Expert Knowledge as a Basis for Landscape Ecological Predictive Models

  • C. Ashton Drew
  • Ajith H. Perera


Defining an appropriate role for expert knowledge in science can lead to contentious debate. The professional experience of ecologists, elicited as expert judgment, plays an essential role in many aspects of landscape ecological science. Experts may be asked to judge the relevance of competing research or management questions, the quality and suitability of available data, the best balance of complexity and parsimony, and the appropriate application of model output. Even the initial decision to pursue modeling follows expert judgment regarding the cost and benefits of a model relative to data collection and the suitability of alternative modeling approaches for the specific application. Increasingly, however, professionals are asked to provide expertise to complement or even substitute for scarce data in landscape ecological models, by quantifying their personal experiences and anecdotal observations. In such cases, the professional is asked to reference their knowledge against geospatial data or landscape metrics derived from such data. We offer our chapter to raise awareness and promote discussion of this particular development within landscape ecological modeling. We draw examples from cases where expertise is provided as data in support of the predictive species-habitat models used to inform conservation planning objectives and strategies.


Home Range Geographic Information System Expert Knowledge Expert Judgment Landscape Metrics 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We thank J. Collazo and two anonymous reviewers for helpful ­comments provided on an earlier draft of this chapter.


  1. Al-Awadhi SA, Garthwaite PH (2006) Quantifying expert opinion for modelling fauna habitat distributions. Comp Stat 21:121–140.CrossRefGoogle Scholar
  2. Anderson JL (1998) Embracing uncertainty: the interface of Bayesian statistics and cognitive psychology. Ecol Soc 2 [online]
  3. Aspinall W (2010) A route to more tractable expert advice. Nature 463:294–295.CrossRefPubMedGoogle Scholar
  4. Ayyub BM (2001) Elicitation of expert opinions for uncertainty and risks. CRC Press, Boca Raton, Florida.CrossRefGoogle Scholar
  5. Baddeley MC, Curtis A, Wood RA (2004) An introduction to prior information derived from probabilistic judgements: elicitation of knowledge, cognitive bias and herding. In: Curtis A, Wood R (eds) Geological prior information: informing science and engineering. Special Publications 239, Geological Society, London.Google Scholar
  6. Balmford A, Cowling M (2006) Fusion or failure? The future of conservation. Conserv Biol 20:692–695.CrossRefPubMedGoogle Scholar
  7. Bashari H, Smith C, Bosch OJH (2009) Developing decision support tools for rangeland management by combining state and transition models and Bayesian belief networks. Agri Sys 99:23–34.CrossRefGoogle Scholar
  8. Battisti C, Luiselli L, Pantano D, Teofili C (2008) On threats analysis approach applied to a Mediterranean remnant wetland: is the assessment of human-induced threats related to different level of expertise of respondents? Biodiv Conserv 17:1529–1542.CrossRefGoogle Scholar
  9. Beier P, Noss RF (1998) Do habitat corridors provide connectivity? Conserv Biol 12:1241–1252.CrossRefGoogle Scholar
  10. Bissonette JA, Storch I (eds) (2003) Landscape ecology and resource management: linking theory with practice. Island Press, Washington DC.Google Scholar
  11. Brown JH, Stevens GC, Kaufman DM (1996) The geographic range: size, shape, boundaries, and internal structure. Ann Rev Ecol Syst 27:597–623.CrossRefGoogle Scholar
  12. Cleaves DA (1994) Assessing uncertainty in expert judgments about natural resources. General Technical Report so-1 10, USDA Forest Service, Southern Forest Experimental Station, New Orleans, Louisiana.Google Scholar
  13. Cooke RM (1991) Experts in uncertainty: opinion and subjective probability in science. Oxford University Press, New York.Google Scholar
