Transtorno de ansiedade social e insatisfação com a imagem corporal em estudantes de medicina: prevalência e fatores associados

Pós-graduação em Saúde Coletiva - FMB

Efeitos da desconexão de habitat na diversidade funcional de anfíbios anuros (Amphibia: Anura) na Mata Atlântica

Amphibian populations worldwide have been suffering declines generated by habitat degradation, loss, fragmentation and habitat split. With habitat loss and fragmentation in the landscape comes habitat split, which is the separation between the adult anuran habitat and breeding sites, forcing individuals to move through matrix during breeding seasons. Thus, habitat split increases the chance of extinction of amphibians with aquatic larval development and acts as a filter in the selection of species having great influence on species richness and community structure. The use of functional diversity allows us to consider the identity and characteristics of each species to understand the effects of fragmentation processes. The objective of this study was to estimate the effects of habitat split, as well as habitat loss in the landscape, on amphibians functional diversity (FD) and species richness (S). We selected 26 landscapes from a database with anuran surveys of Brazilian Atlantic Forest. For each landscape we calculated DF, S and landscape metrics at multiple scales. To calculate the DF we considered traits that influenced species use and persistence in the landscape. We refined maps of forest remnants and water bodies for metrics calculation. To relate DF and S (response variables) to landscape variables (explanatory variables), we used a model selection approach, fitting generalized linear models (GLMS) and making your selection with AICc. We compared the effect of model absence and models with habitat split, habitat amount and habitat connectivity effects, as well as their interaction. The most plausible models for S were the sum and interaction between habitat split in 7.5 km scale. For anurans with terrestrial development, habitat amount was the only plausible explanatory variable, in the 5 km scale. For anurans with aquatic larvae habitat amount in larger scales and the addition of habitat amount and habitat split were plausible...

Efeitos da desconexão de habitat na diversidade funcional de anfíbios anuros (Amphibia: Anura) na Mata Atlântica

Amphibian populations worldwide have been suffering declines generated by habitat degradation, loss, fragmentation and habitat split. With habitat loss and fragmentation in the landscape comes habitat split, which is the separation between the adult anuran habitat and breeding sites, forcing individuals to move through matrix during breeding seasons. Thus, habitat split increases the chance of extinction of amphibians with aquatic larval development and acts as a filter in the selection of species having great influence on species richness and community structure. The use of functional diversity allows us to consider the identity and characteristics of each species to understand the effects of fragmentation processes. The objective of this study was to estimate the effects of habitat split, as well as habitat loss in the landscape, on amphibians functional diversity (FD) and species richness (S). We selected 26 landscapes from a database with anuran surveys of Brazilian Atlantic Forest. For each landscape we calculated DF, S and landscape metrics at multiple scales. To calculate the DF we considered traits that influenced species use and persistence in the landscape. We refined maps of forest remnants and water bodies for metrics calculation. To relate DF and S (response variables) to landscape variables (explanatory variables), we used a model selection approach, fitting generalized linear models (GLMS) and making your selection with AICc. We compared the effect of model absence and models with habitat split, habitat amount and habitat connectivity effects, as well as their interaction. The most plausible models for S were the sum and interaction between habitat split in 7.5 km scale. For anurans with terrestrial development, habitat amount was the only plausible explanatory variable, in the 5 km scale. For anurans with aquatic larvae habitat amount in larger scales and the addition of habitat amount and habitat split were plausible...

The relationship between banking market competition and risk-taking: Do size and capitalization matter?

This paper addresses the effects of bank competition on the risk-taking behaviors of banks in 10 Latin American countries between 2003 and 2008. We conduct our empirical approach in two steps. First, we estimate the Boone indicator, which is a measure of competition. We then regress this measure and other explanatory variables on the banking "stability inefficiency" derived simultaneously from the estimation of a stability stochastic frontier. Unlike previous findings, this paper concludes that competition affects risk-taking behavior in a non-linear way as both high and low competition levels enhance financial stability, while we find the opposite effect for average competition. In addition, bank size and capitalization are essential factors in explaining this relationship. On the one hand, the larger a bank is, the more it benefits from competition. On the other hand, a greater capital ratio is advantageous for banks that operate in collusive markets, while capitalization only enhances the stability of larger banks under high and average competition. These results are of extreme importance when considering bank regulations, especially in light of the recent turmoil in the global financial markets. (C) 2012 Elsevier B.V. All rights reserved.

