Sustainability Science

, Volume 9, Issue 3, pp 247–261 | Cite as

Adaptation options for marine industries and coastal communities using community structure and dynamics

  • S. J. MetcalfEmail author
  • E. I. van Putten
  • S. D. Frusher
  • M. Tull
  • N. Marshall
Original Article


Identifying effective adaptation strategies for coastal communities dependent on marine resources and impacted by climate change can be difficult due to the dynamic nature of marine ecosystems. The task is more difficult if current and predicted shifts in social and economic trends are considered. Information about social and economic change is often limited to qualitative data. A combination of qualitative and quantitative models provide the flexibility to allow the assessment of current and future ecological and socio-economic risks and can provide information on alternative adaptations. Here, we demonstrate how stakeholder input, qualitative models and Bayesian belief networks (BBNs) can provide semi-quantitative predictions, including uncertainty levels, for the assessment of climate and non-climate-driven change in a case study community. Issues are identified, including the need to increase the capacity of the community to cope with change. Adaptation strategies are identified that alter positive feedback cycles contributing to a continued decline in population, local employment and retail spending. For instance, the diversification of employment opportunities and the attraction of new residents of different ages would be beneficial in preventing further population decline. Some impacts of climate change can be combated through recreational bag or size limits and monitoring of popular range-shifted species that are currently unmanaged, to reduce the potential for excessive removal. Our results also demonstrate that combining BBNs and qualitative models can assist with the effective communication of information between stakeholders and researchers. Furthermore, the combination of techniques provides a dynamic, learning-based, semi-quantitative approach for the assessment of climate and socio-economic impacts and the identification of potential adaptation strategies.


Climate change Qualitative modelling Bayesian belief network Fisheries Socio-economic Stakeholder input 



This research was funded by the Fisheries Research and Development Corporation (FRDC) and the Department of Climate Change and Energy Efficiency. Special thanks go to all the community participants for their valuable contributions. We would also like to thank Jeff Dambacher and the anonymous referees for their useful comments and suggestions.


