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Registros recuperados: 4
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Aerial and snorkelling census techniques for estimating green turtle abundance on foraging areas: A pilot study in Mayotte Island (Indian Ocean) ArchiMer
Roos, David; Pelletier, Dominique; Ciccione, Stéphane; Taquet, Marc; Hughes, George.
Monitoring the abundance of green turtles (Chelonia mydas) is necessary to assess population trends and risks of collapse. This note presents a study aimed at comparing three techniques for the direct estimation of green turtle numbers in their foraging habitats (seagrass beds and reef flats). The experiment was carried out at Mayotte Island, Western Indian Ocean. The techniques involved were surveys by snorkel, and aerial surveys using a microlight aircraft and a paramotor. Each technique had shortcomings and advantages. While each technique provided estimations of turtle numbers only surveys by snorkel permitted identification of species and sex, whenever visibility and turtle behaviour permitted. Along the shorelines, and over foraging areas, the...
Tipo: Text Palavras-chave: Foraging habitats; Snorkelling survey; Aerial survey; Abundance estimation; Chelonia mydas; Green turtle.
Ano: 2005 URL: http://archimer.ifremer.fr/doc/2005/publication-432.pdf
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Density estimator for strip transects when animals show directional movement and observation speed is slow ArchiMer
Trenkel, Verena.
A strip transect population density estimator and its variance are presented. These take into account stochastic survey velocity as well as stochastic swimming velocity and non-random swimming direction of the surveyed animals. The estimator is mainly of interest for surveys of animals with a directional swimming behaviour and swimming velocities similar to the survey velocity, such as those carried out by divers or remotely operated vehicles.
Tipo: Text Palavras-chave: Variance estimators; Abundance estimation; Bias; Fish movement; Visual transects.
Ano: 2003 URL: http://archimer.ifremer.fr/doc/2003/publication-6655.pdf
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Méthodes d'évaluation des ressources marines vivantes pour une exploitation durable ArchiMer
Trenkel, Verena.
In my work, which is summarised in this paper for obtaining accreditation to supervise research (the HDR), I addressed three areas: i) statistical methods of estimating the density of living resources, ii) mathematical models of population dynamics for estimating the abundance of marine populations and iii) methods for detecting temporal changes in the status of exploited populations. My work has focused on: i) Many studies of the observability of fish by trawling and by video and the development of stochastic models to better assess local fish densities. ii) Development of models without commercial catches, using Bayesian and frequentist approaches; the study of multi-specific relationships and the proposal for a threshold predator-prey model. iii)...
Tipo: Text Palavras-chave: Statistics; Abundance estimation; Stock assessment; Statistiques; Estimation d'abondance; Evaluation des stocks.
Ano: 2006 URL: http://archimer.ifremer.fr/doc/2006/rapport-1545.pdf
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Use of a disjunctive kriging to model areas of high pelagic fish density in acoustic fisheries surveys ArchiMer
Petitgas, Pierre.
Schooling fish may aggregate in very high densities covering very small areas. Thus the probability of hitting such high-density spots during a large-scale sampling is very low. The sampling fluctuations of the tail of the histogram are thought to be very significant. The stock biomass estimate and its precision rely greatly on how precisely the tail of the histogram can be sampled. In order to acquire elements for improving survey designs and abundance estimators wc study here the relation in space that the high values have with the other values. A disjunctive kriging approach is used. Different quantiles of the histogram are coded by indicators. The spatial structure of each indicator and its spatial covariation with the others are studied by computing...
Tipo: Text Palavras-chave: Distribution spatiale; Agrégation; Abondance; Estimation; Géostatistique; Échantillonnage; Spatial distribution; Aggregation; Abundance estimation; Geostatistics; Sampling.
Ano: 1993 URL: http://archimer.ifremer.fr/doc/00190/30076/28564.pdf
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