Modeling the Behavior of Marlin Anglers in the Western Pacific

Duffield, John W.; Neher, Chris; Allen, Stewart; Patterson, David A.; Gentner, Brad

doi:10.5950/0738-1360-27.4.343

Cited by 10 publications

(8 citation statements)

References 10 publications

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“…In addition, our estimates are similar to Duffield et al. 's () WTP estimate of $276.44 for catching a Blue Marlin Makaira nigricans among private‐boat Hawaiian anglers (the survey did not distinguish between harvested and released fish). Given their elite status as both a food and sport fish, the high WTP estimated for Bluefin Tuna harvest is not surprising.…”

Section: Discussionsupporting

confidence: 86%

“…Species in the meta-analysis with higher WTPs (>$100/fish) generally included popular food and sport fish such as salmon (e.g., Jones and Stokes Associates 1987;Morey et al 1993) and big-game species such as billfish and sharks (e.g., Schuhmann 1996reviewed in Johnston et al 2006). In addition, our estimates are similar to Duffield et al's (2012) WTP estimate of $276.44 for catching a Blue Marlin Makaira nigricans among private-boat Hawaiian anglers (the survey did not distinguish between harvested and released fish). Given their elite status as both a food and sport fish, the high WTP estimated for Bluefin Tuna harvest is not surprising.…”

Section: Wtp Comparisons With Previous Studiessupporting

confidence: 73%

“…Assuming independence of choices (and error terms) across the choice sets, the probability that a person makes a given sequence of choices across multiple choice sets becomes the product of individual choice probabilities for that sequence, resulting in the following log‐likelihood:

l n L = \sum_{n = 1}^{N} l n (\sum_{m = 1}^{M} (\frac{e^{{normalλ}_{m} Z_{n}}}{\sum_{m = 1}^{M} e^{λ_{m} Z_{n}}}) \{\prod_{t = 1}^{T} [(\frac{e^{{normalβ}_{m} X_{it}}}{e^{β_{m} X_{italicit}} + e^{β_{m} X_{italicjt}} + e^{β_{m} X_{italickt}}}) (\frac{e^{{normalβ}_{m} X_{jt}}}{e^{β_{m} X_{italicjt}} + e^{β_{m} X_{italickt}}})]\}),

where t represents each of up to four choice sets answered by each respondent.The utility of a given trip alternative (and thus the probability of selecting that trip) for members of a given class was assumed to be a linear function of the 11 attributes that characterized each trip, while an alternative‐specific constant (ASC) was used to represent the utility of not going Bluefin Tuna fishing (option C), as has been done in previous choice experiments for recreational fisheries (e.g., Carter and Liese ; Duffield et al. ; Lew and Larson ). The probability of class membership, meanwhile, was assumed to be a function of individual‐specific variables, including those relating to fishing behavior (e.g, avidity, target species), attitudes (e.g., consumptive orientation), and demographics (e.g., region, income).…”

Section: Methodsmentioning

confidence: 99%

“…where t represents each of up to four choice sets answered by each respondent. The utility of a given trip alternative (and thus the probability of selecting that trip) for members of a given class was assumed to be a linear function of the 11 attributes that characterized each trip, while an alternative-specific constant (ASC) was used to represent the utility of not going Bluefin Tuna fishing (option C), as has been done in previous choice experiments for recreational fisheries (e.g., Carter and Liese 2012;Duffield et al 2012;Lew and Larson 2012). The probability of class membership, meanwhile, was assumed to be a function of individual-specific variables, including those relating to fishing behavior (e.g, avidity, target species), attitudes (e.g., consumptive orientation), and demographics (e.g., region, income).…”

Section: Number Of Levels (Values)mentioning

confidence: 99%

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Characterizing the Preferences and Values of U.S. Recreational Atlantic Bluefin Tuna Anglers

