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Gloaguen, Pierre; Mahevas, Stephanie; Rivot, Etienne; Woillez, Mathieu; Guitton, Jerome; Vermard, Youen; Etienne, Marie-pierre. |
The understanding of the dynamics of fishing vessels is of great interest to characterize the spatial distribution of the fishing effort and to define sustainable fishing strategies. It is also a prerequisite for anticipating changes in fishermen's activity in reaction to management rules, economic context, or evolution of exploited resources. Analyzing the trajectories of individual vessels offers promising perspectives to describe the activity during fishing trips. A hidden Markov model with two behavioral states (steaming and fishing) is developed to infer the sequence of non-observed fishing vessel behavior along the vessel trajectory based on Global Positioning System (GPS) records. Conditionally to the behavior, vessel velocity is modeled with an... |
Tipo: Text |
Palavras-chave: Hidden Markov model; Vessels dynamics; RECOPESCA; Autoregressive process; Baum-Welch algorithm. |
Ano: 2015 |
URL: https://archimer.ifremer.fr/doc/00179/29049/27485.pdf |
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Simon, Maximilien; Fromentin, Jean-marc; Bonhommeau, Sylvain; Gaertner, Daniel; Brodziak, Jon; Etienne, Marie-pierre. |
The intrinsic population growth rate (r) of the surplus production function used in the biomass dynamic model and the steepness (h) of the stock-recruitment relationship used in age-structured population dynamics models are two key parameters in fish stock assessment. There is generally insufficient information in the data to estimate these parameters that thus have to be constrained. We developed methods to directly estimate the probability distributions of r and h for the Atlantic bluefin tuna (Thunnus thynnus, Scombridae), using all available biological and ecological information. We examined the existing literature to define appropriate probability distributions of key life history parameters associated with intrinsic growth rate and steepness, paying... |
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Ano: 2012 |
URL: http://archimer.ifremer.fr/doc/00115/22640/20362.pdf |
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Gimenez, Olivier; Buckland, Stephen T.; Morgan, Byron J. T.; Bez, Nicolas; Bertrand, Sophie; Choquet, Remi; Dray, Stephane; Etienne, Marie-pierre; Fewster, Rachel; Gosselin, Frederic; Merigot, Bastien; Monestiez, Pascal; Morales, Juan M.; Mortier, Frederic; Munoz, Francois; Ovaskainen, Otso; Pavoine, Sandrine; Pradel, Roger; Schurr, Frank M.; Thomas, Len; Thuiller, Wilfried; Trenkel, Verena; De Valpine, Perry; Rexstad, Eric. |
The desire to predict the consequences of global environmental change has been the driver towards more realistic models embracing the variability and uncertainties inherent in ecology. Statistical ecology has gelled over the past decade as a discipline that moves away from describing patterns towards modelling the ecological processes that generate these patterns. Following the fourth International Statistical Ecology Conference (1–4 July 2014) in Montpellier, France, we analyse current trends in statistical ecology. Important advances in the analysis of individual movement, and in the modelling of population dynamics and species distributions, are made possible by the increasing use of hierarchical and hidden process models. Exciting research perspectives... |
Tipo: Text |
Palavras-chave: Citizen science; Hidden Markov model; Hierarchical model; Movement ecology; Software package; Spatially explicit capture-recapture; Species distribution modelling; State-space model. |
Ano: 2014 |
URL: https://archimer.ifremer.fr/doc/00249/36026/35298.pdf |
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