  1. Adger WN, Arnell NW, Tompkins EL (2005) Successful adaptation to climate change across scales. Glob Environ Change 15:77–86CrossRefGoogle Scholar
  2. Adger WN, Dessai S, Goulden M, Hulme M, Lorenzoni I, Nelson DR, Naess LO, Wolf J, Wreford A (2009) Are there social limits to adaptation to climate change? Clim Change 93:335–354. doi: 10.1007/s10584-008-9520-z CrossRefGoogle Scholar
  3. Allison EH (2001) Big laws, small catches: global ocean governance and the fisheries crisis. J Int Dev 13:933–950CrossRefGoogle Scholar
  4. Aslin HJ, Byron IG (2003) Community perceptions of fishing: implications for industry image, marketing and sustainability. Fisheries Research and Development Corporation. Project No. 2001/309. Available online at:
  5. Australian Bureau of Statistics (ABS) (2011) Themes: community profilesGoogle Scholar
  6. Bassi AM (2009) Analyzing the role of integrated, dynamic, national development planning models to support policy formulation and evaluation. In: Proceedings of the 3rd OECD World Forum on “Statistics, knowledge and policy”: charting progress, building visions, improving life, Busan, Korea, October 2009. Available online at:
  7. Berkhout F, Hertin J (2000) Socio-economic scenarios for climate impact assessment. Glob Environ Change 10(3):165–168CrossRefGoogle Scholar
  8. Berkhout F, Hertin J, Jordan A (2001) Socio-economic futures in climate change impact assessment: using scenarios as ‘learning machines’. Tyndall Centre Working Paper No. 3, University of East Anglia, UKGoogle Scholar
  9. Bodini A, Ricci A, Viaroli P (2000) A multimethodological approach for the sustainable management of perifluvial wetlands of the Po River (Italy). Environ Manage 26:59–72CrossRefGoogle Scholar
  10. Cai W, Shi G, Cowan T, Bi D, Ribbe J (2005) The response of the Southern Annular Mode, the East Australian Current, and the southern mid-latitude ocean circulation to global warming. Geophys Res Lett 32(23):L23706–L23710CrossRefGoogle Scholar
  11. Cheung WWL, Lam VWY, Sarmiento JL, Kearney K, Watson REG, Zeller D, Pauly D (2010) Large-scale redistribution of maximum fisheries catch potential in the global ocean under climate change. Glob Change Biol 16:24–35CrossRefGoogle Scholar
  12. Cinner JE, McClanahan TR, Graham NAJ, Daw TM, Maina J, Stead SM, Wamukota A, Brown K, Bodin Ö (2011) Vulnerability of coastal communities to key impacts of climate change on coral reef fisheries. Glob Environ Change 22(1):12–20CrossRefGoogle Scholar
  13. Dambacher JM, Li HW, Rossignol PA (2002) Relevance of community structure in assessing indeterminacy of ecological predictions. Ecology 83:1372–1385CrossRefGoogle Scholar
  14. Dambacher JM, Luh HK, Li HW, Rossignol PA (2003) Qualitative stability and ambiguity in model ecosystems. Am Nat 161:876–888CrossRefGoogle Scholar
  15. David PA (1994) Why are institutions the ‘carriers of history’?: path dependence and the evolution of conventions, organizations and institutions. Struct Change Econ Dyn 5(2):205–220CrossRefGoogle Scholar
  16. Donelson JM, Munday PL, McCormick MI, Pankhurst NW, Pankhurst PM (2010) Effects of elevated water temperature and food availability on the reproductive performance of a coral reef fish. Mar Ecol Prog Ser 401:233–243CrossRefGoogle Scholar
  17. Duit A, Galaz V (2008) Governance and complexity—emerging issues for governance theory. Governance 21:311–335CrossRefGoogle Scholar
  18. Fletcher WJ, Chesson J, Fisher M, Sainsbury KJ, Hundloe T, Smith ADM, Whitworth B (2003) National application of sustainability indicators for Australian fisheries. Final report to Fisheries and Research Development Corporation on Project 2000/145Google Scholar
  19. Food and Agriculture Organization of the United Nations (FAO) (2000) Fisheries statistics, November 2000. FAO, Rome. Home page at:
  20. Food and Agriculture Organization of the United Nations (FAO) (2008) Climate change and disaster risk management. FAO, RomeGoogle Scholar
  21. Goodman LA (1961) Snowball sampling. Ann Math Stat 32(1):148–170CrossRefGoogle Scholar
  22. Hamon KG, Thébaud O, Frusher S, Richard Little L (2009) A retrospective analysis of the effects of adopting individual transferable quotas in the Tasmanian red rock lobster, Jasus edwardsii, fishery. Aquat Living Res 22:549–558CrossRefGoogle Scholar
  23. Hosack GR, Hayes KR, Dambacher JM (2008) Assessing model structure uncertainty through an analysis of system feedback and Bayesian networks. Ecol App 18:1070–1082CrossRefGoogle Scholar
  24. Huang Y, Li F, Bai X, Cui S (2012) Comparing vulnerability of coastal communities to land use change: analytical framework and a case study in China. Environ Sci Policy 23:133–143CrossRefGoogle Scholar
