Prioritizing plant eradication targets by re-framing the project prioritization protocol (PPP) for use in biosecurity applications

Abstract

The eradication of newly detected alien plant species is often prescribed, but rarely successful. Eradication programs fail for many reasons, however, for eradication to remain a cost-efficient management option it is clear that good decisions must be made at the outset. Here we re-frame the project prioritization protocol (PPP), a tool widely used in conservation biology, for use with the metrics typically used by a biosecurity agency. We then use existing methods to estimate the cost-efficiency of eradicating 50 hypothetical species incursions and compare the reduction in weed risk achieved by allocating resources using the PPP framework with the allocation based on risk ranking. By allocating resources to plant eradication programs using the PPP our analysis indicated that it is possible to improve the return on public expenditure by 25% compared to investing based solely on weed risk assessment scores. We also demonstrate how the cost-efficiency of the overall portfolio is influenced by the choice of planning horizon; including the decline in overall portfolio performance that arises when attempting to eradicate individual species too quickly. Finally, we discuss the logistical benefits to a management agency that arise from the use of a generic overarching framework such as the PPP. We believe that the PPP has considerable potential for use in biosecurity and can help focus attention on those species where management can make the biggest difference.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4

References

  1. ABARES (2008) Climatch, 1.0 edn. Australian Bureau of Agricultural and Resource Economics and Sciences. http://data.daff.gov.au:8080/Climatch/climatch.jsp

  2. Akçakaya HR, Ferson S, Burgman MA, Keith DA, Mace GM, Todd CR (2000) Making consistent IUCN classifications under uncertainty. Conserv Biol 14:1001–1013

    Article  Google Scholar 

  3. Akter S, Kompas T, Ward MB (2015) Application of portfolio theory to asset-based biosecurity decision analysis. Ecol Econ 117:73–85

    Article  Google Scholar 

  4. Beale R, Fairbrother J, Inglis A, Trebeck D (2008) One biosecurity: a working partnership. Commonwealth of Australia, Canberra

    Google Scholar 

  5. Blackburn TM et al (2014) A unified classification of alien species based on the magnitude of their environmental impacts. PLoS Biol 12:e1001850. doi:10.1371/journal.pbio.1001850

    Article  PubMed  PubMed Central  Google Scholar 

  6. Bomford M, O’Brien P (1995) Eradication or control for vertebrate pests? Wildl Soc Bull 23:249–255

    Google Scholar 

  7. Borchers HW (2015) adagio: Discrete and global optimization routines. R package version 0.6.1. The Comprehensive R Archive Network. http://CRAN.R-project.org/package=adagio

  8. Brook BW, O’Grady JJ, Chapman AP, Burgman MA, Akçakaya HR, Frankham R (2000) Predictive accuracy of population viability analysis in conservation biology. Nature 404:385–387

    CAS  Article  PubMed  Google Scholar 

  9. Brooks TM et al (2006) Global biodiversity conservation priorities. Science 313:58–61

    CAS  Article  PubMed  Google Scholar 

  10. Brunel S et al (2010) The EPPO prioritization process for invasive alien plants. EPPO Bull 40:407–422

    Article  Google Scholar 

  11. Bull J, Gordon A, Law E, Suttle K, Milner-Gulland E (2014) Importance of baseline specification in evaluating conservation interventions and achieving no net loss of biodiversity. Conserv Biol 28:799–809

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  12. Burgman MA (2015) Trusting judgements: how to get the best out of experts. Cambridge University Press, Cambridge

    Google Scholar 

  13. Caley P, Lonsdale WM, Pheloung PC (2006) Quantifying uncertainty in predictions of invasiveness, with emphasis on weed risk assessment. Biol Invasions 8:1595–1604

    Article  Google Scholar 

  14. Carwardine J, O’Connor T, Legge S, Mackey B, Possingham HP, Martin TG (2012) Prioritizing threat management for biodiversity conservation. Conserv Lett 5:196–204

    Article  Google Scholar 

  15. Commonwealth of Australia (1997) The national weeds strategy: a strategic approach to weed problems of national significance. Commonwealth of Australia, Canberra

    Google Scholar 

  16. Commonwealth of Australia (2007) The Australian weeds strategy: a national strategy for weed management in Australia. Commonwealth of Australia, Canberra

