946 resultados para 2 SPATIAL SCALES


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El retroceso de las costas acantiladas es un fenómeno muy extendido sobre los litorales rocosos expuestos a la incidencia combinada de los procesos marinos y meteorológicos que se dan en la franja costera. Este fenómeno se revela violentamente como movimientos gravitacionales del terreno esporádicos, pudiendo causar pérdidas materiales y/o humanas. Aunque el conocimiento de estos riesgos de erosión resulta de vital importancia para la correcta gestión de la costa, el desarrollo de modelos predictivos se encuentra limitado desde el punto de vista geomorfológico debido a la complejidad e interacción de los procesos de desarrollo espacio-temporal que tienen lugar en la zona costera. Los modelos de predicción publicados son escasos y con importantes inconvenientes: a) extrapolación, extienden la información de registros históricos; b) empíricos, sobre registros históricos estudian la respuesta al cambio de un parámetro; c) estocásticos, determinan la cadencia y magnitud de los eventos futuros extrapolando las distribuciones de probabilidad extraídas de catálogos históricos; d) proceso-respuesta, de estabilidad y propagación del error inexplorada; e) en Ecuaciones en Derivadas Parciales, computacionalmente costosos y poco exactos. La primera parte de esta tesis detalla las principales características de los modelos más recientes de cada tipo y, para los más habitualmente utilizados, se indican sus rangos de aplicación, ventajas e inconvenientes. Finalmente como síntesis de los procesos más relevantes que contemplan los modelos revisados, se presenta un diagrama conceptual de la recesión costera, donde se recogen los procesos más influyentes que deben ser tenidos en cuenta, a la hora de utilizar o crear un modelo de recesión costera con el objetivo de evaluar la peligrosidad (tiempo/frecuencia) del fenómeno a medio-corto plazo. En esta tesis se desarrolla un modelo de proceso-respuesta de retroceso de acantilados costeros que incorpora el comportamiento geomecánico de materiales cuya resistencia a compresión no supere los 5 MPa. El modelo simula la evolución espaciotemporal de un perfil-2D del acantilado que puede estar formado por materiales heterogéneos. Para ello, se acoplan la dinámica marina: nivel medio del mar, cambios en el nivel medio del lago, mareas y oleaje; con la evolución del terreno: erosión, desprendimiento rocoso y formación de talud de derrubios. El modelo en sus diferentes variantes es capaz de incluir el análisis de la estabilidad geomecánica de los materiales, el efecto de los derrubios presentes al pie del acantilado, el efecto del agua subterránea, la playa, el run-up, cambios en el nivel medio del mar o cambios (estacionales o interanuales) en el nivel medio de la masa de agua (lagos). Se ha estudiado el error de discretización del modelo y su propagación en el tiempo a partir de las soluciones exactas para los dos primeros periodos de marea para diferentes aproximaciones numéricas tanto en tiempo como en espacio. Los resultados obtenidos han permitido justificar las elecciones que minimizan el error y los métodos de aproximación más adecuados para su posterior uso en la modelización. El modelo ha sido validado frente a datos reales en la costa de Holderness, Yorkshire, Reino Unido; y en la costa norte del lago Erie, Ontario, Canadá. Los resultados obtenidos presentan un importante avance en los modelos de recesión costera, especialmente en su relación con las condiciones geomecánicas del medio, la influencia del agua subterránea, la verticalización de los perfiles rocosos y su respuesta ante condiciones variables producidas por el cambio climático (por ejemplo, nivel medio del mar, cambios en los niveles de lago, etc.). The recession of coastal cliffs is a widespread phenomenon on the rocky shores that are exposed to the combined incidence of marine and meteorological processes that occur in the shoreline. This phenomenon is revealed violently and occasionally, as gravitational movements of the ground and can cause material or human losses. Although knowledge of the risks of erosion is vital for the proper management of the coast, the development of cliff erosion predictive models is limited by the complex interactions between environmental processes and material properties over a range of temporal and spatial scales. Published prediction models are scarce and present important drawbacks: extrapolation, that extend historical records to the future; empirical, that based on historical records studies the system response against the change in one parameter; stochastic, that represent of cliff behaviour based on assumptions regarding the magnitude and frequency of events in a probabilistic framework based on historical records; process-response, stability and error propagation unexplored; PDE´s, highly computationally expensive and not very accurate. The first part of this thesis describes the main features of the latest models of each type and, for the most commonly used, their ranges of application, advantages and disadvantages are given. Finally as a synthesis of the most relevant processes that include the revised models, a conceptual diagram of coastal recession is presented. This conceptual model includes the most influential processes that must be taken into account when