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Model development in freshwater ecology with a case study using evolutionary computation

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초록

Ecological modeling faces some unique problems in dealing with complex environment-organism relationships,making it one of the toughest domains that might be encountered by a modeler. Newer technologies and ecosystem modeling paradigms have recently been proposed, all as part of a broader effort to reduce the uncertainty in models arising from qualitative and quantitative imperfections in the ecological data. In this paper, evolutionary computation modeling approaches are introduced and proposed as useful modeling tools for ecosystems. The results of our case study support the applicability of an algal predictive model constructed via genetic programming. In conclusion, we propose that evolutionary computation may constitute a powerful tool for the modeling of highly complex objects, such as river ecosystems.

Abstract

Ecological modeling faces some unique problems in dealing with complex environment-organism relationships,making it one of the toughest domains that might be encountered by a modeler. Newer technologies and ecosystem modeling paradigms have recently been proposed, all as part of a broader effort to reduce the uncertainty in models arising from qualitative and quantitative imperfections in the ecological data. In this paper, evolutionary computation modeling approaches are introduced and proposed as useful modeling tools for ecosystems. The results of our case study support the applicability of an algal predictive model constructed via genetic programming. In conclusion, we propose that evolutionary computation may constitute a powerful tool for the modeling of highly complex objects, such as river ecosystems.

참고문헌 (91)

