Biological Invasions

, Volume 16, Issue 6, pp 1273–1288 | Cite as

Meeting the challenge of quantitative risk assessment for genetic control techniques: a framework and some methods applied to the common Carp (Cyprinus carpio) in Australia

  • Keith R. Hayes
  • Brian Leung
  • Ronald Thresher
  • Jeffrey M. Dambacher
  • Geoffrey R. Hosack
Original Paper

Abstract

In Australia the European carp is widespread, environmentally damaging and difficult to control. Genetic control options are being developed for this species but risk-assessment studies to support these options have been limited. The key science challenge in this context is our limited understanding of complex and highly variable ecosystems. Hierarchical models are one way to approach this complexity and heterogeneity. These models treat the factors that determine risk as a joint probability distribution that can be factored into a series of simpler conditional distributions to allow Bayesian inference following observed outcomes. Designing a risk assessment around this approach, however, requires that the assessment endpoints (such as impacts on native species) are measurable, and that monitoring strategies are carefully designed and implemented in order that risk predictions are compared to outcomes. We therefore suggest that an evidence-based framework, supported by careful hazard analysis and quantitative risk assessment, and implemented within a stage-released protocol, is the safest way to move beyond the current emphasis on contained laboratory studies and qualitative risk assessments. We highlight impediments to this approach, and use the non-target impacts of daughterless carp in Australian billabongs as a case study to illustrate three methodological tools that not only provide solutions to some of these impediments but also encourage stakeholder participation in the risk assessment process.

Keywords

Genetic control Invasive fish Risk assessment Fault tree analysis Loop analysis Bayesian networks 