using or creating a model of coastal recession to evaluate the dangerousness (time/frequency) of the phenomenon to medium-short term. A new process-response coastal recession model developed in this thesis has been designed to incorporate the behavioural and mechanical characteristics of coastal cliffs which are composed of with materials whose compressive strength is less than 5 MPa. The model simulates the spatial and temporal evolution of a cliff-2D profile that can consist of heterogeneous materials. To do so, marine dynamics: mean sea level, waves, tides, lake seasonal changes; is coupled with the evolution of land recession: erosion, cliff face failure and associated protective colluvial wedge. The model in its different variants can include analysis of material geomechanical stability, the effect of debris present at the cliff foot, groundwater effects, beach and run-up effects, changes in the mean sea level or changes (seasonal or inter-annual) in the mean lake level. Computational implementation and study of different numerical resolution techniques, in both time and space approximations, and the produced errors are exposed and analysed for the first two tidal periods. The results obtained in the errors analysis allow us to operate the model with a configuration that minimizes the error of the approximation methods. The model is validated through profile evolution assessment at various locations of coastline retreat on the Holderness Coast, Yorkshire, UK and on the north coast of Lake Erie, Ontario, Canada. The results represent an important stepforward in linking material properties to the processes of cliff recession, in considering the effect of groundwater charge and the slope oversteeping and their response to changing conditions caused by climate change (i.e. sea level, changes in lakes levels, etc.).

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Landcover is subject to continuous changes on a wide variety of temporal and spatial scales. Those changes produce significant effects in human and natural activities. Maintaining an updated spatial database with the occurred changes allows a better monitoring of the Earth?s resources and management of the environment. Change detection (CD) techniques using images from different sensors, such as satellite imagery, aerial photographs, etc., have proven to be suitable and secure data sources from which updated information can be extracted efficiently, so that changes can also be inventoried and monitored. In this paper, a multisource CD methodology for multiresolution datasets is applied. First, different change indices are processed, then different thresholding algorithms for change/no_change are applied to these indices in order to better estimate the statistical parameters of these categories, finally the indices are integrated into a change detection multisource fusion process, which allows generating a single CD result from several combination of indices. This methodology has been applied to datasets with different spectral and spatial resolution properties. Then, the obtained results are evaluated by means of a quality control analysis, as well as with complementary graphical representations. The suggested methodology has also been proved efficiently for identifying the change detection index with the higher contribution.

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Modeling is an essential tool for the development of atmospheric emission abatement measures and air quality plans. Most often these plans are related to urban environments with high emission density and population exposure. However, air quality modeling in urban areas is a rather challenging task. As environmental standards become more stringent (e.g. European Directive 2008/50/EC), more reliable and sophisticated modeling tools are needed to simulate measures and plans that may effectively tackle air quality exceedances, common in large urban areas across Europe, particularly for NO2. This also implies that emission inventories must satisfy a number of conditions such as consistency across the spatial scales involved in the analysis, consistency with the emission inventories used for regulatory purposes and versatility to match the requirements of different air quality and emission projection models. This study reports the modeling activities carried out in Madrid (Spain) highlighting the atmospheric emission inventory development and preparation as an illustrative example of the combination of models and data needed to develop a consistent air quality plan at urban level. These included a series of source apportionment studies to define contributions from the international, national, regional and local sources in order to understand to what extent local authorities can enforce meaningful abatement measures. Moreover, source apportionment studies were conducted in order to define contributions from different sectors and to understand the maximum feasible air quality improvement that can be achieved by reducing emissions from those sectors, thus targeting emission reduction policies to the most relevant activities. Finally, an emission scenario reflecting the effect of such policies was developed and the associated air quality was modeled.

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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.

