The cases of June 2000, November 2002 and September 2002 as examples of Mediterranean floods

International audienceFour flood events that affected three different countries are here described in terms of meteorological genesis and in terms of consequences on the population and on the territory. Each event is a good representative of a class of phenomena that produce important effects on the urban and extra-urban tissue and that must be taken into account in an optic of civil protection and risk evaluation. This is the subject of the HYDROPTIMET project, part of the Interreg IIIB program, which is collocated in the framework of the prevention of natural hazards and, in particular, those related to severe meteo-hydrological events. This paper aims at being a general introduction of the four events which are the subject of more detailed studies, already published or under submission

Multivariate restricted maximum likelihood estimation of genetic parameters for production traits in three selected turkey strains

Genetic parameters related to growth, carcass composition and egg production were estimated on three (two female and one male) commercial strains of turkey using the method of restricted maximum likelihood (REML). In order to account for the sexual dimorphism in turkeys, body weight (BW, measured at 12 and 16 weeks of age) was considered as a sex-limited trait. As many as seven traits were analyzed simultaneously in one strain. Egg numbers were normalized using a Box-Cox transformation. Three different genetic models were used. The first one was a linear mixed model with a direct genetic effect. Model 2 accounted in addition for a dam’s environmental effect, while model 3 introduced a maternal genetic effect. The heritability estimates of BW were very high, especially for female traits (0.77 for female BW16 and 0.68 for male BW16 in strain B). Sexual dimorphism was less heritable (0.23, 0.16, and 0.14 for the 16 weeks body weight sex difference in the three strains considered). One of the female strains exhibited a strongly negative genetic correlation (-0.5) between female BW and egg number. The elevated values of the estimates probably originated from the method used, which accounted for the bias due to the sequential selection that had been carried out, and from the choice of the base population. Use of models 2 and 3 resulted in slightly lower heritability estimates than model 1, due to low maternal effects. The latter, however, offered a reasonable compromise between quality and computational cost of the evaluations.Les paramètres génétiques de caractères relatifs à la croissance (poids corporels à 12 et 16 semaines), la teneur en gras (mesure ultrasonique) et la ponte ont été estimés à l’aide de la méthode du maximum de la vraisemblance restreinte (REML) dans trois souches de dindes sélectionnées. Les caractères de poids ont été séparés selon les sexes, afin de rendre compte du dimorphisme sexuel important dans l’espèce et jusqu’à sept caractères ont ainsi été analysés simultanément dans une des souches. Les données de ponte ont été normalisées à l’aide d’une transformation de Box-Cox. Trois modèles génétiques différents ont été utilisés. Le premier est un modèle linéaire mixte incluant la valeur génétique additive individuelle comme effet aléatoire. Dans les autres on ajoute un effet maternel d’abord considéré comme un effet essentiellement de milieu (modèle 2) puis uniquement génétique (modèle 3). Les héritabilités sont très fortes pour les poids corporels, plus élevées pour les poids femelles que pour les poids mâles (0,77 pour les femelles à 16 semaines dans la lignée B contre 0,68 pour les mâles). Le dimorphisme sexuel est un caractère plus faiblement héritable (0,23; 0,16; et 0,14 pour la différence de poids entre mâles et femelles à 16 semaines dans les trois lignées). Dans une des lignées femelles, la corrélation génétique est fortement négative (-0,5) entre le poids des femelles et le nombre d’oeufs pondus. Les valeurs élevées des paramètres génétiques s’expliquent probablement par la méthode employée qui permet de prendre en compte le biais important lié à la sélection de type séquentiel. Le choix de la population de base permet également d’expliquer ces valeurs inhabituelles. Les modèles 2 et 3 donnent des estimées légèrement moins élevées pour les héritabilités que le modèle 1, à cause de la faiblesse des effets maternels. Le modèle 1 permet néanmoins un bon compromis entre simplicité des calculs et qualité de la description

Multivariate restricted maximum likelihood estimation of genetic parameters for production traits in three selected turkey strains

