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20 - Insights from agent-based modelling to simulate whale-watching tours
- from Part IV - Sustainable management: insights and issues
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- By Clément Chion, Université de Montréal, Jacques-André Landry, University of Québec, Lael Parrott, Université de Montréal, Danielle Marceau, University of Calgary, Philippe Lamontagne, National Research Council Canada, Research & Development, Ottawa, Ontario, Canada, Samuel Turgeon, Université de Montréal, Robert Michaud, Group for Research and Education on Marine Mammals (GREMM), Québec, Canada, Cristiane C. A. Martins, Université de Montréal, Nadia Ménard, Parks Canada, Saguenay St-LawrenceMarine Park, Tadoussac (Québec), Canada, Guy Cantin, Fisheries and Oceans Canada, Oceans Management Division,Mont-Joli (Québec), Canada, Suzan Dionne, Parks Canada, Natural Resource Conservation, Haute-Ville, Québec, Canada
- Edited by James Higham, University of Otago, New Zealand, Lars Bejder, Murdoch University, Western Australia, Rob Williams, University of St Andrews, Scotland
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- Book:
- Whale-watching
- Published online:
- 05 April 2014
- Print publication:
- 27 March 2014, pp 293-306
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- Chapter
- Export citation
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Summary
Introduction
Multi-agent models can bear several names depending on the field they were initially developed in (e.g. agent-based model in social science, individual-based model in ecology). Agent- and individual-based models (ABMs and IBMs) are becoming tools of choice to simulate complex social–ecological systems (Gimblett, 2002; Janssen & Ostrom, 2006; Monticino et al., 2007; Bennett & McGinnis, 2008). The recent development of dedicated programming platforms and libraries has also contributed to the expansion of multi-agent models coupled with geographic information systems (GIS) (Railsback et al., 2006). Such models have been applied in a wide variety of natural resource management contexts where heterogeneous actors interact, including rangeland management in arid zones (Gross et al., 2006), management of water use and access in river basins (Schlüter & Pahl-Wostl, 2007), control of irrigation channels (van Oel et al., 2010), agriculture management (Manson, 2005), and forest clearing for agriculture (Moreno et al., 2007). ABMs have also been used to support national parks and recreation areas' managers by simulating visitor movements to predict over-crowded areas along vehicular routes and hiking trails (Itami et al., 2003), or along riverside rest areas and attraction sites for rafting trips on the Colorado River (Roberts et al., 2002).