  1. Adams DC, "Resampling tests for meta-analysis of ecological data", Ecology, 78, pp.1277~1283 (1997)
  2. Ahmed JA, "Genetic algorithm for optimal operating policy of a multipurpose reservoir", Water Resour Manag, 19, pp.145~161 (2005)
  3. 안광국, "안동호와 임하호에서 관측한 장기 수질자료의 비교 분석", 한국하천호수학회지, 39(1), pp.21~31 (2006), 한국하천호수학회
  4. Arhonditsis GB, "Eutrophication model for Lake Washington (USA): part I. model description and sensitivity analysis", Ecol Model, 187, pp.140~178 (2005)
  5. Atanasova N, "Computational assemblage of ordinary differential equations for chlorophyll-a using a lake process equation library and measured data of Lake Kasumigaura. in: Ecological Informatics: Scope, Techniques and Applications", pp.409~428 (2006), Springer-Verlag
  6. Bobbin J, "Knowledge discovery for prediction and explanation of blue-green algal dynamics in lakes by evolutionary algorithms", Ecol Model, 146, pp.253~262 (2001)
  7. Boerema LK, "Stock assessment of the peruvian anchovy (Engraulis ringens) and management of the fishery", J Fish Res Board Can, 30, pp.2226~2235 (1973)
  8. Brown LC, "The Enhanced Stream Water Quality Models QUAL2E and QUAL2E-UNCAS: Documentation and User Manual. EPA", 600, 007. U.S. Environmental Protection Agency, Athens, GA, 1987[DOI]
  9. Cao H, "Process-based simulation library SALMO-OO for lake ecosystems: part 2. multi-objective parameter optimization by evolutionary algorithms", Ecol Inform, 3, pp.181~190 (2008)
  10. Cao H, "Discovery of predictive rule sets for chlorophyll-a dynamics in the Nakdong River (Korea) by means of the hybrid evolutionary algorithm HEA", Ecol Inform, 1, pp.43~53 (2006)
  11. Cetin L, "Process-based simulation library SALMO-OO for lake ecosystems", International Congress on Modelling and Simulation, pp.318~324 (2005)
  12. Chapra SC, "Engineering Approaches for Lake Management. Vol. II: Mechanistic Modeling" (1983), Butterworth Publishers
  13. 조재현, "영향계수법과 유전알고리즘을 이용한 QUAL2K 모형의 매개변수 최적화", 환경영향평가, 18(2), pp.99~109 (2009), 한국환경영향평가학회
  14. 조재현, "유전알고리즘을 이용한 하천수질관리모형에 관한 연구", 상하수도학회지, 18(4), pp.453~460 (2004), 대한상하수도학회
  15. Cho JH, "A river water quality manage ment model for optimising regional wastewater treatment using a genetic algorithm", J Environ Manag, 73, pp.229~242 (2004)
  16. 최정규, "부영양 하천의 수질예측을 위한 QUAL2E와 QUAL-NIER 모델의 비교 평가", 한국물환경학회지, 24(1), pp.54~62 (2008), 한국물환경학회
  17. Chon TS, "Patterning of community changes in bentic macroinvertebrates collected from urbanized streams for the short term prediction by temporal artificial neuronal networks. In: Artificial Neuronal Networks: Application to Ecology and Evolution" (2000), Springer
  18. Chon TS, "Patterning and short-term predictions of benthic macroinvertebrate community dynamics by using a recurrent artificial neural network", Ecol Model, 146, pp.181~193 (2001)
  19. Cloern JE, "Phytoplankton bloom dynamics in coastal ecosystems: a review with some general lessons from sustained investigation of San Francisco Bay, California", Rev Geophys, 34, pp.127~168 (1996)
  20. Deaton ML, "Dynamic Modeling of Environmental Systems" (2000), Springer-Verlag
  21. Dolk DR, "Integrated model management in the data warehouse era", Eur J Oper Res, 122, pp.199~218 (2000)
  22. Dorado J, "Prediction and modelling of the flow of a typical urban basin through genetic programming. In: Applications of Evolutionary Computing", pp.190~201 (2002), Springer
  23. Everbecq E, "Potamon: a dynamic model for predicting phytoplankton composition and biomass in lowland rivers", Water Res, 35, pp.901~912 (2001)
  24. Fielding AH, "An introduction to machine learning methods. In: Machine Learning Methods for Ecological Applications" (1999), Kluewer Academic Publishers
  25. Giraudel JL, "A comparison of self-organizing map algorithm and some conventional statistical methods for ecological community ordination", Ecol Model, 146, pp.329~339 (2001)
  26. Goethals P, "Development and application of predictive river ecosystem models based on classification trees and artificial neural networks. In: Ecological Informatics", pp.91~107 (2003), Springer-Verlag
  27. Goethals PLM, "Applications of artificial neural networks predicting macroinvertebrates in freshwaters", Aquat Ecol, 41, pp.491~508 (2007)
  28. Ha K, "Role of silica in phytoplankton succession: an enclosure experiment in the downstream Nakdong River (Mulgum)", Korean J Ecol, 23, pp.299~307 (2000)
  29. Ha K, "Winter Stephanodiscus bloom development in the Nakdong River regulated by an estuary dam and tributaries", Hydrobiologia, 506, pp.221~227 (2003)
