What is expert knowledge, how is such knowledge gathered, and how do we use it to address questions in landscape ecology?

Expert Knowledge and its Application in Landscape Ecology

Volumn , Issue , 2014, Pages 11-38

  McBride, Marissa F ^a   Burgman, Mark A ^a  

^a UNIVERSITY OF MELBOURNE   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84929285052     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-1-4614-1034-8_2     Document Type: Chapter

References (160)

1. Al-Awadhi SA, Garthwaite PH (1998) An elicitation method for multivariate normal distributions. Commun Stat A-Theor 27:1123-1142
2. Alho JM, Kangas J (1997) Analyzing uncertainties in experts' opinions of forest plan performance. For Sci 43:521-528
3. Anderson EL, Hattis D (1999) A. Uncertainty and variability. Risk Anal 19:47-49
4. Anderson JL (1998) Embracing uncertainty: the interface of Bayesian statistics and cognitive psychology. Ecol Soc 2(1), article 2. Available from http://www. consecol. org/vol2/iss1/art2/(accessed May 2011)
5. Armstrong JS (ed) (2001) Principles of forecasting: a handbook for researchers and practitioners. Kluwer Academic Publishers, Norwell
6. Armstrong JS (2006) Findings from evidence-based forecasting: methods for reducing forecast error. Int J Forecasting 22:583-598
7. Arnott D (2006) Cognitive biases and decision support systems development: a design science approach. Inform Syst J 16:55-78
8. Ausden M, Sutherland WJ, James R (2001) The effects of fl ooding lowland wet grassland on soil macroinvertebrate prey of breeding wading birds. J Appl Ecol 38:320-338
9. Ayyub BM (2001) Elicitation of expert opinions for uncertainty and risks. CRC Press, Boca Raton
10. Baran N (2000) Effective survey methods for detecting plants. MSc Thesis. University of Melbourne, Melbourne
11. Bates JM, Granger CWJ (1969) The combination of forecasts. Oper Res Q 20:451-468
12. Beyth-Marom R (1982) How probable is probable A numerical translation of verbal probability expressions. J Forecasting 1:257-269
13. Booker JM, McNamara LA (2004) Solving black box computation problems using expert knowledge theory and methods. Reliab Eng Syst Safe 85:331-340
14. Bransford JD, Brown AL, Cocking RR (2000) How people learn: brain, mind, experience and school. National Academy Press, Washington
15. Brun W, Teigen KH (1988) Verbal probabilities: ambiguous, context-dependent, or both. Organ Behav Hum Dec 41:390-404
16. Budescu, DV, Wallsten TS (1985) Consistency in interpretation of probabilistic phrases. Organ Behav Hum Dec 36:391-405
17. Burgman MA (2000) Population viability analysis for bird conservation: prediction, heuristics, monitoring and psychology. Emu 100:347-353
18. Burgman MA (2005) Risks and decisions for conservation and environmental management. Cambridge University Press, Cambridge
19. Burgman MA, Carr A, Godden L et al (2011) Redefi ning expertise and improving ecological judgement. Conserv Lett 4:81-87
20. Camerer CF, Johnson EJ (1997) The process-performance paradox in expert judgment: how can experts know so much and predict so badly In: Goldstein WM, Hogarth RM (eds) Research on judgment and decision making: currents, connections and controversies. Cambridge University Press, Cambridge, pp 342-364
21. Campbell LM (2002) Science and sustainable use: views of marine turtle conservation experts. Ecol Appl 12:1229-1246
22. Carpenter SR (2002) Ecological futures: building an ecology of the long now. Ecology 83:2069-2083
23. Chase WG, Simon HA (1973) The mind's eye in chess. In: Chase WG (ed) Visual information processing. Academic Press, New York, pp 215-281
24. Chi MTH (2006) Two approaches to the study of experts' characteristics. In: Ericsson KA, Charness N, Feltovich PJ, Hoffman, RR (eds) The Cambridge handbook of expertise and expert performance. Cambridge University Press, New York, pp 21-30
