Jérôme Dupuis

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• Type de publi. : Article dans une revue
• Date de publi. : 01/01/2014
• Auteurs : Julien MartinHolly EdwardsFlorent BledChristopher FonnesbeckJérôme DupuisBeht GardnerStacie KoslovskyAllen AvenLeslie Ward-GeigerRuth CarmichaelDaniel FaganMonica RossThomas Reinert
• Organismes : Fish and Wildlife Research Institute Fish and Wildlife Research Institute Patuxent Wildlife Research Center Department of Biostatistics Laboratoire de Statistique et Probabilités Department of Forestry and Environmental Resources Fish and Wildlife Research Institute Dauphin Island Sea Lab Fish and Wildlife Research Institute Dauphin Island Sea Lab Fish and Wildlife Research Institute Sea to Shore Alliance Fish and Wildlife Research Institute
• Publié dans PLoS ONE le 25/10/2020

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Résumé : The explosion of the Deepwater Horizon drilling platform created the largest marine oil spill in U.S. history. As part of the Natural Resource Damage Assessment process, we applied an innovative modeling approach to obtain upper estimates for occupancy and for number of manatees in areas potentially affected by the oil spill. Our data consisted of aerial survey counts in waters of the Florida Panhandle, Alabama and Mississippi. Our method, which uses a Bayesian approach, allows for the propagation of uncertainty associated with estimates from empirical data and from the published literature. We illustrate that it is possible to derive estimates of occupancy rate and upper estimates of the number of manatees present at the time of sampling, even when no manatees were observed in our sampled plots during surveys. We estimated that fewer than 2.4% of potentially affected manatee habitat in our Florida study area may have been occupied by manatees. The upper estimate for the number of manatees present in potentially impacted areas (within our study area) was estimated with our model to be 74 (95%CI 46 to 107). This upper estimate for the number of manatees was conditioned on the upper 95%CI value of the occupancy rate. In other words, based on our estimates, it is highly probable that there were 107 or fewer manatees in our study area during the time of our surveys. Because our analyses apply to habitats considered likely manatee habitats, our inference is restricted to these sites and to the time frame of our surveys. Given that manatees may be hard to see during aerial surveys, it was important to account for imperfect detection. The approach that we described can be useful for determining the best allocation of resources for monitoring and conservation.

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Fichiers liés : journal.pone.0091683.pdf

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• Type de publi. : Article dans une revue
• Date de publi. : 01/01/2014
• Auteurs : Isabelle DreyfusCécile ChouquetKhaled EzzedineSophie HennerChristine ChiaveriniAude MazaSandrine PascalLauriane RodriguezPierre VabresLudovic MartinStephanie MalletSebastien BarbarotJérôme DupuisJuliette Mazereeuw-Hautier
• Organismes : Centre de référence des maladies rares de la peau et des muqueuses d’origine génétique [CHU Toulouse] Institut de Mathématiques de Toulouse UMR5219 Centre de réréfence des maladies rares de la peau, CHU bordeaux Centre de référence des maladies rares de la peau et des muqueuses d’origine génétique [CHU Toulouse] Centre de référence de dermatologie pédiatrique Centre de référence des maladies rares de la peau et des muqueuses d’origine génétique [CHU Toulouse] Institut de Mathématiques de Toulouse UMR5219 Centre de référence des maladies rares de la peau et des muqueuses d’origine génétique [CHU Toulouse] Service de Dermatologie (CHU de Dijon) Département de dermatologie, CHU Angers Département de dermatologie, CHU Marseille Centre de compétence des maladies rares de la peau, CHU Nantes Institut de Mathématiques de Toulouse UMR5219 Centre de référence des maladies rares de la peau et des muqueuses d’origine génétique [CHU Toulouse]
• Publié dans Orphanet Journal of Rare Diseases le 27/10/2020

