899 resultados para Recursive Partitioning and Regression Trees (RPART)
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Irregular computations pose some of the most interesting and challenging problems in automatic parallelization. Irregularity appears in certain kinds of numerical problems and is pervasive in symbolic applications. Such computations often use dynamic data structures which make heavy use of pointers. This complicates all the steps of a parallelizing compiler, from independence detection to task partitioning and placement. In the past decade there has been significant progress in the development of parallelizing compilers for logic programming and, more recently, constraint programming. The typical applications of these paradigms frequently involve irregular computations, which arguably makes the techniques used in these compilers potentially interesting. In this paper we introduce in a tutorial way some of the problems faced by parallelizing compilers for logic and constraint programs. These include the need for inter-procedural pointer aliasing analysis for independence detection and having to manage speculative and irregular computations through task granularity control and dynamic task allocation. We also provide pointers to some of the progress made in these áreas. In the associated talk we demónstrate representatives of several generations of these parallelizing compilers.
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Automatic blood glucose classification may help specialists to provide a better interpretation of blood glucose data, downloaded directly from patients glucose meter and will contribute in the development of decision support systems for gestational diabetes. This paper presents an automatic blood glucose classifier for gestational diabetes that compares 6 different feature selection methods for two machine learning algorithms: neural networks and decision trees. Three searching algorithms, Greedy, Best First and Genetic, were combined with two different evaluators, CSF and Wrapper, for the feature selection. The study has been made with 6080 blood glucose measurements from 25 patients. Decision trees with a feature set selected with the Wrapper evaluator and the Best first search algorithm obtained the best accuracy: 95.92%.
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Active optical sensing (LIDAR and light curtain transmission) devices mounted on a mobile platform can correctly detect, localize, and classify trees. To conduct an evaluation and comparison of the different sensors, an optical encoder wheel was used for vehicle odometry and provided a measurement of the linear displacement of the prototype vehicle along a row of tree seedlings as a reference for each recorded sensor measurement. The field trials were conducted in a juvenile tree nursery with one-year-old grafted almond trees at Sierra Gold Nurseries, Yuba City, CA, United States. Through these tests and subsequent data processing, each sensor was individually evaluated to characterize their reliability, as well as their advantages and disadvantages for the proposed task. Test results indicated that 95.7% and 99.48% of the trees were successfully detected with the LIDAR and light curtain sensors, respectively. LIDAR correctly classified, between alive or dead tree states at a 93.75% success rate compared to 94.16% for the light curtain sensor. These results can help system designers select the most reliable sensor for the accurate detection and localization of each tree in a nursery, which might allow labor-intensive tasks, such as weeding, to be automated without damaging crops.
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There is a growing call for inventories that evaluate geographic patterns in diversity of plant genetic resources maintained on farm and in species' natural populations in order to enhance their use and conservation. Such evaluations are relevant for useful tropical and subtropical tree species, as many of these species are still undomesticated, or in incipient stages of domestication and local populations can offer yet-unknown traits of high value to further domestication. For many outcrossing species, such as most trees, inbreeding depression can be an issue, and genetic diversity is important to sustain local production. Diversity is also crucial for species to adapt to environmental changes. This paper explores the possibilities of incorporating molecular marker data into Geographic Information Systems (GIS) to allow visualization and better understanding of spatial patterns of genetic diversity as a key input to optimize conservation and use of plant genetic resources, based on a case study of cherimoya (Annona cherimola Mill.), a Neotropical fruit tree species. We present spatial analyses to (1) improve the understanding of spatial distribution of genetic diversity of cherimoya natural stands and cultivated trees in Ecuador, Bolivia and Peru based on microsatellite molecular markers (SSRs); and (2) formulate optimal conservation strategies by revealing priority areas for in situ conservation, and identifying existing diversity gaps in ex situ collections. We found high levels of allelic richness, locally common alleles and expected heterozygosity in cherimoya's putative centre of origin, southern Ecuador and northern Peru, whereas levels of diversity in southern Peru and especially in Bolivia were significantly lower. The application of GIS on a large microsatellite dataset allows a more detailed prioritization of areas for in situ conservation and targeted collection across the Andean distribution range of cherimoya than previous studies could do, i.e. at province and department level in Ecuador and Peru, respectively.
