Modelling the spatio-temporal pattern of primary dispersal in stone pine (Pinus pinea L.) stands in the Northern Plateau (Spain)

Natural regeneration in stone pine (Pinus pinea L.) managed forests in the Spanish Northern Plateau is not achieved successfully under current silviculture practices, constituting a main concern for forest managers. We modelled spatio-temporal features of primary dispersal to test whether (a) present low stand densities constrain natural regeneration success and (b) seed release is a climate-controlled process. The present study is based on data collected from a 6 years seed trap experiment considering different regeneration felling intensities. From a spatial perspective, we attempted alternate established kernels under different data distribution assumptions to fit a spatial model able to predict P. pinea seed rain. Due to P. pinea umbrella-like crown, models were adapted to account for crown effect through correction of distances between potential seed arrival locations and seed sources. In addition, individual tree fecundity was assessed independently from existing models, improving parameter estimation stability. Seed rain simulation enabled to calculate seed dispersal indexes for diverse silvicultural regeneration treatments. The selected spatial model of best fit (Weibull, Poisson assumption) predicted a highly clumped dispersal pattern that resulted in a proportion of gaps where no seed arrival is expected (dispersal limitation) between 0.25 and 0.30 for intermediate intensity regeneration fellings and over 0.50 for intense fellings. To describe the temporal pattern, the proportion of seeds released during monthly intervals was modelled as a function of climate variables – rainfall events – through a linear model that considered temporal autocorrelation, whereas cone opening took place over a temperature threshold. Our findings suggest the application of less intensive regeneration fellings, to be carried out after years of successful seedling establishment and, seasonally, subsequent to the main rainfall period (late fall). This schedule would avoid dispersal limitation and would allow for a complete seed release. These modifications in present silviculture practices would produce a more efficient seed shadow in managed stands.

Spatio-temporal dynamics of viruses are differentially affected by parasitoids depending on the mode of transmission by their insect vectors.

Relationships between agents in multitrophic systems are complex and very specific. Insect-transmitted plant viruses are completely dependent on the behaviour and distribution patterns of their vectors. The presence of natural enemies may directly affect aphid behaviour and spread of plant viruses, as the escape response of aphids might cause a potential risk for virus dispersal. The spatio-temporal dynamics of Cucumber mosaic virus (CMV) and Cucurbit aphid-borne yellows virus (CABYV), transmitted by Aphis gossypii in a non-persistent and persistent manner, respectively, were evaluated at short and long term in the presence and absence of the aphid parasitoid, Aphidius colemani. SADIE methodology was used to study the distribution patterns of both the virus and its vector, and their degree of association. Results suggested that parasitoids promoted aphid dispersion at short term, which enhanced CMV spread, though consequences of parasitism suggest potential benefits for disease control at long term. Furthermore, A. colemani significantly limited the spread and incidence of the persistent virus CABYV at long term. The impact of aphid parasitoids on the dispersal of plant viruses with different transmission modes is discussed.

A silviculture-oriented spatio-temporal model for germination in Pinus pinea L. in the Spanish Northern Plateau based on a direct seeding experiment

Natural regeneration in Pinus pinea stands commonly fails throughout the Spanish Northern Plateau under current intensive regeneration treatments. As a result, extensive direct seeding is commonly conducted to guarantee regeneration occurrence. In a period of rationalization of the resources devoted to forest management, this kind of techniques may become unaffordable. Given that the climatic and stand factors driving germination remain unknown, tools are required to understand the process and temper the use of direct seeding. In this study, the spatio-temporal pattern of germination of P. pinea was modelled with those purposes. The resulting findings will allow us to (1) determine the main ecological variables involved in germination in the species and (2) infer adequate silvicultural alternatives. The modelling approach focuses on covariates which are readily available to forest managers. A two-step nonlinear mixed model was fitted to predict germination occurrence and abundance in P. pinea under varying climatic, environmental and stand conditions, based on a germination data set covering a 5-year period. The results obtained reveal that the process is primarily driven by climate variables. Favourable conditions for germination commonly occur in fall although the optimum window is often narrow and may not occur at all in some years. At spatial level, it would appear that germination is facilitated by high stand densities, suggesting that current felling intensity should be reduced. In accordance with other studies on P. pinea dispersal, it seems that denser stands during the regeneration period will reduce the present dependence on direct seeding.