25. Christen JA, Nakamura M (2000) On the analysis of accumulation curves. Biometrics 56:748-754
26. Christensen-Szalanski JJJ, Bushyhead JB (1981) Physicians' use of probabilistic information in a real clinical setting. J Exp Psychol Human Percept Perform 7:125-126
27. Chuenpagdee R, Morgan LE, Maxwell SM et al (2003) Shifting gears: assessing collateral impacts of fi shing methods in the U. S. waters. Front Ecol Environ 10:517-524
28. Clemen RT (1989) Combining forecasts: a review and annotated bibliography. Int J Forecasting 5:559-583
29. Clemen RT, Winkler RL (1985) Limits for the precision and value of information from dependent sources. Oper Res 33:427-442
30. Clemen RT, Winkler RL (1999) Combining probability distributions from experts in risk analysis. Risk Anal 19:187-203
31. Cohen MJ, Carstenn S, Lane CR (2004) Floristic quality indices for biotic assessment of depressional marsh condition in Florida. Ecol Appl 14:784-794
32. Collins, HM, Evans R (2007) Rethinking expertise. University of Chicago Press
33. Chicago Cooke RM (1991) Experts in uncertainty: opinion and subjective probability in science. Oxford University Press, New York
34. Cooke RM, Goossens LHJ (2000) Procedures guide for structured expert judgement in accident consequence modelling. Radiat Prot Dosim 90:303-309
35. Cosmides L, Tooby J (1996) Are humans good intuitive statisticians after all Rethinking some conclusions from the literature on judgment under uncertainty. Cognition 58:1-73
36. Cowling RM, Pressey RL (2003) Introduction to systematic conservation planning in the Cape Floristic Region. Biol Conserv 112:1-13
37. Crance JHBR (1987) Guidelines for using the Delphi technique to develop habitat suitability index curves. U. S. Fish Wildl Serv., Washington. Biological Report#82(10. 134)
38. Crome FHJ, Thomas MR, Moore LA (1996) A novel Bayesian approach to assessing impacts of rain forest logging. Ecol Appl 6:1104-1123
39. Currie F, Elliott G (1997) Forests and birds: a guide to managing forests for rare birds. Forestry Authority, Cambridge, and Royal Society for the Protection of Birds, Sandy
40. Czembor CA, Vesk PA (2009) Incorporating between-expert uncertainty into state-and-transition simulation models for forest restoration. For Ecol Manage 259:165-175
41. Dawes RM, Kagan J (1988) Rational choice in an uncertain world. Harcourt Brace Jovanovich, San Diego
42. Dickinson JP (1973) Some statistical results in combination of forecasts. Oper Res Q 24:253-260
43. Dickinson JP (1975) Some comments on combination of forecasts. Oper Res Q 26:205-210
44. Drescher, MA. Perera AH, Buse LJ et al (2008) Uncertainty in expert knowledge of forest succession: a case study from boreal Ontario. For Chron 84:194-209
45. Ericsson KA (2004) Deliberate practice and the acquisition and maintenance of expert performance in medicine and related domains. Acad Med 79:S70-S81
46. Ericsson KA, Charness N (1994) Expert performance: its structure and acquisition. Am Psychol 49:725-747
47. Ericsson KA, Charness N, Feltovich PJ et al (eds) (2006) The Cambridge handbook of expertise and expert performance. Cambridge University Press, New York
48. Ericsson KA, Kintsch W (1995) Long-term working memory. Psychol Rev 102:211-245
49. Ericsson KA, Lehmann AC (1996) Expert and exceptional performance: evidence of maximal adaptation to task constraints. Annu Rev Psychol 47:273-305
50. Ericsson KA, Towne TJ (2010) Expertise. Wiley Interdisciplinary Reviews: Cognitive Science 1:404-416
51. Fazey I, Fazey JA, Fazey DMA (2005) Learning more effectively from experience. Ecol Soc 10(2), article 4. Available from http://www. ecologyandsociety. org/vol10/iss2/art4/(accessed May 2011)
52. Ferrell WR (1994) Discrete subjective probabilities and decision analysis: elicitation, calibration and combination. In: Wright G, Ayton P (eds) Subjective probability. Wiley, New York
