Is natural bait type a stochastic process for size and condition of fishes in the recreational fishery of Ιzmir Bay?

Aydin, İlker

doi:10.12681/mms.39

Cited by 10 publications

(17 citation statements)

References 9 publications

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“…The CPUE and YPUE values, calculated with the formula recommended by Godøy et al (2003) and customized by Aydın (2011), are presented below.…”

Section: Methodsmentioning

confidence: 99%

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Ateşşahin¹,

Duman²,

Cılbız³

2015

Turk. J. Fish. Aquat. Sci.

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The aim of this study was to determine the relationship between spinner hook sizes (2, 3 and 4) and hook selectivity for Oncorhynchus mykiss (rainbow trout), a species important to recreational fisheries in Karakaya Dam Lake in Eastern Turkey.A total of 24 sampling trips were carried out twice per month by the same three anglers from May 2013 to April 2014. The SELECT method was used to determine the selectivity parameters. An analysis to determine the differences in the catch per unit effort (CPUE), yield per unit effort (YPUE) and condition factor values based on different hook sizes was conducted using one-way ANOVA. During the spinner hook-size experiments, we captured 202 Oncorhynchus mykiss, which ranged from 14.5 cm to 46.0 cm TL in length and weight 30.2 g to 1320.2 g. The mean lengths (±SE) of Oncorhynchus mykiss captured on the three spinner hook sizes were determined. The optimum lengths calculated by log-normal model were found to be 18.28, 27.41 and 36.55 cm for No 2, No 3 and No 4 hook sizes, respectively.

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“…The CPUE and YPUE values, calculated with the formula recommended by Godøy et al (2003) and customized by Aydın (2011), are presented below.…”

Section: Methodsmentioning

confidence: 99%

“…The Kolmogorov-Smirnov (K-S) test was used to determine differences between size frequency distributions of fish caught by hooks of varying sizes (Siegel and Castellan, 1989;Karakulak and Erk, 2008;Aydın, 2011).…”

Section: W= Weight (G)mentioning

confidence: 99%

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Ateşşahin¹,

Duman²,

Cılbız³

2015

Turk. J. Fish. Aquat. Sci.

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“…Smith () detected a relationship between the type of natural bait (either maggots or chironomids) and the vulnerability of the fish. Aydin () compared sardine ( Sardina pilchardus , Clupeidae) and onyx ( Solen vagina , Solenidae) in a Turkish recreational fishery and found that onyx captured considerably more fish than sardine; however, individuals with higher condition factors were more frequently captured using sardine. Similarly, Alós, Arlinghaus et al () found that the Mediterranean fishes were more vulnerable to worms than to shrimp, suggesting that the proper selection of bait by the fisher can move fish from an invulnerable to a vulnerable state.…”

Section: Review Of Factors Underlying Fish Vulnerabilitymentioning

confidence: 99%

What makes fish vulnerable to capture by hooks? A conceptual framework and a review of key determinants

et al. 2017

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Considerable time and money are expended in the pursuit of catching fish with hooks (e.g., handlining, angling, longlining, trolling, drumlining) across the recreational, commercial and subsistence fishing sectors. The fish and other aquatic organisms (e.g., squid) that are captured are not a random sample of the population because external (e.g., turbidity) and underlying internal variables (e.g., morphology) contribute to variation in vulnerability to hooks. Vulnerability is the probability of capture for any given fish in a given location at a given time and mechanistically explains the population‐level catchability coefficient, which is a fundamental and usually time‐varying (i.e., dynamic) variable in fisheries science and stock assessment. The mechanistic drivers of individual vulnerability to capture are thus of interest to fishers by affecting catch rates, but are also of considerable importance to fisheries managers whenever hook‐and‐line‐generated data contribute to stock assessments. In this paper, individual vulnerability to hooks is conceptualized as a dynamic state, in which individual fish switch between vulnerable and invulnerable states as a function of three interdependent key processes: an individual fish's internal state, its encounter with the gear, and the characteristics of the encountered gear. We develop a new conceptual framework of “vulnerability,” summarize the major drivers of fish vulnerability, and conclude that fish vulnerability involves complex processes. To understand vulnerability, a shift to interdisciplinary research and the integration of ecophysiology, fish ecology, fisheries ecology and human movement ecology, facilitated by new technological developments, is required.

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“…The economic and ecological impacts of RF were previously presented in few studies from the Mediterranean SEA (LLORET et al, 2008;ÜNAL et al, 2010;AYDIN, 2011;FONT AND LLORET, 2011a;FONT & LLORET, 2011b;TUNCA et al, 2012;AYDIN et al, 2013;TUNCA et al, 2016). Despite of the fact that RF has important economic and ecological consequences, there is lack of its management besides commercial fishing with high numbers of illegal, unreported and unregulated recreational fishing (GORDOA et al, 2004;LLORET et al, 2008;ÜNAL et al, 2010).…”

Section: Introductionmentioning

confidence: 85%

Recreational Fishing on the Coastal Hot Spots of İzmir Inner Bay (Aegean Sea, Turkey)

Ulaş

Tunca

Aydin

2019

Acta Adriat. (Online)

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In this study, we analyzed social and economic dimensions of shore-based recreational fishing (RF) along İzmir Inner Bay in the Metropolitan Province İzmir of Turkey. 634 shore-based recrea-tional fishers were interviewed via on-site face-to-face interviews during the fishing activity from January to December in 2016. Market value approach was utilized to calculate net economic values and expenses of recreational fishers along in eight coastal districts, Göztepe, Karataş, Konak, Pasa-port, Alsancak, Bayraklı, Karşıyaka and Bostanlı along the coast of the inner bay. The annual fish-ing efforts demonstrated significant differences among districts. For example; Bostanlı fishers that have higher education levels with higher income spent higher time for RF but, finally, this attitude of Bostanlı fishers resulted in low CPUE levels. Considering the RF experience of Bostanlı fishers, they are either not likely or able to target or catch bigger or more fish. In contrast, Göztepe fish-ers seems much professional compared to fishers by having the highest amount of catch in shortest time compared to rest of the districts. The highest mean CPUE was observed for Göztepe, Karataş and Konak fishers even so, these CPUE amounts were much under the ones determined in previous studies in Turkey. Considering the catch composition of fishers, S. auratus was the most common catch for all fishers. Secondly, D. labrax and Mugilid species constituted the majority. High fishing related expenditures were observed in all districts, then harvesting values reached quite high levels considering the previous studies. To conclude, RF in İzmir Inner Bay of Turkey is great social and economic activity by generating increase in RF related expenditures, jobs and indirect economic activity in services sector. The results of this study provide an update information of the recreational fishers’ profile to help regulate recreational fishery.

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Is natural bait type a stochastic process for size and condition of fishes in the recreational fishery of Ιzmir Bay?

Cited by 10 publications

References 9 publications

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What makes fish vulnerable to capture by hooks? A conceptual framework and a review of key determinants

Recreational Fishing on the Coastal Hot Spots of İzmir Inner Bay (Aegean Sea, Turkey)

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