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Habitat suitability modelling for the harbour porpoise (Phocoena phocoena) in the Belgian part of the North Sea
Seghers, S. (2016). Habitat suitability modelling for the harbour porpoise (Phocoena phocoena) in the Belgian part of the North Sea. MSc Thesis. Oceans & Lakes, Interuniversity Master in Marine and Lacustrine Science and Management: Gent, Antwerpen, Brussel. 77 pp.
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| Beschikbaar in | Auteur |
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Documenttype: Doctoraat/Thesis/Eindwerk
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| Trefwoord |
Phocoena phocoena (Linnaeus, 1758) [WoRMS]
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| Abstract |
The harbour porpoise (Phocoena phocoena) is the most common cetacean species in the North Sea and more particularly in the Belgian part of the North Sea (BPNS). Recently, a southern shift was observed in the distribution pattern of harbour porpoises, probably due to a shift in food availability. Marine mammals are facing many anthropogenic threats: bycatch, overfishing, pollution, noise… Therefore, management is necessary to conserve the harbour porpoise. Management requires sufficient knowledge about its ecology. However, little is known about the habitat preferences of harbour porpoises. The aim of the present study was to define suitable habitats for harbour porpoises and to define which environmental variables are most relevant to the distribution of these animals. To achieve this goal, observations of harbour porpoises were obtained from aerial line transect surveys in the BPNS during the period 2008-2014. Based on previous studies, seven predictors were selected to define the habitat suitability of harbour porpoises: depth, bathymetric position index (BPI), macrobenthic community, distance to shipping lanes, suspended particulate matter (SPM), distance to offshore wind turbines and ocean currents (two velocity variables in the x and y directions). To define distribution patterns, univariate relationships between the response variable, i.e. the observations of harbour porpoises, and the environmental variables separately, were determined. Further, the software MaxEnt (Maximum Entropy Species Distribution Modelling) was used to define the relevant predictors. MaxEnt provides an efficient tool in species distribution modelling, because it only requires presence data. The three most important predictors were ocean currents, distance to offshore wind turbines and depth. According to the modelling by MaxEnt, calm and deep waters away from offshore wind farms were the most suitable habitats for harbour porpoises in the BPNS. Although the other predictors contributed less to the model, a clear distribution pattern was still found. However, this study only presented correlations between the occurrence of harbour porpoises and multiple environmental variables; no causalities were derived. Future studies should unravel the causes of their distribution pattern. |
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