Competition may explain the fine-scale spatial patterns and genetic structure of two co-occurring plant congeners

1. The spatial distribution of individual plants within a population and the population’s genetic structure are determined by several factors, like dispersal, reproduction mode or biotic interactions. The role of interspecific interactions in shaping the spatial genetic structure of plant populations remains largely unknown. 2. Species with a common evolutionary history are known to interact more closely with each other than unrelated species due to the greater number of traits they share. We hypothesize that plant interactions may shape the fine genetic structure of closely related congeners. 3. We used spatial statistics (georeferenced design) and molecular techniques (ISSR markers) to understand how two closely related congeners, Thymus vulgaris (widespread species) and T. loscosii (narrow endemic) interact at the local scale. Specific cover, number of individuals of both study species and several community attributes were measured in a 10 × 10 m plot. 4. Both species showed similar levels of genetic variation, but differed in their spatial genetic structure. Thymus vulgaris showed spatial aggregation but no spatial genetic structure, while T. loscosii showed spatial genetic structure (positive genetic autocorrelation) at short distances. The spatial pattern of T. vulgaris’ cover showed significant dissociation with that of T. loscosii. The same was true between the spatial patterns of the cover of T. vulgaris and the abundance of T. loscosii and between the abundance of each species. Most importantly, we found a correlation between the genetic structure of T. loscosii and the abundance of T. vulgaris: T. loscosii plants were genetically more similar when they were surrounded by a similar number of T. vulgaris plants. 5. Synthesis. Our results reveal spatially complex genetic structures of both congeners at small spatial scales. The negative association among the spatial patterns of the two species and the genetic structure found for T. loscosii in relation to the abundance of T. vulgaris indicate that competition between the two species may account for the presence of adapted ecotypes of T. loscosii to the abundance of a competing congeneric species. This suggests that the presence and abundance of close congeners can influence the genetic spatial structure of plant species at fine scales.

Genetic characterization of chestnut (Castanea sativa Mill.) orchards and traditional nut varieties in El Bierzo, a glacial refuge and major cultivation site in Northwestern Spain

This paper presents a detailed genetic study of Castanea sativa in El Bierzo, a major nut production region with interesting features. It is located within a glacial refuge at one extreme of the distribution area (northwest Spain); it has a centenary tradition of chestnut management; and more importantly, it shows an unusual degree of genetic isolation. Seven nuclear microsatellite markers were selected to analyze the genetic variability and structure of 169 local trees grafted for nut production. We analyzed in the same manner 62 local nuts. The selected loci were highly discriminant for the genotypes studied, giving a combined probability of identity of 6.1 × 10−6. An unprecedented density of trees was sampled for this project over the entire region, and nuts were collected representing 18 cultivars marketed by local producers. Several instances of misclassification by local growers were detected. Fixation index estimates and analysis of molecular variance (AMOVA) data are supportive of an unexpectedly high level of genetic differentiation in El Bierzo, larger than that estimated in a previous study with broader geographical scope but based on limited local sampling (Pereira-Lorenzo et al., Tree Genet Genomes 6: 701–715, 2010a). Likewise, we have determined that clonality due to grafting had been previously overestimated. In line with these observations, no significant spatial structure was found using both a model-based Bayesian procedure and Mantel’s tests. Taken together, our results evidence the need for more fine-scale genetic studies if conservation strategies are to be efficiently improved.

Maintaining distances with the engineer: patterns of coexistence in plant communities beyond the patch-bare dichotomy

Two-phase plant communities with an engineer conforming conspicuous patches and affecting the performance and patterns of coexisting species are the norm under stressful conditions. To unveil the mechanisms governing coexistence in these communities at multiple spatial scales, we have developed a new point-raster approach of spatial pattern analysis, which was applied to a Mediterranean high mountain grassland to show how Festuca curvifolia patches affect the local distribution of coexisting species. We recorded 22 111 individuals of 17 plant perennial species. Most coexisting species were negatively associated with F. curvifolia clumps. Nevertheless, bivariate nearest-neighbor analyses revealed that the majority of coexisting species were confined at relatively short distances from F. curvifolia borders (between 0-2 cm and up to 8 cm in some cases). Our study suggests the existence of a fine-scale effect of F. curvifolia for most species promoting coexistence through a mechanism we call 'facilitation in the halo'. Most coexisting species are displaced to an interphase area between patches, where two opposite forces reach equilibrium: attenuated severe conditions by proximity to the F. curvifolia canopy (nutrient-rich islands) and competitive exclusion mitigated by avoiding direct contact with F. curvifolia.