  30. Ha K, "Microcystis bloom formation in the lower Nakdong River, South Korea: importance of hydrodynamics and nutrient loading", Mar Freshw Res, 50, pp.89~94 (1999)
  31. Håkanson L, "A general dynamic model to predict biomass and production of phytoplankton in lakes", Ecol Model, 165, pp.285~301 (2003)
  32. Harding LW, "Long-term increase of phytoplankton biomass in Chesapeake Bay, 1950-1994", Mar Ecol Prog Ser, 157, pp.39~52 (1994)
  33. Holland JH, "Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence" (1975), University of Michigan Press
  34. Icaga Y, "Genetic algorithm usage in water quality monitoring networks optimization in Gediz (Turkey) river basin", Environ Monit Assess, 108, pp.261~277 (2005)
  35. Jeong KS, "Prediction and elucidation of population dynamics of a blue-green algae (Microcystis aeruginosa) and diatom (Stephanodiscus hantzschii) in the Nakdong River-Reservoir System (South Korea) by artificial neural networks. In: Ecological Informatics: Scope, Techniques and Applications", pp.255~273 (2006), Springer
  36. Jeong KS, "Modelling Microcystis aeruginosa bloom dynamics in the Nakdong River by means of evolutionary computation and statistical approach", Ecol Model, 161, pp.67~78 (2003)
  37. Jeong KS, "Prediction and elucidation of phytoplankton dynamics in the Nakdong River(Korea)by means of a recurrent artificial neural network.Ecol Model 146:115-129", Ecol Model, 146, pp.115~129 (2001)
  38. Jeong KS, "Non-linear autoregressive modelling by Temporal Recurrent Neural Networks for the prediction of freshwater phytoplankton dynamics", Ecol Model, 211, pp.292~300 (2008)
  39. Joo GJ, "Long-term trend of the eutrophication of the lower Nakdong River", Korean J Limnol, 30, pp.472~480 (1997)
  40. Jørgensen SE, "Integration of Ecosystem Theories: A Pattern" (1992), Kluwer Academic Publishers
  41. Khu ST, "Ge netic programming and its application in real-time runoff forecasting", J Am Water Resour Assoc, 37, pp.439~451 (2001)
  42. Kilham P, "Hypothesized resource relationships among African planktonic diatoms", Limnol Oceanogr, 31, pp.1169~1181 (1986)
  43. Kim DK, "Winter diatom blooms in a regulated river in South Korea: explanations based on evolutionary computation", Freshw Biol, 52, pp.2021~2041 (2007)
  44. Kim DK, "Predictive function and rules for population dynamics of Microcystis aeruginosa in the regulated Nakdong River (South Korea), discovered by evolutionary algorithms", Ecol Model, 203, pp.147~156 (2007)
  45. 김경아, "다변량 통계분석을 이용한 낙동강 상수원수의 수질변화 특성 조사", 한국물환경학회지, 23(6), pp.814~821 (2007), 한국물환경학회
  46. Kim HW, "Eutrophication of the lower Nakdong River after the construction of an estuarine dam in 1987", Int Rev Hydrobiol, 83, pp.65~72 (1987)
  47. Kim HW, "Zooplankton grazing on bacteria and phytoplankton in a regulated large river (Nakdong River, Korea)", J Plankton Res, 22, pp.1559~1577 (2000)
  48. Kim LH, "Phosphorus release rates from sediments and pollutant characteristics in Han River, Seoul, Korea", Sci Total Environ, 321, pp.115~125 (2004)
  49. Koza JR, "Genetic Programming: On the Programming of Computers by Means of Natural Selection" (1992), The MIT Press
  50. Lavric V, "Genetic algorithm optimisation of water consumption and wastewater network topology", J Clean Prod, 13, pp.1405~1415 (2005)
  51. 이길성, "유전자 알고리즘을 이용한 댐군의 최적운영방안", 대한토목학회 논문집B, 24(1B), pp.9~17 (2004), 대한토목학회
  52. Lek S, "Uncertainty in ecological models", Ecol Model, 207, pp.1~2 (2007)
  53. Lek S, "Application of neural networks to modelling nonlinear relationships in ecology", Ecol Model, 90, pp.39~52 (1996)
  54. Lotka AJ, "Elements of Physical Biology" (1925), Dover Publications
  55. Magadza CHD, "The distribution of zooplankton in the Sanyati Bay, Lake Kariba: a multivariate analysis", Hydrobiologia, 70, pp.57~67 (1980)
  56. Makkeasorn A, "Seasonal change detection of riparian zones with remote sensing images and genetic programming in a semi-arid watershed", J Environ Manag, 90, pp.1069~1080 (2009)
  57. Matta JF, "A multivariate analysis of phytoplankton assemblages in the western North Atlantic", J Plankton Res, 6, pp.663~675 (1984)
  58. McKay RIB, "Model-building with interpolated temporal data", Ecol Inform, 1, pp.259268~ (2006)
  59. McNyset KM, "Use of ecological niche modelling to predict distributions of freshwater fish species in Kansas", Ecol Freshw Fish, 14, pp.243~255 (2005)
  60. Mishra AK, "Drought forecasting using feed-forward recursive neural network", Ecol Model, 98, pp.127~138 (2006)
