in

Cost-effective surveillance of invasive species using info-gap theory

  • 1.

    Jenkins, P. T. Free trade and exotic species introductions. Conserv. Biol. 10, 300–302 (1996).

    Article 

    Google Scholar 

  • 2.

    Sharov, A. A. Bioeconomics of managing the spread of exotic pest species with barrier zones. Risk Anal. 24, 879–892 (2004).

    Article 

    Google Scholar 

  • 3.

    Lodge, D. M. et al. Biological invasions: Recommendations for U.S. policy and management. Ecol. Appl. 16, 2035–2054 (2006).

    Article 

    Google Scholar 

  • 4.

    Yemshanov, D. et al. Optimizing surveillance strategies for early detection of invasive alien species. Ecol. Econ. 162, 87–99 (2019).

    Article 

    Google Scholar 

  • 5.

    Hauser, C. E. & Mccarthy, M. A. Streamlining “search and destroy”: Cost-effective surveillance for invasive species management. Ecol. Lett. 12, 683–692 (2009).

    Article 

    Google Scholar 

  • 6.

    Gottwald, T. R., da Graça, J. V. & Bassanezi, R. B. Citrus Huanglongbing: The pathogen and its impact. Plant Health Prog. https://doi.org/10.1094/PHP-2007-0906-01-RV (2007).

    Article 

    Google Scholar 

  • 7.

    Anderson, D. P. et al. Bio-economic optimisation of surveillance to confirm broadscale eradications of invasive pests and diseases. Biol. Invasions 19, 2869–2884 (2017).

    Article 

    Google Scholar 

  • 8.

    Russell, J. C., Binnie, H. R., Oh, J., Anderson, D. P. & Samaniego-Herrera, A. Optimizing confirmation of invasive species eradication with rapid eradication assessment. J. Appl. Ecol. 54, 160–169 (2017).

    Article 

    Google Scholar 

  • 9.

    Moffitt, L. J., Stranlund, J. K. & Osteen, C. D. Robust detection protocols for uncertain introductions of invasive species. J. Environ. Manag. 89, 293–299 (2008).

    Article 

    Google Scholar 

  • 10.

    Knight, F. H. Risk, Uncertainty, and Profit (Houghton Mifflin Company, 1921).

  • 11.

    Ben-Haim, Y. Uncertainty, probability and information-gaps. Reliab. Eng. Syst. Saf. 85, 249–266 (2004).

    Article 

    Google Scholar 

  • 12.

    Johnson, D. R. & Geldner, N. B. Contemporary decision methods for agricultural, environmental, and resource management and policy. Annu. Rev. Resour. Econ. 11, 19–41 (2019).

    Article 

    Google Scholar 

  • 13.

    Baker, C. M. & Bode, M. Recent advances of quantitative modeling to support invasive species eradication on islands. Conserv. Sci. Pract. 3, e246. https://doi.org/10.1111/csp2.246 (2021).

    Article 

    Google Scholar 

  • 14.

    Bertsimas, D. & Sim, M. The price of robustness. Oper. Res. 52, 35–53 (2004).

    MathSciNet 
    Article 

    Google Scholar 

  • 15.

    Ben-Haim, Y. & Demertzis, M. Decision making in times of knightian uncertainty: An info-gap perspective. Economics 10, 1–29 (2016).

    Article 

    Google Scholar 

  • 16.

    Ben-Haim, Y. Management of invasive species: Info-gap perspectives. in Invasive Species: Risk Assessment and Management (eds. Robinson, A., Walshe, T., Burgman, M. A., Nunn, M.) 266–286 (Cambridge University Press, 2017).

  • 17.

    Davidovitch, L. et al. Info-gap theory and robust design of surveillance for invasive species: The case study of Barrow Island. J. Environ. Manag. 90, 2785–2793 (2009).

    Article 

    Google Scholar 

  • 18.

    Rout, T. M., Thompson, C. J. & McCarthy, M. A. Robust decisions for declaring eradication of invasive species. J. Appl. Ecol. 46, 782–786 (2009).

    Article 

    Google Scholar 

  • 19.

    Foxcroft, L. C. Developing thresholds of potential concern for invasive alien species: Hypotheses and concepts. Koedoe. https://doi.org/10.4102/koedoe.v51i1.157 (2009).

    Article 

    Google Scholar 

  • 20.

    Pitt, J. P. W. Modelling the Spread of Invasive Species Across Heterogeneous Landscapes. (Lincoln University, 2008).

  • 21.

    Mehta, S. V., Haight, R. G., Homans, F. R., Polasky, S. & Venette, R. C. Optimal detection and control strategies for invasive species management. Ecol. Econ. 61, 237–245 (2007).

    Article 

    Google Scholar 

  • 22.