Spatio-temporal filtering with morphological operators for robust cell migration estimation in "in-vivo" images

The understanding of the embryogenesis in living systems requires reliable quantitative analysis of the cell migration throughout all the stages of development. This is a major challenge of the "in-toto" reconstruction based on different modalities of "in-vivo" imaging techniques -spatio-temporal resolution and image artifacts and noise. Several methods for cell tracking are available, but expensive manual interaction -time and human resources- is always required to enforce coherence. Because of this limitation it is necessary to restrict the experiments or assume an uncontrolled error rate. Is it possible to obtain automated reliable measurements of migration? can we provide a seed for biologists to complete cell lineages efficiently? We propose a filtering technique that considers trajectories as spatio-temporal connected structures that prunes out those that might introduce noise and false positives by using multi-dimensional morphological operators.

Adaptive spatio-temporal filter for low-cost camera depth maps

In this paper we present an adaptive spatio-temporal filter that aims to improve low-cost depth camera accuracy and stability over time. The proposed system is composed by three blocks that are used to build a reliable depth map of static scenes. An adaptive joint-bilateral filter is used to obtain consistent depth maps by jointly considering depth and video information and by adapting its parameters to different levels of estimated noise. Kalman filters are used to reduce the temporal random fluctuations of the measurements. Finally an interpolation algorithm is used to obtain consistent depth maps in the regions where the depth information is not available. Results show that this approach allows to considerably improve the depth maps quality by considering spatio-temporal information and by adapting its parameters to different levels of noise.

Efficient spatio-temporal hole filling strategy for Kinect depth maps

In this paper we present an efficient hole filling strategy that improves the quality of the depth maps obtained with the Microsoft Kinect device. The proposed approach is based on a joint-bilateral filtering framework that includes spatial and temporal information. The missing depth values are obtained applying iteratively a joint-bilateral filter to their neighbor pixels. The filter weights are selected considering three different factors: visual data, depth information and a temporal-consistency map. Video and depth data are combined to improve depth map quality in presence of edges and homogeneous regions. Finally, the temporal-consistency map is generated in order to track the reliability of the depth measurements near the hole regions. The obtained depth values are included iteratively in the filtering process of the successive frames and the accuracy of the hole regions depth values increases while new samples are acquired and filtered

Spatio-temporal distribution of pyrethroids in soil in Mediterranean paddy fields

Purpose The demand of rice by the increase in population in many countries has intensified the application of pesticides and the use of poor quality water to irrigate fields. The terrestrial environment is one compartment affected by these situations, where soil is working as a reservoir, retaining organic pollutants. Therefore, it is necessary to develop methods to determine insecticides in soil and monitor susceptible areas to be contaminated, applying adequate techniques to remediate them. Materials and methods This study investigates the occurrence of ten pyrethroid insecticides (PYs) and its spatio-temporal variance in soil at two different depths collected in two periods (before plow and during rice production), in a paddy field area located in the Mediterranean coast. Pyrethroids were quantified using gas chromatography?mass spectrometry (GC?MS) after ultrasound-assisted extraction with ethyl acetate. The results obtained were assessed statistically using non-parametric methods, and significant statistical differences (p < 0.05) in pyrethroids content with soil depth and proximity to wastewater treatment plants were evaluated. Moreover, a geographic information system (GIS) was used to monitor the occurrence of PYs in paddy fields and detect risk areas. Results and discussion Pyrethroids were detected at concentrations ?57.0 ng g?1 before plow and ?62.3 ng g?1 during rice production, being resmethrin and cyfluthrin the compounds found at higher concentrations in soil. Pyrethroids were detected mainly at the top soil, and a GIS program was used to depict the obtained results, showing that effluents from wastewater treatment plants (WWTPs) were the main sources of soil contamination. No toxic effects were expected to soil organisms, but it is of concern that PYs may affect aquatic organisms, which represents the worst case scenario. Conclusions A methodology to determine pyrethroids in soil was developed to monitor a paddy field area. The use of water fromWWTPs to irrigate rice fields is one of the main pollution sources of pyrethroids. It is a matter of concern that PYs may present toxic effects on aquatic organisms, as they can be desorbed from soil. Phytoremediation may play an important role in this area, reducing the possible risk associated to PYs levels in soil.