Factors Associated with Height Catch-Up and Catch-Down Growth Among Schoolchildren

In developed countries, children with intrauterine growth restriction (IUGR) or born preterm (PT) tend to achieve catch-up growth. There is little information about height catch-up in developing countries and about height catch-down in both developed and developing countries. We studied the effect of IUGR and PT birth on height catch-up and catch-down growth of children from two cohorts of liveborn singletons. Data from 1,463 children was collected at birth and at school age in Ribeirao Preto (RP), a more developed city, and in Sao Luis (SL), a less developed city. A change in z-score between schoolchild height z-score and birth length z-score >= 0.67 was considered catch-up; a change in z-score <=-0.67 indicated catch-down growth. The explanatory variables were: appropriate weight for gestational age/PT birth in four categories: term children without IUGR (normal), IUGR only (term with IUGR), PT only ( preterm without IUGR) and preterm with IUGR; infant's sex; maternal parity, age, schooling and marital status; occupation of family head; family income and neonatal ponderal index (PI). The risk ratio for catch-up and catch-down was estimated by multinomial logistic regression for each city. In RP, preterms without IUGR (RR = 4.13) and thin children (PI<10th percentile, RR = 14.39) had a higher risk of catch-down; catch-up was higher among terms with IUGR (RR = 5.53), preterms with IUGR (RR = 5.36) and children born to primiparous mothers (RR = 1.83). In SL, catch-down was higher among preterms without IUGR (RR = 5.19), girls (RR = 1.52) and children from low-income families ( RR = 2.74); the lowest risk of catch-down (RR = 0.27) and the highest risk of catch-up (RR = 3.77) were observed among terms with IUGR. In both cities, terms with IUGR presented height catch-up growth whereas preterms with IUGR only had height catch-up growth in the more affluent setting. Preterms without IUGR presented height catch-down growth, suggesting that a better socioeconomic situation facilitates height catch-up and prevents height catch-down growth.

Multilevel Analysis in Household Survey: An Application to Health Condition Data

The aim of this thesis is to apply multilevel regression model in context of household surveys. Hierarchical structure in this type of data is characterized by many small groups. In last years comparative and multilevel analysis in the field of perceived health have grown in size. The purpose of this thesis is to develop a multilevel analysis with three level of hierarchy for Physical Component Summary outcome to: evaluate magnitude of within and between variance at each level (individual, household and municipality); explore which covariates affect on perceived physical health at each level; compare model-based and design-based approach in order to establish informativeness of sampling design; estimate a quantile regression for hierarchical data. The target population are the Italian residents aged 18 years and older. Our study shows a high degree of homogeneity within level 1 units belonging from the same group, with an intraclass correlation of 27% in a level-2 null model. Almost all variance is explained by level 1 covariates. In fact, in our model the explanatory variables having more impact on the outcome are disability, unable to work, age and chronic diseases (18 pathologies). An additional analysis are performed by using novel procedure of analysis :"Linear Quantile Mixed Model", named "Multilevel Linear Quantile Regression", estimate. This give us the possibility to describe more generally the conditional distribution of the response through the estimation of its quantiles, while accounting for the dependence among the observations. This has represented a great advantage of our models with respect to classic multilevel regression. The median regression with random effects reveals to be more efficient than the mean regression in representation of the outcome central tendency. A more detailed analysis of the conditional distribution of the response on other quantiles highlighted a differential effect of some covariate along the distribution.

Reporting of research quality characteristics of studies published in 6 major clinical dental specialty journals

The objective of this article was to record reporting characteristics related to study quality of research published in major specialty dental journals with the highest impact factor (Journal of Endodontics, Journal of Oral and Maxillofacial Surgery, American Journal of Orthodontics and Dentofacial Orthopedics; Pediatric Dentistry, Journal of Clinical Periodontology, and International Journal of Prosthetic Dentistry). The included articles were classified into the following 3 broad subject categories: (1) cross-sectional (snap-shot), (2) observational, and (3) interventional. Multinomial logistic regression was conducted for effect estimation using the journal as the response and randomization, sample calculation, confounding discussed, multivariate analysis, effect measurement, and confidence intervals as the explanatory variables. The results showed that cross-sectional studies were the dominant design (55%), whereas observational investigations accounted for 13%, and interventions/clinical trials for 32%. Reporting on quality characteristics was low for all variables: random allocation (15%), sample size calculation (7%), confounding issues/possible confounders (38%), effect measurements (16%), and multivariate analysis (21%). Eighty-four percent of the published articles reported a statistically significant main finding and only 13% presented confidence intervals. The Journal of Clinical Periodontology showed the highest probability of including quality characteristics in reporting results among all dental journals.

