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Opportunities for agent‐based modelling in human dimensions of fisheries
Fish and Fisheries ( IF 5.6 ) Pub Date : 2020-02-28 , DOI: 10.1111/faf.12447
Matthew G. Burgess 1, 2 , Ernesto Carrella 3 , Michael Drexler 4 , Robert L. Axtell 5 , Richard M. Bailey 3 , James R. Watson 6 , Reniel B. Cabral 7, 8 , Michaela Clemence 7, 8 , Christopher Costello 7, 8 , Chris Dorsett 4 , Steven D. Gaines 7, 8 , Emily S. Klein 9 , Philipp Koralus 10 , George Leonard 4 , Simon A. Levin 11 , Lorne Richard Little 12 , John Lynham 13 , Jens Koed Madsen 3 , Andreas Merkl 4 , Brandon Owashi 7, 8 , Steven E. Saul 14 , Ingrid E. Putten 12, 15 , Sharon Wilcox 4
Affiliation  

Models 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.

中文翻译:

在渔业的人类层面上进行基于主体的建模的机会

渔业的人类尺度模型对于理解和预测捕鱼业如何对海洋生态系统和管理机构的变化至关重要。计算的进步使构建基于代理的模型(ABM)成为可能,该模型可明确描述个人,公司或船只的行为,以便了解和预测其总体行为。反弹道导弹在许多场合被广泛用于学术和应用目的,包括金融,城市规划和军事,但尽管文献不断增加,但仍未成为渔业科学和管理的主流。反弹道导弹非常适合理解渔民互动,异质性和有限理性的紧急后果,特别是在复杂的生态,社会和制度环境下。由于这些原因,我们认为,人类行为的ABM可以在三个方面极大地促进渔业的人类规模:(a)了解多个管理机构之间的相互作用;(b)将认知和行为科学纳入渔业科学和实践;(c)了解和预测管理机构的社会后果。我们使用POSEIDON模型的概念(“玩具”)版本提供了简单的示例来说明在这些领域中可能存在的反弹道导弹。我们认为,在这些领域取得显着的战略进展可能为在渔业管理环境中增加对ABM的战术使用铺平道路。我们回顾了ABM的常见开发和应用挑战,旨在为新手ABM开发人员和用户研究渔业的人文因素提供指导。
更新日期:2020-02-28
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