Scientia Marina, Vol 77, No 4 (2013)

Reconstruction of spatiotemporal capture data by means of orthogonal functions: the case of skipjack tuna (Katsuwonus pelamis) in the central-east Atlantic

Unai Ganzedo
Department of Fisheries Management and Marine Research, Echebastar fleet s.l.u. , Spain

Oihane Erdaide
Research Center for Experimental Marine Biology and Biotechnology, Plentzia Marine Station (PIE), University of the Basque Country (UPV/EHU) , Spain

Aaron Trujillo-Santana
Faculty of Marine Sciences, University of Las Palmas de Gran Canaria , Spain

Aida Alvera-Azcárate
Department of AGO-GHER, University of Liège , Spain

José J. Castro
Faculty of Marine Sciences, University of Las Palmas de Gran Canaria , Spain


The information provided by the International Commission for the Conservation of Atlantic Tunas (ICCAT) on captures of skipjack tuna (Katsuwonus pelamis) in the central-east Atlantic has a number of limitations, such as gaps in the statistics for certain fleets and the level of spatiotemporal detail at which catches are reported. As a result, the quality of these data and their effectiveness for providing management advice is limited. In order to reconstruct missing spatiotemporal data of catches, the present study uses Data INterpolating Empirical Orthogonal Functions (DINEOF), a technique for missing data reconstruction, applied here for the first time to fisheries data. DINEOF is based on an Empirical Orthogonal Functions decomposition performed with a Lanczos method. DINEOF was tested with different amounts of missing data, intentionally removing values from 3.4% to 95.2% of data loss, and then compared with the same data set with no missing data. These validation analyses show that DINEOF is a reliable methodological approach of data reconstruction for the purposes of fishery management advice, even when the amount of missing data is very high.


catches; missing data; spatiotemporal data reconstruction; singular value decomposition; DINEOF

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