Which School Attributes Matter? The Influence of School District Performance and Demographic Composition on Property Values

Increasing levels of segregation in American schools raises the question: do home buyers pay for test scores or demographic composition? This paper uses Connecticut panel data spanning eleven years from 1994 to 2004 to ascertain the relationship between property values and explanatory variables that include school district performance and demographic attributes, such as racial and ethnic composition of the student body. Town and census tract fixed effects are included to control for neighborhood unobservables. The effect of changes in school district attributes is also examined over a decade long time frame in order to focus on the effect of long run changes, which are more likely to be capitalized into prices. The study finds strong evidence that increases in percent Hispanic has a negative effect on housing prices in Connecticut, but mixed evidence concerning the impact of test scores on property values. Evidence is also found to suggest that student test scores have increased in importance for explaining housing prices in recent years while the importance of percent Hispanic has declined. Finally, the study finds that estimates of property tax capitalization increase substantially when the analysis focuses on long run changes.

ECONOMIC ANALYSIS OF THE DEMAND FOR PRESCRIPTION MEDICINE IN THE UNITED STATES

The purpose of this study was to understand the role of principle economic, sociodemographic and health status factors in determining the likelihood and volume of prescription drug use. Econometric demand regression models were developed for this purpose. Ten explanatory variables were examined: family income, coinsurance rate, age, sex, race, household head education level, size of family, health status, number of medical visits, and type of provider seen during medical visits. The economic factors (family income and coinsurance) were given special emphasis in this study.^ The National Medical Care Utilization and Expenditure Survey (NMCUES) was the data source. The sample represented the civilian, noninstitutionalized residents of the United States in 1980. The sample method used in the survey was a stratified four-stage, area probability design. The sample was comprised of 6,600 households (17,123 individuals). The weighted sample provided the population estimates used in the analysis. Five repeated interviews were conducted with each household. The household survey provided detailed information on the United States health status, pattern of health care utilization, charges for services received, and methods of payments for 1980.^ The study provided evidence that economic factors influenced the use of prescription drugs, but the use was not highly responsive to family income and coinsurance for the levels examined. The elasticities for family income ranged from -.0002 to -.013 and coinsurance ranged from -.174 to -.108. Income has a greater influence on the likelihood of prescription drug use, and coinsurance rates had an impact on the amount spent on prescription drugs. The coinsurance effect was not examined for the likelihood of drug use due to limitations in the measurement of coinsurance. Health status appeared to overwhelm any effects which may be attributed to family income or coinsurance. The likelihood of prescription drug use was highly dependent on visits to medical providers. The volume of prescription drug use was highly dependent on the health status, age, and whether or not the individual saw a general practitioner. ^