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Résumé : BACKGROUND:Inherited ichthyoses represent a group of rare skin disorders characterized by scaling, hyperkeratosis and inconstant erythema, involving most of the tegument. Epidemiology remains poorly described. This study aims to evaluate the prevalence of inherited ichthyosis (excluding very mild forms) and its different clinical forms in France.METHODS:Capture - recapture method was used for this study. According to statistical requirements, 3 different lists (reference/competence centres, French association of patients with ichthyosis and internet network) were used to record such patients. The study was conducted in 5 areas during a closed period.RESULTS:The prevalence was estimated at 13.3 per million people (/M) (CI95%, [10.9 - 17.6]). With regard to autosomal recessive congenital ichthyosis, the prevalence was estimated at 7/M (CI 95% [5.7 - 9.2]), with a prevalence of lamellar ichthyosis and congenital ichthyosiform erythroderma of 4.5/M (CI 95% [3.7 - 5.9]) and 1.9/M (CI 95% [1.6 - 2.6]), respectively. Prevalence of keratinopathic forms was estimated at 1.1/M (CI 95% [0.9 - 1.5]). Prevalence of syndromic forms (all clinical forms together) was estimated at 1.9/M (CI 95% [1.6 - 2.6]).CONCLUSIONS:Our results constitute a crucial basis to properly size the necessary health measures that are required to improve patient care and design further clinical studies.

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Fichiers liés : 1750-1172-9-1_3_.pdf

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• Type de publi. : Communication dans un congrès
• Date de publi. : 03/07/2013
• Auteurs : Jérôme DupuisMichel GoulardJean Joachim
• Organismes : Laboratoire de Statistique et Probabilités Dynamiques Forestières dans l'Espace Rural Unité de recherche Comportement et Ecologie de la Faune Sauvage

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• Type de publi. : Article dans une revue
• Date de publi. : 01/01/2011
• Auteurs : Florent BledJean JoachimJérôme Dupuis
• Organismes : Evolution et Diversité Biologique Unité de recherche Comportement et Ecologie de la Faune Sauvage Laboratoire de Statistique et Probabilités
• Publié dans Biodiversity and Conservation le 28/10/2020

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Résumé : Species that are affected by climatic variations can undergo modification in range and/or abundance. Knowing how individuals or species occupy their habitat is essential to understand how species use their environment, and detecting variations that might affect this use can be determinant in species management. Hierarchical modeling is regularly used to assess for occupancy rate (i.e. proportion of patches occupied in a region), particularly when it is required to consider detectability-related issues. The present study is the first application of the conditional model presented in Dupuis et al. (Biometrics 2010), which is applied in the case of a heterogeneous area that might be divided into homogeneous sub-areas. Their approach is used to study the impact of three consecutive particularly cold winters on a selected set of bird species in a forest of southern France in the context of available prior information on birds detectability. We examined a limited range of factors that might influence the response of some bird species to climate. We considered the case of sedentary, partially migrating and migrating species. We also assessed if the biogeographical origins of the different species affect their occupancy rates. Globally, changes in occupancy rates between 1985 and 1987 indicates for the first time a continentalization of the regional forest fauna, reflected by the expansion of Palearctic and Turkestano-European faunistic type species, with depletion or extinction of European, Turkestano-Mediterranean and Mediterranean sedentary species. We have also shown the importance of prior information.

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Fichiers liés : BledJoachimDupuis_Biodiv_Conserv.pdf

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• Type de publi. : Article dans une revue
• Date de publi. : 01/01/2011
• Auteurs : Jérôme DupuisMichel Goulard
• Organismes : Institut de Mathématiques de Toulouse UMR5219 Unité de gestion du département de biométrie et intelligence artificielle
• Publié dans Biometrics le 25/10/2020

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Résumé : We consider the problem of estimating the number of species (denoted by S) of a biological community located in a region divided into n quadrats. To address this question, different hierarchical parametric approaches have been recently developed. Despite a detailed modeling of the underlying biological processes, they all have some limitations. Indeed, some assume that n is theoretically infinite; as a result, n and the sampling fraction are not a part of such models. Others require some prior information on S to be efficiently implemented. Our approach is more general in that it applies without limitation on the size of n, and it can be used in the presence, as well as in the absence, of prior information on S. Moreover, it can be viewed as an extension of the approach of Dorazio and Royle (2005, Journal of the American Statistical Association 100, 389–398) in that n is a part of the model and a prior distribution is placed on S. Despite serious computational difficulties, we have perfected an efficient Markov chain Monte Carlo algorithm, which allows us to obtain the Bayesian estimate of S. We illustrate our approach by estimating the number of species of a bird community located in a forest.

