Open AccessReconciling the economic and biological fishery data gathered through the European Data Collection Framework: A new R-tool
Author(s) -
Isabella Bitetto,
Loretta Malvarosa,
Jörg Berkenhagen,
Maria Teresa Spedicato,
Evelina Sabatella,
Ralf Döring
Publication year - 2022
Publication title -
plos one
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.99
H-Index - 332
ISSN - 1932-6203
DOI - 10.1371/journal.pone.0264334
Subject(s) - fishing , variety (cybernetics) , data collection , variable (mathematics) , computer science , biological data , data management , variable cost , environmental resource management , operations research , business , environmental science , fishery , database , engineering , statistics , mathematics , accounting , mathematical analysis , artificial intelligence , biology , genetics
Fishing fleets and targeted stocks are the basis for the design of multiannual management plans at European or Mediterranean levels. Management Strategy Evaluation and bioeconomic modeling need data at a specific level of resolution in terms of time, area and type of fishing activity for analyzing measures for management procedures using simulations. Within the Data Collection Framework, data are to be aggregated at different levels, e.g.: fleet segment and métier, the former linked to the predominant gear and the size of the vessel and the latter to the activity itself. Fishing costs are collected by fleet segment, effort and landings by fleet segment and métier. Bioeconomic modeling for management purposes requires data at the same resolution. The aim of this paper is to describe a methodology, implemented in SECFISH R package, to disaggregate variable cost data from the fleet segment to the métier level. The presented tool allows to determine the correlation between the variable costs of a vessel and its activities to estimate costs at the activity level (e.g. métiers). The tool is applied to selected Italian fleet segments characterized by a variety of métiers and high dynamicity.