Fuzzy cognitive mapping as a tool to define management objectives for complex ecosystems

Ecological Applications

Volumn 12, Issue 5, 2002, Pages 1548-1565

  Hobbs, Benjamin F ^a   Ludsin, Stuart A ^b,g   Knight, Roger L ^c   Ryan, Phil A ^d   Biberhofer, Johann ^e   Ciborowski, Jan J H ^f  

^a JOHNS HOPKINS UNIVERSITY   (United States)

^b OHIO STATE UNIVERSITY   (United States)

^c OHIO DEPARTMENT OF NATURAL RESOURCES   (United States)

^d ONTARIO MINISTRY OF NATURAL RESOURCES   (Canada)

^e ENVIRONMENT CANADA   (Canada)

^f UNIVERSITY OF WINDSOR   (Canada)

^g UNIVERSITY OF WINDSOR   (Canada)

Author keywords

Cluster analysis; Ecosystem management; Ecosystem modeling; Fisheries management; Fuzzy cognitive maps; Fuzzy sets; Lake Erie watershed; Principal components analysis

Indexed keywords

ECOSYSTEM MANAGEMENT; ECOSYSTEM MODELING; FUZZY MATHEMATICS; RESTORATION ECOLOGY; WATERSHED;

GREAT LAKES (LAKE ERIE); NORTH AMERICA;

EID: 0036826037     PISSN: 10510761     EISSN: None     Source Type: Journal    
DOI: 10.1890/1051-0761(2002)012[1548:FCMAAT]2.0.CO;2     Document Type: Article

References (79)

