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| Maufroy, Alexandra; Chassot, Emmanuel; Joo, Rocio; Kaplan, David. |
| Since the 1990s, massive use of drifting Fish Aggregating Devices (dFADs) to aggregate tropical tunas has strongly modified global purse-seine fisheries. For the first time, a large data set of GPS positions from buoys deployed by French purse-seiners to monitor dFADs is analysed to provide information on spatio-temporal patterns of dFAD use in the Atlantic and Indian Oceans during 2007-2011. First, we select among four classification methods the model that best separates "at sea" from "on board" buoy positions. A random forest model had the best performance, both in terms of the rate of false "at sea" predictions and the amount of over-segmentation of "at sea" trajectories (i.e., artificial division of trajectories into multiple, shorter pieces due to... |
| Tipo: Text |
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| Ano: 2015 |
URL: https://archimer.ifremer.fr/doc/00271/38256/73660.pdf |
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| Bertrand, Sophie; Joo, Rocio; Fablet, Ronan. |
| How organisms move and disperse is crucial to understand how population dynamics relates to the spatial heterogeneity of the environment. Random walk (RW) models are typical tools to describe movement patterns. Whether Levy or alternative RW better describes forager movements is keenly debated. We get around this issue using the Generalized Pareto Distribution (GPD). GPD includes as specific cases Normal, exponential and power law distributions, which underlie Brownian, Poisson-like and Levy walks respectively. Whereas previous studies typically confronted a limited set of candidate models, GPD lets the most likely RW model emerge from the data. We illustrate the wide applicability of the method using GPS-tracked seabird foraging movements and fishing... |
| Tipo: Text |
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| Ano: 2015 |
URL: https://archimer.ifremer.fr/doc/00275/38641/37160.pdf |
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