Dynamics of trawling effort in the Aegean Sea: investigating the potential of Vessel Monitoring System (VMS) data. (2nd July 2018)

• Record Type: Journal Article
• Authors: Maina, I; Kavadas, S; Damalas, D; Pantazi, M; Katsanevakis, S
• Editors: Poos, Jan Jaap
• Is Part Of: ICES journal of marine science. Volume 75:Number 6(2018)
• Page Start: 2265
• Page End: 2275
• Publication Date: 2018-07-02
• Subjects: autocorrelation -- bottom trawling -- eastern Mediterranean -- ecosystem-based spatial management -- fishing effort -- GAM -- hot spot analysis -- space–time interaction; Ocean -- Periodicals; Fisheries -- Periodicals; Fishes -- Periodicals; Marine biology -- Bibliography -- Periodicals; 551.4605
• DOI: 10.1093/icesjms/fsy083
• Languages: English
• ISSNs: 1054-3139

Abstract

Abstract: A better understanding of the spatiotemporal variation of human pressures, such as fishing, is crucial in the framework of ecosystem-based management. In this context, the spatiotemporal patterns of fishing effort from Greek trawlers operating in the eastern Mediterranean were studied using Vessel Monitoring System data over a 6-year period (2010–2015). The exploratory analysis of the data consisted of spatial autocorrelation techniques assessing clusters of high fishing effort (hotspots). Cycles, seasonality, trends, and the inter/intra-annual persistence of hotspots were also examined. The spatiotemporal association between the fishing effort (fine-scale: 5 × 5 km, monthly basis) and environmental/economic variables (depth, chlorophyll-a, fuel price, distance from port) was investigated through Generalized Additive Modelling. The results revealed higher fishing effort at depths <250 m, at distances between 15 and 55 km from the departure port and in areas of relatively high primary productivity. In winter, fishing effort was observed in shallower waters while during mid/late spring in deeper strata. In autumn, the effort was higher than any other season. Fishing effort was negatively correlated with fuel price and a decrease was noticeable during 2012–2013, the period of fuel price peaks. Potential implications of the methodology and results on spatial planning and management are discussed.