53. Ferson S, Ginzburg LR (1996) Different methods are needed to propagate ignorance and variability. Reliab Eng Syst Safe 54:133-144
54. Fischhoff B, Slovic P, Lichtenstein S (1982) Lay foibles and expert fables in judgments about risk. Am Stat 36:240-255
55. Fisher L (2009) The perfect swarm: the science of complexity in everyday life. Basic Books, New York
56. Garthwaite PH, Kadane JB, O'Hagan A (2005) Statistical methods for eliciting probability distributions. J Am Stat Assoc 100:680-700
57. Genest C, McConway KJ (1990) Allocating the weights in the linear opinion pool. J Forecasting 9:53-73
58. Genest C, Zidek JV (1986) Combining probability distributions: a critique and an annotated bibliography. Stat Sci 1:114-148
59. Gigerenzer G (1999) Simple heuristics that make us smart. Oxford University Press, New York
60. Gigerenzer G (2002) Calculated risks: how to know when the numbers deceive you. Simon and Schuster, New York
61. Gigerenzer G (2008) Rationality for mortals: how people cope with uncertainty. Oxford University Press, New York
62. Gigerenzer G, Hoffrage U (1995) How to improve Bayesian reasoning without instruction: frequency formats. Psychol Rev 102:684-704
63. Gilovich T, Griffi n D, Kahneman D (eds) (2002) Heuristics and biases: the psychology of intuitive judgement. Cambridge University Press, Cambridge
64. Grier JW, Elder JB, Gramlich FJ et al (1993) The bald eagle in the northern United States. Bird Conserv 1:41-66
65. Griffi ths SP, Kuhnert PM, Venables WN, Blaber SJM (2007) Estimating abundance of pelagic fi shes using gillnet catch data in data-limited fi sheries: a Bayesian approach. Can J Fish Aquat Sci 64:1019-1033
66. Helander B, Marquiss M, Bowerman W (eds) (2003) Sea Eagle 2000. In: Proceedings from an International Conference at Bjökö, Sweden, 13-17 September 2000. Swedish Society for Nature Conservation, Stockholm, pp 129-132
67. Helander B, Stjernberg,T (2003) Action plan for the conservation of white-tailed Sea Eagle (Haliaeetus albicilla). The Convention on the Conservation of European Wildlife and Natural Habitats, Strasbourg
68. Hertwig R, Gigerenzer G (1999) The 'conjunction fallacy' revisited: how intelligent inferences look like reasoning errors. J Behav Dec Making 12:275-305
69. Hofer E (1996) When to separate uncertainties and when not to separate. Reliab Eng Syst Safe 54:113-118
70. Hoffman FO, Kaplan S (1999) Beyond the domain of direct observation: how to specify a probability distribution that represents the "state of knowledge" about uncertain inputs. Risk Anal 19:131-134
71. Hoffman RR (1998) How can expertise be defi ned Implications of research from cognitive psychology. In: Williams R, Faulkner W, Fleck J (eds) Exploring expertise. Macmillan, New York, pp 81-100
72. Hogarth RM (1977) Methods for aggregating opinions. In: Jungermann H, DeZeeuw G (eds) Decision making and change in human affairs. Reidel, Dordrecht, pp 231-255
73. Hogarth RM (1987) Judgment and choice: the psychology of decision. Wiley, New York
74. Hogarth RM (2001) Educating intuition. The University of Chicago Press, Chicago
75. Hokstad P, Oien K, Reinertsen R (1998) Recommendations on the use of expert judgment in safety and reliability engineering studies: two offshore case studies. Reliab Eng Syst Safe 61:65-76
76. Hora SC (1992) Acquisition of expert judgment: examples from risk assessment. J Energy Dev 118:136-148
77. Hora SC (2004) Probability judgments for continuous quantities: linear combinations and calibration. Manage Sci 50:597-604
78. Jacobs RA (1995) Methods for combining experts probability assessments. Neural Comput 7:867-888
79. Johnson CJ, Gillingham MP (2004) Mapping uncertainty: sensitivity of wildlife habitat ratings to expert opinion. J Appl Ecol 41:1032-1041
80. Kadane JB, Dickey JM, Winkler RL et al (1980) Interactive elicitation of opinion for a normal linear model. J Am Stat Assoc 75:845-854