Integration of temporal and semantic components into the Geographic Information. Part II: Methodology

The overall objective of this research project is to enrich geographic data with temporal and semantic components in order to significantly improve spatio-temporal analysis of geographic phenomena. To achieve this goal, we intend to establish and incorporate three new layers (structures) into the core of the Geographic Information by using mark-up languages as well as defining a set of methods and tools for enriching the system to make it able to retrieve and exploit such layers (semantic-temporal, geosemantic, and incremental spatio-temporal). Besides these layers, we also propose a set of models (temporal and spatial) and two semantic engines that make the most of the enriched geographic data. The roots of the project and its definition have been previously presented in Siabato & Manso-Callejo 2011. In this new position paper, we extend such work by delineating clearly the methodology and the foundations on which we will base to define the main components of this research: the spatial model, the temporal model, the semantic layers, and the semantic engines. By putting together the former paper and this new work we try to present a comprehensive description of the whole process, from pinpointing the basic problem to describing and assessing the solution. In this new article we just mention the methods and the background to describe how we intend to define the components and integrate them into the GI.

Predicción espacio-temporal de la irradiancia solar global a corto plazo en España mediante geoestadística y redes neuronales artificiales

El enriquecimiento del conocimiento sobre la Irradiancia Solar (IS) a nivel de superficie terrestre, así como su predicción, cobran gran interés para las Energías Renovables (ER) - Energía Solar (ES)-, y para distintas aplicaciones industriales o ecológicas. En el ámbito de las ER, el uso óptimo de la ES implica contar con datos de la IS en superficie que ayuden tanto, en la selección de emplazamientos para instalaciones de ES, como en su etapa de diseño (dimensionar la producción) y, finalmente, en su explotación. En este último caso, la observación y la predicción es útil para el mercado energético, la planificación y gestión de la energía (generadoras y operadoras del sistema eléctrico), especialmente en los nuevos contextos de las redes inteligentes de transporte. A pesar de la importancia estratégica de contar con datos de la IS, especialmente los observados por sensores de IS en superficie (los que mejor captan esta variable), estos no siempre están disponibles para los lugares de interés ni con la resolución espacial y temporal deseada. Esta limitación se une a la necesidad de disponer de predicciones a corto plazo de la IS que ayuden a la planificación y gestión de la energía. Se ha indagado y caracterizado las Redes de Estaciones Meteorológicas (REM) existentes en España que publican en internet sus observaciones, focalizando en la IS. Se han identificado 24 REM (16 gubernamentales y 8 redes voluntarios) que aglutinan 3492 estaciones, convirtiéndose éstas en las fuentes de datos meteorológicos utilizados en la tesis. Se han investigado cinco técnicas de estimación espacial de la IS en intervalos de 15 minutos para el territorio peninsular (3 técnicas geoestadísticas, una determinística y el método HelioSat2 basado en imágenes satelitales) con distintas configuraciones espaciales. Cuando el área de estudio tiene una adecuada densidad de observaciones, el mejor método identificado para estimar la IS es el Kriging con Regresión usando variables auxiliares -una de ellas la IS estimada a partir de imágenes satelitales-. De este modo es posible estimar espacialmente la IS más allá de los 25 km identificados en la bibliografía. En caso contrario, se corrobora la idoneidad de utilizar estimaciones a partir de sensores remotos cuando la densidad de observaciones no es adecuada. Se ha experimentado con el modelado de Redes Neuronales Artificiales (RNA) para la predicción a corto plazo de la IS utilizando observaciones próximas (componentes espaciales) en sus entradas y, los resultados son prometedores. Así los niveles de errores disminuyen bajo las siguientes condiciones: (1) cuando el horizonte temporal de predicción es inferior o igual a 3 horas, las estaciones vecinas que se incluyen en el modelo deben encentrarse a una distancia máxima aproximada de 55 km. Esto permite concluir que las RNA son capaces de aprender cómo afectan las condiciones meteorológicas vecinas a la predicción de la IS. ABSTRACT ABSTRACT The enrichment of knowledge about the Solar Irradiance (SI) at Earth's surface and its prediction, have a high interest for Renewable Energy (RE) - Solar Energy (SE) - and for various industrial and environmental applications. In the field of the RE, the optimal use of the SE involves having SI surface to help in the selection of sites for facilities ES, in the design stage (sizing energy production), and finally on their production. In the latter case, the observation and prediction is useful for the market, planning and management of the energy (generators and electrical system operators), especially in new contexts of smart transport networks (smartgrid). Despite the strategic importance of SI data, especially those observed by sensors of SI at surface (the ones that best measure this environmental variable), these are not always available to the sights and the spatial and temporal resolution desired. This limitation is bound to the need for short-term predictions of the SI to help planning and energy management. It has been investigated and characterized existing Networks of Weather Stations (NWS) in Spain that share its observations online, focusing on SI. 24 NWS have been identified (16 government and 8 volunteer networks) that implies 3492 stations, turning it into the sources of meteorological data used in the thesis. We have investigated five technical of spatial estimation of SI in 15 minutes to the mainland (3 geostatistical techniques and HelioSat2 a deterministic method based on satellite images) with different spatial configurations. When the study area has an adequate density of observations we identified the best method to estimate the SI is the regression kriging with auxiliary variables (one of them is the SI estimated from satellite images. Thus it is possible to spatially estimate the SI beyond the 25 km identified in the literature. Otherwise, when the density of observations is inadequate the appropriateness is using the estimates values from remote sensing. It has been experimented with Artificial Neural Networks (ANN) modeling for predicting the short-term future of the SI using observations from neighbor’s weather stations (spatial components) in their inputs, and the results are promising. The error levels decrease under the following conditions: (1) when the prediction horizon is less or equal than 3 hours the best models are the ones that include data from the neighboring stations (at a maximum distance of 55 km). It is concluded that the ANN is able to learn how weather conditions affect neighboring prediction of IS at such Spatio-temporal horizons.