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Liquid-fueled burners are used in a number of propulsion devices ranging from internal combustion engines to gas turbines. The structure of spray flames is quite complex and involves a wide range of time and spatial scales in both premixed and non-premixed modes (Williams 1965; Luo et al. 2011). A number of spray-combustion regimes can be observed experimentally in canonical scenarios of practical relevance such as counterflow diffusion flames (Li 1997), as sketched in figure 1, and for which different microscalemodelling strategies are needed. In this study, source terms for the conservation equations are calculated for heating, vaporizing and burning sprays in the single-droplet combustion regime. The present analysis provides extended formulation for source terms, which include non-unity Lewis numbers and variable thermal conductivities.

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El concepto tradicional de reglas de ensamblaje refleja la idea de que las especies no co-ocurren al azar sino que están restringidos en su co-ocurrencia por la competencia interespecífica o por un filtrado ambiental. En está tesis abordé la importancia de los procesos que determinan el ensamble de la comunidad en la estructuración de los Bosques Secos en el Sur del Ecuador. Este estudio se realizó en la región biogeográfica Tumbesina, donde se encuentra la mayor concentración de bosques secos tropicales bien conservados del sur de Ecuador, y que constituyen una de las áreas de endemismo más importantes del mundo. El clima se caracteriza por una estación seca que va desde mayo a diciembre y una estación lluviosa de enero a abril, su temperatura anual varía entre 20°C y 26°C y una precipitación promedio anual entre 300 y 700 mm. Mi primer tema fue orientado a evaluar si la distribución de los rasgos funcionales a nivel comunitario es compatible con la existencia de un filtro ambiental (filtrado del hábitat) o con la existencia de un proceso de limitación de la semejanza funcional impuesta por la competencia inter-específica entre 58 especies de plantas leñosas repartidas en 109 parcelas (10x50m). Para ello, se analizó la distribución de los valores de cinco rasgos funcionales (altura máxima, densidad de la madera, área foliar específica, tamaño de la hoja y de masa de la semilla), resumida mediante varios estadísticos (rango, varianza, kurtosis y la desviación estándar de la distribución de distancias funcionales a la especies más próxima) y se comparó con la distribución esperada bajo un modelo nulo con ausencia de competencia. Los resultados obtenidos apoyan que tanto el filtrado ambiental como la limitación a la semejanza afectan el ensamble de las comunidades vegetales de los bosques secos Tumbesinos. Un segundo tema fue identificar si la diversidad funcional está condicionada por los gradientes ambientales, y en concreto si disminuye en los ambientes más estresantes a causa del filtrado ambiental, y si por el contrario aumenta en los ambientes más benignos donde la competencia se vuelve más importante, teniendo en cuenta las posibles modificaciones a este patrón general a causa de las interacciones de facilitación. Para abordar este estudio analizamos tanto las variaciones en la diversidad funcional (respecto a los de los cinco rasgos funcionales empleados en el primer capítulo de la tesis) como las variaciones de diversidad filogenética a lo largo de un gradiente de estrés climático en los bosques tumbesinos, y se contrastaron frente a las diversidades esperadas bajo un modelo de ensamblaje completamente aleatorio de la comunidad. Los análisis mostraron que tan sólo la diversidad de tamaños foliares siguió el patrón de variación esperado, disminuyendo a medida que aumentó el estrés abiótico mientras que ni el resto de rasgos funcionales ni la diversidad funcional multivariada ni la diversidad filogenética mostraron una variación significativa a lo largo del gradiente ambiental. Un tercer tema fue evaluar si los procesos que organizan la estructura funcional de la comunidad operan a diferentes escalas espaciales. Para ello cartografié todos los árboles y arbustos de más de 5 cm de diámetro en una parcela de 9 Ha de bosque seco y caractericé funcionalmente todas las especies. Dicha parcela fue dividida en subparcelas de diferente tamaño, obteniéndose subparcelas a seis escalas espaciales distintas. Los resultados muestran agregación de estrategias funcionales semejantes a escalas pequeñas, lo que sugiere la existencia bien de filtros ambientales actuando a escala fina o bien de procesos competitivos que igualan la estrategia óptima a dichas escalas. Finalmente con la misma información de la parcela permanente de 9 Ha. Nos propusimos evaluar el efecto y comportamiento de las especies respecto a la organización de la diversidad taxonómica, funcional y filogenética. Para ello utilicé tres funciones sumario espaciales: ISAR- para el nivel taxonómico, IFDAR para el nivel funcional y IPSVAR para el nivel filogenética y las contrastamos frente a modelos nulos que describen la distribución espacial de las especies individuales. Los resultados mostraron que en todas las escalas espaciales consideradas para ISAR, IFDAR y IPSVAR, la mayoría de las especies se comportaron como neutras, es decir, que están rodeados por la riqueza de diversidad semejante a la esperada. Sin embargo, algunas especies aparecieron como acumuladoras de diversidad funcional y filogenética, lo que sugiere su implicación en procesos competitivos de limitación de la semejanza. Una pequeña proporción de las especies apareció