81. Kadane JB, Wolfson LJ (1998) Experiences in elicitation. J Roy Stat Soc D-Sta 47:3-19
82. Kahneman D (1991) Judgment and decision making: a personal view. Psychol Sci 2:142-145
83. Kahneman D, Tversky A (eds) (1982) Judgment under uncertainty: heuristics and biases. Cambridge University Press, Cambridge
84. Kangas AS, Kangas J (2004) Probability, possibility and evidence: approaches to consider risk and uncertainty in forestry decision analysis. For Policy Econ 6:169-188
85. Kaplan S (1992) 'Expert information' versus 'expert opinions'. Another approach to the problem of eliciting/combining/using expert knowledge in PRA. Reliab Eng Syst Safe 35:61-72
86. Kardes FR (2006) When should consumers and managers trust their intuition? J Consum Psychol 16:20-24
87. Keeney RL, von Winterfeldt D (1991) Eliciting probabilities from experts in complex technical problems. IEEE Trans Eng Manage 38:191-201
88. Keith DW (1996) When is it appropriate to combine expert judgments? Climatic Change 33:139-143
89. Kidd A, Welbank M (1984) Knowledge acquisition. In: Fox J (ed) Infotech state of the art report on expert systems. Pergamon, London
90. Kuhnert PM, Martin TG, Griffi ths SP (2010) A guide to eliciting and using expert knowledge in Bayesian ecological models. Ecol Lett 7:900-914
91. Kunda Z (1990) The case for motivated reasoning. Psychol Bull 108:480-498
92. Kynn M (2004) Eliciting expert knowledge for Bayesian logistic regression in species habitat modelling. Department of statistics, Queensland University of Technology, Brisbane
93. Larkin J, McDermott J, Simon DP, Simon, HA (1980) Expert and novice performance in solving physics problems. Science 208:1335-1342
94. Lock A (1987) Integrating group judgments in subjective forecasts. In: Wright G, Ayton P (eds) Judgmental forecasting. Wiley, Chichester, pp 109-128
95. Low-Choy S, O'Leary R, Mengersen K (2009) Elicitation by design in ecology: using expert opinion to inform priors for Bayesian statistical models. Ecology 90:265-277
96. Ludwig D, Mangel M, Haddad B (2001) Ecology, conservation, and public policy. Annu Rev Ecol Syst 32:481-517
97. MacMillan DC, Marshall K (2006) The Delphi process: an expert-based approach to ecological modelling in data-poor environments. Anim Conserv 9:11-19
98. MacNally, R (2007) Consensus weightings of evidence for inferring breeding success in broadscale bird studies. Austral Ecol 32:479-484
99. Marsh H, Dennis A, Hines H et al (2007) Optimizing allocation of management resources for wildlife. Conserv Biol 21:387-399
100. 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 Appl 15:266-280
101. McCoy ED, Sutton PE, Mushinsky HR (1999) The role of guesswork in conserving the threatened sand skink. Conserv Biol 13:190-194
102. Meyer M, Booker J (1991) Eliciting and analyzing expert judgment: a practical guide. Academic Press, New York
103. Morgan MG, Henrion M (1990) Uncertainty: a guide to dealing with uncertainty in quantitative risk and policy analysis. Cambridge University Press, New York
104. Morris PA (1974) Decision analysis expert use. Manage Sci 20:1233-1241
105. Morris PA (1977) Combining expert judgments: a Bayesian approach. Manage Sci 23:679-693
106. Moss R, Schneider, SH (2000) Uncertainties in the IPCC TAR: Recommendations to lead authors for more consistent assessment and reporting. In: Pachauri R, Taniguchi R, Tanaka K (eds) Guidance papers on the cross cutting issues of the third assessment report of the IPCC. World Meteorological Organisation, Geneva, pp 33-51
107. Murphy AH, Winkler RL (1984) Probability forecasting in meteorology. J Am Stat Assoc 79:489-500
108. O'Hagan A (1998) Eliciting expert beliefs in substantial practical applications. J Roy Stat Soc D-Statistics 47:21-35
109. O'Hagan A, Buck CE, Daneshkhah AR et al (2006). Uncertain judgments: eliciting expert probabilities. John Wiley, West Sussex
