Abstract :
[en] The information provided by the International Commission for the Conservation of Atlantic Tunas (ICCAT) about 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 or the level of spatiotemporal detail at which catches are reported. As a result, the quality of such data and their effectiveness for providing management advice is limited. In order to reconstruct missing spatial-temporal data of catches, the present study uses Data INterpolating Empirical Orthogonal Functions (DINEOF), a technique for missing data reconstruction applied here for first time to fisheries data. DINEOF is based on an Empirical Orthogonal Functions (EOF) 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 to 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.
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