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In the present paper, 1-year PM10 and PM 2.5 data from roadside and urban background monitoring stations in Athens (Greece), Madrid (Spain) and London (UK) are analysed in relation to other air pollutants (NO,NO2,NOx,CO,O3 and SO2)and several meteorological parameters (wind velocity, temperature, relative humidity, precipitation, solar radiation and atmospheric pressure), in order to investigate the sources and factors affecting particulate pollution in large European cities. Principal component and regression analyses are therefore used to quantify the contribution of both combustion and non-combustion sources to the PM10 and PM 2.5 levels observed. The analysis reveals that the EU legislated PM 10 and PM2.5 limit values are frequently breached, forming a potential public health hazard in the areas studied. The seasonal variability patterns of particulates varies among cities and sites, with Athens and Madrid presenting higher PM10 concentrations during the warm period and suggesting the larger relative contribution of secondary and natural particles during hot and dry days. It is estimated that the contribution of non-combustion sources varies substantially among cities, sites and seasons and ranges between 38-67% and 40-62% in London, 26-50% and 20-62% in Athens, and 31-58% and 33-68% in Madrid, for both PM10 and PM 2.5. Higher contributions from non-combustion sources are found at urban background sites in all three cities, whereas in the traffic sites the seasonal differences are smaller. In addition, the non-combustion fraction of both particle metrics is higher during the warm season at all sites. On the whole, the analysis provides evidence of the substantial impact of non-combustion sources on local air quality in all three cities. While vehicular exhaust emissions carry a large part of the risk posed on human health by particle exposure, it is most likely that mitigation measures designed for their reduction will have a major effect only at traffic sites and additional measures will be necessary for the control of background levels. However, efforts in mitigation strategies should always focus on optimal health effects.
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La tomografía axial computerizada (TAC) es la modalidad de imagen médica preferente para el estudio de enfermedades pulmonares y el análisis de su vasculatura. La segmentación general de vasos en pulmón ha sido abordada en profundidad a lo largo de los últimos años por la comunidad científica que trabaja en el campo de procesamiento de imagen; sin embargo, la diferenciación entre irrigaciones arterial y venosa es aún un problema abierto. De hecho, la separación automática de arterias y venas está considerado como uno de los grandes retos futuros del procesamiento de imágenes biomédicas. La segmentación arteria-vena (AV) permitiría el estudio de ambas irrigaciones por separado, lo cual tendría importantes consecuencias en diferentes escenarios médicos y múltiples enfermedades pulmonares o estados patológicos. Características como la densidad, geometría, topología y tamaño de los vasos sanguíneos podrían ser analizados en enfermedades que conllevan remodelación de la vasculatura pulmonar, haciendo incluso posible el descubrimiento de nuevos biomarcadores específicos que aún hoy en dípermanecen ocultos. Esta diferenciación entre arterias y venas también podría ayudar a la mejora y el desarrollo de métodos de procesamiento de las distintas estructuras pulmonares. Sin embargo, el estudio del efecto de las enfermedades en los árboles arterial y venoso ha sido inviable hasta ahora a pesar de su indudable utilidad. La extrema complejidad de los árboles vasculares del pulmón hace inabordable una separación manual de ambas estructuras en un tiempo realista, fomentando aún más la necesidad de diseñar herramientas automáticas o semiautomáticas para tal objetivo. Pero la ausencia de casos correctamente segmentados y etiquetados conlleva múltiples limitaciones en el desarrollo de sistemas de separación AV, en los cuales son necesarias imágenes de referencia tanto para entrenar como para validar los algoritmos. Por ello, el diseño de imágenes sintéticas de TAC pulmonar podría superar estas dificultades ofreciendo la posibilidad de acceso a una base de datos de casos pseudoreales bajo un entorno restringido y controlado donde cada parte de la imagen (incluyendo arterias y venas) está unívocamente diferenciada. En esta Tesis Doctoral abordamos ambos problemas, los cuales están fuertemente interrelacionados. Primero se describe el diseño de una estrategia para generar, automáticamente, fantomas computacionales de TAC de pulmón en humanos. Partiendo de conocimientos a priori, tanto biológicos como de características de imagen de CT, acerca de la topología y relación entre las distintas estructuras pulmonares, el sistema desarrollado es capaz de generar vías aéreas, arterias y venas pulmonares sintéticas usando métodos de crecimiento iterativo, que posteriormente se unen para formar un pulmón simulado con características realistas. Estos casos sintéticos, junto a imágenes reales de TAC sin contraste, han sido usados en el desarrollo de un método completamente automático de segmentación/separación AV. La estrategia comprende una primera extracción genérica de vasos pulmonares usando partículas espacio-escala, y una posterior clasificación AV de tales partículas mediante el uso de Graph-Cuts (GC) basados en la similitud