Preliminary data on movements and health condition of the first radio-collared huemul (Hippocamelus bisulcus) population study in Argentina

Aun cuando solo quedan menos de 500 ejemplares de huemul patagonico (Hippocamelus bisulcus) en Argentina, existe escasa información sobre su ecología y dinámicas poblacionales. Por primera vez en la historia de Argentina, se instalaron equipos de radio telemetría en un grupo de huemules para entender de mejor forma los factores que no han permito la recuperación de las poblaciones. Durante el invierno del 2017, se procedió a la captura de seis ejemplares en seis días (tres de cada género), al interior del parque protegido Shoonem, provincia de Chubut. Se presenta en este artículo una descripción de las condiciones particulares del clima y las características del paisaje que serán útiles considerar para mejorar el éxito de capturas de huemules, particularmente en Argentina. Aun cuando los animales capturados presentaban un aspecto sano a primera vista, durante la última evaluación (25 enero 2018), identificamos signos clínicos de enfermedad en 5 de 6 animales capturados durante el procedimiento; incluyendo renguera, pezuñas deterioradas, perdida de 2-7 incisivos y atrofia muscular. Los desplazamientos registrados desde el sitio de captura en régimen de invernada a zonas de uso estival fueron 187% mayores en las hembras comparativamente a los machos.Even though less than 500 Patagonian huemul (Hippocamelus bisulcus) remain in Argentina, information on their population ecology and dynamics is severely lacking. For the first time in Argentine history, radio-telemetry collars were placed on a group of huemul to better understand the factors behind the population?s failure to recover. Six adult huemul (3 of each gender) were captured in six days, the winter of 2017, inside Shoonem Protected Park, Chubut province. In this article, we present a description of the unique climatic conditions and characteristics of the environment that would be useful to consider in order improving the success of huemul captures, particularly in Argentina. Despite the outwardly healthy appearance of each radio-collared huemul on the last observation date (January 25, 2018), we identified clinical symptoms of disease in 5 of these 6 animals during their capture; these included lameness, affected hoof, exfoliation of 2-7 incisors, and muscular atrophy. Movement distances from the winter capture site to maximum summer distance recorded were 187% greater for females than males (n=6, p =0.05, Mann Whitney).Fil: Smith Flueck, Jo Anne. Universidad Nacional del Comahue; ArgentinaFil: Fluck, Werner Thomas. Universidad de Basilea; Suiza. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Patagonia Norte; ArgentinaFil: Escobar Ruiz, Miguel. Fundación Shoonem; Argentin

Robust statistics: a functional approach

International audienceFor a given statistical method, good properties are usually obtained under strong hypotheses that are likely not to be verified in practice. In this context, the robustness of a method refers to its capability of keeping good properties even when the hypotheses are not verified. Statistics imply the treatment of data sets that are assumed to be the realization of random variables. The assumptions usually concern the probability distribution from which the data set is generated. One field in Statistics called “robust statistics” consists in defining some measures of robustness and proposes robust methods in the sense of these measures. After giving some basic notions of statistics, we present different well-known measures of robustness from the “robust statistics” field. In order to illustrate the ideas we consider the simple case of estimating a “mean” using the arithmetic mean, the median, the trimmed and the winzorised mean. The paper is an introductory presentation of robust statistics for readers who are not necessarily statisticians but it contains some technical details. The reader not interested in such details can read the introduction of each section and subsection where general ideas are given in simple words.Les bonnes propriétés d’une méthode statistique donnée sont généralement obtenues sous des hypothèses fortes qui ne sont pas vérifiées en pratique. Dans ce contexte, la robustesse d’une méthode consiste en sa capacité à garder de bonnes propriétés même lorsque les hypothèses ne sont pas vérifiées. La Statistique implique le traitement de donnéées qui sont supposées être la réalisation de variables aléatoires. Les hypothèses portent en général sur la distribution de probabilités sous-jacente aux données. Un domaine de la Statistique appelé “statistique robuste” consiste à définir des mesures de robustesse et à proposer des méthodes robustes au sens des mesures précédemment définies. Après avoir présenté des notions de base en statistique, nous donnons différentes mesures de robustesse bien connues dans le domaine. Pour illustrer les idées, nous considérons le cas simple de l’estimation d’une “moyenne” par la moyenne arithmétique, la médiane, la moyenne tronquée et la moyenne winzorisée. Le papier se veut un exposé introductif à la statistique robuste qui s’adresse à des lecteurs non nécessairement statisticiens mais il contient toutefois des détails techniques. Le lecteur qui n’est pas intéressé par ces détails pourra se contenter de lire l’introduction des différentes sections et sous-sections