como repelente de la diversidad funcional y filogenética, lo que sugiere su implicación en un proceso de filtrado de hábitat. En este estudio pone de relieve cómo el análisis de las dimensiones alternativas de la biodiversidad, como la diversidad funcional y filogenética, puede ayudarnos a entender la co-ocurrencia de especies en diversos ensambles de comunidad. Todos los resultados de este estudio aportan nuevas evidencias de los procesos de ensamblaje de la comunidad de los Bosques Estacionalmente secos y como las variables ambientales y la competencia juegan un papel importante en la estructuración de la comunidad. ABSTRACT The traditional concept of the rules assembly for species communities reflects the idea that species do not co-occur at random but are restricted in their co-occurrence by interspecific competition or an environmental filter. In this thesis, I addressed the importance of the se processes in the assembly of plant communities in the dry forests of southern Ecuador. This study was conducted in the biogeographic region of Tumbesina has the largest concentration of well-conserved tropical dry forests of southern Ecuador, and is recognized as one of the most important areas of endemism in the world. The climate is characterized by a dry season from May to December and a rainy season from January to April. The annual temperature varies between 20 ° C and 26 ° C and an average annual rainfall between 300 and 700 mm. I first assessed whether the distribution of functional traits at the level of the community is compatible with the existence of an environmental filter (imposed by habitat) or the existence of a limitation on functional similarity imposed by interspecific competition. This analysis was conducted for 58 species of woody plants spread over 109 plots of 10 x 50 m. Specifically, I compared the distribution of values of five functional traits (maximum height, wood density, specific leaf area, leaf size and mass of the seed), via selected statistical properties (range, variance, kurtosis and analyzed the standard deviation of the distribution of the closest functional species) distances and compared with a expected distribution under a null model of no competition. The results support that both environmental filtering and a limitation on trait similarity affect the assembly of plant communities in dry forests Tumbesina. My second chapter evaluated whether variation in functional diversity is conditioned by environmental gradients. In particular, I tested whether it decreases in the most stressful environments because of environmental filters, or if, on the contrary, functional diversity is greater in more benign environments where competition becomes more important (notwithstanding possible changes to this general pattern due to facilitation). To address this theme I analyzed changes in both the functional diversity (maximum height, wood density, specific leaf area, leaf size and mass of the seed) and the phylogenetic diversity, along a gradient of climatic stress in Tumbes forests. The observed patterns of variation were contrasted against the diversity expected under a completely random null model of community assembly. Only the diversity of leaf sizes followed the hypothesis decreasing in as trait variation abiotic stress increased, while the other functional traits multivariate functional diversity and phylogenetic diversity no showed significant variation along the environmental gradient. The third theme assess whether the processes that organize the functional structure of the community operate at different spatial scales. To do this I mapped all the trees and shrubs of more than 5 cm in diameter within a plot of 9 hectares of dry forest and functionally classified each species. The plot was divided into subplots of different sizes, obtaining subplots of six different spatial scales. I found aggregation of similar functional strategies at small scales, which may indicate the existence of environmental filters or competitive processes that correspond to the optimal strategy for these fine scales. Finally, with the same information from the permanent plot of 9 ha, I evaluated the effect and behavior of individual species on the organization of the taxonomic, functional and phylogenetic diversity. The analysis comprised three spatial summary functions: ISAR- for taxonomic level analysis, IFDAR for functional level analysis, and IPSVAR for phylogenetic level analysis, in each case the pattern of diversity was contrasted against null models that randomly reallocate describe the spatial distribution of individual species and their traits. For all spatial scales considering ISAR, IFDAR and IPSVAR, most species behaved as neutral, i.e. they are surrounded by the diversity of other traits similar to that expected under a null model. However, some species appeared as accumulator of functional and phylogenetic diversity, suggesting that they may play a role in competitive processes that limiting similarity. A small proportion of the species appeared as repellent of functional and phylogenetic diversity, suggesting their involvement in a process of habitat filtering. These analysis highlights that the analysis of alternative dimensions of biodiversity, such as functional and phylogenetic diversity, can help us understand the co-occurrence of species in the assembly of biotic communities. All results of this study provide further evidence of the processes of assembly of the community of the seasonally dry forests as environmental variables and competition play an important role in structuring the community.