References

  1. Andow DA, Lovei GL, Arpaia S (2006) Ecological risk assessment for Bt crops. Nature Biotechnol 24:749–751PubMedCrossRefGoogle Scholar
  2. AquaBounty Technologies Incorporated (2010) Environmental Assessment for AquAdvantage® Salmon. Technical report, AquaBounty Technologies, Maynard, USAGoogle Scholar
  3. Arhonditsis GB, Papantou D, Zhang W, Perhar G, Massos E, Shi M (2008) Bayesian calibration of mechanistic aquatic biogeochemical models and benefits for environmental management. J Mar Syst 73:8–30CrossRefGoogle Scholar
  4. Bax NJ, Thresher RE (2009) Ecological, behavioral and genetic factors influencing the recombinant control of invasive pests. Ecol Appl 19:873–888PubMedCrossRefGoogle Scholar
  5. Bedford T, Cooke R (2001) Probabilistic risk analysis: foundations and methods. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  6. Bishop CM (2006) Pattern recognition and machine learning. Springer, New YorkGoogle Scholar
  7. Bjornstad O, Grenfell BT (2001) Noisy clockwork: time series analysis of population fluctuations in animals. Science 293:638–643PubMedCrossRefGoogle Scholar
  8. Burgman MA (2005) Risks and decisions for conservation and environmental management. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  9. Clark JS (2007) Models for ecological data: an introduction. Princeton University Press, PrincetonGoogle Scholar
  10. Clark JS, Gelfand AE (2006) A future for models and data in environmental science. Trends Ecol Evol 21:375–380PubMedCrossRefGoogle Scholar
  11. Colvin ME (2012) Impacts of nuisance species in a shallow lake: a systems modeling approach for evaluating restoration and management policies. PhD thesis, Iowa State University, Ames, USA. Available online. http://people.oregonstate.edu/colvinmi/pdfs/ClearLakeFinal.pdf. Accessed 04.10.12
  12. Cox LA (2008) What’s wrong with risk matrices? Risk Anal 28:497–512PubMedCrossRefGoogle Scholar
  13. Cox LA, Babayev D, Huber W (2005) Some limitations of qualitative risk rating systems. Risk Anal 25:651–662PubMedCrossRefGoogle Scholar
  14. Cressie N, Calder CA, Clark JS, ver Hoef JM, Wikle CK (2009) Accounting for uncertainty in ecological analysis: the strengths and limitations of hierarchical statistical modeling. Ecol Appl 19:553–570PubMedCrossRefGoogle Scholar
  15. Dall D, Neumann G (2004) Daughterless carp: an analysis of legal, technical and other risks to delivery. Technical report, Pest Animal CRC, Canberra, AustraliaGoogle Scholar
  16. Dambacher JM, Li HW, Rossignol PA (2002) Relevance of community structure in assessing indeterminacy of ecological predictions. Ecology 83:1372–1385CrossRefGoogle Scholar
  17. Dambacher JM, Li HW, Rossignol PA (2003) Qualitative predictions in model ecosystems. Ecol Model 161:79–93CrossRefGoogle Scholar
  18. Dambacher JM, Ramos-Jiliberto R (2007) Understanding and predicting effects of modified interactions through a qualitative analysis of community structure. Q Rev Biol 82:227–250PubMedCrossRefGoogle Scholar
  19. Devlin RH, D’Andrade M, Uh M, Biagi CA (2004) Population effects of GH transgenic Salmon are dependant upon food availability and genotype by environment interactions. Proc Nat Acad Sci 101:9303–9308PubMedCentralPubMedCrossRefGoogle Scholar
  20. Duan JJ, Lundgren JG, Naranjo S, Marvier M (2009) Extrapolating non-target risk of bt crops from laboratory to field. Biol Lett. doi:10.1098/rsbl.2009.0612
  21. Ellison AM (2004) Bayesian inference in ecology. Ecol Lett 7:509–520CrossRefGoogle Scholar
  22. Ferson S, Hajagos JG (2004) Arithmetic with uncertain numbers: rigorous and (often) best possible answers. Reliab Eng Syst Saf 85:135–152CrossRefGoogle Scholar
  23. Ferson S, Nelsen RB, Hajagos J, Berleant DJ, Zhang J, Tucker WT, Ginzburg LR, Oberkampf WL (2004) Dependence in probabilistic modeling, dempster-shafer theory and probability bounds analysis. Technical report, SAND2004-3072, Sandia National Laboratories, Albuquerque, New Mexico, USAGoogle Scholar
  24. Fisher N, Cribb J (2005) Monitoring community attitudes to using gene technology methods (daughterless carp) for managing common carp. Technical report, Pest Animal CRC, Canberra, AustraliaGoogle Scholar
  25. Fletcher R, Morison A, Hume D (1985) Effects of carp Cyprinus carpio L. on communities of aquatic vegetation and turbidity of waterbodies in the Lower Goulbourn river basin. Aust J Mar Freshw Res 36:311–327CrossRefGoogle Scholar