The origins of women's rights movement in the United States: the Seneca Falls Convention

25 p. : il. -- Bibliogr.: p. 20-22In the 19th century, women had very limited or almost inexistent rights. They lived in a male dominated world where they had restricted access to many fields and they were considered to be an ornament of their husband in public life, and as a domestic agent to the interior of the family, as the Spanish contemporary expression ángel del hogar denotes. In the eyes of the law, they were civilly dead. They were considered fragile and delicate, because they were dependent on a man from birth to death. Tired of being considered less than their male companions, a women’s rights movement emerged in the small town of Seneca Falls, New York, in 1848. Women gathered for the first time in history at the Wesleyan Chapel to discuss women’s rights and to find a solution to the denigration they had suffered by men and society during the years. Around 300 people gathered in Seneca Falls, both men and women. As an attempt to amend the wrongs of men, these women created the Declaration of Rights and Sentiments, a document based on the Declaration of Independence, expressing their discontent with how the society had treated them and asking for a change and equal rights, among which there was the right for suffrage. These women based their ideas on previous feminist influences, such as Mary Wollstonecraft and Olympe de Gouges. In fact, de Gouges’ Declaration of the Rights of Woman and of the Female Citizen resembles to the Declaration of Rights and Sentiments created 57 years later by Elizabeth Cady Stanton. Nonetheless, it was not until the 19th Amendment passed in 1992 that the United States finally granted the right to vote to women

Voces de las buenas mujeres: An ethnographic study of marianismo among Mexican American and Mexican women

Research has focused on gender roles of the Hispanic male and female in regards to the machismo social construct. The current study examines the other side of machismo, via Gil and Vasquez\u27s (1996) Ten Commandments of Marianismo, and explores the validity of this social construct through interviews with Mexican American and Mexican women. Twenty Mexican American and Mexican women were selected through a nonrandom purposive sample to participate in the interviews. The taped interviews were analyzed verbatim. Eight categories emerged which are directly related to marianismo. The women\u27s responses are used to convey their attitudes, roles, and relationships and to identify any similarities between the Mexican American and Mexican women concerning the marianismo construct

Storms prediction : Logistic regression vs random forest for unbalanced data

The aim of this study is to compare two supervised classification methods on a crucial meteorological problem. The data consist of satellite measurements of cloud systems which are to be classified either in convective or non convective systems. Convective cloud systems correspond to lightning and detecting such systems is of main importance for thunderstorm monitoring and warning. Because the problem is highly unbalanced, we consider specific performance criteria and different strategies. This case study can be used in an advanced course of data mining in order to illustrate the use of logistic regression and random forest on a real data set with unbalanced classes

Improving the estimation of the odds ratio in sampling surveys using auxiliary information

The odds-ratio measure is widely used in Health and Social surveys where the aim is to compare the odds of a certain event between a population at risk and a population not at risk. It can be defined using logistic regression through an estimating equation that allows a generalization to continuous risk variable. Data from surveys need to be analyzed in a proper way by taking into account the survey weights. Because the odds-ratio is a complex parameter, the analyst has to circumvent some difficulties when estimating confidence intervals. The present paper suggests a nonparametric approach that can take advantage of some auxiliary information in order to improve on the precision of the odds-ratio estimator. The approach consists in B-spline modelling which can handle the nonlinear structure of the parameter in a exible way and is easy to implement. The variance estimation issue is solved through a linearization approach and confidence intervals are derived. Two small applications are discussed