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El bosque tropical de montaña, es considerado zona de mega diversidad y de alto grado de endemismo, por las diferentes zonas ecológicas que presenta. Durante las últimas décadas estos bosques han recibido mayor atención por parte de investigadores, sin embargo, aún existe poca investigación en determinar cuáles son las respuestas de los bosques a los cambios ambientales a los que son sometidos. Estos bosques están sufriendo serias amenazas como pérdida de cobertura vegetal y cambios en los ciclos de nutrientes. El trabajo se dividió en cuatro objetivos específicos. i) Caracterización y análisis de patrones altitudinales de la riqueza de especies en el bosque tropical de montaña en el sur del Ecuador; con el fin de conocer cómo varía la diversidad de especies riqueza lo largo de un gradiente altitudinal. ii) Conocer los patrones espaciales del crecimiento en tres remanentes boscosos de un bosque tropical de montaña para determinar cómo la vecindad y la semejanza funcional de ésta influyen en el crecimiento forestal. iii) Conocer los efectos de la fertilización en el crecimiento diamétrico de especies arbóreas, en el bosque tropical de montaña; se analizó cómo reaccionan los árboles a la adición de nutrientes N y P en tres tipos de bosque. iv) Saber la respuesta de la comunidad de árboles a la adición de nutrientes en el bosque montano andino; este objetivo se basó con el supuesto de la deficiencia de tres tipos de nutrientes N, P y Ca, en esta formación boscosa y cómo reaccionan los árboles a la adición de nutrientes. El presente trabajo se llevó a cabo, en el bosque tropical de montaña que se encuentra localizada en la parte adyacente del Parque Nacional Podocarpus (PNP) en la cordillera del Consuelo, forma parte de la cadena oriental de los Andes del sur del Ecuador El trabajo de desarrollo entre los años 2008 y 2014. Para abordar el primer objetivo se establecieron 54 parcelas ubicadas aleatoriamente a lo largo de un gradiente altitudinal (3 niveles de altitud) y se e midieron e identificaron todos los individuos mayores a 5cm de DAP. Se construyó una filogenia con Phylocom y se calcularon diferentes componentes de diversidad para cada parcela ( riqueza taxonómica, diversidad filogenética y edad media de las especies). Ajustando modelos lineares se contrastó el efecto de la altitud sobre dichos componentes y se vio que la riqueza taxonómica y la edad media de las especies aumentaron con la altitud, en sentido contrario a las predicciones de la "hipótesis del conservadurismo tropical" (Tropical Conservatism Hypothesis). Para abordar el segundo objetivo se realizó una remedición de todos los árboles cartografiados en tres parcelas permanentes de alrededor de 5000 m2 cada una, representativas de tres estados diferentes de la sucesión del bosque montano. A partir de las coordenadas y de los datos de registrados, y empleando diferentes funciones de correlación de marca se analizó la distribución espacial del tamaño y del crecimiento relativo y del tamaño. Se constató que mientras que el tamaño de los árboles presentó una correlación espacial negativa, el crecimiento presentó correlación espacial positiva, en ambos casos a distancias cortas. El rango y la magnitud de ambas correlaciones aumentaron al avanzar la sucesión. La distribución espacial del crecimiento mostró una correlación negativa con la distribución espacial de tamaños. Por otro lado, la distribución espacial del crecimiento mostró una correlación negativa para árboles semejantes funcionalmente y positiva cuando se calculó entre árboles con diferente estrategia funcional. En conjunto, los resultados obtenidos señalan un aumento de la importancia de procesos competitivos y una mayor estructuración espacial del crecimiento y de la distribución de tamaños al avanzar la sucesión. Para el tercer y cuarto objetivo se instalaron 52 parcelas distribuidas en bloques donde se fertilizaron dos veces al año durante 6,4 años, se identificaron todos los individuos mayores a 10 cm de DAP, y se midió el crecimiento diamétrico durante estos años Con la adición de nutrientes realizada a los diferentes tipos de bosque en la gradiente altitudinal, encontramos que el efecto sobre el crecimiento diamétrico en la comunidad varia con el rango altitudinal, y el tipo de nutriente, analizando