1. Anderberg, M. R. 1973. Clustering analysis for applications. Academic Press, New York, New York, USA.
2. Anderson, R. A., B. F. Hobbs, J. F. Koonce, and A. B. Locci. 2001. Using decision analysis to choose phosphorus targets for Lake Erie. Environmental Management 28:235-252.
3. Axelrod, R. M., editor. 1976. Structure of decision: the cognitive map of political elites. Princeton University Press, Princeton, New Jersey, USA.
4. Barros, L. C., R. C. Bassanezi, and P. A. Tonelli. 2000. Fuzzy modeling in population dynamics. Ecological Modelling 128:27-33.
5. Bertram, P. E., and T. B. Reynoldson. 1992. Developing ecosystem objectives for the Great Lakes: policy, progress, and public participation. Journal of Aquatic Ecosystem Health 1:89-95.
6. Bock, W., and A. Salski. 1998. A fuzzy knowledge-based model of population dynamics of the Yellow-necked mouse in a beech forest. Ecological Modelling 108:155-161.
7. Borsuk, M. E., R. T. Clemen, L. A. Maguire, and K. H. Reckhow. 2001. Stakeholder values and scientific modeling in the Neuse River Watershed. Group Decision and Negotiation 10:355-373.
8. Bosserman, R. W., and R. K. Ragade. 1982. Ecosystem analysis using fuzzy set-theory. Ecological Modelling 16:191-208.
9. Buede, D. M., and D. O. Ferrell. 1993. Convergence in problem solving: a prelude to quantitative analysis. IEEE Transactions on Systems, Man, and Cybernetics 23:746-765.
10. Burgman, M. A., D. R. Breininger, B. W. Duncan, and S. Ferson. 2001. Setting reliability bounds on habitat suitability indices. Ecological Applications 11:70-78.
11. Burns, N. M. 1985. Erie: the lake that survived. Rowman and Allanheld, Totowa, New Jersey, USA.
12. Canada and United States of America. 1987. Great lakes water quality agreement of 1978. Agreement, with annexes and terms of reference, between the United States and Canada signed at Ottawa, November 2, 1978; and Phosphorus load reduction supplement signed October 7, 1983 as amended by Protocol signed November 18, 1987. Consolidated by the International Joint Commission, Windsor, Ontario, Canada.
13. Chung, F.-L., and T. Lee. 1997. A new look at solving a system of fuzzy relational equations. Fuzzy Sets and Systems 88:343-353.
14. Colavecchia, M., S. Ludsin, P. Bertram, R. Knight, S. George, H. Biberhofer, and P. Ryan. 2000. Identification of ecosystem alternatives for Lake Erie to support development of ecosystem objectives. Ecosystem Objectives Subcommittee, Lake Erie Lakewide Management Plan, Environment Canada, Burlington, Ontario, Canada.
15. Cottle, R. W., J. S. Pang, and R. E. Stone. 1992. The linear complementarity problem. Academic Press, New York, New York, USA.
16. Daunicht, W., A. Salski, P. Nohr, and C. Neubert. 1996. A fuzzy knowledge-based model of annual production of skylarks. Ecological Modelling 85:67-73.
17. Droesen, W. J. 1996. Formalisation of ecohydrological expert knowledge applying fuzzy techniques. Ecological Modelling 85:75-81.
18. DiToro, D. M., and J. P. Connolly. 1980. Mathematical models of water quality in large lakes. Part 2: Lake Erie. Report No. EPA-600/3-80-065. U.S. EPA, Large Lakes Research Station, ERL-Duluth, Grosse Ile, Michigan, USA.
19. Ducey, M. J., and B. C. Larson. 1999. A fuzzy set approach to the problem of sustainability. Forest Ecology and Management 115:29-40.
20. Eden, C. 1988. Cognitive mapping. European Journal of Operational Research 36:1-13.
21. Enea, M., and G. Salemi. 2001. Fuzzy approach to environmental impact evaluation. Ecological Modelling 136:131-147.
22. Freyer, B., Y. Reisner, and D. Zuberbuhler. 2000. Potential impact model to assess agricultural pressure to landscape ecological functions. Ecological Modelling 130:121-129.
23. Gauch, H. G. 1982. Multivariate analyses in community ecology. Cambridge University Press, New York, New York, USA.
24. Harris, H. J., R. B. Wenger, V. A. Harris, and D. S. DeVault. 1994. A method for assessing environmental risk: a case-study of Green Bay, Lake Michigan, USA. Environmental Management 18:295-306.
25. Hartman, W. L. 1972. Lake Erie: effects of exploitation, environmental changes and new species on the fisheries resources. Journal of the Fishery Resources Board of Canada 29:899-912.
26. Holland, R. E., T. H. Johengen, and A. M. Beeton. 1995. Trends in nutrient concentration in Hatchery Bay, western Lake Erie, before and after Dreissena polymorpha. Canadian Journal of Fisheries and Aquatic Sciences 52:1202-1209.