110. O'Neill SJ, Osborn TJ, Hulme M et al (2008) Using expert knowledge to assess uncertainties in future polar bear populations under climate change. J Appl Ecol 45:1649-1659
111. Otway H, von Winterfeldt D (1992) Expert judgment in risk analysis and management: process, context, and pitfalls. Risk Anal 12:83-93
112. Pate-Cornell ME (1996) Uncertainties in risk analysis: six levels of treatment. Reliab Eng Syst Safe 54:95-111
113. Payne S (1951) The art of asking questions. Princeton University Press, Princeton
114. Pearce JL, Cherry K, Drielsma M et al (2001) Incorporating expert opinion and fi ne-scale vegetation mapping into statistical models of faunal distribution. J Appl Ecol 38:412-424
115. Pellikka J, Kuikka S, Lindén H, Varis O (2005) The role of game management in wildlife populations: uncertainty analysis of expert knowledge. Eur J Wildlife Res 51:48-59
116. Peterson CR, Beach LF (1967) Man as an intuitive statistician. Psychol Bull 68:29-46
117. Price PC (1998) Effects of a relative-frequency elicitation question on likelihood judgment accuracy: the case of external correspondence. Organ Behav Hum Dec 76:277-297
118. Reading RP, Clark TW, Seebeck JH, Pearce J (1996) Habitat suitability index model for the eastern barred bandicoot, Perameles gunnii. Wildlife Res 23:221-235
119. Regan HM, Colyvan M, Burgman MA (2002) A taxonomy and treatment of uncertainty for ecology and conservation biology. Ecol Appl 12:618-628
120. Renooij S (2001) Probability elicitation for belief networks: issues to consider. Knowl Eng Rev 16:255-269
121. Richman HB, Gobet F, Staszewski JJ, Simon HA (1995) Simulation of expert memory using EPAM IV. Psychol Rev 102:305-333
122. Roloff GJ, Kernohan BJ (1999) Evaluating reliability of habitat suitability index models. Wildlife Soc Bull 27:973-985
123. Rosqvist T, Tuominen R (2004) Qualifi cation of formal safety assessment: an exploratory study. Safety Sci 42:99-120
124. Rothlisberger JD, Lodge DM, Cooke RM, Finnoff DC (2010) Future declines of the binational Laurentian Great Lakes fi sheries: the importance of environmental and cultural change. Front Ecol Environ 8:239-244
125. Saati TL (1980) The analytic hierarchy process. New York, McGraw-Hill
126. Sanderson EW, Redford KH, Chetkiewicz CLB et al (2002) Planning to save a species: the jaguar as a model. Conserv Biol 16:58-72
127. Seaver DA (1978) Assessing probability with multiple individuals: group interaction versus mathematical aggregation. Social Science Research Institute, University of Southern California, Los Angeles. Report# SSRI-78-3
128. Shanteau J (1992) Competence in experts: the role of task characteristics. Organ Behav Hum Dec 53:252-266
129. Shanteau J, Stewart TR (1992) Why study expert decision-making: some historical perspectives and comments. Organ Behav Hum Dec 53:95-106
130. Shephard GG, Kirkwood CW (1994) Managing the judgmental probability elicitation process: a case study of analyst/manager interaction. IEEE Trans Eng Manage 41:414-425
131. Shrader-Frechette K (1996) Value judgments in verifying and validating risk assessment models. In: Cothern CR (ed) Handbook for environmental risk decision making: values, perception and ethics. CRC Lewis Publishers, Boca Raton, pp 291-309
132. Slottje P, van der Sluijs JP, Knol AB (2008) Expert elicitation: methodological suggestions for its use in environmental health impact assessments. RIVM, Copernicus Institute for Sustainable Development and Innovation., Bilthoven. Report 630004001/2008
133. Slovic P (1999) Trust, emotion, sex, politics and science: surveying the risk-assessment battlefi eld. Risk Anal 19:689-701
134. Slovic P, Finucane ML, Peters E, MacGregor DG (2004) Risk as analysis and risk as feelings: some thoughts about affect, reason, risk, and rationality. Risk Anal 24:311-322