a nivel de las especies, en la mayoría de los casos las especies comunes no tuvieron cambios significativos a la adición de nutrientes. Los resultados de este estudio aportan nuevas evidencias para el entendimiento de la diversidad, estructura y dinámica de los bosques tropicales de montaña. ABSTRACT The montane tropical forest is considered a megadiverse habitat that harbor an enormous degree of endemism. This is mainly due to the high degree of environmental heterogeneity found and the presence of different well defined ecological areas. These forests have received more attention during the last decades, however, the information regarding the responses of these forests to environmental change, is still scarce. These forests are seriously endangered and are suffering serious threats, such as loss of vegetative cover, changes in the nutrient cycles. The work was divided in four specific objectives: i) Characterization and analysis of the species richness altitudinal patterns in the montane tropical forest of south Ecuador. Specifically, how species diversity changes along altitudinal gradients. ii) Exploring the spatial patterns of tree growth in three remnants of a montane tropical forest, and analyze how tree neighborhood and functional similarity among trees influence tree growth. Tropical Conservatism Hypothesis iii) Understanding the effects of fertilization in arboreal species growth (increase in diameter) of the montane tropical forest. Specifically we studied the effects of P and N addition on three different forests across an altitudinal gradient. iv) Know the response of the community of trees to the addition of nutrients in the Andean montane forest; this objective was based on the supposition of deficiency of three types of nutrients: P, N and Ca in this forest all formation and how the trees react to the addition of these nutrients. The present work was carried out in the montane tropical forest located in Bombuscaro, San Francisco and Cajanuma close to Podocarpus National Park (PNP) on Consuelo mountain range (Andean oriental range) at South of Ecuador. Field work was carried out during 2008 and 2014. To address the first objective, we randomly placed 54 plots along an altitudinal gradient. In these plots, every individual larger than 5 cm of DBH was measured and identified. A phylogeny was build with Phylocom and different diversity components (taxonomic richness, phylogenetic diversity and average species age) were computed for each plot. Linear models were used to test the effects of altitude on the diversity components. Our results showed that, contrary to the Tropical Conservatism Hypothesis, both taxonomic richness and average species age increased with altitude. To address our second objective, all mapped trees in three successional permanent plots (around ~5000 m2 each) were re-measured. Using different mark correlation functions, we analyzed the spatial distribution of tree-size and tree relative growth rate. Whereas tree size showed negative spatial correlation at fine spatial scales, relative growth rate showed positive correlation at the same scales. The range and magnitude of those correlations increased along successional stage. The spatial distribution of the relative growth rate was negatively correlated with the spatial distribution of tree sizes. Additionally, we found that the spatial correlation of the relative growth rate was negative for functionally similar trees and positive when computed for functionally different trees. In synthesis, our results point to an increase of competitive processes and strong spatial structure of relative growth rate and tree size along succession. For the third and fourth objectives, 52 plots were placed in a block design and were fertilized twice a year for 6,4 years. In these plots all the individuals with DBH > 10 cm were identified, and the diametrical growth was measured during these years. The nutrient addition at the three different altitude forests, revealed that the effect on the diametrical growth in the community varied with the altitudinal range. When analyzed at species level, the addition of nutrients was no significant in most cases. These results represent new evidences that will improved our understanding of diversity patterns and structure, and the dynamics of tropical montane forests.