  25. Hughes L (2000) Biological consequences of global warming: is the signal already apparent? Trends Ecol Evol 15(2):56–61CrossRefGoogle Scholar
  26. Hughes L (2003) Climate change and Australia: trends, projections and impacts. Aust Ecol 28:423–443CrossRefGoogle Scholar
  27. Kalaugher E, Bornman JF, Clark A, Beukes P (2013) An integrated biophysical and socio-economic framework for analysis of climate change adaptation strategies: the case of a New Zealand dairy farming system. Environ Model Softw 39:176–187CrossRefGoogle Scholar
  28. Kruse JA, White RG, Epstein HE, Archie B, Berman M, Braund SR, Chapin FS III, Charlie J Sr, Daniel CJ, Eamer J, Flanders N, Griffith B, Haley S, Huskey L, Joseph B, Klein DR, Kofinas GP, Martin SM, Murphy SM, Nebesky W, Nicolson C, Russell DE, Tetlichi J, Tussing A, Walker MD, Young OR (2004) Modeling sustainability of arctic communities: an interdisciplinary collaboration of researchers and local knowledge holders. Ecosystems 7(8):815–828CrossRefGoogle Scholar
  29. Lahsen M, Sanchez-Rodriguez R, Lankao PR, Dube P, Leemans R, Gaffney O, Mirza M, Pinho P, Osman-Elasha B, Smith MS (2010) Impacts, adaptation and vulnerability to global environmental change: challenges and pathways for an action-oriented research agenda for middle-income and low-income countries. Curr Opin Environ Sustain 2:364–374CrossRefGoogle Scholar
  30. Last PR, White WT, Gledhill DC, Hobday AJ, Brown R, Edgar GJ, Pecl GT (2011) Long-term shifts in abundance and distribution of a temperate fish fauna: a response to climate change and fishing practices. Glob Ecol Biogeogr 20(1):58–72CrossRefGoogle Scholar
  31. Latour RJ, Brush MJ, Bonzek CF (2003) Toward ecosystem-based fisheries management: strategies for multispecies modelling and associated data requirements. Fisheries 28:10–22CrossRefGoogle Scholar
  32. Levins R (1968) Evolution in changing environments: some theoretical explorations. Princeton University Press, PrincetonGoogle Scholar
  33. Levins R (1974) Discussion paper: the qualitative analysis of partially specified systems. Ann NY Acad Sci 231:123–138CrossRefGoogle Scholar
  34. Levins R (1998) Qualitative mathematics for understanding, prediction, and intervention in complex ecosystems. In: Rapport D, Costanza R, Epstein PR, Gaudet C, Levins R (eds) Ecosystem health. Blackwell Science, Malden, pp 178–204Google Scholar
  35. Levontin P, Kulmala S, Haapasaari P, Kuikka S (2011) Integration of biological, economic, and sociological knowledge by Bayesian belief networks: the interdisciplinary evaluation of potential management plans for Baltic salmon. ICES J Mar Sci 68(3):632–638CrossRefGoogle Scholar
  36. Ling SD (2008) Range expansion of a habitat-modifying species leads to loss of taxonomic diversity: a new and impoverished reef state. Oecologia 156:883–894CrossRefGoogle Scholar
  37. Ling SD, Johnson CR, Ridgway K, Hobday AJ, Haddon M (2009) Climate-driven range extension of a sea urchin: inferring future trends by analysis of recent population dynamics. Glob Change Biol 15(3):719–731CrossRefGoogle Scholar
  38. Madin EMP, Ban N, Doubleday ZA, Holmes TH, Pecl GT, Smith F (2012) Socio-economic and management implications of range-shifting species in marine systems. Glob Environ Change 22:137–146CrossRefGoogle Scholar
  39. Marcot BG, Holthausen RS, Raphael MG, Rowland MM, Wisdom MJ (2001) Using Bayesian belief networks to evaluate fish and wildlife population viability under land management alternatives from an environmental impact statement. For Ecol Manag 153:29–42CrossRefGoogle Scholar
  40. Matthews R, Selman P (2006) Landscape as a focus for integrating human and environmental processes. J Agric Econ 57(2):199–212CrossRefGoogle Scholar
  41. McCann RK, Marcot BG, Ellis R (2006) Bayesian belief networks: applications in ecology and natural resource management. Can J For Res 36:3053–3062. doi: 10.1139/X06-238 CrossRefGoogle Scholar
  42. McGoodwin JR (1990) Crisis in the world’s fisheries: people, problems, and policies. Stanford University Press, StanfordGoogle Scholar
  43. Meinke H, Howden SM, Struik PC, Nelson R, Rodriguez D, Chapman SC (2009) Adaptation science for agriculture and natural resource management—urgency and theoretical basis. Curr Opin Environ Sustain 1:69–76CrossRefGoogle Scholar
  44. Metcalf SJ (2010) Qualitative models to complement quantitative ecosystem models for the analysis of data-limited marine ecosystems and fisheries. Rev Fish Sci 18(3):248–265CrossRefGoogle Scholar