Statistical models for short-term wind power ramp forecasting

La predicción de energía eólica ha desempeñado en la última década un papel fundamental en el aprovechamiento de este recurso renovable, ya que permite reducir el impacto que tiene la naturaleza fluctuante del viento en la actividad de diversos agentes implicados en su integración, tales como el operador del sistema o los agentes del mercado eléctrico. Los altos niveles de penetración eólica alcanzados recientemente por algunos países han puesto de manifiesto la necesidad de mejorar las predicciones durante eventos en los que se experimenta una variación importante de la potencia generada por un parque o un conjunto de ellos en un tiempo relativamente corto (del orden de unas pocas horas). Estos eventos, conocidos como rampas, no tienen una única causa, ya que pueden estar motivados por procesos meteorológicos que se dan en muy diferentes escalas espacio-temporales, desde el paso de grandes frentes en la macroescala a procesos convectivos locales como tormentas. Además, el propio proceso de conversión del viento en energía eléctrica juega un papel relevante en la ocurrencia de rampas debido, entre otros factores, a la relación no lineal que impone la curva de potencia del aerogenerador, la desalineación de la máquina con respecto al viento y la interacción aerodinámica entre aerogeneradores. En este trabajo se aborda la aplicación de modelos estadísticos a la predicción de rampas a muy corto plazo. Además, se investiga la relación de este tipo de eventos con procesos atmosféricos en la macroescala. Los modelos se emplean para generar predicciones de punto a partir del modelado estocástico de una serie temporal de potencia generada por un parque eólico. Los horizontes de predicción considerados van de una a seis horas. Como primer paso, se ha elaborado una metodología para caracterizar rampas en series temporales. La denominada función-rampa está basada en la transformada wavelet y proporciona un índice en cada paso temporal. Este índice caracteriza la intensidad de rampa en base a los gradientes de potencia experimentados en un rango determinado de escalas temporales. Se han implementado tres tipos de modelos predictivos de cara a evaluar el papel que juega la complejidad de un modelo en su desempeño: modelos lineales autorregresivos (AR), modelos de coeficientes variables (VCMs) y modelos basado en redes neuronales (ANNs). Los modelos se han entrenado en base a la minimización del error cuadrático medio y la configuración de cada uno de ellos se ha determinado mediante validación cruzada. De cara a analizar la contribución del estado macroescalar de la atmósfera en la predicción de rampas, se ha propuesto una metodología que permite extraer, a partir de las salidas de modelos meteorológicos, información relevante para explicar la ocurrencia de estos eventos. La metodología se basa en el análisis de componentes principales (PCA) para la síntesis de la datos de la atmósfera y en el uso de la información mutua (MI) para estimar la dependencia no lineal entre dos señales. Esta metodología se ha aplicado a datos de reanálisis generados con un modelo de circulación general (GCM) de cara a generar variables exógenas que posteriormente se han introducido en los modelos predictivos. Los casos de estudio considerados corresponden a dos parques eólicos ubicados en España. Los resultados muestran que el modelado de la serie de potencias permitió una mejora notable con respecto al modelo predictivo de referencia (la persistencia) y que al añadir información de la macroescala se obtuvieron mejoras adicionales del mismo orden. Estas mejoras resultaron mayores para el caso de rampas de bajada. Los resultados también indican distintos grados de conexión entre la macroescala y la ocurrencia de rampas en los dos parques considerados. Abstract One of the main drawbacks of wind energy is that it exhibits intermittent generation greatly depending on environmental conditions. Wind power forecasting has proven to be an effective tool for facilitating wind power integration from both the technical and the economical perspective. Indeed, system operators and energy traders benefit from the use of forecasting techniques, because the reduction of the inherent uncertainty of wind power allows them the adoption of optimal decisions. Wind power integration imposes new challenges as higher wind penetration levels are attained. Wind power ramp forecasting is an example of such a recent topic of interest. The term ramp makes reference to a large and rapid variation (1-4 hours) observed in the wind power output of a wind farm or portfolio. Ramp events can be motivated by a broad number of meteorological processes that occur at different time/spatial scales, from the passage of large-scale frontal systems to local processes such as thunderstorms and thermally-driven flows. Ramp events may also be conditioned by features related to the wind-to-power conversion process, such as yaw misalignment, the wind turbine shut-down and the aerodynamic interaction between wind turbines of a wind farm (wake effect). This work is devoted to wind power ramp forecasting, with special focus on the connection between the global scale and ramp events observed at the wind farm level. The framework of this study is the point-forecasting approach. Time series based models were implemented for very short-term prediction, this being characterised by prediction horizons up to six hours ahead. As a first step, a methodology to characterise ramps within a wind power time series was proposed. The so-called ramp function is based on the wavelet transform and it provides a continuous index related to the ramp intensity at each time step. The underlying idea is that ramps are characterised by high power output gradients evaluated under different time scales. A number of state-of-the-art time series based models were considered, namely linear autoregressive (AR) models, varying-coefficient models (VCMs) and artificial neural networks (ANNs). This allowed us to gain insights into how the complexity of the model contributes to the accuracy of the wind power time series modelling. The models were trained in base of a mean squared error criterion and the final set-up of each model was determined through cross-validation techniques. In order to investigate the contribution of the global scale into wind power ramp forecasting, a methodological proposal to identify features in atmospheric raw data that are relevant for explaining wind power ramp events was presented. The proposed methodology is based on two techniques: principal component analysis (PCA) for atmospheric data compression and mutual information (MI) for assessing non-linear dependence between variables. The methodology was applied to reanalysis data generated with a general circulation model (GCM). This allowed for the elaboration of explanatory variables meaningful for ramp forecasting that were utilized as exogenous variables by the forecasting models. The study covered two wind farms located in Spain. All the models outperformed the reference model (the persistence) during both ramp and non-ramp situations. Adding atmospheric information had a noticeable impact on the forecasting performance, specially during ramp-down events. Results also suggested different levels of connection between the ramp occurrence at the wind farm level and the global scale.

Modelling uncertainty of flood quantile estimation at ungauged sites by Bayesian networks

Prediction at ungauged sites is essential for water resources planning and management. Ungauged sites have no observations about the magnitude of floods, but some site and basin characteristics are known. Regression models relate physiographic and climatic basin characteristics to flood quantiles, which can be estimated from observed data at gauged sites. However, these models assume linear relationships between variables Prediction intervals are estimated by the variance of the residuals in the estimated model. Furthermore, the effect of the uncertainties in the explanatory variables on the dependent variable cannot be assessed. This paper presents a methodology to propagate the uncertainties that arise in the process of predicting flood quantiles at ungauged basins by a regression model. In addition, Bayesian networks were explored as a feasible tool for predicting flood quantiles at ungauged sites. Bayesian networks benefit from taking into account uncertainties thanks to their probabilistic nature. They are able to capture non-linear relationships between variables and they give a probability distribution of discharges as result. The methodology was applied to a case study in the Tagus basin in Spain.