  14. Coulson RN, Folse LJ, Loh DK (1987) Artificial intelligence and natural resource management. Science 237:262–267.CrossRefPubMedGoogle Scholar
  15. Davis JLD (2000) Changes in tidepool fish assemblages on two scales of environmental variation: seasonal and El Niño Southern Oscillation. Limnol Oceanogr 45:1368–1379.CrossRefGoogle Scholar
  16. Denham R, Mengersen KL (2007) Geographically assisted elicitation of expert opinion for regression models. Bayes Anal 2:99–136.CrossRefGoogle Scholar
  17. Doyon F, Sturtevant BR, Papaik M, Fall A, Messier C, Kneeshaw D (2010) A comparison of landscape dynamics derived from expert knowledge-based succession models and process-based landscape models. In: Perera AH, Drew CA, Johnson C (eds) Expert knowledge and landscape ecological applications. Springer, New York.Google Scholar
  18. Drescher M, Perera AH (2010) Comparing two steps of forest cover change knowledge used in forest landscape management planning. J Environ Plan Manag. DOI: 10.1080.109640561003727110.Google Scholar
  19. Drescher M, Perera AH, Buse LJ, Ride K, Vasiliauskas S (2006) Identifying uncertainty in practitioner knowledge of boreal forest succession in Ontario through a workshop approach. Forest Research Report 165, Ontario Ministry of Natural Resources, Ontario Forest Research Institute, Canada.Google Scholar
  20. Drescher M, Perera AH, Buse LJ, Ride K, Vasiliauskas S (2008) Uncertainty in expert knowledge of forest succession: a case study from boreal Ontario. Forest Chron 84:194–209.Google Scholar
  21. Drescher M, Buse LJ, Perera AH, Ouellette MR (in press) Eliciting and formalizing expert knowledge of forest succession supported by a software tool. In: Perera AH, Drew CA, Johnson C (eds) Expert knowledge and landscape ecological applications. Springer, New York.Google Scholar
  22. Drew CA, Collazo JC (in press) Expert knowledge as a foundation for management of rare or secretive species and their habitat. In: Perera AH, Drew CA, Johnson C (eds) Expert knowledge and landscape ecological applications. Springer, New York.Google Scholar
  23. Elith J, Burgman MA, Regan HM (2002) Mapping epistemic uncertainties and vague concepts in predictions of species distribution. Ecol Model 157:313–329.CrossRefGoogle Scholar
  24. Garthwaite PH, Kadane JB, O’Hagan A (2005) Statistical methods for eliciting probability distributions. J Am Stat Assoc 100:680–701.CrossRefGoogle Scholar
  25. Geneletti D (2005) Formalising expert opinion through multi-attribute value functions: an application in landscape ecology. J Environ Manag 76:255–262.CrossRefGoogle Scholar
  26. Giles Jr, RH (1998) Natural resource management tomorrow: four currents. Wild Soc Bull 26:51–55.Google Scholar
  27. Gilchrist G, Mallory M, Merkel F (2005) Can local ecological knowledge contribute to wildlife management? Case studies of migratory birds. Ecol Soc 10 [online] URL:
  28. Gutzwiller KJ (ed) (2002) Applying landscape ecology in biological conservation. Springer, New York.Google Scholar
  29. Hess GR, King TJ (2002) Planning open spaces for wildlife I. Selecting focal species using a Delphi survey approach. Landsc Urban Plan 58:25–40.CrossRefGoogle Scholar
  30. Holling CS (2001) Understanding the complexity of economic, ecological, and social systems. Ecosystems 4:390–405.CrossRefGoogle Scholar
  31. Huntington HP (2000) Using traditional ecological knowledge in science: methods and applications. Ecol App 10:1270–1274.CrossRefGoogle Scholar
  32. James A, Low Choy S, Mengersen KL (2010) Elicitator: an expert elicitation tool for regression in ecology. Environ Model Softw 25:129–145.CrossRefGoogle Scholar
  33. Johnson CJ, Gillingham MP (2004) Mapping uncertainty: sensitivity of wildlife habitat ratings to expert opinion. J App Ecol 41:1032–1041.CrossRefGoogle Scholar
  34. Jones J (2001) Habitat selection studies in avian ecology: a critical review. Auk 118:557–562.CrossRefGoogle Scholar