27. Holling, C. S. 1978. Adaptive environmental assessment and management. J. Wiley, London, UK.
28. Hutchinson, G. E. 1978. An introduction to population ecology. Yale University Press, New Haven, Connecticut, USA.
29. Johnson, B. L., H. E. Hicks, and C. T. DeRosa. 1999. Key environmental human health issues in the Great Lakes and St. Lawrence River basins. Environmental Research 80:S-12(Part 2).
30. Jongman, R. H. G., C. J. F. ter Braak, and O. F. R. van Tongeren. 1995. Data analysis in community and landscape ecology. Cambridge University Press, Cambridge, UK.
31. Kosko, B. 1992. Neural networks and fuzzy systems: a dynamical systems approach to machine intelligence. Prentice Hall, Englewood Cliffs, New Jersey, USA.
32. Lake Erie Lakewide Management Plan. 2000. Lake Erie Lakewide Management Plan 2000 report. Ohio Environmental Protection Agency, Columbus, Ohio, USA.
33. Lam, D. C. L., and T. J. Simons. 1976. Numerical computations of advective and diffusive transports of chloride, 1970. Journal of the Fisheries Resources Board of Canada 33:537-549.
34. Leach, J. H., and S. J. Nepszy. 1976. The fish community in Lake Erie. Journal of the Fisheries Research Board of Canada 33:622-638.
35. Levins, R. 1966. The strategy of model building in population biology. American Scientist 54:421-431.
36. Locci, A. B., and J. F. Koonce. 1999. A theoretical analysis of food web constraints on walleye dynamics in Lake Erie. Pages 497-510 in M. Munawar, T. Edsall, and I. F. Munawar, editors. State of Lake Erie: past, present, and future. Backhuys, Leiden, The Netherlands.
37. Ludsin, S. A., P. Bertram, H. Biberhofer, J. J. H. Ciborowski, M. Colavecchia, S. George, B. F. Hobbs, R. L. Knight, and P. A. Ryan. 2002. Identification of future ecosystem management objectives for Lake Erie: a fuzzy-cognitive modeling approach. In J. J. H. Ciborowski, M. N. Charlton, R. G. Kreis, Jr., and J. M. Reutter, editors. Lake Erie at the millennium: changes, trends, and trajectories. Canadian Scholars' Press, Toronto, Canada.
38. Ludsin, S. A., M. W. Kershner, K. A. Blocksom, R. L. Knight, and R. A. Stein. 2001. Life after death in Lake Erie: nutrient controls drive fish species richness, rehabilitation. Ecological Applications 11:731-746.
39. Mackinson, S. 2001. Integrating local and scientific knowledge: an example in fisheries science. Environmental Management 27:533-545.
40. Makarewicz, J. C., and P. Bertram. 1991. Evidence for the restoration of the Lake Erie ecosystem. BioScience 41:216-223.
41. Marchant, T. 1999. Cognitive maps and fuzzy implications. European Journal of Operational Research 114:626-637.
42. Mas-Colell, A., M. Whinston, and J. R. Green. 1995. Microeconomic theory. Oxford University Press, New York, New York, USA.
43. Matlock, M. D., D. E. Storm, J. G. Sabbagh, C. T. Hann, M. D. Smolen, and S. L. Burks. 1994. An ecological risk assessment paradigm using the Spatially Integrated Model for Phosphorus Loading and Erosion (SIMPLE). Journal of Aquatic Ecosystem Health 3:287-294.
44. McCune, B., and M. J. Mefford. 1995. PC-ORD: multivariate analysis of ecological data. Version 2.0. MjM Software Design, Gleneden Beach, Oregon, USA.
45. McGlade, J. M., editor. 1999. Advanced ecological theory: principles and applications. Blackwell Science, Oxford, UK.
46. McNeill, F., and E. Thro. 1994. Fuzzy logic: a practical approach. Academic Press, New York, New York, USA.
47. McQueen, D. J., J. R. Post, and E. L. Mills. 1986. Trophic relationships in fresh-water pelagic ecosystems. Canadian Journal of Fisheries and Aquatic Sciences 43:1571-1581.
48. Meesters, E. H., R. P. M. Bak, S. Westmacott, M. Ridgley, and S. Dollar. 1998. A fuzzy logic model to predict coral reef development under nutrient and sediment stress. Conservation Biology 12(5):957-965.
49. Mills, E. L., J. H. Leach, J. T. Carlton, and C. L. Secor. 1993. Exotic species in the Great Lakes: a history of biotic crisis and anthropogenic introductions. Journal of Great Lakes Research 19:1-54.
50. Minns, C. K. 1992. Use of models for integrated assessment of ecosystem health. Journal of Aquatic Ecosystem Health 1:109-118.