Geografía del carbono en alta resolución en bosque tropical amazónico del Ecuador mediante sensores aerotransportados

La estimación de la biomasa de la vegetación terrestre en bosque tropical no sólo es un área de investigación en rápida expansión, sino también es un tema de gran interés para reducir las emisiones de carbono asociadas a la deforestación y la degradación forestal (REDD+). Las estimaciones de densidad de carbono sobre el suelo (ACD) en base a inventarios de campo y datos provenientes de sensores aerotransportados, en especial con sensores LiDAR, han conducido a un progreso sustancial en el cartografiado a gran escala de las reservas de carbono forestal. Sin embargo, estos mapas de carbono tienen incertidumbres considerables, asociadas generalmente al proceso de calibración del modelo de regresión utilizado para producir los mapas. En esta tesis se establece una metodología para la calibración y validación de un modelo general de estimación de ACD usando LiDAR en un sector del Parque Nacional Yasuní en Ecuador. En el proceso de calibración del modelo se considera el tamaño y la ubicación de las parcelas, la influencia de la topografía y la distribución espacial de la biomasa. Para el análisis de los datos se utilizan técnicas geoestadísticas en combinación con variables geomorfométricas derivadas de datos LiDAR, y se propone un esquema de muestreo estratificado por posiciones topográficas (valle, ladera y cima). La validación del modelo general para toda la zona de estudio presentó valores de RMSE = 5.81 Mg C ha-1, R2 = 0.94 y sesgo = 0.59, mientras que, al considerar las posiciones topográficas, el modelo presentó valores de RMSE = 1.67 Mg C ha-1, R2 = 0.98 y sesgo = 0.23 para el valle; RMSE = 3.13 Mg C ha-1, R2 = 0.98 y sesgo = - 0.34 para la ladera; y RMSE = 2.33 Mg C ha-1, R2 = 0.97 y sesgo = 0.74 para la cima. Los resultados obtenidos demuestran que la metodología de muestreo estratificado por posiciones topográficas propuesto, permite calibrar de manera efectiva el modelo general con las estimaciones de ACD en campo, logrando reducir el RMSE y el sesgo. Los resultados muestran el potencial de los datos LiDAR para caracterizar la estructura vertical de la vegetación en un bosque altamente diverso, permitiendo realizar estimaciones precisas de ACD, y conocer patrones espaciales continuos de la distribución de la biomasa aérea y del contenido de carbono en la zona de estudio. ABSTRACT Estimating biomass of terrestrial vegetation in tropical forest is not only a rapidly expanding research area, but also a subject of tremendous interest for reducing carbon emissions associated with deforestation and forest degradation (REDD+). The aboveground carbon density estimates (ACD) based on field inventories and airborne sensors, especially LiDAR sensors have led to a substantial progress in large-scale mapping of forest carbon stocks. However, these carbon maps have considerable uncertainties generally associated with the calibration of the regression model used to produce these maps. This thesis establishes a methodology for calibrating and validating a general ACD estimation model using LiDAR in Ecuador´s Yasuní National Park. The size and location of the plots are considered in the model calibration phase as well as the influence of topography and spatial distribution of biomass. Geostatistical analysis techniques are used in combination with geomorphometrics variables derived from LiDAR data, and then a stratified sampling scheme considering topographic positions (valley, slope and ridge) is proposed. The validation of the general model for the study area showed values of RMSE = 5.81 Mg C ha-1, R2 = 0.94 and bias = 0.59, while considering the topographical positions, the model showed values of RMSE = 1.67 Mg C ha-1, R2 = 0.98 and bias = 0.23 for the valley; RMSE = 3.13 Mg C ha-1, R2 = 0.98 and bias = - 0.34 for the slope; and RMSE = 2.33 Mg C ha-1, R2 = 0.97 and bias = 0.74 for the ridge. The results show that the stratified sampling methodology taking into account topographic positions, effectively calibrates the general model with field estimates of ACD, reducing RMSE and bias. The results show the potential of LiDAR data to characterize the vertical structure of vegetation in a highly diverse forest, allowing accurate estimates of ACD, and knowing continuous spatial patterns of biomass distribution and carbon stocks in the study area.

