{"id":111784,"date":"2018-03-11T10:38:27","date_gmt":"2018-03-11T10:38:27","guid":{"rendered":"https:\/\/www.deberes.net\/tesis\/sin-categoria\/bases-metodologicas-para-un-sistema-de-apoyo-a-la-seleccion-de-especies-en-la-restauracion-de-la-vegetacion\/"},"modified":"2018-03-11T10:38:27","modified_gmt":"2018-03-11T10:38:27","slug":"bases-metodologicas-para-un-sistema-de-apoyo-a-la-seleccion-de-especies-en-la-restauracion-de-la-vegetacion","status":"publish","type":"post","link":"https:\/\/www.deberes.net\/tesis\/ecologia-vegetal\/bases-metodologicas-para-un-sistema-de-apoyo-a-la-seleccion-de-especies-en-la-restauracion-de-la-vegetacion\/","title":{"rendered":"Bases metodol\u00f3gicas para un sistema de apoyo a la selecci\u00f3n de especies en la restauraci\u00f3n de la vegetaci\u00f3n"},"content":{"rendered":"<h2>Tesis doctoral de <strong> Aitor Gast\u00f3n Gonz\u00e1lez <\/strong><\/h2>\n<p>El apoyo a la selecci\u00f3n de especies a la restauraci\u00f3n de la vegetaci\u00f3n en espa\u00f1a en los \u00faltimos 40 a\u00f1os se ha basado fundamentalmente en modelos de distribuci\u00f3n de especies, tambi\u00e9n llamados modelos de nicho ecol\u00f3gico, que estiman la probabilidad de presencia de las especies en funci\u00f3n de las condiciones del medio f\u00edsico (clima, suelo, etc.). Con esta tesis se ha contribuido a la mejora de la capacidad predictiva de los modelos introduciendo algunas propuestas metodol\u00f3gicas adaptadas a los datos disponibles actualmente en espa\u00f1a y enfocadas al uso de los modelos en la selecci\u00f3n de especies.  \tno siempre se dispone de datos a una resoluci\u00f3n espacial adecuada para la escala de los proyectos de restauraci\u00f3n de la vegetaci\u00f3n. Sin embrago es habitual contar con datos de baja resoluci\u00f3n espacial para casi todas las especies vegetales presentes en espa\u00f1a. Se propone un m\u00e9todo de recalibraci\u00f3n que actualiza un modelo de regresi\u00f3n log\u00edstica de baja resoluci\u00f3n espacial con una nueva muestra de alta resoluci\u00f3n espacial. El m\u00e9todo permite obtener predicciones de calidad aceptable con muestras relativamente peque\u00f1as (25 presencias de la especie) frente a las muestras mucho mayores (m\u00e1s de 100 presencias) que requer\u00eda una estrategia de modelizaci\u00f3n convencional que no usara el modelo previo.  \tla selecci\u00f3n del m\u00e9todo estad\u00edstico puede influir decisivamente en la capacidad predictiva de los modelos y por esa raz\u00f3n la comparaci\u00f3n de m\u00e9todos ha recibido mucha atenci\u00f3n en la \u00faltima d\u00e9cada. Los estudios previos consideraban a la regresi\u00f3n log\u00edstica como un m\u00e9todo inferior a t\u00e9cnicas m\u00e1s modernas como las de m\u00e1xima entrop\u00eda. Los resultados de la tesis demuestran que esa diferencia observada se debe a que los modelos de m\u00e1xima entrop\u00eda incluyen t\u00e9cnicas de regularizaci\u00f3n y la versi\u00f3n de la regresi\u00f3n log\u00edstica usada en las comparaciones no. Una vez incorporada la regularizaci\u00f3n a la regresi\u00f3n log\u00edstica usando penalizaci\u00f3n, las diferencias en cuanto a capacidad predictiva desaparecen. La regresi\u00f3n log\u00edstica penalizada es, por tanto, una alternativa m\u00e1s para el ajuste de modelos de distribuci\u00f3n de especies y est\u00e1 a la altura de los m\u00e9todos modernos con mejor capacidad predictiva como los de m\u00e1xima entrop\u00eda.  \ta menudo, los modelos de distribuci\u00f3n de especies no incluyen variables relativas al suelo debido a que no es habitual que se disponga de mediciones directas de sus propiedades f\u00edsicas o qu\u00edmicas. La incorporaci\u00f3n de datos de baja resoluci\u00f3n espacial proveniente de mapas de suelo nacionales o continentales podr\u00eda ser una alternativa. Los resultados de esta tesis sugieren que los modelos de distribuci\u00f3n de especies de alta resoluci\u00f3n espacial mejoran de forma ligera pero estad\u00edsticamente significativa su capacidad predictiva cuando se incorporan variables relativas al suelo procedente de mapas de baja resoluci\u00f3n espacial.  \tla validaci\u00f3n es una de las etapas fundamentales del desarrollo de cualquier modelo emp\u00edrico como los modelos de distribuci\u00f3n de especies. Lo habitual es validar los modelos evaluando su capacidad predictiva especie a especie, es decir, comparando en un conjunto de localidades la presencia o ausencia observada de la especie con las predicciones del modelo. Este tipo de evaluaci\u00f3n no responde a una cuesti\u00f3n clave en la restauraci\u00f3n de la vegetaci\u00f3n \u00c2\u00bfcuales son las n especies m\u00e1s id\u00f3neas para el lugar a restaurar? Se ha propuesto un m\u00e9todo de evaluaci\u00f3n de modelos adaptado a esta cuesti\u00f3n que consiste en estimar la capacidad de un conjunto de modelos para discriminar entre las especies presentes y ausentes de un lugar concreto. El m\u00e9todo se ha aplicado con \u00e9xito a la validaci\u00f3n de 188 modelos de distribuci\u00f3n de especies le\u00f1osas orientados a la selecci\u00f3n de especies para la restauraci\u00f3n de la vegetaci\u00f3n en espa\u00f1a.  \tlas mejoras metodol\u00f3gicas propuestas permiten incrementar la capacidad predictiva de los modelos de distribuci\u00f3n de especies aplicados a la selecci\u00f3n de especies en la restauraci\u00f3n de la vegetaci\u00f3n y tambi\u00e9n permiten ampliar el n\u00famero de especies para  las que se puede contar con un modelo que apoye la toma de decisiones.  summary  \tduring the last 40 years, decision support tools for plant species selection in ecological restoration in spain have been based on species distribution models (also called ecological niche models), that estimate the probability of occurrence of the species as a function of environmental predictors (e.G., Climate, soil). In this thesis some methodological improvements are proposed to contribute to a better predictive performance of such models, given the current data available in spain and focusing in the application of the models to selection of species for ecological restoration.   \tfine grained  species distribution data are required to train models to be used at the scale of the ecological restoration projects, but  this kind of data are not always available for every species. On the other hand, coarse grained data are available for almost every species in spain. A recalibration method is proposed that updates a coarse grained logistic regression model using a new fine grained updating sample. The method allows obtaining acceptable predictive performance with reasonably small updating sample (25 occurrences of the species), in contrast with the much larger samples (more than 100 occurrences) required for a conventional modeling approach that discards the coarse grained data.  \tthe choice of the statistical method may have a dramatic effect on model performance, therefore comparisons of methods have received much interest in the last decade. Previous studies have shown a poorer performance of the logistic regression compared to novel methods like maximum entropy models. The results of this thesis show that the observed difference is caused by the fact that maximum entropy models include regularization techniques and the versions of logistic regression compared do not. Once regularization has been added to the logistic regression using a penalization procedure, the differences in model performance disappear. Therefore, penalized logistic regression may be considered one of the best performing methods to model species distributions.  \tusually, species distribution models do not consider soil related predictors because direct measurements of the chemical or physical properties are often lacking. The inclusion of coarse grained soil data from national or continental soil maps could be a reasonable alternative. The results of this thesis suggest that the performance of the models slightly increase after including soil predictors form coarse grained soil maps.  \tmodel validation is a key stage of the development of empirical models, such as species distribution models. The usual way of validating is based on the evaluation of model performance for each species separately, i.E., Comparing observed species presences or absence to predicted probabilities in a set of sites. This kind of evaluation is not informative for a common question in ecological restoration projects: which n species are the most suitable for the environment of the site to be restored? A method has been proposed to address this question that estimates the ability of a set of models to discriminate among present and absent species in a evaluation site. The method has been successfully applied to the validation of 188 species distribution models used to support decisions on species selection for ecological restoration in spain.  \tthe proposed methodological approaches improve the predictive performance of the predictive models applied to species selection in ecological restoration and increase the number of species for which a model that supports decisions can be fitted.<\/p>\n<p>&nbsp;<\/p>\n<h3>Datos acad\u00e9micos de la tesis doctoral \u00ab<strong>Bases metodol\u00f3gicas para un sistema de apoyo a la selecci\u00f3n de especies en la restauraci\u00f3n de la vegetaci\u00f3n<\/strong>\u00ab<\/h3>\n<ul>\n<li><strong>T\u00edtulo de la tesis:<\/strong>\u00a0 Bases metodol\u00f3gicas para un sistema de apoyo a la selecci\u00f3n de especies en la restauraci\u00f3n de la vegetaci\u00f3n <\/li>\n<li><strong>Autor:<\/strong>\u00a0 Aitor Gast\u00f3n Gonz\u00e1lez <\/li>\n<li><strong>Universidad:<\/strong>\u00a0 Polit\u00e9cnica de Madrid<\/li>\n<li><strong>Fecha de lectura de la tesis:<\/strong>\u00a0 17\/11\/2011<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n<h3>Direcci\u00f3n y tribunal<\/h3>\n<ul>\n<li><strong>Director de la tesis<\/strong>\n<ul>\n<li>Juan  Ignacio Garc\u00eda Vi\u00f1as<\/li>\n<\/ul>\n<\/li>\n<li><strong>Tribunal<\/strong>\n<ul>\n<li>Presidente del tribunal: ramon Elena rossello <\/li>\n<li>Miguel angel De zavala girones (vocal)<\/li>\n<li>adrian Escudero alcantara (vocal)<\/li>\n<li>Rafael Serrada hierro (vocal)<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n<p>&nbsp;<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Tesis doctoral de Aitor Gast\u00f3n Gonz\u00e1lez El apoyo a la selecci\u00f3n de especies a la restauraci\u00f3n de la vegetaci\u00f3n en [&hellip;]<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center 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