Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
Because many biological processes related to the dynamics of infectious diseases are caused by complex interactions between the environment, the host(s) and the agent(s), the necessity to address the methodological implications of this inherent complexity has recently emerged in epidemiology. Most epidemiologists now acknowledge that most human infectious diseases are likely to have complex dynamics. However, this knowledge still percolates with difficulty in their statistical "modus operandi". Indeed, for the study of complex systems, the traditional first-line statistical toolbox of epidemiologists (mainly built around the Generalized Linear Model family), despite its undeniable practicality and robustness, has structural limitations deprecating its usefulness. Three major sources of complexity neglected or not taken into account by this first-line statistical toolbox and having deep statistical implications are the multi-level organization of data, the non-linear relationships between variables and the complex interactions between variables. Three promising candidates to incorporate along with traditional tools for a new first-line statistical toolbox more suitable to apprehend these sources of complexity are the generalized linear mixed models, the generalized additive models, and the structural equation models. The aforementioned methodologies have the advantage to be generalizations of GLM models and are relatively easy to implement. Their assimilation and implementation would thus be greatly facilitated for epidemiologists. More globally, this text underlines that an improved use of other methods as such described here compared to traditional ones has to be performed to better understand the complexity challenging epidemiologists every day. This is particularly true in the field of infectious diseases for which major public health challenges will have to be addressed in the coming decades.
ISSN: 1567-1348

inserm-00872354
http://www.hal.inserm.fr/inserm-00872354
http://www.hal.inserm.fr/inserm-00872354/document
http://www.hal.inserm.fr/inserm-00872354/file/main_document.pdf
DOI : 10.1016/j.meegid.2013.09.006

Éditeur(s) : EDP Sciences
Résumé : Marine Protected Areas (MPA) are often contemplated as a tool for the sustainable management of exploited resources and ecosystem conservation. This paper proposes an approach to establish a statistical diagnostic of the effects of MPAs on fish assemblages, and define corresponding ecological indicators. This requires choosing relevant variables (abundance, diversity, demographic parameters..) and appropriate statistical methods. The study was based on data from the Abore reef Reserve in New Caledonia. Two sets of methods: 1-inferential linear models (ANOVA, GLM): 2- Partial Least Squares (PLS) methods of regression, were used to test the effects of this MPA. PLS enabled us to test simultaneously within a model, density, species richness, biomass and mean size variables of fish community to retain the most sensitive and relevant ones. Habitat variability was also taken into account in these models. Species were grouped according to several criteria: 1-feeding habit; 2- taxonomy; 3-mobility; 4-adult size; 5-demographic strategy. No significant effect of the opening of the Abore reef to fishing was found for mobility. Feeding habit was the only criterion for which the results from the inferential models and PLS showed a significant effect of reserve status for all variables. Species richness, density, and to a lesser extent mean size, were sensitive to the removal of reserve status. but not biomass. Results from ANOVA and PLS regression were consistent but the latter allows a more holistic approach as it integrates all variables within a single model.
Les Aires Marines Protégées (AMP) sont de plus en plus considérées comme des mesures de gestion alternative permettant à la fois une gestion durable des ressources exploitées et la conservation des écosystèmes. Nous proposons une approche pour définir des indicateurs synthétiques et permettre un diagnostic statistique de l'effet des AMP sur les peuplements. Ce travail passe par le choix de variables pertinentes (abondance, richesse spécifique, paramètres démographiques, etc.) et de méthodes statistiques appropriées. Cette étude a été réalisée sur la réserve du récif Aboré en Nouvelle-Calédonie. Les données issues de deux campagnes scientifiques menées sur ce récif sont utilisées pour tester globalement l'effet des AMP grâce à des modèles linéaires inférentiels (ANOVA, GLM), et par des méthodes de régression PLS (Partial Least Squares). Ces dernières permettent de confronter dans un même modèle quatre variables (densité, richesse, biomasse et taille moyenne des poissons), afin de retenir les plus sensibles et les plus pertinentes pour l'évaluation de l'impact de la réserve. La variabilité de l'habitat est également prise en compte dans la modélisation. Les espèces sont regroupées selon plusieurs critères: 1- le régime alimentaire; 2- la taxonomie; 3- la mobilité; 4- des caractéristiques démographiques; 5- des caractéristiques de taille. Les espèces, quel que soit leur mobilité, n'apparaissent pas affectées par l'ouverture à la pêche du récif Aboré, qu'elles soient sédentaires ou très mobiles. Seul le critère trophique révèle un effet du changement de statut Réserve/Non Réserve pour toutes les variables, à la fois d'après les modèles inférentiels et les régressions PLS. Les résultats des modèles inférentiels et des régressions PLS montrent que la richesse spécifique et la densité sont les variables les plus sensibles à l'impact de l'ouverture à la pêche. La taille moyenne est également bien modélisée sur l'ensemble des résultats mais pas la biomasse. Les résultats d'ANOVA et de régression PLS sont cohérents mais la régression PLS permet d'intégrer toutes les variables dans un même modèle
Aquatic Living Resources (0990-7440) (EDP Sciences), 2004-04 , Vol. 17 , N. 2 , P. 139-149

Droits : EDP Sciences, IFREMER, IRD 2004
http://archimer.ifremer.fr/doc/2004/publication-398.pdf
DOI:10.1051/alr:2004022
http://archimer.ifremer.fr/doc/00000/398/

Éditeur(s) : Oxford Univ Press
Résumé : The impact of the fishing effort exerted by a vessel on a population depends on catchability, which depends on population accessibility and fishing power. The work investigated whether the variation in fishing power could be the result of the technical characteristics of a vessel and/or its gear or whether it is a reflection of inter-vessel differences not accounted for by the technical attributes. These inter-vessel differences could be indicative of a skipper/crew experience effect. To improve understanding of the relationships, landings per unit effort (lpue) from logbooks and technical information on vessels and gears (collected during interviews) were used to identify variables that explained variations in fishing power. The analysis was undertaken by applying a combination of generalized additive models and generalized linear models to data from several European fleets. The study highlights the fact that taking into account information that is not routinely collected, e. g. length of headline, weight of otter boards, or type of groundrope, will significantly improve the modelled relationships between lpue and the variables that measure relative fishing power. The magnitude of the skipper/crew experience effect was weaker than the technical effect of the vessel and/or its gear.
Ices Journal Of Marine Science (1054-3139) (Oxford Univ Press), 2011-11 , Vol. 68 , N. 10 , P. 2252-2263

Droits : 2011 International Council for the Exploration of the Sea. Published by Oxford University Press. All rights reserved.
http://archimer.ifremer.fr/doc/00049/16043/15172.pdf
DOI:10.1093/icesjms/fsr150
http://archimer.ifremer.fr/doc/00049/16043/