  26. Fung K, Yau P (2002) Daughterless carp technology business plan. Technical report. Report prepared for Murray-Darling Basin CommissionGoogle Scholar
  27. Gehrke PC, Brown P, Schiller CB, Moffatt DB, Bruce AM (1995) River regulation and fish communities in the Murray-Darling river system, Australia. Regul Rivers Res Manag 11:363–375CrossRefGoogle Scholar
  28. Gehrke PC, Clarke M, Matveev V, St Pierre S, Palmer A (2011) Carp control improves the health of aquatic ecosystems. Water 35:91–95Google Scholar
  29. Gehrke PC, St Pierre S, Matveev V, Clake M (2010) Ecosystem responses to carp population reduction in the Murray-Darling Basin. Technical report, Project MD923 Final Report to the Murray-Darling Basin Authority, Canberra, AustraliaGoogle Scholar
  30. Gilligan D, Rayner T (2007) The distribution, spread, ecological impacts and potential control of carp in the upper Murray River. Technical report, NSW Department of Primary Industries Fisheries Research Report 14, NSW Department of Primary Industries, Cronulla, NSWGoogle Scholar
  31. Gong Z, Maclean N, Devlin RH, Martinez R, Omitogun O, Estrada MP (2007) Gene construct and expression: information relevant for risk assessment and management, chapter 4. In: Kapuscinski AR, Hayes KR, Li S, Dana G (eds) Environmental risk assessment of genetically modified organisms, vol 3: methodologies for transgenic fish. CABI Publishing, OxfordshireGoogle Scholar
  32. Hayes K, Gregg P, Gupta V, Jessop R, Lonsdale M, Sindel B, Stanley J, Williams C (2004) Identifying hazards in complex ecological systems, Part 3: Hierarchical Holographic Model for herbicide tolerant oilseed rape. Environ BioSaf Res 3:1–20Google Scholar
  33. Hayes KR (2002a) Identifying hazards in complex ecological systems, Part 1: fault tree analysis for biological invasions. Biol Invasions 4:235–249CrossRefGoogle Scholar
  34. Hayes KR (2002b) Identifying hazards in complex ecological systems. Part 2: infection modes and effects analysis for biological invasions. Biol Invasions 4:251–261CrossRefGoogle Scholar
  35. Hayes KR (2011) Uncertainty and uncertainty analysis methods. Technical report, CSIRO Division of Mathematics, Informatics and Statistics, Hobart, Australia, 136 pp. Available online. http://www.acera.unimelb.edu.au/materials/core.html. Accessed 25.10.11
  36. Hayes KR, Kapuscinski AR, Dana G, Li S, Devlin RH (2007) Introduction to environmental risk assessment for transgenic fish, chapter 1. In: Kapuscinski AR, Hayes KR, Li S, Dana G (eds) Environmental risk assessment of genetically modified organisms, vol 3: methodologies for transgenic fish. CABI Publishing, Oxfordshire, pp 1–28Google Scholar
  37. Hoey P, Mitchell G, Krueger C (2008) An independent review of the freshwater products and strategies program of the invasives animals. Technical report, Murray Darling Basin CommissionGoogle Scholar
  38. Hosack GR, Hayes KR, Dambacher JM (2008) Assessing model structure uncertainty through an analysis of system feedback and bayesian networks. Ecol Appl 18:1070–1082PubMedCrossRefGoogle Scholar
  39. Hosack GRH, Li W, Rossignol PA (2009) Sensitivity of system stability to model structure. Ecol Model 220:1054–1062CrossRefGoogle Scholar
  40. Inland Fisheries Service (2009) Carp management program. Technical report. Annual report (2008–2009) of the Inland Fisheries Service, New Norfolk, Tasmania, AustraliaGoogle Scholar
  41. Kapuscinksi AR, Hard JJ, Paulson KM, Neira R, Ponniah A, Kamonrat W, Mwanja W, Fleming IA, Gallardo J, Devlin RH, Trisak J (2007) Approaches to assessing gene flow, chapter 5. In: Kapuscinski AR, Hayes KR, Li S, Dana G (eds) Environmental risk assessment of genetically modified organisms, vol 3: methodologies for transgenic fish. CABI Publishing, Oxfordshire, pp 112–150CrossRefGoogle Scholar
  42. Kapuscinski AR, Hayes KR, Li S, Dana G (eds) (2007) Environmental risk assessment of genetically modified organisms, vol 3: methodologies for transgenic fish. CABI Publishing, OxfordshireGoogle Scholar
  43. King AJ, Robertson AI, Healey MR (1997) Experimental manipulations of the biomass of introduced carp (Cyprinus carpio) in billabongs 1. Impacts on water-column properties. Mar Freshw Res 48:435–443CrossRefGoogle Scholar
