2010
DOI: 10.1016/j.fishres.2009.12.006
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The role of climatic variability on the short-term fluctuations of octopus captures at the Canary Islands

Abstract: The effect of temperature on the common octopus life cycle has been well studied. However, how other climatic patterns affect them is poorly understood. The present work emphasises the importance of the temperature on common octopus catches by the small-scale trap fishery off the Canary Islands, and also highlights the effect of the North Atlantic Oscillation (NAO) pattern. As well as an inverse and significant correlation between octopus abundance (measured as CPUE) and Sea Surface Temperature (SST), a direct… Show more

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Cited by 24 publications
(17 citation statements)
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“…Hernández-García et al (2002) and Caballero-Alfonso et al (2010) have shown that there is an effect of environmental variability on O. vulgaris abundance off the Canary Islands due to SST. The delay between both variables can be explained alluding to the consequence of the effect of sea water temperature on octopus recruitment, which affects crucial phases in the life cycle of this cephalopod (i.e., paralarvae survival, growth rates, age of juvenile benthic settlement and timing of the reproductive peaks).…”
Section: Discussionmentioning
confidence: 99%
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“…Hernández-García et al (2002) and Caballero-Alfonso et al (2010) have shown that there is an effect of environmental variability on O. vulgaris abundance off the Canary Islands due to SST. The delay between both variables can be explained alluding to the consequence of the effect of sea water temperature on octopus recruitment, which affects crucial phases in the life cycle of this cephalopod (i.e., paralarvae survival, growth rates, age of juvenile benthic settlement and timing of the reproductive peaks).…”
Section: Discussionmentioning
confidence: 99%
“…Several realizations (500,000) of an AR(1) process with the corresponding autocorrelation for each of the tested series were created, and the correlation coefficients of segments with the same length as the tested series were used to create an histogram, which represents the distribution of correlation coefficients from AR(1) processes. Values of the correlation coefficient under (above) the 2.5% (97.5%) percentiles in the distribution of correlation coefficients were considered significant (Caballero-Alfonso et al, 2010).…”
Section: Methodsmentioning
confidence: 99%
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