Adaptive management improves decisions about where to search for invasive species

Tracy M. Rout, Cindy E. Hauser, Michael A. McCarthy, Joslin L. Moore

Research output: Contribution to journalArticleResearchpeer-review

1 Citation (Scopus)

Abstract

Invasive species managers must decide how best to allocate surveillance and control effort through space. Doing this requires the predicted location of the invasive species, and these predictions come with uncertainty. While optimal surveillance designs have been developed for many invasive species, few have considered uncertainty in species distribution and abundance. Adaptive management has long been recommended for managing natural systems under uncertainty, but has not yet been applied to searching for invasive species. We investigate whether an adaptive management approach can increase the number of individuals found and removed, as compared to a naïve allocation of search effort or “common sense” rules of thumb. We develop a simple illustrative model where search effort must be allocated to maximise plant removals across two sites in which species abundance is unknown. We tested the performance of both passive and active adaptive strategies through simulation. There are substantial benefits to employing an adaptive strategy, although the two forms of adaptive management performed similarly. The optimal active adaptive strategy is complex to calculate, whereas the passive strategy could be calculated for a large number of sites using widely accessible spreadsheet software. We therefore recommend the passive adaptive strategy for achieving approximately the same outcome while being much more practical to implement, facilitating application to much larger and more realistic search problems in a way that is accessible to managers.

Original languageEnglish
Pages (from-to)249-255
Number of pages7
JournalBiological Conservation
Volume212
Issue numberPart A
DOIs
Publication statusPublished - 1 Aug 2017

Keywords

  • Abundance estimation
  • Imperfect detection
  • Optimisation
  • Search effort
  • Surveys
  • Weeds

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