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20 - Insights from agent-based modelling to simulate whale-watching tours

Influence of captains’ strategy on whale exposure and excursion content

from Part IV - Sustainable management: insights and issues

Published online by Cambridge University Press:  05 April 2014

Clément Chion
Affiliation:
Université de Montréal
Jacques-André Landry
Affiliation:
University of Québec
Lael Parrott
Affiliation:
Université de Montréal
Danielle Marceau
Affiliation:
University of Calgary
Philippe Lamontagne
Affiliation:
National Research Council Canada, Research & Development, Ottawa, Ontario, Canada
Samuel Turgeon
Affiliation:
Université de Montréal
Robert Michaud
Affiliation:
Group for Research and Education on Marine Mammals (GREMM), Québec, Canada
Cristiane C. A. Martins
Affiliation:
Université de Montréal
Nadia Ménard
Affiliation:
Parks Canada, Saguenay St-LawrenceMarine Park, Tadoussac (Québec), Canada
Guy Cantin
Affiliation:
Fisheries and Oceans Canada, Oceans Management Division,Mont-Joli (Québec), Canada
Suzan Dionne
Affiliation:
Parks Canada, Natural Resource Conservation, Haute-Ville, Québec, Canada
James Higham
Affiliation:
University of Otago, New Zealand
Lars Bejder
Affiliation:
Murdoch University, Western Australia
Rob Williams
Affiliation:
University of St Andrews, Scotland
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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).

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