New research reports in library

Two new Cooperative Research Reports (CRRs) published on salmon tag recoveries and acoustic target classification.
Published: 26 October 2018

​​​​​​​​​​​​​​​​​​​​​Report no. 343, 'Fifty years of marine tag recoveries from Atlantic salmon', is a compilation of information from four ICES workshops run between 2007 and 2012 to assemble and analyse historic marine tag data on salmon. Results from the 2011 ICES/NASCO symposium “Salmon at Sea: Scientific Advances and their Implications for Management" held in La Rochelle, France are also featured.

The data are on salmon tagged in home waters and subsequently recaptured in the oceanic salmon fisheries around Faroes, Greenland in Norwegian Sea as well as adults tagged in oceanic areas and recaptured in home waters. They are presented in four datasets, together referred to as the North Atlantic Salmon Tag Recovery database (NASTR).

Tagging and related data efforts are crucial as scientists seek to improve understanding of wild Atlantic salmon distribution and migration at sea and the underlying causes of mortality. This is particularly important given that, despite initiatives that have mitigated some declines, abundance of the species has continued to drop in the last two decades.

Targeted acoustics

CRR no. 344, 'Acoustic target classification' presents case studies that describe methods for classifying acoustic target species in data from multiple narrowband frequencies. Some of these methods may be applicable to broadband data or to narrowband frequencies derived from broadband measurements.

Data are collected from a variety of acoustics systems in many countries for a range of ecosystem monitoring and stock management objectives. In fisheries acoustics data, identifying species through classifying acoustic backscatter is a key step in estimating abundance and biomass.

The CRR is aimed at four audiences: users who conduct surveys and derive abundance estimates, those with an understanding of existing and modified process tools but may not be familiar with theory underlying classification methods, developers who use existing and develop advanced tools, and those with theoretical knowledge.

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New research reports in library

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