Foraging habits of reef fishes associated with mangroves and seagrass beds in a caribbean lagoon: A stable isotope approach [Hábitos de alimentación de peces arrecifales asociados con manglares y pastos marinos en una laguna del Caribe: Un enfoque de isótopos estables]
Vaslet A.,University Antilles Guyane Campus Of Fouillole |
Bouchon-Navaro Y.,University Antilles Guyane Campus Of Fouillole |
Harmelin-Vivien M.,Aix - Marseille University |
Lepoint G.,University of Liège |
And 2 more authors.
Ciencias Marinas | Year: 2015
Mangroves and seagrass beds represent suitable fish habitats as nurseries or feeding areas. This study was conducted in a Caribbean lagoon to assess the foraging habits of juvenile transient reef fishes in these two habitats. Twelve fish species were sampled in coastal mangroves, an offshore mangrove islet, and a seagrass bed site, and stable isotope analyses were performed on fishes and their prey items. The SIAR mixing model indicated that transient fishes from both mangroves and seagrass beds derived most of their food from seagrass beds and their associated epiphytic community. Only a few species including planktivores (Harengula clupeola, Anchoa lyolepis) and carnivores (Centropomus undecimalis and small specimens of Ocyurus chrysurus) presented depleted carbon values, showing reliance on mangrove prey in their diets. Mangrove-derived organic matter contributed marginally to the diet of transient fishes, which relied more on seagrass food sources. Thus, mangroves seem to function more as refuge than feeding habitats for juvenile transient fishes. © 2015 Universidad Autonoma de Baja California. All rights reserved.
Robinel A.,University Antilles Guyane Campus Of Fouillole |
Puzenat D.,University Antilles Guyane Campus Of Fouillole
Expert Systems with Applications | Year: 2014
We describe in this paper a new methodology for blood alcohol content (BAC) estimation of a subject. Rather than using external devices to determine the BAC value of a subject, we perform a behaviour analysis of this subject using intelligent systems. We monitor the user's actions in an ordinary task and label those data to various measured BAC values. The obtained data-set is then used to train learning systems to detect alcoholic consumption and perform BAC estimation. We obtain good results on a mono-user base, and lower results with multiple users. We improve the results by combining multiple classifiers and regression algorithms. © 2013 Elsevier Ltd. All rights reserved.