Exploring the role of social capital influence variables on travel behaviour

This paper explores the potential role of individual trip characteristics and social capital network variables in the choice of transport mode. A sample of around 100 individuals living or working in one suburb of Madrid (i.e. Las Rosas district of Madrid) participated in a smartphone short panel survey, entering travel data for an entire working week. A Mixed Logit model was estimated with this data to analyze shifts to metro as a consequence of the opening of two new stations in the area. Apart from classical explanatory variables, such as travel time and cost, gender, license and car ownership, the model incorporated two “social capital network” variables: participation in voluntary activities and receiving help for various tasks (i.e. child care, housekeeping, etc.). Both variables improved the capacity of the model to explain transport mode shifts. Further, our results confirm that the shift towards metro was higher in the case of people “helped” and lower for those participating in some voluntary activities.

Perfil de playas sustentadas : estudio hidrodinámico y experimental : directrices de diseño

Las playas sustentadas por medio de un pie sumergido son una atractiva alternativa de diseño de regeneración de playas especialmente cuando las condiciones física del emplazamiento o las características de la arena nativa y de préstamo producen perfiles de alimentación que no se intersectan. La observación y propuesta de este tipo de solución data de los años 1960’s, así como la experiencia internacional en la construcción de este tipo de playas. Sin embargo, a pesar de su utilización y los estudios en campo y laboratorio, no se dispone de criterios ingenieriles que apoyen el diseño de las mismas. Esta tesis consiste en un análisis experimental del perfil de playas sustentadas en un pie sumergido (o colgadas) que se concreta en una propuesta de directrices de diseño general que permiten estimar la ubicación y características geométricas del pie sumergido frente a un oleaje y material que constituye la playa determinados. En la tesis se describe el experimento bidimensional realizado en el modelo físico de fondo móvil, donde se combinan cinco tipos de oleaje con tres configuraciones del pie sumergido (“Sin estructura”, configuración baja o “Estructura 1” y configuración alta o “Estructura 2”), se presentan los resultados obtenidos y se realiza una discusión detallada de las implicaciones de los resultados desde el punto de vista hidrodinámico utilizando monomios adimensionales. Se ha realizado un análisis detallado del estado del arte sobre playas colgadas, presentando el concepto y las experiencias de realizaciones en distintos países. Se ha realizado una cuidadosa revisión de la literatura publicada sobre estudios experimentales de playas colgadas, modelos teóricos y otras cuestiones auxiliares, necesarias para la formulación de la metodología de la tesis. El estudio realizado se ha estructurado en dos fases. En la primera fase se ha realizado una experimentación en un modelo físico de fondo móvil construido en las instalaciones del Centro de Estudios de Puertos y Costas (CEPYC) del Centro de Estudios y Experimentación de Obras Públicas (CEDEX), consistente en un canal de 36 m de longitud, 3 m de anchura y 1.5 m de altura, provisto de un generador de oleaje de tipo pistón. Se ha diseñado una campaña de 15 ensayos, que se obtienen sometiendo a cinco tipos de oleaje tres configuraciones distintas de playa colgada. En los ensayos se ha medido el perfil de playa en distintos instantes hasta llegar al equilibrio, determinando a partir de esos datos el retroceso de la línea de costa y el volumen de sedimentos perdido. El tiempo total efectivo de ensayo asciende a casi 650 horas, y el número de perfiles de evolución de playa obtenidos totaliza 229. En la segunda fase se ha abordado el análisis de los resultados obtenidos con la finalidad de comprender el fenómeno, identificar las variables de las que depende y proponer unas directrices ingenieriles de diseño. Se ha estudiado el efecto de la altura de ola, del periodo del oleaje, del francobordo adimensional y del parámetro de Dean, constatándose la dificultad de comprensión del funcionamiento de estas obras ya que pueden ser beneficiosas, perjudiciales o inocuas según los casos. También se ha estudiado la respuesta del perfil de playa en función de otros monomios adimensionales, tales como el número de Reynolds o el de Froude. En el análisis se ha elegido el monomio “plunger” como el más significativo, encontrando relaciones de éste con el peralte de oleaje, la anchura de coronación adimensional, la altura del pie de playa adimensional y el parámetro de Dean. Finalmente, se propone un método de diseño de cuatro pasos que permite realizar un primer encaje del diseño funcional de la playa sustentada frente a un oleaje de características determinadas. Las contribuciones más significativas desde el punto de vista científico son: - La obtención del juego de resultados experimentales. - La caracterización del comportamiento de las playas sustentadas. - Las relaciones propuestas entre el monomio plunger y las distintas variables explicativas seleccionadas, que permiten predecir el comportamiento de la obra. - El método de diseño propuesto, en cuatro pasos, para este tipo de esquemas de defensa de costas. Perched beaches are an attractive beach nourishment design alternative especially when either the site conditions or the characteristics of both the native and the borrow sand lead to a non-intersecting profile The observation and suggestion of the use of this type of coastal defence scheme dates back to the 1960’s, as well as the international experience in the construction of this type of beaches. However, in spite of its use and the field and laboratory studies performed to-date, no design engineering guidance is available to support its design. This dissertation is based on the experimental work performed on a movable bed physical model and the use of dimensionless parameters in analyzing the results to provide general functional design guidance that allow the designer, at a particular stretch of coast - to estimate the location and geometric characteristics of the submerged sill as well as to estimate the suitable sand size to be used in the nourishment. This dissertation consists on an experimental analysis of perched beaches by means of a submerged sill, leading to the proposal of general design guidance that allows to estimate the location and geometric characteristics of the submerged sill when facing a wave condition and for a given beach material. The experimental work performed on a bi-dimensional movable bed physical model, where five types of wave conditions are combined with three configurations of the submerged sill (“No structure”, low structure or “Structure 1”, and high structure or “Structure 2”) is described, results are presented, and a detailed discussion of the results - from the hydrodynamic point of view – of the implications of the results by using dimensionless parameters is carried out. A detailed state of the art analysis about perched beaches has been performed, presenting the “perched beach concept” and the case studies of different countries. Besides, a careful revision of the literature about experimental studies on perched beaches, theoretical models, and other topics deemed necessary to formulate the methodology of this work has been completed. The study has been divided into two phases. Within the first phase, experiments on a movable-bed physical model have been developed. The physical model has been built in the Centro de Estudios de Puertos y Costas (CEPYC) facilities, Centro de Estudios y Experimentación de Obras Públicas (CEDEX). The wave flume is 36 m long, 3 m wide and 1.5 m high, and has a piston-type regular wave generator available. The test plan consisted of 15 tests resulting from five wave conditions attacking three different configurations of the perched beach. During the development of the tests, the beach profile has been surveyed at different intervals until equilibrium has been reached according to these measurements. Retreat of the shoreline and relative loss of sediment in volume have been obtained from the measurements. The total effective test time reaches nearly 650 hours, whereas the total number of beach evolution profiles measured amounts to 229. On the second phase, attention is focused on the analysis of results with the aim of understanding the phenomenon, identifying the governing variables and proposing engineering design guidelines. The effect of the wave height, the wave period, the dimensionless freeboard and of the Dean parameter have been analyzed. It has been pointed out the difficulty in understanding the way perched beaches work since they turned out to be beneficial, neutral or harmful according to wave conditions and structure configuration. Besides, the beach profile response as a function of other dimensionless parameters, such as Reynolds number or Froude number, has been studied. In this analysis, the “plunger” parameter has been selected as the most representative, and relationships between the plunger parameter and the wave steepness, the dimensionless crest width, the dimensionless crest height, and the Dean parameter have been identified. Finally, an engineering 4-step design method has been proposed, that allows for the preliminary functional design of the perched beach for a given wave condition. The most relevant contributions from the scientific point of view have been: - The acquisition of a consistent set of experimental results. - The characterization of the behavior of perched beaches. - The proposed relationships between the plunger parameter and the different explanatory variables selected, that allow for the prediction of the beach behavior. - The proposed design method, four-step method, for this type of coastal defense schemes.

Deforestación y Pérdida de hábitat en Bosques de montaña en la Cuenca alta del Río Zamora (Loja, Ecuador)