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Dispersive wave turbulence is studied numerically for a class of one-dimensional nonlinear wave equations. Both deterministic and random (white noise in time) forcings are studied. Four distinct stable spectra are observed—the direct and inverse cascades of weak turbulence (WT) theory, thermal equilibrium, and a fourth spectrum (MMT; Majda, McLaughlin, Tabak). Each spectrum can describe long-time behavior, and each can be only metastable (with quite diverse lifetimes)—depending on details of nonlinearity, forcing, and dissipation. Cases of a long-live MMT transient state dcaying to a state with WT spectra, and vice-versa, are displayed. In the case of freely decaying turbulence, without forcing, both cascades of weak turbulence are observed. These WT states constitute the clearest and most striking numerical observations of WT spectra to date—over four decades of energy, and three decades of spatial, scales. Numerical experiments that study details of the composition, coexistence, and transition between spectra are then discussed, including: (i) for deterministic forcing, sharp distinctions between focusing and defocusing nonlinearities, including the role of long wavelength instabilities, localized coherent structures, and chaotic behavior; (ii) the role of energy growth in time to monitor the selection of MMT or WT spectra; (iii) a second manifestation of the MMT spectrum as it describes a self-similar evolution of the wave, without temporal averaging; (iv) coherent structures and the evolution of the direct and inverse cascades; and (v) nonlocality (in k-space) in the transferral process.

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A fundamental question in ecology is how many species occur within a given area. Despite the complexity and diversity of different ecosystems, there exists a surprisingly simple, approximate answer: the number of species is proportional to the size of the area raised to some exponent. The exponent often turns out to be roughly 1/4. This power law can be derived from assumptions about the relative abundances of species or from notions of self-similarity. Here we analyze the largest existing data set of location-mapped species: over one million, individually identified trees from five tropical forests on three continents. Although the power law is a reasonable, zeroth-order approximation of our data, we find consistent deviations from it on all spatial scales. Furthermore, tropical forests are not self-similar at areas ≤50 hectares. We develop an extended model of the species-area relationship, which enables us to predict large-scale species diversity from small-scale data samples more accurately than any other available method.

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In the cerebral cortex, the small volume of the extracellular space in relation to the volume enclosed by synapses suggests an important functional role for this relationship. It is well known that there are atoms and molecules in the extracellular space that are absolutely necessary for synapses to function (e.g., calcium). I propose here the hypothesis that the rapid shift of these atoms and molecules from extracellular to intrasynaptic compartments represents the consumption of a shared, limited resource available to local volumes of neural tissue. Such consumption results in a dramatic competition among synapses for resources necessary for their function. In this paper, I explore a theory in which this resource consumption plays a critical role in the way local volumes of neural tissue operate. On short time scales, this principle of resource consumption permits a tissue volume to choose those synapses that function in a particular context and thereby helps to integrate the many neural signals that impinge on a tissue volume at any given moment. On longer time scales, the same principle aids in the stable storage and recall of information. The theory provides one framework for understanding how cerebral cortical tissue volumes integrate, attend to, store, and recall information. In this account, the capacity of neural tissue to attend to stimuli is intimately tied to the way tissue volumes are organized at fine spatial scales.

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Humans' desire for knowledge regarding animal species and their interactions with the natural world have spurred centuries of studies. The relatively new development of remote sensing systems using satellite or aircraft-borne sensors has opened up a wide field of research, which unfortunately largely remains dependent on coarse-scale image spatial resolution, particularly for habitat modeling. For habitat-specialized species, such data may not be sufficient to successfully capture the nuances of their preferred areas. Of particular concern are those species for which topographic feature attributes are a main limiting factor for habitat use. Coarse spatial resolution data can smooth over details that may be essential for habitat characterization. Three studies focusing on sea turtle nesting beaches were completed to serve as an example of how topography can be a main deciding factor for certain species. Light Detection and Ranging (LiDAR) data were used to illustrate that fine spatial scale data can provide information not readily captured by either field work or coarser spatial scale sources. The variables extracted from the LiDAR data could successfully model nesting density for loggerhead (Caretta caretta), green (Chelonia mydas), and leatherback (Dermochelys coriacea) sea turtle species using morphological beach characteristics, highlight beach changes over time and their correlations with nesting success, and provide comparisons for nesting density models across large geographic areas. Comparisons between the LiDAR dataset and other digital elevation models (DEMs) confirmed that fine spatial scale data sources provide more similar habitat information than those with coarser spatial scales. Although these studies focused solely on sea turtles, the underlying principles are applicable for many other wildlife species whose range and behavior may be influenced by topographic features.