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https://doi.org/10.31235/osf.i...
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Fish and Fisheries
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Opportunities for agent‐based modelling in human dimensions of fisheries

Authors: Michael Drexler; Robert L. Axtell; Ingrid van Putten; Ingrid van Putten; Sharon Wilcox; George H. Leonard; Chris Dorsett; +18 Authors

Opportunities for agent‐based modelling in human dimensions of fisheries

Abstract

AbstractModels of human dimensions of fisheries are important to understanding and predicting how fishing industries respond to changes in marine ecosystems and management institutions. Advances in computation have made it possible to construct agent‐based models (ABMs)—which explicitly describe the behaviour of individual people, firms or vessels in order to understand and predict their aggregate behaviours. ABMs are widely used for both academic and applied purposes in many settings including finance, urban planning and the military, but are not yet mainstream in fisheries science and management, despite a growing literature. ABMs are well suited to understanding emergent consequences of fisher interactions, heterogeneity and bounded rationality, especially in complex ecological, social and institutional contexts. For these reasons, we argue that ABMs of human behaviour can contribute significantly to human dimensions of fisheries in three areas: (a) understanding interactions between multiple management institutions; (b) incorporating cognitive and behavioural sciences into fisheries science and practice; and (c) understanding and projecting the social consequences of management institutions. We provide simple examples illustrating the potential for ABMs in each of these areas, using conceptual (“toy”) versions of the POSEIDON model. We argue that salient strategic advances in these areas could pave the way for increased tactical use of ABMs in fishery management settings. We review common ABM development and application challenges, with the aim of providing guidance to beginning ABM developers and users studying human dimensions of fisheries.

Countries
Australia, United Kingdom, United States
Keywords

bepress|Social and Behavioral Sciences|Psychology|Other Psychology, Other Social and Behavioral Sciences, bepress|Social and Behavioral Sciences|Economics, Economics, Environmental Studies, Fisheries, Social and Behavioral Sciences, Other Psychology, SocArXiv|Social and Behavioral Sciences|Other Social and Behavioral Sciences, Psychology, bepress|Social and Behavioral Sciences|Environmental Studies, bepress|Social and Behavioral Sciences|Other Social and Behavioral Sciences, bepress|Social and Behavioral Sciences|Psychology, bepress|Social and Behavioral Sciences|Agricultural and Resource Economics, Ecology, human behaviour, SocArXiv|Social and Behavioral Sciences|Economics, 501, sustainability, Fisheries Sciences, SocArXiv|Social and Behavioral Sciences|Environmental Studies, SocArXiv|Social and Behavioral Sciences|Agricultural and Resource Economics, social-ecological systems, governance, Agricultural and Resource Economics, bepress|Social and Behavioral Sciences, SocArXiv|Social and Behavioral Sciences, ecosystem-based fishery management, socialecological systems, SocArXiv|Social and Behavioral Sciences|Psychology, complexity, SocArXiv|Social and Behavioral Sciences|Psychology|Other Psychology

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    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
24
Top 10%
Average
Top 10%
Green
hybrid
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