2010
DOI: 10.1016/j.fishres.2010.08.008
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Qualitative analysis of recreational fisher response and the ecosystem impacts of management strategies in a data-limited situation

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Cited by 16 publications
(12 citation statements)
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References 31 publications
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“…Thus, harvest regulations (e.g., bag limits, size limits, bait bans) in addition to catch-related and non-catch-related (e.g., proximity to residence) attributes of the fishing experience are all important determinants of anglereffort dynamics (e.g., Beard et al, 2003). However, behavioural responses of recreational anglers to regulation changes are rarely studied (Metcalf et al, 2010), despite their implications for management (Metcalf et al, 2010;Johnston et al, 2010).…”
Section: Introductionmentioning
confidence: 99%
“…Thus, harvest regulations (e.g., bag limits, size limits, bait bans) in addition to catch-related and non-catch-related (e.g., proximity to residence) attributes of the fishing experience are all important determinants of anglereffort dynamics (e.g., Beard et al, 2003). However, behavioural responses of recreational anglers to regulation changes are rarely studied (Metcalf et al, 2010), despite their implications for management (Metcalf et al, 2010;Johnston et al, 2010).…”
Section: Introductionmentioning
confidence: 99%
“…We suggest this technique will have similar effectiveness in guiding research 629 and focussing management on key issues in other fields dealing with complex systems. The 630 theory behind the technique was first implemented in economics in the mid 1960s (Quirk and 631 Ruppert 1965) and has also been used in fisheries management (Metcalf et al 2010(Metcalf et al , 2011, 632 assessment of mining impacts (Dambacher et al 2007) and the identification of climate 633 change and coastal governance issues (Stocker 2011). The method is relatively quick to use, 634 in comparison to other data-intensive models, cost-efficient and easily incorporates 635 stakeholder input.…”
Section: Modelling Scenarios 317mentioning
confidence: 99%
“…For example, a 642 large (> 20 variables) model that is also very complex (i.e., variables with numerousreciprocal links) will tend to be highly ambiguous and may therefore be relatively unreliable 644 (Dambacher et al 2003). This limitation may be overcome by ensuring models focus on a 645 relevant subsystem of a size and complexity that will allow high predictability while also 646 ensuring inclusion of key variables, or through the integration with quantitative modelling 647 techniques (Metcalf 2010). 648…”
Section: Modelling Scenarios 317mentioning
confidence: 99%
“…When fisheries resources become scarce, recreational angling effort, and the mortality it induces on fish populations, may need to be regulated (Post et al, 2002;Lewin et al, 2006). Any form of effective planning of recreational fishing regulations, however, necessitates understanding of anglers' behavioural responses to new regulations because almost inevitably changes in regulations change the attractiveness of a given fishing opportunity to anglers (e.g., Radomski and Goeman, 1996;Johnston et al, 2010;Metcalf et al, 2010). Anglers may respond to a suite of changes in the fishing experience (e.g., type of regulation in place, catch rates, size of fish, crowding) by (i) changing angling frequency, (ii) substituting alternative sites, or (iii) substituting other species to target (e.g., Post et al, 2002;Beard et al, 2003;Ditton and Sutton, 2004).…”
Section: Introductionmentioning
confidence: 99%