New insights into the regulation of NADPH oxidase dependent reactive oxygen species signaling during the plant immune response

Las NADPH oxidasas de plantas, denominadas “respiratory burst oxidase homologues” (RBOHs), producen especies reactivas del oxígeno (ROS) que median un amplio rango de funciones. En la célula vegetal, el ajuste preciso de la producción de ROS aporta la especificidad de señal para generar una respuesta apropiada ante las amenazas ambientales. RbohD y RbohF, dos de los diez genes Rboh de Arabidopsis, son pleiotrópicos y median diversos procesos fisiológicos en respuesta a patógenos. El control espacio-temporal de la expresión de los genes RbohD y RbohF podría ser un aspecto crítico para determinar la multiplicidad de funciones de estas oxidasas. Por ello, generamos líneas transgénicas de Arabidopsis con fusiones de los promoters de RbohD y RbohF a los genes delatores de la B-glucuronidasa y la luciferasa. Estas líneas fueron empleadas para revelar el patrón de expresión diferencial de RbohD y RbohF durante la respuesta inmune de Arabidopsis a la bacteria patógena Pseudomonas syringae pv. tomato DC3000, el hongo necrótrofo Plectosphaerella cucumerina y en respuesta a señales relacionadas con la respuesta inmune. Nuestros experimentos revelan un patrón de expresión diferencial de los promotores de RbohD y RbohF durante el desarrollo de la planta y en la respuesta inmune de Arabidopsis. Además hemos puesto de manifiesto que existe una correlación entre el nivel de actividad de los promotores de RbohD y RbohF con la acumulación de ROS y el nivel de muerte celular en respuesta a patógenos. La expression de RbohD y RbohF también es modulada de manera diferencial en respuesta a patrones moleculares asociados a patógenos (PAMPs) y por ácido abscísico (ABA). Cabe destacar que, mediante una estrategia de intercambio de promotores, hemos revelado que la región promotora de RbohD, es necesaria para dirigir la producción de ROS en respuesta a P. cucumerina. Adicionalmente, la activación del promotor de RbohD en respuesta al aislado de P. cucumerina no adaptado a Arabidopsis 2127, nos llevó a realizar ensayos de susceptibilidad con el doble mutante rbohD rbohF que han revelado un papel desconocido de estas oxidasas en resistencia no-huesped. La interacción entre la señalización dependiente de las RBOHs y otros componentes de la respuesta inmune de plantas podría explicar también las distintas funciones que median estas oxidasas en relación con la respuesta inmune. Entre la gran cantidad de señales coordinadas con la actividad de las RBOHs, existen evidencias genéticas y farmacológicas que indican que las proteínas G heterotriméricas están implicadas en algunas de las rutas de señalización mediadas por ROS derivadas de los RBOHs en respuesta a señales ambientales. Por ello hemos estudiado la relación entre estas RBOH-NADPH oxidasas y AGB1, la subunidad β de las proteínas G heterotriméricas en la respuesta inmune de Arabidopsis. Análisis de epistasis indican que las proteínas G heterotriméricas están implicadas en distintas rutas de señalización en defensa mediadas por las RBOHs. Nuestros resultados ilustran la relación compleja entre la señalización mediada por las RBOHs y las proteínas G heterotriméricas, que varía en función de la interacción planta-patógeno analizada. Además, hemos explorado la posible asociación entre AGB1 con RBOHD y RBOHF en eventos tempranos de la respuesta immune. Cabe señalar que experimentos de coímmunoprecipitación apuntan a una posible asociación entre AGB1 y la kinasa citoplasmática reguladora de RBOHD, BIK1. Esto indica un posible mecanismo de control de la función de esta NADPH oxidase por AGB1. En conjunto, estos datos aportan nuevas perspectivas sobre cómo, a través del control transcripcional o mediante la interacción con las proteínas G heterotriméricas, las