Environment Systems and Decisions

, Volume 39, Issue 3, pp 349–367 | Cite as

The provision and utility of earth science to decision-makers: synthesis and key findings

  • Mark C. QuigleyEmail author
  • Luke G. Bennetts
  • Patricia Durance
  • Petra M. Kuhnert
  • Mark D. Lindsay
  • Keith G. Pembleton
  • Melanie E. Roberts
  • Christopher J. White


This paper synthesizes important elements from case studies presented in its companion paper (Quigley et al. in Environ Syst Decis, 2019, to define mutual and distinct characteristics, and to develop a more holistic understanding of how earth science was used to support diverse examples of decision-making. We identify a suite of 28 different science actions used within the case studies that are classified as pertaining to (i) evidence acquisition and analysis, (ii) provision of science to target audience, or (iii) enhancing future science provision and utility. Sample action pathways provide empirically evidenced, albeit simplified, examples of how scientists may contribute to the progression of science through complex decision-making frameworks. Decision trees with multiple scientific and non-scientific inputs are presented based on empirical evidence and theory to provide scientists and decision-makers with simplified examples of complex multi-step decision-making processes under conditions of risk and uncertainty. Evidence for nonlinear engagement between decision-makers and science providers is presented, including non-traditional approaches such as provision of unsolicited science through the media and stakeholders. Examples of scientifically informed, precautionary decision-making with adaptive capacity, even where economically favourable decision alternatives exist, are provided. We undertake a self-elicitation exercise of case studies to derive values and uncertainties for % scientific agreement amongst utilized inputs and % uptake of potentially relevant and available science. We observe a tendency towards increased scientific uptake with increasing scientific agreement, but this is not ubiquitous; politically affected decisions and/or complex multi-decision scenarios under time pressure complicate this relationship. An increasing need for decision-making expediency that is not met by increased availability of relevant science evidence may rely on expert judgement, based on incomplete knowledge that is manifested as large uncertainties in defining a singular value for scientific agreement and uptake. We encourage scientists to further document their experiences using the science-action classification scheme provided herein to stimulate further comparative analyses of this nature.


Earth science Policy Decision-making Natural disasters 



MQ thanks Sue Stubenvoll for the funding and encouragment to participate in, and submit evidence to, the Christchurch District Replacement Plan Hearings. The modelling conducted in case study 2 and analysis activities reported, and the development of the tools were made possible through funding provided by the Queensland Department of Agriculture and Fisheries under the Department of Agriculture and Fisheries—University of Southern Queensland Broad Acre Grains Partnership. Dr Lance Pedergast (Senior Development Agronomist with the Queensland Department of Agriculture and Fisheries) assisted in the design, analysis and communication of chickpea analysis presented in this case study. Mr Howard Cox (Senior Agronomist Department of Agriculture and Fisheries) has contributed to the design and development of the ARM online tools. The author of case study 5 (PD) would like to thank Ray Wood and Renee Grogan for discussing many aspects of the CRP application and EPANZ hearing and decision. Their comments and suggestion greatly improved the original document. Hamish Campbell is also acknowledged for providing a thorough review of the draft. The paper benefited from a highly thoughtful review by Emma Hudson-Doyle and two anonymous reviewers. We thank Igor Linkov for the professional editorship of the manuscript.


