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Fine-scale recognition and use of mesoscale fronts by foraging Cape gannets in the Benguela upwelling region ArchiMer
Sabarros, Philippe S.; Gremillet, David; Demarcq, Herve; Moseley, Christina; Pichegru, Lorien; Mullers, Ralf H. E.; Stenseth, Nils C.; Machu, Eric.
Oceanic structures such as mesoscale fronts may become hotspots of biological activity through concentration and enrichment processes. These fronts generally attract fish and may therefore be targeted by marine top-predators. In the southern Benguela upwelling system, such fronts might be used as environmental cues by foraging seabirds. In this study we analyzed high-frequency foraging tracks (GPS, 1 s sampling) of Cape gannets Morus capensis from two colonies located on the west and east coast of South Africa in relation to mesoscale fronts detected on daily high-resolution chlorophyll-a maps (MODIS, 1 km). We tested the association of (i) searching behavior and (ii) diving activity of foraging birds with mesoscale fronts. We found that Cape gannets shift...
Tipo: Text Palavras-chave: Seabird; Environmental cue; Behavioral shift; Area-restricted search; Feeding activity; Fractal landscape; Oceanographic fronts; Morus capensis; Southern Benguela; South Africa.
Ano: 2014 URL: https://archimer.ifremer.fr/doc/00236/34756/34575.pdf
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"M2B" package in R: Deriving multiple variables from movement data to predict behavioural states with random forests ArchiMer
Thiebault, Andrea; Dubroca, Laurent; Mullers, Ralf H. E.; Tremblay, Yann; Pistorius, Pierre A..
1. The behaviour of individuals affect their distributions and is therefore fundamental in determining ecological patterns. While, the direct observation of behaviour is often limited due to logistical constraints, collection of movement data has been greatly facilitated through the development of bio-logging. Movement data obtained through tracking instrumentation may potentially constitute a relevant proxy to infer behaviour. 2. To infer behaviour from movement data is a key focus within the "movement ecology" discipline. Statistical learning constitutes a number of methods that can be used to assess the link between given variables from a fully informed training dataset and then predict the values on a non-informed variable. We chose the random forest...
Tipo: Text Palavras-chave: Cape gannet; Fisheries; GPS; Local enhancement; Machine learning; Onboard observers; Social interactions; Video cameras.
Ano: 2018 URL: https://archimer.ifremer.fr/doc/00445/55683/57354.pdf
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