NADPH oxidases de plantas median la producción de ROS y la señalización por ROS en la respuesta inmune. Nuestro trabajo ejemplifica cómo la regulación diferencial de dos miembros de una familia multigénica, les permite realizar distintas funciones fisiológicas especializadas usando un mismo mecanismo enzimático. ABSTRACT The plant NADPH oxidases, termed respiratory burst oxidase homologues (RBOHs), produce reactive oxygen species (ROS) which mediate a wide range of functions. Fine tuning this ROS production provides the signaling specificity to the plant cell to produce the appropriate response to environmental threats. RbohD and RbohF, two of the ten Rboh genes present in Arabidopsis, are pleiotropic and mediate diverse physiological processes in response to pathogens. One aspect that may prove critical to determine the multiplicity of functions of RbohD and RbohF is the spatio-temporal control of their gene expression. Thus, we generated Arabidopsis transgenic lines with RbohD- and RbohF-promoter fusions to the β-glucuronidase and the luciferase reporter genes. These transgenics were employed to reveal RbohD and RbohF promoter activity during Arabidopsis immune response to the pathogenic bacterium Pseudomonas syringae pv tomato DC3000, the necrotrophic fungus Plectosphaerella cucumerina and in response to immunity-related cues. Our experiments revealed a differential expression pattern of RbohD and RbohF throughout plant development and during Arabidopsis immune response. Moreover, we observed a correlation between the level of RbohD and RbohF promoter activity, the accumulation of ROS and the amount of cell death in response to pathogens. RbohD and RbohF gene expression was also differentially modulated by pathogen associated molecular patterns and abscisic acid. Interestingly, a promoter-swap strategy revealed the requirement for the promoter region of RbohD to drive the production of ROS in response to P. cucumerina. Additionally, since the RbohD promoter was activated during Arabidopsis interaction with a non-adapted P. cucumerina isolate 2127, we performed susceptibility tests to this fungal isolate that uncovered a new role of these oxidases on non-host resistance. The interplay between RBOH-dependent signaling with other components of the plant immune response might also explain the different immunity-related functions mediated by these oxidases. Among the plethora of signals coordinated with RBOH activity, pharmacological and genetic evidence indicates that heterotrimeric G proteins are involved in some of the signaling pathways mediated by RBOH–derived ROS in response to environmental cues. Therefore, we analysed the interplay between these RBOH-NADPH oxidases and AGB1, the Arabidopsis β-subunit of heterotrimeric G proteins during Arabidopsis immune response. We carried out epistasis studies that allowed us to test the implication of AGB1 in different RBOH-mediated defense signaling pathways. Our results illustrate the complex relationship between RBOH and heterotrimeric G proteins signaling, that varies depending on the type of plant-pathogen interaction. Furthermore, we tested the potential association between AGB1 with RBOHD and RBOHF during early immunity. Interestingly, our co-immunoprecipitation experiments point towards an association of AGB1 and the RBOHD regulatory kinase BIK1, thus providing a putative mechanism in the control of the NADPH oxidase function by AGB1. Taken all together, these studies provide further insights into the role that transcriptional control or the interaction with heterotrimeric G-proteins have on RBOH-NADPH oxidase-dependent ROS production and signaling in immunity. Our work exemplifies how, through a differential regulation, two members of a multigenic family achieve specialized physiological functions using a common enzymatic mechanism.

