Optimal spatial prioritization of control resources for elimination of invasive species under demographic uncertainty

Authors

Kim M. Pepin, USDA-APHIS, Fort CollinsFollow
Timothy J. Smyser, USDA APHIS/Wildlife Services/NWRCFollow
Amy J. Davis, USDA National Wildlife Research CenterFollow
Ryan S. Miller, USDA APHISFollow
Sophie McKee, USDA/APHIS/WS National Wildlife Research Center & Colorado State UniversityFollow
Kurt C. Vercauteren, APHISFollow
William Kendall, U.S. Geological Survey, Colorado State UniversityFollow
Chris Slootmaker, USDA APHIS Wildlife Services

ORCID IDs

Kim M. Pepin https://orcid.org/0000-0002-9931-8312

Amy J. Davis https://orcid.org/0000-0002-4962-9753

Date of this Version

2020

Citation

Ecological Applications, 30(6), 2020, e2126

Comments

© 2020 by the Ecological Society of America

Abstract

Populations of invasive species often spread heterogeneously across a landscape, consisting of local populations that cluster in space but are connected by dispersal. A fundamental dilemma for invasive species control is how to optimally allocate limited fiscal resources across local populations. Theoretical work based on perfect knowledge of demographic connectivity suggests that targeting local populations from which migrants originate (sources) can be optimal. However, demographic processes such as abundance and dispersal can be highly uncertain, and the relationship between local population density and damage costs (damage function) is rarely known. We used a metapopulation model to understand how budget and uncertainty in abundance, connectivity, and the damage function, together impact return on investment (ROI) for optimal control strategies. Budget, observational uncertainty, and the damage function had strong effects on the optimal resource allocation strategy. Uncertainty in dispersal probability was the least important determinant of ROI. The damage function determined which resource prioritization strategy was optimal when connectivity was symmetric but not when it was asymmetric. When connectivity was asymmetric, prioritizing source populations had a higher ROI than allocating effort equally across local populations, regardless of the damage function, but uncertainty in connectivity structure and abundance reduced ROI of the optimal prioritization strategy by 57% on average depending on the control budget. With low budgets (monthly removal rate of 6.7% of population), there was little advantage to prioritizing resources, especially when connectivity was high or symmetric, and observational uncertainty had only minor effects on ROI. Allotting funding for improved monitoring appeared to be most important when budgets were moderate (monthly removal of 13–20% of the population). Our result showed that multiple sources of observational uncertainty should be considered concurrently for optimizing ROI. Accurate estimates of connectivity direction and abundance were more important than accurate estimates of dispersal rates. Developing cost-effective surveillance methods to reduce observational uncertainties, and quantitative frameworks for determining how resources should be spatially apportioned to multiple monitoring and control activities are important and challenging future directions for optimizing ROI for invasive species control programs.