Mapping of mechanical properties of cement paste microstructures

The presented study is related to the EU 7 th Framework Programme CODICE (COmputationally Driven design of Innovative CEment-based materials). The main aim of the project is the development of a multi-scale model for the computer based simulation of mechanical and durability performance of cementitious materials. This paper reports results of micro/nano scale characterisation and mechanical property mapping of cementitious skeletons formed by the cement hydration at different ages. Using the statistical nanoindentation and micro-mechanical property mapping technique, intrinsic properties of different hydrate phases, and also the possible interaction (or overlapping) of different phases (e.g. calcium-silcate-hydrates) has been studied. Results of the mapping and statistical indentation testing appear to suggest the possible existence of more hydrate phases than the commonly reported LD and HD C-S-H and CH phases

Mycorrhizal preferences and fine spatial structure of the epiphytic orchid Epidendrum rhopalostele

• Premise of the study: The presence of compatible fungi is necessary for epiphytic orchid recruitment. Thus, identifying associated mycorrhizal fungi at the population level is essential for orchid conservation. Recruitment patterns may also be conditioned by factors such as seed dispersal range and specific environmental characteristics. • Methods: In a forest plot, all trees with a diameter at breast height >1 cm and all individuals of the epiphytic orchid Epidendrum rhopalostele were identified and mapped. Additionally, one flowering individual of E. rhopalostele per each host tree was randomly selected for root sampling and DNA extraction. • Key results: A total of 239 E. rhopalostele individuals were located in 25 of the 714 potential host trees. Light microscopy of sampled roots showed mycorrhizal fungi in 22 of the 25 sampled orchids. Phylogenetic analysis of ITS1-5.8S-ITS2 sequences yielded two Tulasnella clades. In four cases, plants were found to be associated with both clades. The difference between univariate and bivariate K functions was consistent with the random labeling null model at all spatial scales, indicating that trees hosting clades A and B of Tulasnella are not spatially segregated. The analysis of the inhomogenous K function showed that host trees are not clustered, suggesting no limitations to population-scale dispersal. χ2 analysis of contingency tables showed that E. rhopalostele is more frequent on dead trees than expected. • Conclusions: Epidendrum rhopalostele establishes mycorrhizal associations with at least two different Tulasnella species. The analysis of the distribution patterns of this orchid suggests a microsite preference for dead trees and no seed dispersal limitation.