    Google Scholar 

  17. Daehler CC, Virtue JG (2010) Likelihood and consequences: reframing the Australian weed risk assessment to reflect a standard model of risk. Plant Prot Q 25:52–55

    Google Scholar 

  18. Dana ED, Jeschke JM, García-de-Lomas J (2014) Decision tools for managing biological invasions: existing biases and future needs. Oryx 48:56–63

    Article  Google Scholar 

  19. Darin GMS, Schoenig S, Barney JN, Panetta FD, DiTomaso JM (2011) WHIPPET: a novel tool for prioritizing invasive plant populations for regional eradication. J Environ Manag 92:131–139

    Article  Google Scholar 

  20. De Wit M, Crookes D, Van Wilgen B (2001) Conflicts of interest in environmental management: estimating the costs and benefits of a tree invasion. Biol Invasions 3:167–178

    Article  Google Scholar 

  21. Dodd AJ, Ainsworth N, Burgman MA, McCarthy MA (2015) Plant extirpation at the site scale: implications for eradication programmes. Divers Distrib 21:151–162. doi:10.1111/ddi.12262

    Article  Google Scholar 

  22. Downey PO, Johnson SB, Virtue JG, Williams PA (2010a) Assessing risk across the spectrum of weed management. CAB Rev Perspect Agric Vet Sci Nutr Nat Resour 5:1–15

    Google Scholar 

  23. Downey PO, Scanlon TJ, Hosking JR (2010b) Prioritizing weed species based on their threat and ability to impact on biodiversity: a case study from New South Wales. Plant Prot Q 25:111–126

    Google Scholar 

  24. Elith J (2013) Predicting distributions of invasive species. arXiv preprint arXiv:13120851

  25. Estévez RA, Walshe T, Burgman MA (2013) Capturing social impacts for decision-making: a multicriteria decision analysis perspective. Divers Distrib 19:608–616. doi:10.1111/ddi.12058

    Article  Google Scholar 

  26. Ferraro PJ, Pattanayak SK (2006) Money for nothing? a call for empirical evaluation of biodiversity conservation investments. PLoS Biol 4:e105

    Article  PubMed  PubMed Central  Google Scholar 

  27. Firn J, Martin T, Walters B, Hayes J, Nicol S, Chadès I, Carwardine J (2013) Priority threat management of invasive plant species in the Lake Eyre Basin. CSIRO, Canberra

    Google Scholar 

  28. Firn J, Martin TG, Chadès I, Walters B, Hayes J, Nicol S, Carwardine J (2015) Priority threat management of non-native plants to maintain ecosystem integrity across heterogeneous landscapes. J Appl Ecol 52:1135–1144

    Article  Google Scholar 

  29. Forsyth G, Le Maitre D, O’Farrell P, Van Wilgen B (2012) The prioritisation of invasive alien plant control projects using a multi-criteria decision model informed by stakeholder input and spatial data. J Environ Manag 103:51–57

    CAS  Article  Google Scholar 

  30. Game ET, Kareiva P, Possingham HP (2013) Six common mistakes in conservation priority setting. Conserv Biol 27:480–485

    Article  PubMed  PubMed Central  Google Scholar 

  31. Gordon DR, Onderdonk DA, Fox AM, Stocker RK (2008) Consistent accuracy of the Australian weed risk assessment system across varied geographies. Divers Distrib 14:234–242

    Article  Google Scholar 

  32. Guillera-Arroita G et al (2015) Is my species distribution model fit for purpose? Matching data and models to applications. Glob Ecol Biogeogr 24:276–292

    Article  Google Scholar 

  33. Harris S, Timmins SM (2009) Estimating the benefit of early control of all newly naturalised plants. New Zealand Department of Conservation, Wellington

    Google Scholar 

  34. Harris S, Brown J, Timmins S (2001) Weed surveillance—how often to search? Science for conservation. Department of Conservation, Wellington

    Google Scholar 

  35. Heikkilä J (2011a) Economics of biosecurity across levels of decision-making: a review. Agron Sustain Dev 31:119–138

    Article  Google Scholar 

  36. Heikkilä J (2011b) A review of risk prioritisation schemes of pathogens, pests and weeds: principles and practices. Agric Food Sci 20:15–28