  61. Odum HT, "Ecological and General Systems: An Introduction to Systems Ecology" (1983), University Press of Colorado
  62. Paik K, "A conceptual rainfall-runoff model considering seasonal variation", Hydrol Process, 19, pp.3837~3850 (2005)
  63. Park SS, "A water quality modeling study of the Nakdong River, Korea", Ecol Model, 152, pp.65~75 (2002)
  64. Park SY, "Design of a water quality monitoring network in a large river system using the genetic algorithm", Ecol Model, 199, pp.289~297 (2006)
  65. Park YS, "Application of a self-organizing map to select representative species in multivariate analysis: a case study determining diatom distribution patterns across France", Ecol Inform, 1, pp.247~257 (2006)
  66. Pelletier GJ, "QUAL2Kw: a framework for modeling water quality in streams and rivers using a genetic algorithm for calibration", Environ Model Software, 21, pp.419~425 (2006)
  67. Peterson AT, "Predicting distributions of Mexican birds using ecological niche modelling methods", Ibis, 144, pp.E27~E32 (2002)
  68. Rabuñal JR, "Determination of the unit hydrograph of a typical urban basin using genetic programming and artificial neural networks", Hydrol Process, 21, pp.476~485 (2007)
  69. Recknagel F, "Applications of machine learning to ecological modelling", Ecol Model, 146, pp.303~310 (2001)
  70. Recknagel F, "Ecological Informatics: Scope, Techniques and Applications" (2006), Springer-Verlag
  71. Recknagel F, "Validation of the ecological simulation model “SALMO”", Int Rev Gesamten Hydrobiol, 67, pp.113~125 (1982)
  72. Recknagel F, "Comparative application of artificial neural networks and genetic algorithms for multivariate time-series modelling of algal blooms in freshwater lakes", J Hydroinformatics, 4, pp.125~133 (2002)
  73. Recknagel F, "Generic limnological models on the touchstone: testing the lake simulation library SALMO-OO and the rule-based Microcystis agent for warm-monomictic hypertrophic lakes in South Africa", Ecol Model, 215, pp.144~158 (2008)
  74. Romo S, "A multivariate analysis of phytoplankton and food web changes in a shallow biomanipulated lake", Freshw Biol, 36, pp.683~696 (1996)
  75. Savic DA, "A genetic programming approach to rainfall-runoff modelling", Water Resour Manag, 13, pp.219~231 (1999)
  76. Schaefer MB, "Methods of estimating effects of fishing on fish populations", Trans Am Fish Soc, 97, pp.231~241 (1968)
  77. Shan Y, "Machine learning of poorly predictable ecological data", Ecol Model, 195, pp.129~138 (2006)
  78. Shim SB, "Eutrophication forecasting of Daechong Reservoir using WASP5 water quality model", J Inst Constr Technol, 14, pp.41~53 (1995)
  79. Silvert W, "Ecological impact classification with fuzzy sets", Ecol Model, 96, pp.1~10 (1997)
  80. Stockman AK, "An evaluation of a GARP model as an approach to predicting the spatial distribution of non-vagile invertebrate species", Divers Distrib, 12, pp.81~89 (2006)
  81. ter Braak CJF, "Canonical correspondence analysis and related multivariate methods in aquatic ecology", Aquat Sci, 57, pp.255~289 (1995)
  82. Underwood EC, "Predicting patterns of non-native plant invasions in Yosemite National Park, California, USA", Divers Distrib, 10, pp.447~459 (2004)
  83. van Tongeren OFR, "Multivariate analysis of the plankton communities in the Loosdrecht lakes: relationship with the chemical and physical environment", Hydrobiologia, 233, pp.105~117 (1992)
  84. Volterra V, "Fluctuations in the abundance of a species considered mathematically", Nature, 118, pp.558~560 (1926)
  85. Welk A, "Rule-based agents for forecasting algal population dynamics in freshwater lakes discovered by hybrid, evolutionary algorithms", Ecol Inform, 3, pp.46~54 (2008)
  86. Whigham PA, "Induction of a marsupial density model using genetic programming and spatial relationships", Ecol Model, 131, pp.299~317 (2000)
  87. Whigham PA, "An inductive approach to ecological time series modelling by evolutionary computation", Ecol Model, 146, pp.275~287 (2001)
  88. Whigham PA, "Predicting chlorophyll-a in freshwater lakes by hybridising process-based models and genetic algorithms", Ecol Model, 146, pp.243~251 (2001)
  89. 유호식, "한강수질에 영향을 끼치는 요인들의 통계분석", 대한환경공학회지, 24(12), pp.2139~2150 (2002), 대한환경공학회
  90. Zar JH, "Biostatistical Analysis" (1999), Prentice-Hall
  91. Zuur AF, "Limitations of linear regression applied on ecological data. In: Mixed Effects Models and Extensions in Ecology with R", pp.11~33 (2009), Springer

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