchical model estimate accounting varying effort, used simulations assess conditions under which estimates obtained. applied this site-specific an species, feral swine (Sus scrofa), aerial gunning 59 site/time-frame combinations (480-19,600 acres) throughout Oklahoma Texas, USA. Simulations showed that were generally accurate when effective rates (removal rate total effort) above 0.40. abundances small (<50) needed accurately was considerably higher (0.70). Based our post-validation method, 78% site/time frame accurate. To use modeling framework it important have multiple removals (more than three) within time during demographic changes minimized (i.e., closed population; ≤3 months swine). Our results show probability improves with increased sampling effort (8+ flight hours across 3-month window best) rate. inverse relationship between inaccurate rates, we suggest auxiliary information could be collected included covariates (e.g., habitat effects, differences pilots) improve accuracy hence estimates.