    Mcdonald-madden, E., Peter, W. J. B. & Possingham, H. P. Making robust decisions for conservation with restricted money and knowledge. J. Appl. Ecol. 45, 1630–1638 (2008).

    Article 

    Google Scholar 

  • 23.

    Rout, T. M., Moore, J. L. & Mccarthy, M. A. Prevent, search or destroy? A partially observable model for invasive species management. J. Appl. Ecol. 51, 804–813 (2014).

    Article 

    Google Scholar 

  • 24.

    Yemshanov, D. et al. Robust surveillance and control of invasive species using a scenario optimization approach. Ecol. Econ. 133, 86–98 (2017).

    Article 

    Google Scholar 

  • 25.

    Rödder, D., Solé, M. & Böhme, W. Predicting the potential distributions of two alien invasive Housegeckos (Gekkonidae: Hemidactylus frenatus, Hemidactylus mabouia). North-West. J. Zool. 4, 236–246 (2008).

    Google Scholar 

  • 26.

    Hoskin, C. J. The invasion and potential impact of the Asian House Gecko (Hemidactylus frenatus) in Australia. Austral. Ecol. 36, 240–251 (2011).

    Article 

    Google Scholar 

  • 27.

    García-Díaz, P., Ross, J. V., Vall-llosera, M. & Cassey, P. Low detectability of alien reptiles can lead to biosecurity management failure: A case study from Christmas Island (Australia). NeoBiota 45, 75–92 (2019).

    Article 

    Google Scholar 

  • 28.

    Scott, J. K. et al. Zero-tolerance biosecurity protects high-conservation-value island nature reserve. Sci. Rep. 7, 772–779 (2017).

    ADS 
    Article 

    Google Scholar 

  • 29.

    Commonwealth Government of Australia. Approval—Gorgon Gas Development (EPBC Reference: 2008/4178). (2009).

  • 30.

    Jarrad, F. C. et al. Improved design method for biosecurity surveillance and early detection of non-indigenous rats. N. Z. J. Ecol. 35, 132–144 (2011).

    Google Scholar 

  • 31.

    Metlay, D. From tin roof to torn wet blanket: Predicting and observing ground water movement at a proposed nuclear waste site. in Prediction: Science, Decision Making, and the Future of Nature (eds. Sarewitz, D. R., Byerly, R., Pielke, R. A.). 276–319. (Island Press, 2000).

  • 32.

    Wintle, B. & Burgman, M. Expert Elicitation for Barrow Island Surveillance System Revision, Project Report. (2015).

  • 33.

    Vanderduys, E. & Kutt, A. Is the Asian house gecko, Hemidactylus frenatus, really a threat to Australia’s biodiversity?. Aust. J. Zool. 60, 361–367 (2013).

    Article 

    Google Scholar 

  • 34.

    McGinnis, S. M. & Stebbins, R. C. A Field Guide to Western Reptiles and Amphibians. 4th edn. (Houghton Mifflin Harcourt, 2018).

  • 35.

    Whittle, P., Jarrad, F., Edwards, K. & Mengersen, K. Design of the quarantine surveillance for non-indigenous species of invertebrates on Barrow Island. Rec. West. Aust. Mus. Suppl. 83, 113–130 (2013).

    Article 

    Google Scholar 

  • 36.

    Ben-Haim, Y. Info-gap Decision Theory: Decisions Under Severe Uncertainty. 2nd edn. (Academic Press, 2006).

  • 37.

    MathWorks. MATLAB R2018b. (MathWorks, 2018).

  • 38.

    Bogich, T. L., Liebhold, A. M. & Shea, K. To sample or eradicate? A cost minimization model for monitoring and managing an invasive species. J. Appl. Ecol. 45, 1134–1142 (2008).

    Article 

    Google Scholar 

  • 39.

    Epanchin-Niell, R. S., Haight, R. G., Berec, L., Kean, J. M. & Liebhold, A. M. Optimal surveillance and eradication of invasive species in heterogeneous landscapes. Ecol. Lett. 15, 803–812 (2012).

    Article 

    Google Scholar 

  • 40.

    Trebitz, A. S. et al. Early detection monitoring for aquatic non-indigenous species: Optimizing surveillance, incorporating advanced technologies, and identifying research needs. J. Environ. Manag. 202, 299–310 (2017).

    CAS 
    Article 

    Google Scholar 

  • 41.

    Molina, R., Horton, T., Trappe, J. & Marcot, B. Addressing uncertainty: How to conserve and manage rare or little-known fungi. Fungal Ecol. 4, 134–146 (2011).

    Article 

    Google Scholar 

  • Foraging dive frequency predicts body mass gain in the Adélie penguin

    Pleistocene allopatric differentiation followed by recent range expansion explains the distribution and molecular diversity of two congeneric crustacean species in the Palaearctic