  35. Kim DH, Slack RD, Chavez-Ramirez F (2008) Impacts of El Niño-Southern Oscillation events on the distribution of wintering raptors. J Wildl Manag 72:231–239.CrossRefGoogle Scholar
  36. King AW, Perera AH (2006) Transfer and extension of forest landscape ecology: a matter of models and scale. In: Perera AH, Buse LJ, Crow TR (eds) Forest landscape ecology: transferring knowledge to practice. Springer, New York.Google Scholar
  37. Kontic B (2000) Why are some experts more credible than others? Environ Impact Assess Rev 20:427–434.CrossRefGoogle Scholar
  38. Kynn M (2008) The ‘heuristics and biases’ bias in expert elicitation. J R Stat Soc A: Stat Soc 171:239–264.Google Scholar
  39. Lefsky MA, Cohen WB, Parker GG, Harding DJ (2002) Lidar remote sensing for ecosystem studies. BioScience 52:19–30.CrossRefGoogle Scholar
  40. Liu J, Taylor WW (eds) (2002) Integrating landscape ecology into natural resource management. Cambridge University Press, New York.Google Scholar
  41. Low Choy SL, O’Leary R, Mengersen, KL (2009) Elicitation by design in ecology: using expert opinion to inform priors for Bayesian statistical models. Ecology 90:265–277.CrossRefGoogle Scholar
  42. Lyons JE, Runge MC, Lasowski HP, Kendall WL (2008) Monitoring in the context of structured decision making and adaptive management. J Wildl Manag 72:1683–1692.CrossRefGoogle Scholar
  43. MacKenzie DI, Nichols JD, Hines JE, Knutson MG, Franklin AB (2003) Estimating site occupancy, colonization, and extinction when a species is detected imperfectly. Ecology 84:2200–2207.CrossRefGoogle Scholar
  44. MacMillan DC, Marshall K (2006) The Delphi process – an expert-based approach to ecological modeling in data-poor environments. Anim Conserv 9:11–19.CrossRefGoogle Scholar
  45. 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. Forest Ecol Manag 153:29–42.CrossRefGoogle Scholar
  46. Marcot BG, Steventon JD, Sutherland GD, McCann RK (2006) Guidelines for developing and updating Bayesian belief networks applied to ecological modeling and conservation. Can J For Res 36:3063–3074.CrossRefGoogle Scholar
  47. Martin TG, Kuhnert PM, Mengersen K, Possingham HP (2005) The power of expert opinion in ecological models using Bayesian methods: impact of grazing on birds. Ecol App 15:266–280.CrossRefGoogle Scholar
  48. McCarthy MA (2007) Bayesian methods in ecology. Cambridge University Press, New York.Google Scholar
  49. Meyer, MA, Booker JM (2001) Eliciting and analyzing expert judgment: a practical guide. Society for Industrial and Applied Mathematics, Philadelphia, Pennsylvania.Google Scholar
  50. Millspaugh JJ, Thompson III FR (eds) (2009) Models for planning wildlife conservation in large landscapes. Academic Press, Massachusetts.Google Scholar
  51. Moody AT, Grand JB (in press) Incorporating expert knowledge in decision support models for bird conservation. In: Perera AH, Drew CA, Johnson C (eds) Expert knowledge and landscape ecological applications. Springer, New York.Google Scholar
  52. Morris PA (1977) Combining expert judgements: a Bayesian approach. Manag Sci 23:679–693.CrossRefGoogle Scholar
  53. Murray JV, Goldizen AW, O’Leary RA, McAlpine CA, Possingham HP, Choy SL (2009) How useful is expert opinion for predicting the distribution of a species within and beyond the region of expertise? A case study using brush-tailed rock-wallabies Petrogale penicillata. J App Ecol 46: 842–851.CrossRefGoogle Scholar
  54. Nyberg JB, Marcot BG, Sulyma R (2006) Using Bayesian belief networks in adaptive management. Can J For Res 36:3104–3116.CrossRefGoogle Scholar
  55. O’Hagan A (1998) Eliciting expert beliefs in substantial practical applications. J R Stat Soc Ser D: the Statistician 47:21–35 (with discussion, pp. 55–68).CrossRefGoogle Scholar
  56. O’Hagan A (2006) Research in elicitation. In: Upadhyay SK, Singh U, Dey DK (eds) Bayesian statistics and its applications. Anamaya, New Delhi.Google Scholar