    Article  Google Scholar 

  37. Hester SM, Cacho OJ, Panetta FD, Hauser CE (2013) Economic aspects of post-border weed risk management. Divers Distrib 19:580–589

    Article  Google Scholar 

  38. Hiebert RD (1997) Prioritizing invasive plants and planning for management. In: Luken JO, Thieret JW (eds) Assessment and management of plant invasions. Springer, New York, pp 195–212

    Google Scholar 

  39. Hijmans RJ, van Etten J (2013) raster: Geographic data analysis and modeling. R package version 2.1-37. The comprehensive R archive network, http://CRAN.R-project.org/package=raster

  40. Hijmans RJ, Phillips S, Leathwick J, Elith J (2013) dismo: Species distribution modeling. R package version 0.8-14/r510. The comprehensive R archive network, http://R-Forge.R-project.org/projects/dismo/

  41. Hosmer DW, Lemeshow S (1999) Applied survival analysis: regression modelling of time to event data. Wiley, New York

    Google Scholar 

  42. Howell CJ (2012) Progress toward environmental weed eradication in New Zealand. Invasive Plant Sci Manag 5:249–258

    Article  Google Scholar 

  43. Hulme PE (2012) Weed risk assessment: a way forward or a waste of time? J Appl Ecol 49:10–19. doi:10.1111/j.1365-2664.2011.02069.x

    Article  Google Scholar 

  44. IUCN (2012) IUCN Red list categories and criteria: version 3.1. International Union for Conservation of Nature. www.iucnredlist.org/technical-documents/categories-and-criteria. Accessed 2/12/2015

  45. Joseph LN, Maloney RF, Possingham HP (2009) Optimal allocation of resources among threatened species: a project prioritization protocol. Conserv Biol 23:328–338

    Article  PubMed  Google Scholar 

  46. Kleinbaum DG, Klein M (2012) Survival analysis: a self-learning text. Statistics for biology and health, vol 3. Springer, New York

    Google Scholar 

  47. Kumschick S et al (2012) A conceptual framework for prioritization of invasive alien species for management according to their impact. NeoBiota 15:69–100

    Article  Google Scholar 

  48. Leung B et al (2012) TEASIng apart alien species risk assessments: a framework for best practices. Ecol Lett 15:1475–1493

    Article  PubMed  Google Scholar 

  49. Mace GM et al (2008) Quantification of extinction risk: IUCN’s system for classifying threatened species. Conserv Biol 22:1424–1442

    Article  PubMed  Google Scholar 

  50. Mack RN, Lonsdale WM (2002) Eradicating invasive plants: hard won lessons for islands. In: Veitch CR, Clout M (eds) Turning the tide: the eradication of invasive species. IUCN SSC Invasive Species Specialist Group, Gland, pp 164–172

    Google Scholar 

  51. Martin TG, Burgman MA, Fidler F, Kuhnert PM, Low-Choy S, McBride M, Mengersen K (2012) Eliciting expert knowledge in conservation science. Conserv Biol 26:29–38

    Article  PubMed  Google Scholar 

  52. McCarthy MA, Thompson CJ, Garnett ST (2008) Optimal investment in conservation of species. J Appl Ecol 45:1428–1435

    Article  Google Scholar 

  53. McCarthy MA et al (2010) Resource allocation for efficient environmental management. Ecol Lett 13:1280–1289

    Article  PubMed  Google Scholar 

  54. McConnachie MM, van Wilgen BW, Ferraro PJ, Forsyth AT, Richardson DM, Gaertner M, Cowling RM (2016) Using counterfactuals to evaluate the cost-effectiveness of controlling biological invasions. Ecol Appl 26:475–483

    Article  PubMed  Google Scholar 

  55. McGeoch MA, Genovesi P, Bellingham PJ, Costello MJ, McGrannachan C, Sheppard A (2015) Prioritizing species, pathways, and sites to achieve conservation targets for biological invasion. Biol Invasions 18:299–314

    Article  Google Scholar 

  56. Metrick A, Weitzman ML (1998) Conflicts and choices in biodiversity preservation. J Econ Perspect 12:21–34

    Article  Google Scholar 

  57. Moon K, Blackman D, Brewer T (2015) Understanding and integrating knowledge to improve invasive species management. Biol Invasions 17:2675–2689. doi:10.1007/s10530-015-0904-5