  45. Nursey-Bray M, Pecl GT, Frusher SD, Gardner C, Haward M, Hobday AJ, Jennings S, Punt AE, Revill H, van Putten I (2012) Communicating climate change: climate change risk perceptions and rock lobster fishers, Tasmania. Mar Policy 36(3):753–759CrossRefGoogle Scholar
  46. Ommer RE (2007) Coasts under stress: restructuring and social-ecological health. McGill-Queen’s University Press, Montreal, Ontario, CanadaGoogle Scholar
  47. Pahl-Wostl C (2009) A conceptual framework for analysing adaptive capacity and multi-level learning processes in resource governance regimes. Glob Environ Change 19:354–365CrossRefGoogle Scholar
  48. Perry AL, Low PJ, Ellis JR, Reynolds JD (2005) Climate change and distribution shifts in marine fishes. Science 308:1912–1915CrossRefGoogle Scholar
  49. Phillipson J, Lowe P, Proctor A, Ruto E (2012) Stakeholder engagement and knowledge exchange in environmental research. J Environ Manag 95:56–65CrossRefGoogle Scholar
  50. Plaganyi EE, Butterworth DS (2004) A critical look at the potential of Ecopath with Ecosim to assist in practical fisheries management. Afr J Mar Sci 26:261–287CrossRefGoogle Scholar
  51. Poloczanska ES, Babcock RC, Butler A, Hobday AJ, Hoegh-Guldberg O, Kunz TJ, Matear R, Milton DA, Okey TA, Richardson AJ (2007) Climate change and Australian marine life. Oceanogr Mar Biol 45:407–478Google Scholar
  52. Puccia CJ, Levins R (1985) Qualitative modeling of complex systems: an introduction to loop analysis and time averaging. Harvard University Press, CambridgeCrossRefGoogle Scholar
  53. Reed MS (2008) Stakeholder participation for environmental management: a literature review. Biol Conserv 141(10):2417–2431. doi: 10.1016/j.biocon.2008.07.014 CrossRefGoogle Scholar
  54. Ruhanen L, Shakeela A (2013) Responding to climate change: Australian tourism industry perspectives on current challenges and future directions. Asia Pac J Tourism Res 18(1–2):35–51CrossRefGoogle Scholar
  55. Spittlehouse DL, Stewart RB (2003) Adaptation to climate change in forest management. BC J Ecosyst Manag 4(1):1–11Google Scholar
  56. Storper M (1997) The regional world: territorial development in a global economy. Guilford Press, New YorkGoogle Scholar
  57. Sturtevant BR, Fall A, Kneeshaw DD, Simon NPP, Papaik MJ, Berninger K, Doyon F, Morgan DG, Messier C (2007) A toolkit modeling approach for sustainable forest management planning: achieving balance between science and local needs. Ecol Soc 12(2):7. Available online at: Google Scholar
  58. Ticehurst JL, Newham LTH, Rissik D, Letcher RA, Jakeman AJ (2007) A Bayesian network approach for assessing the sustainability of coastal lakes in New South Wales, Australia. Environ Model Softw 22(8):1129–1139CrossRefGoogle Scholar
  59. Tuler S, Agyeman J, Pinto da Silva P, Roth LoRusso K, Kay R (2008) Assessing vulnerabilities: integrating information about driving forces that affect risks and resilience in fishing communities. Hum Ecol Rev 15(2):171–184Google Scholar
  60. Turner RK, Subak S, Adger WN (1996) Pressures, trends, and impacts in coastal zones: interactions between socioeconomic and natural systems. Environ Manag 20(2):159–173CrossRefGoogle Scholar
  61. Urwin K, Jordan A (2008) Does public policy support or undermine climate change adaptation? Exploring policy interplay across different scales of governance. Glob Environ Change 18:180–191CrossRefGoogle Scholar
  62. van de Sluijs JP, Risbey JS, Kloprogge P, Ravetz JR, Functowicz SO, Corral Quintana S, Guimaraes Pereira A, De Marchi B, Petersen AC, Janssen PHM, Hoppe R, Huijs SWF (2003) RIVM/MNP guidance for uncertainty assessment and communication, vol 3. Netherlands Environmental Assessment Agency (RIVM/MNP), Utrecht University, Heidelberglaan, 65 ppGoogle Scholar
  63. Young OR, Berkhout F, Gallopin GC, Janssen MA, Ostrom E, van der Leeuw S (2006) The globalization of socio-ecological systems: an agenda for scientific research. Glob Environ Change 16:304–316CrossRefGoogle Scholar
  64. Zuber-Skerritt O (2002) A model for designing action learning and action research programs. Learn Organ 9(4):143–149CrossRefGoogle Scholar

Copyright information

© Springer Japan 2013

Authors and Affiliations

  • S. J. Metcalf
    • 1
    Email author
  • E. I. van Putten
    • 2
    • 3
  • S. D. Frusher
    • 2
  • M. Tull
    • 1
  • N. Marshall
    • 4
  1. 1.School of Management and GovernanceMurdoch UniversityMurdoch, PerthAustralia
  2. 2.The Institute for Marine and Antarctic Studies (IMAS)University of TasmaniaSandy Bay, HobartAustralia
  3. 3.CSIRO Marine and Atmospheric ResearchHobartAustralia
  4. 4.CSIRO Ecosystem SciencesTownsvilleAustralia

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