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• Type de publi. : Article dans une revue
• Date de publi. : 01/01/2011
• Auteurs : Jérôme DupuisFlorent BledJean Joachim
• Organismes : Institut de Mathématiques de Toulouse UMR5219 Evolution et Diversité Biologique Unité de recherche Comportement et Ecologie de la Faune Sauvage
• Publié dans Biometrics le 25/10/2020

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Résumé : We consider the problem of estimating the occupancy rate of a target species in a region divided in spatial units (called quadrats); this quantity being defined as the proportion of quadrats occupied by this species. We mainly focus on spatially rare or hard to detect species that are typically detected in very few quadrats, and for which estimating the occupancy rate (with an acceptable precision) is problematic. We develop a conditional approach for estimating the quantity of interest; we condition on the presence of the target species in the region of study. We show that conditioning makes identifiable the occurrence and detectability parameters, regardless of the number of visits made in the sampled quadrats. Compared with an unconditional approach, it proves to be complementary, in that this allows us to deal with biological questions that cannot be addressed by the former. Two Bayesian analyses of the data are performed: one is noninformative, and the other takes advantage of the fact that some prior information on detectability is available. It emerges that taking such a prior into account significantly improves the precision of the estimate when the target species has been detected in few quadrats and is known to be easily detectable.

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• Type de publi. : Pré-publication, Document de travail
• Date de publi. : 18/07/2010
• Auteurs : Jérôme DupuisMichel Goulard
• Organismes : Laboratoire de Statistique et Probabilités Dynamiques Forestières dans l'Espace Rural

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Résumé : We consider the problem of estimating the number of species (denoted by S) of a biological community located in a region composed of $n$ quadrats. To address this question, different parametric approaches have been recently developed. However, they all have some limitations which reduce their use in practice: indeed, either they presuppose that the sampled quadrats are taken from a large population of quadrats (theoretically infinite), or they require an upper bound on S. Our approach is more general in that it applies without limitation on $n$ and it can be used in the presence of prior information on S, as well as in totally unknown regions. We pay attention to the prior adopted for S; in particular, different non informative priors are considered and motivated. We first consider a simple model which assumes that occurrence and detectability parameters do not depend on quadrats. It constitutes a suitable framework to clarify the links existing between current approaches and ours. We then extend this model by assuming that the region of study is spatially heterogeneous. We illustrate our approach by estimating the number of species of a birds community located in a forest.

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Fichiers liés : Hal_Dupuis_Goulard.pdf

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• Type de publi. : Pré-publication, Document de travail
• Date de publi. : 10/07/2008
• Auteurs : Jérôme Dupuis
• Organismes : Laboratoire de Statistique et Probabilités

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Résumé : We consider the problem of estimating the number of species of a biological community located in a region R divided into J quadrats. Recently, two parametric approaches have been developed which both take into account in a same modeling framework the detectability and the occurence of species in the quadrats. One developed by Dorazio and Royle (2005, J.A.S.A. 100, 389-398) ignores the unsampled part of R (thus also J) and models the occurence of species only in the sampled quadrats. We show that this approach can be used only if J is large, which limits its use in practice, since the value of J can strongly vary from one study to another. The other developed by Dupuis and Joachim (2006, Biometrics 62, 706-712) does not have this limitation but it applies only in the presence of prior information. In this paper, we propose a new approach which extends these two approaches since it can be used in non informative setups, and applies without limitation on J. We develop our approach within a simple model, which assumes that the species population is homogeneous. This constitutes the suitable framework for examining the effect that ignoring J has on the Bayesian estimate of species richness. In particular, a simulation study is undertaken which shows that the approach of Dorazio and Royle generates an error which can be important for small or moderate values of J, when species are spatially rare or hard to detect.

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Fichiers liés : Hal10juillet.pdf

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• Type de publi. : Article dans une revue
• Date de publi. : 01/01/2007
• Auteurs : Jérôme DupuisCarl James Schwarz
• Organismes : Laboratoire de Statistique et Probabilités Institut de Mathématiques de Toulouse UMR5219
• Publié dans Biometrics le 25/10/2020

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• Type de publi. : Article dans une revue
• Date de publi. : 01/01/2006
• Auteurs : Jérôme DupuisJean Joachim
• Organismes : Université Toulouse III - Paul Sabatier Unité de recherche Comportement et Ecologie de la Faune Sauvage
• Publié dans Biometrics le 25/10/2020

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Résumé : We consider the problem of estimating the number of species of an animal community. It is assumed that it is possible to draw up a list of species liable to be present in this community. Data are collected from quadrat sampling. Models considered in this article separate the assumptions related to the experimental protocol and those related to the spatial distribution of species in the quadrats. Our parameterization enables us to incorporate prior information on the presence, detectability, and spatial density of species. Moreover, we elaborate procedures to build the prior distributions on these parameters from information furnished by external data. A simulation study is carried out to examine the influence of different priors on the performances of our estimator. We illustrate our approach by estimating the number of nesting bird species in a forest

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