51. Munda, G. 1995. Multicriteria evaluation in a fuzzy environment: theory and applications in ecological economics. Physica-Verlag Heidelberg, Heidelberg, Germany.
52. Ney, J. J. 1996. Oligotrophication and its discontents: effects of reduced nutrient loading on reservoir fisheries. American Fisheries Society Symposium 16:285-295.
53. Nicholls, K. H., and C. Tudorancea. 2001. Application of fuzzy cluster analysis to Lake Simcoe crustacean zooplankton community structure. Canadian Journal of Fisheries and Aquatic Sciences 58:231-240.
54. Novello-Hogarth, A., and J. M. McGlade. 1997. Sustainable management of coastal resources. HYDRO International 1(October):6-9.
55. Parashar, A., R. Paliwal, and P. Rambabu. 1997. Utility of fuzzy cross-impact simulation in environmental assessment. Environmental Impact Assessment Review 40:427-447.
56. Pedrycz, W. 1991a. Processing in relational structures: fuzzy relational equations. Fuzzy Sets and Systems. 40:77-106.
57. Pedrycz, W. 1991b. Fuzzy modeling: fundamentals, construction, and evaluation. Fuzzy Sets and Systems 41:1-15.
58. Radomski, P. J., and T. J. Goeman. 1996. Decision making and modeling in freshwater sport-fisheries management. Fisheries 21(12):6-11.
59. Ramsey, F. L. 1986. A fable of PCA. American Statistician 40:323-324.
60. Redfield, G. W. 2000. Ecological research for aquatic science and environmental restoration in south Florida. Ecological Applications 10:990-1005.
61. Roberts, D. W. 1989. Analysis of forest succession with fuzzy graph theory. Ecological Modelling 45:261-274.
62. Ryan, P. A., L. D. Witzel, J. R. Paine, M. J. Freeman, M. Hardy, S. Scholten, J. L. Sztramko, and R. MacGregor. 1999. Recent trends in fish populations in eastern Lake Erie in relation to changing trophic state and food web. Pages 241-289 in M. Munawar and T. Edsall, editors. State of Lake Erie (SOLE): past, present, and future. Backhuys, Leiden, The Netherlands.
63. Salski, A. 1992. Fuzzy knowledge-based models in ecological research. Ecological Modelling 63:103-112.
64. Salski, A., O. Franzle, and P. Kandzia, editors. 1996. Fuzzy logic in ecological modelling. Ecological Modelling 85:1-98.
65. Silvert, W. 2000. Fuzzy indices of environmental conditions. Ecological Modelling 130(1-3):111-119.
66. Simons, T. J. 1976. Continual dynamical computations of water transports in Lake Erie for 1970. Journal of the Fisheries Research Board of Canada 33:371-384.
67. Smith, P. N. 1999. Environmental project evaluation based on fuzzy relational equations. Journal of Environmental Systems 27:113-125.
68. Stansbury, J., I. Bogardi, and E. Z. Stakhiv 1999. Risk-cost optimization under uncertainty for dredged material disposal. Journal of Water Resources Planning and Management 125:342-351.
69. Stockner, J. G., E. Rydin, and P. Hyenstrand. 2000. Cultural oligotrophication: causes and consequences for fishery resources. Fisheries 25(5):7-14.
70. Sun, R. 1994. A neural network model of causality. IEEE Transactions on Neural Networks 5:604-611.
71. Tester, J. R., A. M. Starfield, and L. E. Frelich. 1997. Modeling for ecosystem management in Minnesota pine forests. Biological Conservation 80:313-324.
72. Thomann, R. V. 1998. The future "golden age" of predictive models for surface water quality and ecosystem management. Journal of Environmental Engineering (American Society of Civil Engineers) 124:94-103.
73. Tsadiras, A. K., and K. G. Margaritis. 1999. An experimental study of the dynamics of the certainty neuron fuzzy cognitive maps. Neurocomputing 24:95-116.
74. Ulengin, F., and I. Topcu. 1997. Cognitive map: KBDSS integration in transportation planning. Journal of the Operational Research Society 48:1065-1078.
75. van der Werf, H. M. G., and C. Zimmer. 1998. An indicator of pesticide environmental impact based on a fuzzy expert system. Chemosphere 36:2225-2249.
76. Walters, C., J. Korman, L. E. Stevens, and B. Gold. 2000. Ecosystem modeling for evaluation of adaptive management in the Grand Canyon. Conservation Ecology 2(4):9-14.
77. Ward, J. 1973. Hierarchical grouping to optimize an objective function. Journal of the American Statistical Association 58:236-244.
78. Wu, H. I., B. L. Li, R. Stoker, and Y. Li. 1996. A semi-arid grazing ecosystem simulation model with probabilistic and fuzzy parameters. Ecological Modelling 90:147-160.
79. Zadeh, L. 1965. Fuzzy sets. Information and Control 8:338-353.