    Article  Google Scholar 

  58. Moore JL, Runge MC, Webber BL, Wilson JRU (2011) Contain or eradicate? Optimizing the management goal for Australian acacia invasions in the face of uncertainty. Divers Distrib 17:1047–1059

    Article  Google Scholar 

  59. Nel J et al (2004) A proposed classification of invasive alien plant species in South Africa: towards prioritizing species and areas for management action: working for water. S Afr J Sci 100:53–64

    Google Scholar 

  60. Newsom LD (1978) Eradication of plant pests—con. Bull Entomol Soc Am 24:35–40

    Google Scholar 

  61. O’Grady JJ, Reed DH, Brook BW, Frankham R (2004) What are the best correlates of predicted extinction risk? Biol Conserv 118:513–520. doi:10.1016/j.biocon.2003.10.002

    Article  Google Scholar 

  62. Panetta FD (2009) Weed eradication—an economic perspective. Invasive Plant Sci Manag 2:360–368

    Article  Google Scholar 

  63. Panetta F (2015) Weed eradication feasibility: lessons of the twenty first century. Weed Res 55:226–238

    Article  Google Scholar 

  64. Panetta FD, Lawes R (2005) Evaluation of weed eradication programs: the delimitation of extent. Divers Distrib 11:435–442

    Article  Google Scholar 

  65. Panetta FD, Timmins S (2004) Evaluating the feasibility of eradication for terrestrial weed incursions. Plant Prot Q 19:5–11

    Google Scholar 

  66. Panetta FD, Csurhes S, Markula A, Hannan-Jones M (2011) Predicting the cost of eradication for 41 class 1 declared weeds in Queensland. Plant Prot Q 26:42–46

    Google Scholar 

  67. Pannell DJ, Gibson FL (2015) The environmental cost of using poor decision metrics to prioritize environmental projects. Conserv Biol 30:382–391. doi:10.111/cobi.12628

    Article  Google Scholar 

  68. Pheloung P, Williams PA, Halloy SR (1999) A weed risk assessment model for use as a biosecurity tool evaluating plant introductions. J Environ Manag 57:239–251

    Article  Google Scholar 

  69. Pluess T, Cannon R, Jarosik V, Pergl J, Pyšek P, Bacher S (2012) When are eradication campaigns successful? A test of common assumptions. Biol Invasions 14:1365–1378

    Article  Google Scholar 

  70. Possingham H, Andelman S, Noon B, Trombulak S, Pulliam H (2001) Making smart conservation decisions. In: Orians G, Soule M (eds) Conservation biology: research priorities for the next decade. Island Press, Washington, DC, pp 225–244

    Google Scholar 

  71. Possingham HP, Andelman SJ, Burgman MA, Medellín RA, Master LL, Keith DA (2002) Limits to the use of threatened species lists. Trends Ecol Evol 17:503–507. doi:10.1016/S0169-5347(02)02614-9

    Article  Google Scholar 

  72. R Core Team (2013) R: a language and environment for statistical computing vol 3.0. R Foundation for statistical computing, Vienna

    Google Scholar 

  73. Randall R (2000) Which are my worst weeds? A simple ranking system for prioritizing weeds. Plant Prot Q 15:109–115

    Google Scholar 

  74. Rejmánek M, Pitcairn MJ (2002) When is eradication of exotic pest plants a realistic goal? In: Veitch CR, Clout MN (eds) Turning the tide: the eradication of invasive species. IUCN SSC Invasive Species Specialist Group, Gland, pp 249–253

    Google Scholar 

  75. Robertson M et al (2003) A proposed prioritization system for the management of invasive alien plants in South Africa: research in action. S Afr J Sci 99:37–43

    Google Scholar 

  76. Rodrigues ASL, Pilgrim JD, Lamoreux JF, Hoffmann M, Brooks TM (2006) The value of the IUCN red list for conservation. Trends Ecol Evol 21:71–76. doi:10.1016/j.tree.2005.10.010

    Article  PubMed  Google Scholar 

  77. Speirs-Bridge A, Fidler F, McBride M, Flander L, Cumming G, Burgman M (2010) Reducing overconfidence in the interval judgments of experts. Risk Anal 30:512–523