Methods for the analysis of multi-scale cell dynamics from fluorescence microscopy images

La embriogénesis es el proceso mediante el cual una célula se convierte en un ser un vivo. A lo largo de diferentes etapas de desarrollo, la población de células va proliferando a la vez que el embrión va tomando forma y se configura. Esto es posible gracias a la acción de varios procesos genéticos, bioquímicos y mecánicos que interaccionan y se regulan entre ellos formando un sistema complejo que se organiza a diferentes escalas espaciales y temporales. Este proceso ocurre de manera robusta y reproducible, pero también con cierta variabilidad que permite la diversidad de individuos de una misma especie. La aparición de la microscopía de fluorescencia, posible gracias a proteínas fluorescentes que pueden ser adheridas a las cadenas de expresión de las células, y los avances en la física óptica de los microscopios han permitido observar este proceso de embriogénesis in-vivo y generar secuencias de imágenes tridimensionales de alta resolución espacio-temporal. Estas imágenes permiten el estudio de los procesos de desarrollo embrionario con técnicas de análisis de imagen y de datos, reconstruyendo dichos procesos para crear la representación de un embrión digital. Una de las más actuales problemáticas en este campo es entender los procesos mecánicos, de manera aislada y en interacción con otros factores como la expresión genética, para que el embrión se desarrolle. Debido a la complejidad de estos procesos, estos problemas se afrontan mediante diferentes técnicas y escalas específicas donde, a través de experimentos, pueden hacerse y confrontarse hipótesis, obteniendo conclusiones sobre el funcionamiento de los mecanismos estudiados. Esta tesis doctoral se ha enfocado sobre esta problemática intentando mejorar las metodologías del estado del arte y con un objetivo específico: estudiar patrones de deformación que emergen del movimiento organizado de las células durante diferentes estados del desarrollo del embrión, de manera global o en tejidos concretos. Estudios se han centrado en la mecánica en relación con procesos de señalización o interacciones a nivel celular o de tejido. En este trabajo, se propone un esquema para generalizar el estudio del movimiento y las interacciones mecánicas que se desprenden del mismo a diferentes escalas espaciales y temporales. Esto permitiría no sólo estudios locales, si no estudios sistemáticos de las escalas de interacción mecánica dentro de un embrión. Por tanto, el esquema propuesto obvia las causas de generación de movimiento (fuerzas) y se centra en la cuantificación de la cinemática (deformación y esfuerzos) a partir de imágenes de forma no invasiva. Hoy en día las dificultades experimentales y metodológicas y la complejidad de los sistemas biológicos impiden una descripción mecánica completa de manera sistemática. Sin embargo, patrones de deformación muestran el resultado de diferentes factores mecánicos en interacción con otros elementos dando lugar a una organización mecánica, necesaria para el desarrollo, que puede ser cuantificado a partir de la metodología propuesta en esta tesis. La metodología asume un medio continuo descrito de forma Lagrangiana (en función de las trayectorias de puntos materiales que se mueven en el sistema en lugar de puntos espaciales) de la dinámica del movimiento, estimado a partir de las imágenes mediante métodos de seguimiento de células o de técnicas de registro de imagen. Gracias a este esquema es posible describir la deformación instantánea y acumulada respecto a un estado inicial para cualquier dominio del embrión. La aplicación de esta metodología a imágenes 3D + t del pez zebra sirvió para desvelar estructuras mecánicas que tienden a estabilizarse a lo largo del tiempo en dicho embrión, y que se organizan a una escala semejante al del mapa de diferenciación celular y con indicios de correlación con patrones de expresión genética. También se aplicó la metodología al estudio del tejido amnioserosa de la Drosophila (mosca de la fruta) durante el cierre dorsal, obteniendo indicios de un acoplamiento entre escalas subcelulares, celulares y supracelulares, que genera patrones complejos en respuesta a la fuerza generada por los esqueletos de acto-myosina. En definitiva, esta tesis doctoral propone una estrategia novedosa de análisis de la dinámica celular multi-escala que permite cuantificar patrones de manera inmediata y que además ofrece una representación que