Los bosques húmedos de montaña se encuentran reconocidos como uno de los ecosistemas más amenazados en el mundo, llegando inclusive a ser considerado como un “hotspot” por su alta diversidad y endemismo. La acelerada pérdida de cobertura vegetal de estos bosques ha ocasionado que, en la actualidad, se encuentren restringidos a una pequeña fracción de su área de distribución histórica. Pese a esto, los estudios realizados sobre cual es efecto de la deforestación, fragmentación, cambios de uso de suelo y su efecto en las comunidades de plantas presentes en este tipo de vegetación aún son muy escuetos, en comparación a los realizados con sus similares amazónicos. En este trabajo, el cual se encuentra dividido en seis capítulos, abordaremos los siguientes objetivos: a) Comprender cuál es la dinámica que han seguido los diferentes tipos de bosques montanos andinos de la cuenca del Rio Zamora, Sur de Ecuador durante entre 1976 y 2002. b) Proveer de evidencia de las tasas de deforestación y fragmentación de todos los tipos diferentes de bosques montanos andinos presentes en la cuenca del Rio Zamora, Sur de Ecuador entre 1976 y 2002. c) Determinar qué factores inducen a la fragmentación de bosques de montaña en la cuenca alta del río Zamora entre 1976 y 2002. d) Determinar cuáles son y cómo afectan los factores ambientales y socioeconómicos a la dinámica de la deforestación y regeneración (pérdida y recuperación del hábitat) sufrida por los bosques de montaña dentro de la zona de estudio y e) Determinar si la deforestación y fragmentación actúan sobre la diversidad y estructura de las comunidades de tres tipos de organismos (comunidades de árboles, comunidades de líquenes epífitos y comunidades de hepáticas epífitas). Este estudio se centró en el cuenca alta del río Zamora, localizada al sur de Ecuador entre las coordenadas 3º 00´ 53” a 4º 20´ 24.65” de latitud sur y 79º 49´58” a 78º 35´ 38” de longitud oeste, que cubre alrededor de 4300 km2 de territorio situado entre las capitales de las provincias de Loja y Zamora-Chinchipe. Con objeto de predecir la dinámica futura de la deforestación en la región de Loja y cómo se verán afectados los diferentes tipos de hábitat, así como para detectar los factores que más influyen en dicha dinámica, se han construido modelos basados en la historia de la deforestación derivados de fotografías aéreas e imágenes satelitales de tres fechas (1976, 1989 y 2002). La cuantificación de la deforestación se realizó mediante la tasa de interés compuesto y para la caracterización de la configuración espacial de los fragmentos de bosque nativo se calcularon índices de paisaje los cuales fueron calculados utilizando el programa Fragstats 3.3. Se ha clasificado el recubrimiento del terreno en forestal y no forestal y se ha modelado su evolución temporal con Modelos Lineales Generalizados Mixtos (GLMM), empleando como variables explicativas tanto variables ambientales espacialmente explícitas (altitud, orientación, pendiente, etc) como antrópicas (distancia a zonas urbanizadas, deforestadas, caminos, entre otras). Para medir el efecto de la deforestación sobre las comunidades modelo (de árboles, líquenes y hepáticas) se monitorearon 11 fragmentos de vegetación de distinto tamaño: dos fragmentos de más de cien hectáreas, tres fragmentos de entre diez y noventa ha y seis fragmentos de menos de diez hectáreas. En ellos se instalaron un total de 38 transectos y 113 cuadrantes de 20 x 20 m a distancias que se alejaban progresivamente del borde en 10, 40 y 80 m. Nuestros resultados muestran una tasa media anual de deforestación del 1,16% para todo el período de estudio, que el tipo de vegetación que más alta tasa de destrucción ha sufrido, es el páramo herbáceo, con un 2,45% anual. El análisis de los patrones de fragmentación determinó un aumento en 2002 de más del doble de fragmentos presentes en 1976, lo cual se repite en el análisis del índice de densidad promedio. El índice de proximidad media entre fragmentos muestra una reducción progresiva de la continuidad de las áreas forestadas. Si bien las formas de los fragmentos se han mantenido bastante similares a lo largo del período de estudio, la conectividad entre estos ha disminuido en un 84%. Por otro lado, de nuestros análisis se desprende que las zonas con mayor probabilidad de deforestarse son aquellas que están cercanas a zonas previamente deforestadas; la cercanía a las vías también influye significativamente en la deforestación, causando un efecto directo en la composición y estructura de las comunidades estudiadas, que en el caso de los árboles viene mediado por el tamaño del fragmento y en el caso del componente epífito (hepáticas y líquenes), viene mediado tanto por el tamaño del fragmento como por la distancia al borde del mismo. Se concluye la posibilidad de que, de mantenerse esta tendencia, este tipo de bosques desaparecerá