Agent-Based Models in Ecology: Patterns and Alternative Theories of Adaptive Behaviour

Ecologists have used agent-based models for a long time, but refer to them as “individual-based models” (IBMs). Common characteristics of IBMs are discrete representation of unique individuals; local interactions; use of adaptive, fitness-seeking behaviour; explicit representation of how individuals and their environment affect each other; and representation of full life cycles.

[1]  Karin Frank,et al.  Pattern-oriented modelling in population ecology , 1996 .

[2]  Steven F. Railsback,et al.  Concepts from complex adaptive systems as a framework for individual-based modelling , 2001 .

[3]  H. Shugart A Theory of Forest Dynamics , 1984 .

[4]  Christian Wissel,et al.  Reconstructing spatiotemporal dynamics of Central European natural beech forests: the rule-based forest model BEFORE , 2004 .

[5]  Howard B. Stauffer,et al.  WHAT CAN HABITAT PREFERENCE MODELS TELL US? TESTS USING A VIRTUAL TROUT POPULATION , 2003 .

[6]  Steven F. Railsback,et al.  ANALYSIS OF HABITAT‐SELECTION RULES USING ANINDIVIDUAL‐BASED MODEL , 2002 .

[7]  Thorsten Wiegand,et al.  RULE-BASED ASSESSMENT OF SUITABLE HABITAT AND PATCH CONNECTIVITY FOR THE EURASIAN LYNX , 2002 .

[8]  Thorsten Wiegand,et al.  Dealing with Uncertainty in Spatially Explicit Population Models , 2004, Biodiversity & Conservation.

[9]  Iain D. Couzin,et al.  Self‐Organization in Biological Systems.Princeton Studies in Complexity. ByScott Camazine,, Jean‐Louis Deneubourg,, Nigel R Franks,, James Sneyd,, Guy Theraulaz, and, Eric Bonabeau; original line drawings by, William Ristineand, Mary Ellen Didion; StarLogo programming by, William Thies. Princeton (N , 2002 .

[10]  D. DeAngelis,et al.  New Computer Models Unify Ecological TheoryComputer simulations show that many ecological patterns can be explained by interactions among individual organisms , 1988 .

[11]  H. Shugart A Theory of Forest Dynamics , 1984 .

[12]  J. Platt Strong Inference: Certain systematic methods of scientific thinking may produce much more rapid progress than others. , 1964, Science.

[13]  William K. Lauenroth,et al.  Models in Ecosystem Science , 2003, Models in Ecosystem Science.

[14]  Laurent Seuront,et al.  Handbook of Scaling Methods in Aquatic Ecology: Measurement, Analysis, Simulation , 2007 .

[15]  Susanne Winter,et al.  Totholz im Buchen-Urwald: Generische Vorhersagen des Simulationsmodells BEFORECWD zur Menge, räumlichen Verteilung und Verfügbarkeit , 2003, Forstwissenschaftliches Centralblatt vereinigt mit Tharandter forstliches Jahrbuch.

[16]  D. DeAngelis,et al.  Individual-Based Models and Approaches in Ecology , 1992 .

[17]  Steven F. Railsback,et al.  GETTING “RESULTS”: THE PATTERN‐ORIENTED APPROACH TO ANALYZING NATURAL SYSTEMS WITH INDIVIDUAL‐BASED MODELS , 2001 .

[18]  G. Huse Individual‐based Modeling and Ecology , 2008 .

[19]  Guy Theraulaz,et al.  Self-Organization in Biological Systems , 2001, Princeton studies in complexity.

[20]  Derek E. Lee,et al.  POPULATION‐LEVEL ANALYSIS AND VALIDATION OF AN INDIVIDUAL‐BASED CUTTHROAT TROUT MODEL , 2002 .

[21]  Steven F. Railsback,et al.  Movement rules for individual-based models of stream fish , 1999 .

[22]  D. Botkin Forest Dynamics: An Ecological Model , 1993 .

[23]  J Uchmański,et al.  Individual-based modelling in ecology: what makes the difference? , 1996, Trends in ecology & evolution.

[24]  H. Remmert,et al.  The Mosaic-Cycle Concept of Ecosystems , 1991, Ecological Studies.

[25]  S. R. J. Woodell,et al.  The Mosaic-Cycle Concept of Ecosystems. Ecological Studies. , 1991 .

[26]  Donald L. DeAngelis,et al.  In Praise of Mechanistically Rich Models , 2003, Models in Ecosystem Science.

[27]  W. V. Winkle,et al.  Individual-based model of sympatric populations of brown and rainbow trout for instream flow assessment: model description and calibration , 1998 .

[28]  Craig W. Reynolds Flocks, herds, and schools: a distributed behavioral model , 1987, SIGGRAPH.

[29]  V. Grimm Ten years of individual-based modelling in ecology: what have we learned and what could we learn in the future? , 1999 .

[30]  Christian Wissel,et al.  Modelling the mosaic cycle of a Middle European beech forest , 1992 .

[31]  François Bousquet,et al.  Multi-agent simulations and ecosystem management: a review , 2004 .

[32]  H. Remmert,et al.  The Mosaic-Cycle Concept of Ecosystems — An Overview , 1991 .

[33]  Volker Grimm,et al.  Using pattern-oriented modeling for revealing hidden information: a key for reconciling ecological theory and application , 2003 .

[34]  J. R. Wallis,et al.  Some ecological consequences of a computer model of forest growth , 1972 .

[35]  Steven F. Railsback,et al.  Elevated turbidity reduces abundance and biomass of stream trout in an individual-based model , 2003 .

[36]  J. Platt Strong Inference , 2007 .

[37]  Uta Berger,et al.  Seeing the Forest for the Trees, and Vice Versa: Pattern-Oriented Ecological Modeling , 2003 .

[38]  Jianguo Liu,et al.  Individual-based simulation models for forest succession and management , 1995 .

[39]  Volker Grimm,et al.  MATHEMATICAL MODELS AND UNDERSTANDING IN ECOLOGY , 1994 .

[40]  Neha Bhooshan,et al.  The Simulation of the Movement of Fish Schools , 2001 .