reconstruye la evolución de los procesos como los ven las células, en lugar de como son observados desde el microscopio. Esta metodología por tanto permite nuevas formas de análisis y comparación de embriones y tejidos durante la embriogénesis a partir de imágenes in-vivo. ABSTRACT The embryogenesis is the process from which a single cell turns into a living organism. Through several stages of development, the cell population proliferates at the same time the embryo shapes and the organs develop gaining their functionality. This is possible through genetic, biochemical and mechanical factors that are involved in a complex interaction of processes organized in different levels and in different spatio-temporal scales. The embryogenesis, through this complexity, develops in a robust and reproducible way, but allowing variability that makes possible the diversity of living specimens. The advances in physics of microscopes and the appearance of fluorescent proteins that can be attached to expression chains, reporting about structural and functional elements of the cell, have enabled for the in-vivo observation of embryogenesis. The imaging process results in sequences of high spatio-temporal resolution 3D+time data of the embryogenesis as a digital representation of the embryos that can be further analyzed, provided new image processing and data analysis techniques are developed. One of the most relevant and challenging lines of research in the field is the quantification of the mechanical factors and processes involved in the shaping process of the embryo and their interactions with other embryogenesis factors such as genetics. Due to the complexity of the processes, studies have focused on specific problems and scales controlled in the experiments, posing and testing hypothesis to gain new biological insight. However, methodologies are often difficult to be exported to study other biological phenomena or specimens. This PhD Thesis is framed within this paradigm of research and tries to propose a systematic methodology to quantify the emergent deformation patterns from the motion estimated in in-vivo images of embryogenesis. Thanks to this strategy it would be possible to quantify not only local mechanisms, but to discover and characterize the scales of mechanical organization within the embryo. The framework focuses on the quantification of the motion kinematics (deformation and strains), neglecting the causes of the motion (forces), from images in a non-invasive way. Experimental and methodological challenges hamper the quantification of exerted forces and the mechanical properties of tissues. However, a descriptive framework of deformation patterns provides valuable insight about the organization and scales of the mechanical interactions, along the embryo development. Such a characterization would help to improve mechanical models and progressively understand the complexity of embryogenesis. This framework relies on a Lagrangian representation of the cell dynamics system based on the trajectories of points moving along the deformation. This approach of analysis enables the reconstruction of the mechanical patterning as experienced by the cells and tissues. Thus, we can build temporal profiles of deformation along stages of development, comprising both the instantaneous events and the cumulative deformation history. The application of this framework to 3D + time data of zebrafish embryogenesis allowed us to discover mechanical profiles that stabilized through time forming structures that organize in a scale comparable to the map of cell differentiation (fate map), and also suggesting correlation with genetic patterns. The framework was also applied to the analysis of the amnioserosa tissue in the drosophila’s dorsal closure, revealing that the oscillatory contraction triggered by the acto-myosin network organized complexly coupling different scales: local force generation foci, cellular morphology control mechanisms and tissue geometrical constraints. In summary, this PhD Thesis proposes a theoretical framework for the analysis of multi-scale cell dynamics that enables to quantify automatically mechanical patterns and also offers a new representation of the embryo dynamics as experienced by cells instead of how the microscope captures instantaneously the processes. Therefore, this framework enables for new strategies of quantitative analysis and comparison between embryos and tissues during embryogenesis from in-vivo images.