  1. Aspinall W (2010) A route to more tractable expert advice. Nature 463:294–295CrossRefGoogle Scholar
  2. Aven T, Renn O (2010) Risk management. In: Aven T, Renn O (eds) Risk management and governance. Springer, Berlin, pp 121–158CrossRefGoogle Scholar
  3. Brownson R, Fielding J, Maylahn C (2009) Evidence-based public health: a fundamental concept for public health practice. Annu Rev Public Health 30:175–201CrossRefGoogle Scholar
  4. Cash DW, Borck JC, Patt AG (2006) Countering the loading-dock approach to linking science and decision making: comparative analysis of el niño/southern oscillation (enso) forecasting systems. Sci Technol Hum Value 31(4):465–494CrossRefGoogle Scholar
  5. Colyvan M, Kitto K, Quigley M, Bennetts L, Durance P, Galton-Fenzi B, Geenens G, Hamilton K, Ickowicz A, Killedar M, Kuhnert P, Lindsay M, Pembleton K, Roberts M, Verdejo-Garcia A, White C (2017) Addressing Risk in Conditions of Uncertainty, Ignorance, and Partial Knowledge . In: An interdisciplinary approach to living in a risky world. Recommendations from the Theo Murphy High Flyers Workshop, pp 5–7Google Scholar
  6. Dilling L, Lemos MC (2011) Creating usable science: opportunities and constraints for climate knowledge use and their implications for science policy. Glob Environ Chang 21(2):680–689CrossRefGoogle Scholar
  7. Doubleday R, Wilsdon J (2012) Science policy: beyond the great and good. Nature 485:301–302CrossRefGoogle Scholar
  8. Doyle EE, Johnston DM, Smith R, Paton D (2019) Communicating model uncertainty for natural hazards: a qualitative systematic thematic review. Int J Disaster Risk Reduct 33:449–476. CrossRefGoogle Scholar
  9. Doyle EEH, Paton D (2018) Decision-making: preventing miscommunication and creating shared meaning between stakeholders. Springer, Cham, pp 549–570. CrossRefGoogle Scholar
  10. Doyle EEH, Paton D, Johnston DM (2015) Enhancing scientific response in a crisis: evidence-based approaches from emergency management in New Zealand. J Appl Volcanol 4(1):1. CrossRefGoogle Scholar
  11. Dudo A, Besley J (2016) Scientists’ prioritization of communication objectives for public engagement. PLoS ONE 11:e0148867CrossRefGoogle Scholar
  12. Feldman IHMDL (2009) Making science useful to decision makers: climate forecasts, water management, and knowledge networks. Weather Clim Soc 1(1):9–21CrossRefGoogle Scholar
  13. Fischoff B, Davis A (2014) Communicating scientific uncertainty. Proc Natl Acad Sci USA 111:13664–13671CrossRefGoogle Scholar
  14. Foster K, Vecchia P, Repacholi M (2000) Science and the precautionary principle. Science 288:979–981CrossRefGoogle Scholar
  15. Frodeman R (1995) Geological reasoning: geology as an interpretive and historical science. Geol Soc Am Bull 107:960–968CrossRefGoogle Scholar
  16. Gillieson D (2004) Submission to the alpine grazing taskforce, victoria. Tech. rep., Australian Academy of ScienceGoogle Scholar
  17. Gluckman P (2014) Policy: the art of science advice to government. Nature 507:163CrossRefGoogle Scholar
  18. Gluckman P (2016) Making decisions in the face of uncertainty: Understanding risk. Tech. rep., Office of the Prime Minister’s Chief Science Advisor, Auskland, New ZealandGoogle Scholar
  19. Haasnoot M, Kwakkel JH, Walker WE, ter Maat J (2013) Dynamic adaptive policy pathways: a method for crafting robust decisions for a deeply uncertain world. Glob Environ Chang 23(2):485–498. CrossRefGoogle Scholar
  20. Kapucu N, Garayev V (2011) Collaborative decision-making in emergency and disaster management. Int J Public Admin 34(6):366–375CrossRefGoogle Scholar
  21. Karr J (2006) When governments ignore science, scientists should speak up. BioScience 56:287–288CrossRefGoogle Scholar
  22. King A, Middleton D, Brown C, Johnston D, Johal S (2014) Insurance: its role in recovery from the 2010–2011 Canterbury earthquake sequence. Earthq Spectra 30:475–491CrossRefGoogle Scholar
  23. Kirchhoff CJ, Lemos MC, Dessai S (2013) Actionable knowledge for environmental decision making: broadening the usability of climate science. Ann Rev Environ Resour 38:393–414CrossRefGoogle Scholar
  24. Krupnick A, Morgenstern R, Batz M, Nelson P, Burtraw D, Shih JS, McWilliams M (2006) Not a sure thing: making regulatory choices under uncertainty. Resources for the Future, Washington, DCGoogle Scholar
  25. Langer L, Tripney J, Gough D (2016) The science of using science: researching the use of research evidence in decision-making. Tech. rep., University College London, LondonGoogle Scholar
  26. Lorenzoni I, Nicholson-Cole S, Whitmarsh L (2007) Barriers perceived to engaging with climate change among the UK public and their policy implications. Glob Environ Chang 17:445–459CrossRefGoogle Scholar
  27. Mackey B, Quigley M (2014) Strong proximal earthquakes revealed by cosmogenic 3he dating of prehistoric rockfalls, Christchurch, New Zealand. Geology 42:975–978CrossRefGoogle Scholar