  44. Kletz T (1999) HAZOP and HAZAN: identifying and assessing process industry hazards. Taylor and Francis, LondonGoogle Scholar
  45. Klir GJ, Folger TA (1988) Fuzzy sets, uncertainty and information. Prentice Hall, Englewood CliffsGoogle Scholar
  46. Koehn J, Brumley A, Gehrke P (2000) Managing the impact of carp. Technical report, Bureau of Rural Sciences, Canberra, Australia. Available online. http://www.daff.gov.au/__data/assets/pdf_file/0010/1193167/Impacts_of_Carpv1.pdf. Accessed 01.11.11
  47. Koehn JD (2004) Carp (Cyprinus carpio) as a powerful invader in Australian waterways. Freshw Biol 49:882–894CrossRefGoogle Scholar
  48. Kuhnert PM, Martin TG, Griffiths SP (2010) A guide to eliciting and using expert knowledge in Bayesian ecological models. Ecol Lett. doi:10.1111/j.1461-0248.2010.01477.x
  49. Kurle CM, Croll DA, Tershy BR (2008) Introduced rats indirectly change marine rocky intertidal communities from algae- to invertebrate-dominated. Proc Nat Acad Sci 105:3800–3804PubMedCentralPubMedCrossRefGoogle Scholar
  50. Kynn M (2008) The “heuristics and biases” bias in expert elicitation. J R Stat Soc Series A 171:239–264Google Scholar
  51. Lapidge KE (2003) Proceedings of the national carp control workshop. Technical report, Pest Animal Control CRC, Canberra, Australia. Available online. http://www.feral.org.au/wp-content/uploads/2010/03/CarpProc.pdf. Accessed 01.11.11
  52. Lever C (2002) Naturalized fishes of the world. Academic Press, New YorkGoogle Scholar
  53. Levins R (1974) The qualitative analysis of partially specified systems. Ann N Y Acad Sci 231:123–138PubMedCrossRefGoogle Scholar
  54. Lonsdale M, Hayes KR, Mahon R, Oakeshott J, Pech R, Williams K (2002) Internal csiro review of risks of the daughterless technology for the control of carp in australia. Technical report, CSIRO Executive, CSIRO, AustraliaGoogle Scholar
  55. Metcalf SJ, Dambacher JM, Hobday AJ, Lyle JM (2008) Importance of trophic information, simplification and aggregation error in ecosystem models. Mar Ecol Prog Ser 360:25–36CrossRefGoogle Scholar
  56. Morris WF, Doak DF (2002) Quantitative conservation biology. Sinauer Associates, SunderlandGoogle Scholar
  57. Novak M, Wootton JT, Doak DF, Emmerson M, Estes JA, Tinker MT (2011) Predicting community responses to perturbations in the face of imperfect knowledge and network complexity. Ecology 92:836–846PubMedCrossRefGoogle Scholar
  58. NRC (2002) Environmental effects of transgenic plants: the scope and adequacy of regulation. National Academies Press, Washington, DCGoogle Scholar
  59. Pascual MA, Kareiva P, Hilborn R (1997) The influence of model structure on conclusions about the viability and harvesting of serengti wildebeest. Conserv Biol 11:966–976CrossRefGoogle Scholar
  60. Pate-Cornell ME (1984) Fault trees vs event trees in reliability analysis. Risk Anal 4:177–186CrossRefGoogle Scholar
  61. Pearl J (1986) Fusion, propagation and structuring in belief networks. Artif Intell 29:241–288CrossRefGoogle Scholar
  62. Regan HM, Colyvan M, Burgman MA (2002) A taxonomy and treatment of uncertainty for ecology and conservation biology. Ecol Appl 12:618–628CrossRefGoogle Scholar
  63. Robertson AI, R HM, J KA (1997) Experimental manipulations of the biomass of introduced carp (Cyprinus carpio) in billabongs 2. Impacts on benthic properties and processes. Mar Freshw Res 48:445–454CrossRefGoogle Scholar
  64. Swirepik J (1999) Physical disturbance of Potamogeton tricarinatus and sediment by carp (Cyprinus carpio) in experimental ponds. Master’s thesis, University of Canberra, Canberra, AustraliaGoogle Scholar
  65. Wood SN, Thomas MB (1999) Super-sensitivity to structure in biological models. Proc R Soc Lond Series B Biol Sci 266:565–570CrossRefGoogle Scholar
  66. Woodbridge M (2008) Microbial risk analysis of foods, chapter qualitative risk assessment. ASM Press, Washington, DC, pp 1–26Google Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2013

Authors and Affiliations

  • Keith R. Hayes
    • 1
  • Brian Leung
    • 2
  • Ronald Thresher
    • 3
  • Jeffrey M. Dambacher
    • 1
  • Geoffrey R. Hosack
    • 1
  1. 1.CSIRO Mathematics, Informatics and StatisticsHobartAustralia
  2. 2.Department of BiologyMcGill UniversityMontrealCanada
  3. 3.CSIRO Marine and Atmospheric ResearchHobartAustralia

Personalised recommendations