en corto tiempo y los servicios ecosistémicos que prestan, se verán seriamente comprometidos. ABSTRACT Mountain rainforests are recognized as one of the most threatened ecosystems in the world, and have even come to be considered as a “hotspot” due to their high degree of diversity and endemism. The accelerated loss of plant cover of these forests has caused them to be restricted today to a small fraction of their area of historic distribution. In spite of this, studies done on the effect of deforestation, fragmentation, changes in soil use and their effect on the plant communities present in this type of vegetation are very brief compared to those done on their analogues in the Amazon region. In this study, which is divided into six chapters, we will address the following objectives: a) To understand what the dynamic followed by the different types of Andean mountain forests in the Zamora River watershed of southern Ecuador has been between 1976 and 2002. b) To provide evidence of the rates of deforestation and fragmentation of all the different types of Andean mountain forests existing in the upper watershed of the Zamora River between 1976 and 2002. c) To determine the factors that induces fragmentation of all different types of Andean mountain forests existing in the upper watershed of the Zamora River between 1976 and 2002. d) To determine what the environmental and anthropogenic factors are driving the dynamic of deforestation and regeneration (loss and recuperation of the habitat) suffered by the mountain forests in the area of the study and e) To determine if the deforestation and fragmentation act upon the diversity and structure of three model communities: trees, epiphytic lichens and epiphytic liverworts. This study is centered on the upper Zamora River watershed, located in southern Ecuador between 3º 00´ 53” and 4º 20´ 24.65 south latitude and 79º 49´ 58” to 78º 35´ 38” west longitude, and covers around 4,300 km2 of territory located between Loja and Zamora-Chinchipe provinces. For the purpose of predicting the future dynamic of deforestation in the Loja region and how different types of habitats will be affected, as well as detecting the environmental and socioeconomic factors that influence landscape dynamics, models were constructed based on deforestation history, derived from aerial photographs and satellite images for three dates (1976, 1989 and 2002). Quantifying the deforestation was done using the compound interest rate; to characterize the spatial configuration of fragments of native forest, landscape indices were calculated with Fragstats 3.3 program. Land cover was classified as forested and not forested and its evolution over time was modeled with Generalized Linear Mixed Models (GLMM), using spatially explicit environmental variables (altitude, orientation, slope, etc.) as well as anthropic variables (distance to urbanized, deforested areas and roads, among others) as explanatory variables. To measure the effects of fragmentation on three types of model communities (forest trees and epiphytic lichen and liverworts), 11 vegetation fragments of different sizes were monitored: two fragments of more than one hundred hectares, three fragments of between ten and ninety ha and six fragments of fewer than ten hectares . In these fragments, a total of 38 transects and 113 20 x 20 m quadrats were installed at distances that progressively moved away from the edge of the fragment by 10, 40 and 80 m. Our results show an average annual rate of deforestation of 1.16% for the entire period of the study, and that the type of vegetation that suffered the highest rate of destruction was grassy paramo, with an annual rate of 2.45%. The analysis of fragmentation patterns determined the number of fragments in 2002 more than doubled the number of fragments present in 1976, and the same occurred for the average density index. The variation of the average proximity index among fragments showed a progressive reduction of the continuity of forested areas. Although fragment shapes have remained quite similar over the period of the study, connectivity among them has diminished by 84%. On the other hand, it emerged from our analysis that the areas of greatest probability of deforestation were those that are close to previously deforested areas; proximity to roads also significantly favored the deforestation causing a direct effect on the composition of our model communities, that in the case of forest trees is determined by the size of the fragment, and in the case of the epiphyte communities (liverworts and lichens), is determined, by the size of the fragment as well as the distance to edge. A subject under discussion is the possibility that if this tendency continues, this type of forest will disappear in a short time, and the ecological services it provides, will be seriously endangered.