Seed Dispersal Spectrum of Woody Species in South Ecuadorian Dry Forests: Environmental Correlates and the Effect of Considering Species Abundance

This study examines the seed dispersal spectrum of the tropical dry forests of Southern Ecuador, in an effort to contribute to the knowledge of the complex dynamics of tropical dry forests. Seed dispersal spectrum was described for a total number of 160 species. Relationships of dispersal syndromes with plant growth form and climatic seasonality were explored. For a subset of 97 species, we determined whether dispersal spectrum changes when species abundance, in addition to species number, is taken into account. The same subset was used to relate dispersal syndromes with the environmental conditions. Zoochorous species dominated in the studied community. When considering the individual abundance of each species, however, anemochory was the prevalent dispersal syndrome. We found a significant difference in the frequency of dispersal syndromes among plant growth forms, with epizoochory only occurring in shrub species. The dispersal spectrum was dependent on climatic seasonality. The largest proportion of anemochorous species fructified during the dry season, while zoochorous diaspores dominated during the rainy season. A fourth-corner analysis indicated that the seed dispersal spectrum of Southern Ecuador dry forests is controlled by environmental conditions such as annual precipitation, annual temperature range or topography. Our results suggest that spatio-temporal changes in the environmental conditions may affect important ecological processes for dispersal. Thus, the predominance of one syndrome or another may depend on the spatial variation of environmental conditions.

Space-time Reconstruction of Oceanic Sea States via Variational Stereo Methods

We present a remote sensing observational method for the measurement of the spatio-temporal dynamics of ocean waves. Variational techniques are used to recover a coherent space-time reconstruction of oceanic sea states given stereo video imagery. The stereoscopic reconstruction problem is expressed in a variational optimization framework. There, we design an energy functional whose minimizer is the desired temporal sequence of wave heights. The functional combines photometric observations as well as spatial and temporal regularizers. A nested iterative scheme is devised to numerically solve, via 3-D multigrid methods, the system of partial differential equations resulting from the optimality condition of the energy functional. The output of our method is the coherent, simultaneous estimation of the wave surface height and radiance at multiple snapshots. We demonstrate our algorithm on real data collected off-shore. Statistical and spectral analysis are performed. Comparison with respect to an existing sequential method is analyzed.

Auxin - oxylipin crosstalk in stress responses of plant roots

Phytohormones regulate a wide array of developmental processes throughout the life cycle of plants. Over recent years, mounting evidence led to the widely accepted concept that plant hormone action is not the read-out of linear pathways, but determined by the extensive combinatorial activity of the signaling molecules and the integration of their signaling pathways, both in terms of regulating growth and development and in adapting to external stimuli. Recent work is beginning to shed light on the crosstalk of both nominally synergistically and antagonistically acting plant hormones such as, for example, auxins with oxylipins. Here, we report that oxylipins directly contribute to the regulation of the expression of two Arabidopsis YUCCA (YUC) genes, YUC8 and YUC9. Similar to previously characterized YUC family members, we identify both YUC8 and YUC9 as involved in local auxin biosynthesis, as demonstrated by the altered auxin contents and auxin-dependent phenotypes displayed by loss-of function mutants and transgenic overexpressing lines. Gene expression data obtained by qPCR analysis and microscopic examination of promoter-reporter lines reveal an oxylipin-mediated regulation of YUC9 expression that is dependent on the COI1 signal transduction pathway. The microscopic data indicate a functional overlap of the two analyzed auxin biosynthesis genes, but also point out specific functions for YUC8 and YUC9, which are in part related to different spatio-temporal expression pattern. In support of these findings, the analyzed yuc knockout mutants had lower free auxin contents and displayed a reduced response to oxylipins. This work provides evidence of a molecular mechanism that links oxylipin signaling with auxin homeostasis.

Hydrologic models for emergency decision support using Bayesian networks

In the presence of a river flood, operators in charge of control must take decisions based on imperfect and incomplete sources of information (e.g., data provided by a limited number sensors) and partial knowledge about the structure and behavior of the river basin. This is a case of reasoning about a complex dynamic system with uncertainty and real-time constraints where bayesian networks can be used to provide an effective support. In this paper we describe a solution with spatio-temporal bayesian networks to be used in a context of emergencies produced by river floods. In the paper we describe first a set of types of causal relations for hydrologic processes with spatial and temporal references to represent the dynamics of the river basin. Then we describe how this was included in a computer system called SAIDA to provide assistance to operators in charge of control in a river basin. Finally the paper shows experimental results about the performance of the model.