135. Slovic P, Monahan J, MacGregor DG (2000) Violence risk assessment and risk communication: the effects of using actual cases, providing instruction, and employing probability versus frequency formats. Law Human Behav 24:271-296
136. Speirs-Bridge A, Fidler F, McBride M et al (2010) Reducing overconfi dence in the interval judgments of experts. Risk Anal 30:512-523
137. Spetzler CS, Stael Von Holstein CAS (1975) Probability encoding in decision analysis. Manage Sci 22:340-358
138. Stern PC, Fineberg HV (eds) (1996) Understanding risk: informing decisions in a democratic society. National Academies Press, Washington
139. Sutherland WJ (2006) Predicting the ecological consequences of environmental change: a review of the methods. J Appl Ecol 43:599-616
140. Sutherland WJ, Bailey MJ, Bainbridge IP et al (2008) Future novel threats and opportunities facing UK biodiversity identifi ed by horizon scanning. J Appl Ecol 45:821-833
141. Sutherland WJ, Pullin AS, Dolman PM, Knight TM (2004) The need for evidence-based conservation. Trends Ecol Evol 19:305-308
142. Tallman I, Leik RK, Gray LN, Stafford MC (1993) A theory of problem-solving behavior. Soc Psychol Quart 56:157-177
143. Tavana M, Kennedy DT, Mohebbi B (1997) An applied study using the analytic hierarchy process to translate common verbal phrases to numerical probabilities. J Behav Dec Making 10:133-150
144. Teck SJ, Halpern BS, Kappel CV et al (2010) Using expert judgment to estimate marine ecosystem vulnerability in the California Current. Ecol Appl 20:1402-1416
145. Tversky A, Kahneman D (1974) Judgment under uncertainty: heuristics and biases. Science 185:1124-1131
146. Tversky A, Kahneman D (1983) Extensional versus intuitive reasoning: the conjunction fallacy in probability judgment. Psychol Rev 90:293-315
147. Tversky A, Koehler DJ (1994) Support theory: a nonextensional representation of subjective-probability. Psychol Rev 101:547-567
148. van der Gaag LC, Renooij S, Witteman CLM et al (1999) How to elicit many probabilities. In: Laskey KB, Prade H (eds) Proceedings of the 15th Conference on Uncertainty in Artifi cial Intelligence, Stockholm, July-August 1999. Morgan Kaufmann, San Francisco
149. van der Gaag LC, Renooij S, Witteman CLM et al (2002) Probabilities for a probabilistic network: a case study in oesophageal cancer. Artif Intell Med 25:123-148
150. van Steen JFJ (1992) A perspective on structured expert judgment. J Hazard Mater 29:365-385
151. von Winterfeldt D, Edwards W (1986) Decision analysis and behavioral research. Cambridge University Press, Cambridge
152. Walls L, Quigley J (2001) Building prior distributions to support Bayesian reliability growth modelling using expert judgement. Reliab Eng Syst Safe 74:117-128
153. Wallsten TS, Budescu DV (1995) A review of human linguistic probability processing: general principles and empirical evidence. Knowl Eng Rev 10:43-62
154. Wallsten TS, Budescu DV, Erev I, Diederich A (1997) Evaluating and combining subjective probability estimates. J Behav Dec Making 10:243-268
155. Wallsten TS, Budescu DV, Rapoport A et al (1986) Measuring the vague meanings of probability terms. J Exp Psychol Gen 115:348-365
156. Whitfi eld DP, Ruddock M, Bullman R (2008) Expert opinion as a tool for quantifying bird tolerance to human disturbance. Biol Conserv 141:2708-2717
157. Wilson AG (1994) Cognitive factors affecting subjective probability assessment. Duke University, Institute of Statistics and Decision Sciences, Durham. Report #94-02
158. Windschitl PD, Wells GL (1996) Measuring psychological uncertainty: verbal versus numeric methods. J Exp Psychol-Appl, 2:343-364
159. Winkler RL, Makridakis S (1983) The combination of forecasts. J Roy Stat Soc A-Sta 146:150-157
160. Yamada K, Elith J, McCarthy M, Zerger A (2003) Eliciting and integrating expert knowledge for wildlife habitat modelling. Ecol Model 165:251-264