  57. O’Leary RA, Murray JV, Low Choy SJ, Mengersen KL (2008) Expert elicitation for Bayesian classification trees. J App Prob Stat 3:95–106.Google Scholar
  58. Pearce JL, Cherry K, Drielsma M, Ferrier S, Whish G (2001) Incorporating expert opinion and fine-scale vegetation mapping into statistical models of faunal distribution. J App Ecol 38:412–424.CrossRefGoogle Scholar
  59. Perera AH, Buse LJ, Crow TR (eds) (2006) Forest landscape ecology: transferring knowledge to practice. Springer, New York.Google Scholar
  60. Perera AH, Drew CA, Johnson C (eds) (in press) Expert knowledge and ecological applications. Springer, New York.Google Scholar
  61. Petit S, Chamberlain D, Haysom K, Pywell R, Vickery J, Warman L, Allen D, Firbank L (2003) Knowledge-based models for predicting species occurrence in arable conditions. Ecography 26:626–640.CrossRefGoogle Scholar
  62. Ralls K, Starfield AM (1995) Choosing a management strategy: two structured decision making methods for evaluating the predictions of stochastic simulation models. Conserv Biol 9:175–181.CrossRefGoogle Scholar
  63. Ray N, Burgman MA (2006) Subjective uncertainties in habitat suitability maps. Ecol Model 195:172–186.CrossRefGoogle Scholar
  64. Root T (1988) Environmental factors associated with avian distributional boundaries. J Biogeogr 15:489–505.CrossRefGoogle Scholar
  65. Rothlisberger JD, Lodge DM, Cooke RM, Finnoff DC (2010) Future declines of the binational Laurentian Great Lakes fisheries: the importance of environmental and cultural change. Front Ecol Environ 8: 239–244.CrossRefGoogle Scholar
  66. Rykiel Jr, EJ (1989) Artificial intelligence and expert systems in ecology and natural resource management. Ecol Model 46:3–8.CrossRefGoogle Scholar
  67. Silbernagel JM, Price J, Miller N, Swaty R, White M (in press) An iterative, interactive elicitation process sheds light into black box of forest conservation scenarios. In: Perera AH, Drew CA, Johnson C (eds) Expert knowledge and landscape ecological applications. Springer, New York.Google Scholar
  68. Starfield A, Bleloch AL (1991) Building models for conservation and wildlife management. Second edition, The Burgess Press, Edina, Minnesota.Google Scholar
  69. Stenseth NC, Mysterud A, Ottersen G, Hurrell JW, Chan KS, Lima M (2002) Ecological effects of climate fluctuations. Science 297:1292–1296.CrossRefPubMedGoogle Scholar
  70. Store R, Kangas J (2001) Integrating spatial multi-criteria evaluation and expert knowledge for GIS-based habitat suitability modeling. Landsc Urban Plan 55:79–93.CrossRefGoogle Scholar
  71. Teck SJ, Halpern BS, Kappel CV, Micheli F, Selkoe KA, Crain CM, Martone R, Shearer C, Arvai J, Fischhoff B, Murray G, Neslo R, Cooke R (2010) Using expert judgment to estimate marine ecosystem vulnerability in the California Current. Ecol App. DOI: 10.1890/09-1173.Google Scholar
  72. Tversky A, Kahneman D (1974) Judgement under uncertainty: heuristics and biases. Science 185:1124–1131.CrossRefPubMedGoogle Scholar
  73. Troll C (1939) Luftbildplan und ökologische Bodenforschung. Zeitschrift der Gesellschaft für Erdkunde, Berlin, pp 241–298.Google Scholar
  74. Uusitalo L (2007) Advantages and challenges of Bayesian networks in environmental modeling. Ecol Model 203:312–318.CrossRefGoogle Scholar
  75. Williams BK (2003) Policy, research, and adaptive management in avian conservation. Auk 120:212–217.CrossRefGoogle Scholar
  76. Williams BK, Szaro RC, Shapiro CD (2009) Adaptive management: the US Department of the Interior technical guide. Adaptive Management Working Group, US Department of the Interior, Washington, DC.Google Scholar
  77. Yamada K, Elith J, McCarthy M, Zerger A (2003) Eliciting and integrating expert knowledge for wildlife habitat modelling. Ecol Model 165:251–264.CrossRefGoogle Scholar

Copyright information

© Springer Science+BUsiness Media, LLC 2011

Authors and Affiliations

  1. 1.North Carolina Fish and Wildlife Cooperative Research Unit, Department of BiologyNorth Carolina State UniversityRaleighUSA

Personalised recommendations