Skip to main content

Advertisement

SpringerLink
Log in

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

  • Original Paper
  • Published:
Biological Invasions Aims and scope Submit manuscript

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 via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

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

  • 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 

  • 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 

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

    Google Scholar 

  • 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 

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

    Google Scholar 

  • 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

  • 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

    Article  CAS  PubMed  Google Scholar 

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

    Article  CAS  PubMed  Google Scholar 

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

    Article  Google Scholar 

  • 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

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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

    Google Scholar 

  • 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 

  • 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 

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

    Google Scholar 

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

    Google Scholar 

  • 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 

  • 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 

  • 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 

  • 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 

  • 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 

  • 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 

  • 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 

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

  • 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 

  • 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 

  • 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 

  • 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 

  • 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

    Article  CAS  Google Scholar 

  • 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 

  • 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 

  • 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 

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

    Google Scholar 

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

    Google Scholar 

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

    Article  Google Scholar 

  • 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 

  • 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 

  • 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

    Chapter  Google Scholar 

  • 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

  • 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/

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

    Google Scholar 

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

    Article  Google Scholar 

  • 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 

  • 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

  • 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 

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

    Book  Google Scholar 

  • 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 

  • 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 

  • 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 

  • 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 

  • 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 

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

    Article  Google Scholar 

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

    Article  PubMed  Google Scholar 

  • 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 

  • 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 

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

    Article  Google Scholar 

  • 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 

  • 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 

  • 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 

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

    Google Scholar 

  • 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 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

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

    Google Scholar 

  • 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 

  • 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 

  • 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 

  • 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 

  • 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 

  • 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 

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

    Google Scholar 

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

    Google Scholar 

  • 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 

  • 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 

  • 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 

  • 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 

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

    Article  CAS  PubMed  Google Scholar 

  • 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 

  • 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 

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

    Google Scholar 

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

    Google Scholar 

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

    Google Scholar 

  • 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 

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

    Google Scholar 

  • 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 

  • 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 

  • 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

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

    Article  Google Scholar 

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

    Book  Google Scholar 

  • 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

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

    Article  CAS  PubMed  Google Scholar 

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

    Book  Google Scholar 

  • 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

Authors and Affiliations

  1. Centre of Excellence for Biosecurity Risk Analysis, School of BioSciences, The University of Melbourne, Parkville, 3010, Australia

    Aaron J. Dodd & Mark A. Burgman

  2. Victorian Department of Economic Development, Jobs, Transport and Resources, 475 Mickleham Rd, Attwood, 3049, Australia

    Aaron J. Dodd & Nigel Ainsworth

  3. School of BioSciences, The University of Melbourne, Parkville, 3010, Australia

    Cindy E. Hauser & Michael A. McCarthy

Authors
  1. Aaron J. Dodd
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nigel Ainsworth
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Cindy E. Hauser
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Mark A. Burgman
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Michael A. McCarthy
    View author publications

    You can also search for this author in PubMed Google Scholar

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

Check for updates. 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

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10530-016-1335-7

Keywords

Search

Navigation