Nursery areas and recruitment variation of northeast atlantic mackerel (scomber scombrus)

• Main Authors: Jansen, Teunis, Kristensen, Kasper, van der Kooij, Jeroen, Post, Søren, Campbell, Andrew, Utne, Kjell Rong, Carrera, Pablo, Jacobsen, Jan Arge, Gudmundssdottir, Asta, Roel, Beatriz A., Hatfield, Emma M. C.
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Oxford University Press (OUP) 2014
• Subjects: acoustic; cantabrian sea; catchability; demersal trawl survey; forecast; geostatistics; lgc; mackerel; northeast atlantic; north sea; recruitment; scomber scombrus; stock assessment; North Atlantic; Northeast Atlantic
• Online Access: http://hdl.handle.net/10379/12073; https://doi.org/10.13025/28530; https://doi.org/10.1093/icesjms/fsu186

There are currently no dedicated recruitment survey data available in support of the assessment of the abundance and distribution of Northeast Atlantic (NEA) mackerel (Scomber scombrus), one of the most widespread and commercially important fish stocks in the North Atlantic. This is despite the fact that an estimate of recruitment is an important requirement for the provision of advice to fishery managers. The work here addresses this by compiling catch rates of juvenile mackerel from bottom-trawl surveys conducted between October and March during 1998-2012 and applying a log Gaussian Cox (LGC) process geostatistical model incorporating spatio-temporal correlations. A statistically significant correlation between the modelled catch rates in adjacent quarters 4 and 1 (Q4 and Q1) demonstrates that bottom-trawl surveys in winter are an appropriate platform for sampling juvenile mackerel, and that the LCG model is successful in extracting a population abundance signal from the data. In this regard, the model performed appreciably better than a more commonly used raising algorithm based on survey swept-area estimates. Therefore, the LCG model was expanded to include data from the entire survey time-series, and a recruitment index was developed for use in the annual ICES stock assessment. We hypothesize that catchability is positively density-dependant and provides supporting evidence from acoustic observations. Various density-dependant transformations of the modelled catch rates were furthermore found to improve the correlation between the derived annual recruitment index and recruitment estimated by back calculation of adult mackerel data. Square root transformation led to the strongest correlation, so this is recommended for further analysis of mackerel abundance. Finally, we provide maps of spatial distributions, showing that the most important nursery areas are around Ireland, north and west of Scotland, in the northern North Sea north of 59 degrees N and, to some extent, also in the Bay of Biscay.