Genetic parameters related to growth, carcass composition and egg production were estimated on three (two female and one male) commercial strains of turkey using the method of restricted maximum likelihood (REML). In order to account for the sexual dimorphism in turkeys, body weight (BW, measured at 12 and 16 weeks of age) was considered as a sex-limited trait. As many as seven traits were analyzed simultaneously in one strain. Egg numbers were normalized using a Box-Cox transformation. Three different genetic models were used. The first one was a linear mixed model with a direct genetic effect. Model 2 accounted in addition for a dam’s environmental effect, while model 3 introduced a maternal genetic effect. The heritability estimates of BW were very high, especially for female traits (0.77 for female BW16 and 0.68 for male BW16 in strain B). Sexual dimorphism was less heritable (0.23, 0.16, and 0.14 for the 16 weeks body weight sex difference in the three strains considered). One of the female strains exhibited a strongly negative genetic correlation (-0.5) between female BW and egg number. The elevated values of the estimates probably originated from the method used, which accounted for the bias due to the sequential selection that had been carried out, and from the choice of the base population. Use of models 2 and 3 resulted in slightly lower heritability estimates than model 1, due to low maternal effects. The latter, however, offered a reasonable compromise between quality and computational cost of the evaluations.Les paramètres génétiques de caractères relatifs à la croissance (poids corporels à 12 et 16 semaines), la teneur en gras (mesure ultrasonique) et la ponte ont été estimés à l’aide de la méthode du maximum de la vraisemblance restreinte (REML) dans trois souches de dindes sélectionnées. Les caractères de poids ont été séparés selon les sexes, afin de rendre compte du dimorphisme sexuel important dans l’espèce et jusqu’à sept caractères ont ainsi été analysés simultanément dans une des souches. Les données de ponte ont été normalisées à l’aide d’une transformation de Box-Cox. Trois modèles génétiques différents ont été utilisés. Le premier est un modèle linéaire mixte incluant la valeur génétique additive individuelle comme effet aléatoire. Dans les autres on ajoute un effet maternel d’abord considéré comme un effet essentiellement de milieu (modèle 2) puis uniquement génétique (modèle 3). Les héritabilités sont très fortes pour les poids corporels, plus élevées pour les poids femelles que pour les poids mâles (0,77 pour les femelles à 16 semaines dans la lignée B contre 0,68 pour les mâles). Le dimorphisme sexuel est un caractère plus faiblement héritable (0,23; 0,16; et 0,14 pour la différence de poids entre mâles et femelles à 16 semaines dans les trois lignées). Dans une des lignées femelles, la corrélation génétique est fortement négative (-0,5) entre le poids des femelles et le nombre d’oeufs pondus. Les valeurs élevées des paramètres génétiques s’expliquent probablement par la méthode employée qui permet de prendre en compte le biais important lié à la sélection de type séquentiel. Le choix de la population de base permet également d’expliquer ces valeurs inhabituelles. Les modèles 2 et 3 donnent des estimées légèrement moins élevées pour les héritabilités que le modèle 1, à cause de la faiblesse des effets maternels. Le modèle 1 permet néanmoins un bon compromis entre simplicité des calculs et qualité de la description

Heritability of longevity in Large White and Landrace sows using continuous time and grouped data models

<p>Abstract</p> <p>Background</p> <p>Using conventional measurements of lifetime, it is not possible to differentiate between productive and non-productive days during a sow's lifetime and this can lead to estimated breeding values favoring less productive animals. By rescaling the time axis from continuous to several discrete classes, grouped survival data (discrete survival time) models can be used instead.</p> <p>Methods</p> <p>The productive life length of 12319 Large White and 9833 Landrace sows was analyzed with continuous scale and grouped data models. Random effect of herd*year, fixed effects of interaction between parity and relative number of piglets, age at first farrowing and annual herd size change were included in the analysis. The genetic component was estimated from sire, sire-maternal grandsire, sire-dam, sire-maternal grandsire and animal models, and the heritabilities computed for each model type in both breeds.</p> <p>Results</p> <p>If age at first farrowing was under 43 weeks or above 60 weeks, the risk of culling sows increased. An interaction between parity and relative litter size was observed, expressed by limited culling during first parity and severe risk increase of culling sows having small litters later in life. In the Landrace breed, heritabilities ranged between 0.05 and 0.08 (s.e. 0.014-0.020) for the continuous and between 0.07 and 0.11 (s.e. 0.016-0.023) for the grouped data models, and in the Large White breed, they ranged between 0.08 and 0.14 (s.e. 0.012-0.026) for the continuous and between 0.08 and 0.13 (s.e. 0.012-0.025) for the grouped data models.</p> <p>Conclusions</p> <p>Heritabilities for length of productive life were similar with continuous time and grouped data models in both breeds. Based on these results and because grouped data models better reflect the economical needs in meat animals, we conclude that grouped data models are more appropriate in pig.</p

Estimation of genetic parameters of egg production traits of laying hens by restricted maximum likelihood applied to a multiple-trait reduced animal model

International audienc

Genetic parameters for social effects on survival in cannibalistic layers: Combining survival analysis and a linear animal model

<p>Abstract</p> <p>Background</p> <p>Mortality due to cannibalism in laying hens is a difficult trait to improve genetically, because censoring is high (animals still alive at the end of the testing period) and it may depend on both the individual itself and the behaviour of its group members, so-called associative effects (social interactions). To analyse survival data, survival analysis can be used. However, it is not possible to include associative effects in the current software for survival analysis. A solution could be to combine survival analysis and a linear animal model including associative effects. This paper presents a two-step approach (2STEP), combining survival analysis and a linear animal model including associative effects (LAM).</p> <p>Methods</p> <p>Data of three purebred White Leghorn layer lines from Institut de Sélection Animale B.V., a Hendrix Genetics company, were used in this study. For the statistical analysis, survival data on 16,780 hens kept in four-bird cages with intact beaks were used. Genetic parameters for direct and associative effects on survival time were estimated using 2STEP. Cross validation was used to compare 2STEP with LAM. LAM was applied directly to estimate genetic parameters for social effects on observed survival days.</p> <p>Results</p> <p>Using 2STEP, total heritable variance, including both direct and associative genetic effects, expressed as the proportion of phenotypic variance, ranged from 32% to 64%. These results were substantially larger than when using LAM. However, cross validation showed that 2STEP gave approximately the same survival curves and rank correlations as LAM. Furthermore, cross validation showed that selection based on both direct and associative genetic effects, using either 2STEP or LAM, gave the best prediction of survival time.</p> <p>Conclusion</p> <p>It can be concluded that 2STEP can be used to estimate genetic parameters for direct and associative effects on survival time in laying hens. Using 2STEP increased the heritable variance in survival time. Cross validation showed that social genetic effects contribute to a large difference in survival days between two extreme groups. Genetic selection targeting both direct and associative effects is expected to reduce mortality due to cannibalism in laying hens.</p