Goldsmith

Scheld

Graves

2018

N American J Fish Manag

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The Atlantic Bluefin Tuna Thunnus thynnus is the target of a recreational fishery along the U.S. East Coast that is thought to be of considerable economic value. In some years, recreational landings have exceeded the sector's annual subquota due to changes in fish availability, limited predictability of angler effort, and difficulties in real‐time monitoring of catch. Understanding the drivers of angler behavior is critical for predicting how effort and harvest may vary as a function of changing fish availability, regulations, or costs. To investigate angler decision making, preferences, and values, we surveyed private recreational anglers from Maine to North Carolina and employed discrete choice experiments to determine how regulatory and nonregulatory trip‐specific variables influence trip‐taking behavior. A latent class‐ranked logit model identified two distinct classes of anglers who exhibited differing preferences in regard to the importance of nonconsumptive aspects of Bluefin Tuna fishing (e.g., catch and release). Income and recent Bluefin Tuna targeting were the primary determinants of class membership, and higher‐income anglers who had targeted Bluefin Tuna in the past 5 years were significantly more likely to be in the class that derives substantive benefits from nonconsumptive angling activities. An annual consumer surplus exceeding US$14 million was estimated for the 2015 fishery. We considered potential angler welfare impacts of possible management changes (compensating surplus) and identified a large amount of latent effort currently present in the fishery in the form of consumptive‐oriented anglers. As a result, liberalization of harvest regulations could potentially lead to a large influx of effort into the fishery, which could impede the ability of managers to maintain harvest levels within prescribed limits.

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Section: Discussionsupporting

confidence: 86%

Section: Wtp Comparisons With Previous Studiessupporting

confidence: 73%

l n L = \sum_{n = 1}^{N} l n (\sum_{m = 1}^{M} (\frac{e^{{normalλ}_{m} Z_{n}}}{\sum_{m = 1}^{M} e^{λ_{m} Z_{n}}}) \{\prod_{t = 1}^{T} [(\frac{e^{{normalβ}_{m} X_{it}}}{e^{β_{m} X_{italicit}} + e^{β_{m} X_{italicjt}} + e^{β_{m} X_{italickt}}}) (\frac{e^{{normalβ}_{m} X_{jt}}}{e^{β_{m} X_{italicjt}} + e^{β_{m} X_{italickt}}})]\}),

Section: Methodsmentioning

confidence: 99%

Section: Number Of Levels (Values)mentioning

confidence: 99%

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Characterizing the Preferences and Values of U.S. Recreational Atlantic Bluefin Tuna Anglers

Goldsmith

Scheld

Graves

2018

N American J Fish Manag

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“…Oh, Ditton, Gentner, and Reichers () analysed preferences for various management options in recreational fisheries using a choice experiment. Duffield, Neher, Allen, Patterson, and Gentner () modelled the behaviour of recreational marlin anglers in the Western Pacific. Eggert and Martinsson () used a choice experiment to explore the levels of risk tolerance in commercial fishers.…”

Section: Introductionmentioning

confidence: 99%

Fisher's preferences and trade‐offs between management options

et al. 2017

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Failure to understand the potential responses of fishers to management measures creates a significant risk of revisiting the familiar scenario of perverse and unintended consequences of those measures. This paper reports on a choice experiment survey to evaluate fisher's preferences for various management measures proposed under the EU Common Fisheries Policy (CFP) reform process, but the conclusions have wider relevance as similar measures are used by comparable fleets in fisheries globally. The survey was conducted with fishers involved in mixed pelagic and demersal fisheries in Ireland, pelagic fisheries in Denmark and demersal fisheries in Greece. Fisheries management policies were characterized by five attributes designed both to cover the principal CFP reform proposals and to integrate ecological, social, economic and institutional factors affecting fisher's decisions. The study uses a random utility modelling framework to reveal the preferences of the fishers across the alternative policy attributes. Results show that while there are generally preferences both for healthy stocks and for maintaining the importance of fishing to the local community, strong interfishery preference differences exist. These differences are most notable in relation to a discard ban and to the use of individual transferable fishing rights, favoured in Denmark, but not in Ireland for instance. The strength of these interfishery differences supports the assertion that there are no panaceas in fisheries management and that solutions should be tailored within the context of specific fisheries. Not doing so could create a significant risk of inappropriately managed fisheries that may lead to unsustainable outcomes.

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Recreational fishing for sea trout—Resource for whom and to what value?

Blicharska

Rönnbäck

2018

Fisheries Research

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Modeling the Behavior of Marlin Anglers in the Western Pacific

Cited by 10 publications

References 10 publications

Characterizing the Preferences and Values of U.S. Recreational Atlantic Bluefin Tuna Anglers

Characterizing the Preferences and Values of U.S. Recreational Atlantic Bluefin Tuna Anglers

Fisher's preferences and trade‐offs between management options

Recreational fishing for sea trout—Resource for whom and to what value?

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