Testing alternative models for the conservation of koalas in fragmented rural-urban landscapes

Predicting the various responses of different species to changes in landscape structure is a formidable challenge to landscape ecology. Based on expert knowledge and landscape ecological theory, we develop five competing a priori models for predicting the presence/absence of the Koala (Phascolarctos cinereus) in Noosa Shire, south-east Queensland (Australia). A priori predictions were nested within three levels of ecological organization: in situ (site level) habitat (< 1 ha), patch level (100 ha) and landscape level (100-1000 ha). To test the models, Koala surveys and habitat surveys (n = 245) were conducted across the habitat mosaic. After taking into account tree species preferences, the patch and landscape context, and the neighbourhood effect of adjacent present sites, we applied logistic regression and hierarchical partitioning analyses to rank the alternative models and the explanatory variables. The strongest support was for a multilevel model, with Koala presence best predicted by the proportion of the landscape occupied by high quality habitat, the neighbourhood effect, the mean nearest neighbour distance between forest patches, the density of forest patches and the density of sealed roads. When tested against independent data (n = 105) using a receiver operator characteristic curve, the multilevel model performed moderately well. The study is consistent with recent assertions that habitat loss is the major driver of population decline, however, landscape configuration and roads have an important effect that needs to be incorporated into Koala conservation strategies.