    Article  PubMed  Google Scholar 

  78. Sutherland WJ, Burgman MA (2015) Use experts wisely. Nature 526:317–318

    CAS  Article  PubMed  Google Scholar 

  79. van Wilgen BW, Richardson DM (2014) Challenges and trade-offs in the management of invasive alien trees. Biol Invasions 16:721–734

    Article  Google Scholar 

  80. van Wilgen BW et al (2011) National-scale strategic approaches for managing introduced plants: insights from Australian acacias in South Africa. Divers Distrib 17:1060–1075

    Article  Google Scholar 

  81. Victorian Government (2010) Invasive plants and animals policy framework. DPI Victoria, Melbourne

    Google Scholar 

  82. Virtue J (2005) SA weed risk management guide. Department of Water Land and Biodiversity Conservation, Adelaide

    Google Scholar 

  83. Virtue JG (2010) South Australia’s weed risk management system. Plant Prot Q 25:90–94

    Google Scholar 

  84. Virtue JG, Bennett SJ, Randall RP (2004) Plant introductions in Australia: how can we resolve ‘weedy’ conflicts of interest. In: Sindel BM, Johnson SB (eds) Proceedings of the 14th Australian weeds conference, Wagga Wagga 2004. Weed Society of New South Wales, Sydney, pp 42–48

    Google Scholar 

  85. Virtue J et al (2006) HB 294:2006 National post-border weed risk management protocol. HB. Standards Australia, Sydney

    Google Scholar 

  86. Walshe T, Cole M, Grant N, Failing L, Long G, Gregory R (2012) A review of current methods and tools used by biosecurity agencies to estimate consequence impacts on primary production, amenity, and the environment. Australian Centre of Excellence for Risk Analysis, Melbourne

    Google Scholar 

  87. Weber J, Panetta FD, Virtue J, Pheloung P (2009) An analysis of assessment outcomes from eight years’ operation of the Australian border weed risk assessment system. J Environ Manag 90:798–807

    Article  Google Scholar 

  88. Weiss J, McLaren DA (2002) Victoria’s pest plant prioritisation process. In: Spafford Jacob H, Dodd J, Moore JH (eds) Proceedings of the 13th Australian weeds conference, Perth 2002. Plant protection society of Western Australia, pp 509–512

  89. Weitzman ML (1998) The Noah’s ark problem. Econometrica 66:1279–1298

    Article  Google Scholar 

  90. Wickham H (2009) ggplot2: elegant graphics for data analysis. Springer, New York

    Google Scholar 

  91. Wickham H (2012) scales: Scale functions for graphics. R package version 0.2.3. The Comprehensive R Archive Network. http://CRAN.R-project.org/package=scales

  92. Wilson KA, McBride MF, Bode M, Possingham HP (2006) Prioritizing global conservation efforts. Nature 440:337–340

    CAS  Article  PubMed  Google Scholar 

  93. Wittenberg R, Cock M (2001) Invasive alien species: a toolkit of best prevention and management parctices. GISP/CAB International, Wallingford

    Google Scholar 

  94. Yemshanov D, Koch FH, Lu B, Lyons DB, Prestemon JP, Scarr T, Koehler K (2014) There is no silver bullet: the value of diversification in planning invasive species surveillance. Ecol Econ 104:61–72

    Article  Google Scholar 

Download references

Acknowledgements

The authors would like to acknowledge Tom Kompas, Susie Hester, John Virtue, John Wilson and three anonymous reviewers for their helpful comments on earlier versions of this manuscript. The Australian Department of Agriculture and Water Resources provided access to their weed risk assessment database. This research was also supported by an Australian Research Council (ARC) Future Fellowship to M.A.M. and the ARC Centre of Excellence for Environmental Decisions. C.E.H was supported by the National Environmental Research Program Environmental Decisions Hub.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Aaron J. Dodd.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary material 1 (DOCX 21 kb)

Supplementary material 2 (DOCX 65 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Dodd, A.J., Ainsworth, N., Hauser, C.E. et al. Prioritizing plant eradication targets by re-framing the project prioritization protocol (PPP) for use in biosecurity applications. Biol Invasions 19, 859–873 (2017). https://doi.org/10.1007/s10530-016-1335-7

Download citation

Keywords

  • Cost–benefit analysis
  • Eradication feasibility
  • Expert elicitation
  • Invasive plants
  • Species distribution model
  • Weed risk assessment