  28. Massey C, McSaveney M, Taig T, Richards L, Litchfield N, Rhoades D, McVerry G, Lukovic B, Heron D, Ries W, Van Dissena R (2014) Determining rockfall risk in Christchurch using rockfalls triggered by the 2010–2011 Canterbury Earthquake Sequence. Earthq Spectra 30:155–181CrossRefGoogle Scholar
  29. Mervis J (2017) Trump’s 2018 budget proposal ‘devalues’ science. Science 355:1246–1247CrossRefGoogle Scholar
  30. Nisbet M, Markowitz E (2015) Understanding public opinion in debates over biomedical research: looking beyond political partisanship to focus on beliefs about science and society. PLoS ONE 9:e88473CrossRefGoogle Scholar
  31. North DW (1968) A tutorial introduction to decision theory. IEEE Trans Syst Sci Cybern 4(3):200–210CrossRefGoogle Scholar
  32. Nutbeam D, Boxall A (2008) What influences the transfer of research into health policy and practice? Observations from England and Australia. Public Health 122:747–753CrossRefGoogle Scholar
  33. Owen C, Bearman C, Brooks B, Chapman J, Paton D, Hossain L (2013) Developing a research framework for complex multi-team coordination in emergency management. Int J Emerg Manag 9(1):1–17. CrossRefGoogle Scholar
  34. Pielke RA Jr (2003) The role of models in prediction for decision. In: Canham CD, Cole JJ, Lauenroth WK (eds) Models in ecosystem science. Princeton University Press, Princeton, pp 111–135 chap 7Google Scholar
  35. Pielke RA Jr, Conant RT (2003) Best practices in prediction for decision-making: lessons from the atmospheric and earth sciences. Ecology 84:1351–1358CrossRefGoogle Scholar
  36. Quigley MC, Bennetts LG, Durance P, Kuhnert PM, Lindsay MD, Pembleton KG, Roberts ME, White CJ (2019) The provision and utility of science and uncertainty to decision-makers: earth science case studies. Environ Syst Decis.
  37. Reardon S, Tollefson J, Witze A, Ross E (2017) US science agencies face deep cuts in trump budget. Nature 543:471–472CrossRefGoogle Scholar
  38. Schaal B (2017) Informing policy with science. Science 355:435CrossRefGoogle Scholar
  39. Science Council of Japan (2013) Code of conduct for scientists—revised version., english version, translated from the original Japanese version
  40. Seeger M (2006) Best practices in crisis communication: an expert panel process. J Appl Commun Res 34:232–244CrossRefGoogle Scholar
  41. 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(3):512–523. CrossRefGoogle Scholar
  42. Sutherland W, Spiegelhalter D, Burgman M (2013) Twenty tips for interpreting scientific claims. Nature 503:335–337CrossRefGoogle Scholar
  43. Van Asselt MB, Renn O (2011) Risk governance. J Risk Res 14(4):431–449CrossRefGoogle Scholar
  44. Varis O (1997) Bayesian decision analysis for environmental and resource management. Environ Model Softw 12(2–3):177–185CrossRefGoogle Scholar
  45. White C, Remenyi T, McEvoy D, Trundle A, Corney S (2016) 2016 Tasmanian state natural disaster risk assessment: all hazard summary. Tech. rep. University of Tasmania, HobartGoogle Scholar
  46. White DJ (2018) Decision theory. Routledge, LondonCrossRefGoogle Scholar
  47. Whitmer A, Ogden L, Lawton J, Sturner P, Groffman P, Schneider L, Hart D, Halpern B, Schlesinger W, Raciti S, Bettez N (2010) The engaged university: providing a platform for research that transforms society. Front Ecol Environ 8:314–321CrossRefGoogle Scholar
  48. Zhou L, Wu X, Xu Z, Fujita H (2018) Emergency decision making for natural disasters: an overview. Int J Disaster Risk Reduct 27:567–576CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  • Mark C. Quigley
    • 1
    • 2
    Email author
  • Luke G. Bennetts
    • 3
  • Patricia Durance
    • 4
  • Petra M. Kuhnert
    • 5
  • Mark D. Lindsay
    • 6
  • Keith G. Pembleton
    • 7
  • Melanie E. Roberts
    • 8
    • 9
  • Christopher J. White
    • 10
    • 11
  1. 1.School of Earth SciencesUniversity of MelbourneParkvilleAustralia
  2. 2.Department of Geological SciencesUniversity of CanterburyChristchurchNew Zealand
  3. 3.School of Mathematical SciencesUniversity of AdelaideAdelaideAustralia
  4. 4.GNS ScienceLower HuttNew Zealand
  5. 5.CSIRO Data61CanberraAustralia
  6. 6.Centre for Exploration Targeting, School of Earth SciencesUniversity of Western AustraliaCrawleyAustralia
  7. 7.School of Agricultural, Computational and Environmental Sciences and Centre for Sustainable Agricultural SystemsUniversity of Southern QueenslandToowoombaAustralia
  8. 8.Australian Rivers InstituteGriffith UniversityNathanAustralia
  9. 9.School of Mathematics and StatisticsUniversity of MelbourneParkvilleAustralia
  10. 10.School of EngineeringUniversity of TasmaniaHobartAustralia
  11. 11.Department of Civil and Environmental EngineeringUniversity of StrathclydeGlasgowUK

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