Vision-Based Tracking, Odometry and Control for UAV Autonomy

El principal objetivo de este trabajo es proporcionar una solución en tiempo real basada en visión estéreo o monocular precisa y robusta para que un vehículo aéreo no tripulado (UAV) sea autónomo en varios tipos de aplicaciones UAV, especialmente en entornos abarrotados sin señal GPS. Este trabajo principalmente consiste en tres temas de investigación de UAV basados en técnicas de visión por computador: (I) visual tracking, proporciona soluciones efectivas para localizar visualmente objetos de interés estáticos o en movimiento durante el tiempo que dura el vuelo del UAV mediante una aproximación adaptativa online y una estrategia de múltiple resolución, de este modo superamos los problemas generados por las diferentes situaciones desafiantes, tales como cambios significativos de aspecto, iluminación del entorno variante, fondo del tracking embarullado, oclusión parcial o total de objetos, variaciones rápidas de posición y vibraciones mecánicas a bordo. La solución ha sido utilizada en aterrizajes autónomos, inspección de plataformas mar adentro o tracking de aviones en pleno vuelo para su detección y evasión; (II) odometría visual: proporciona una solución eficiente al UAV para estimar la posición con 6 grados de libertad (6D) usando únicamente la entrada de una cámara estéreo a bordo del UAV. Un método Semi-Global Blocking Matching (SGBM) eficiente basado en una estrategia grueso-a-fino ha sido implementada para una rápida y profunda estimación del plano. Además, la solución toma provecho eficazmente de la información 2D y 3D para estimar la posición 6D, resolviendo de esta manera la limitación de un punto de referencia fijo en la cámara estéreo. Una robusta aproximación volumétrica de mapping basada en el framework Octomap ha sido utilizada para reconstruir entornos cerrados y al aire libre bastante abarrotados en 3D con memoria y errores correlacionados espacialmente o temporalmente; (III) visual control, ofrece soluciones de control prácticas para la navegación de un UAV usando Fuzzy Logic Controller (FLC) con la estimación visual. Y el framework de Cross-Entropy Optimization (CEO) ha sido usado para optimizar el factor de escala y la función de pertenencia en FLC. Todas las soluciones basadas en visión en este trabajo han sido probadas en test reales. Y los conjuntos de datos de imágenes reales grabados en estos test o disponibles para la comunidad pública han sido utilizados para evaluar el rendimiento de estas soluciones basadas en visión con ground truth. Además, las soluciones de visión presentadas han sido comparadas con algoritmos de visión del estado del arte. Los test reales y los resultados de evaluación muestran que las soluciones basadas en visión proporcionadas han obtenido rendimientos en tiempo real precisos y robustos, o han alcanzado un mejor rendimiento que aquellos algoritmos del estado del arte. La estimación basada en visión ha ganado un rol muy importante en controlar un UAV típico para alcanzar autonomía en aplicaciones UAV. ABSTRACT The main objective of this dissertation is providing real-time accurate robust monocular or stereo vision-based solution for Unmanned Aerial Vehicle (UAV) to achieve the autonomy in various types of UAV applications, especially in GPS-denied dynamic cluttered environments. This dissertation mainly consists of three UAV research topics based on computer vision technique: (I) visual tracking, it supplys effective solutions to visually locate interesting static or moving object over time during UAV flight with on-line adaptivity approach and multiple-resolution strategy, thereby overcoming the problems generated by the different challenging situations, such as significant appearance change, variant surrounding illumination, cluttered tracking background, partial or full object occlusion, rapid pose variation and onboard mechanical vibration. The solutions have been utilized in autonomous landing, offshore floating platform inspection and midair aircraft tracking for sense-and-avoid; (II) visual odometry: it provides the efficient solution for UAV to estimate the 6 Degree-of-freedom (6D) pose using only the input of stereo camera onboard UAV. An efficient Semi-Global Blocking Matching (SGBM) method based on a coarse-to-fine strategy has been implemented for fast depth map estimation. In addition, the solution effectively takes advantage of both 2D and 3D information to estimate the 6D pose, thereby solving the limitation of a fixed small baseline in the stereo camera. A robust volumetric occupancy mapping approach based on the Octomap framework has been utilized to reconstruct indoor and outdoor large-scale cluttered environments in 3D with less temporally or spatially correlated measurement errors and memory; (III) visual control, it offers practical control solutions to navigate UAV using Fuzzy Logic Controller (FLC) with the visual estimation. And the Cross-Entropy Optimization (CEO) framework has been used to optimize the scaling factor and the membership function in FLC. All the vision-based solutions in this dissertation have been tested in real tests. And the real image datasets recorded from these tests or available from public community have been utilized to evaluate the performance of these vision-based solutions with ground truth. Additionally, the presented vision solutions have compared with the state-of-art visual algorithms. Real tests and evaluation results show that the provided vision-based solutions have obtained real-time accurate robust performances, or gained better performance than those state-of-art visual algorithms. The vision-based estimation has played a critically important role for controlling a typical UAV to achieve autonomy in the UAV application.