con arteria o vena (obtenida con algoritmos de aprendizaje automático) y la inclusión de información de conectividad entre partículas. La validación de los fantomas pulmonares se ha llevado a cabo mediante inspección visual y medidas cuantitativas relacionadas con las distribuciones de intensidad, dispersión de estructuras y relación entre arterias y vías aéreas, los cuales muestran una buena correspondencia entre los pulmones reales y los generados sintéticamente. La evaluación del algoritmo de segmentación AV está basada en distintas estrategias de comprobación de la exactitud en la clasificación de vasos, las cuales revelan una adecuada diferenciación entre arterias y venas tanto en los casos reales como en los sintéticos, abriendo así un amplio abanico de posibilidades en el estudio clínico de enfermedades cardiopulmonares y en el desarrollo de metodologías y nuevos algoritmos para el análisis de imágenes pulmonares. ABSTRACT Computed tomography (CT) is the reference image modality for the study of lung diseases and pulmonary vasculature. Lung vessel segmentation has been widely explored by the biomedical image processing community, however, differentiation of arterial from venous irrigations is still an open problem. Indeed, automatic separation of arterial and venous trees has been considered during last years as one of the main future challenges in the field. Artery-Vein (AV) segmentation would be useful in different medical scenarios and multiple pulmonary diseases or pathological states, allowing the study of arterial and venous irrigations separately. Features such as density, geometry, topology and size of vessels could be analyzed in diseases that imply vasculature remodeling, making even possible the discovery of new specific biomarkers that remain hidden nowadays. Differentiation between arteries and veins could also enhance or improve methods processing pulmonary structures. Nevertheless, AV segmentation has been unfeasible until now in clinical routine despite its objective usefulness. The huge complexity of pulmonary vascular trees makes a manual segmentation of both structures unfeasible in realistic time, encouraging the design of automatic or semiautomatic tools to perform the task. However, this lack of proper labeled cases seriously limits in the development of AV segmentation systems, where reference standards are necessary in both algorithm training and validation stages. For that reason, the design of synthetic CT images of the lung could overcome these difficulties by providing a database of pseudorealistic cases in a constrained and controlled scenario where each part of the image (including arteries and veins) is differentiated unequivocally. In this Ph.D. Thesis we address both interrelated problems. First, the design of a complete framework to automatically generate computational CT phantoms of the human lung is described. Starting from biological and imagebased knowledge about the topology and relationships between structures, the system is able to generate synthetic pulmonary arteries, veins, and airways using iterative growth methods that can be merged into a final simulated lung with realistic features. These synthetic cases, together with labeled real CT datasets, have been used as reference for the development of a fully automatic pulmonary AV segmentation/separation method. The approach comprises a vessel extraction stage using scale-space particles and their posterior artery-vein classification using Graph-Cuts (GC) based on arterial/venous similarity scores obtained with a Machine Learning (ML) pre-classification step and particle connectivity information. Validation of pulmonary phantoms from visual examination and quantitative measurements of intensity distributions, dispersion of structures and relationships between pulmonary air and blood flow systems, show good correspondence between real and synthetic lungs. The evaluation of the Artery-Vein (AV) segmentation algorithm, based on different strategies to assess the accuracy of vessel particles classification, reveal accurate differentiation between arteries and vein in both real and synthetic cases that open a huge range of possibilities in the clinical study of cardiopulmonary diseases and the development of methodological approaches for the analysis of pulmonary images.
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The Mycetozoa include the cellular (dictyostelid), acellular (myxogastrid), and protostelid slime molds. However, available molecular data are in disagreement on both the monophyly and phylogenetic position of the group. Ribosomal RNA trees show the myxogastrid and dictyostelid slime molds as unrelated early branching lineages, but actin and β-tubulin trees place them together as a single coherent (monophyletic) group, closely related to the animal–fungal clade. We have sequenced the elongation factor-1α genes from one member of each division of the Mycetozoa, including Dictyostelium discoideum, for which cDNA sequences were previously available. Phylogenetic analyses of these sequences strongly support a monophyletic Mycetozoa, with the myxogastrid and dictyostelid slime molds most closely related to each other. All phylogenetic methods used also place this coherent Mycetozoan assemblage as emerging among the multicellular eukaryotes, tentatively supported as more closely related to animals + fungi than are green plants. With our data there are now three proteins that consistently support a monophyletic Mycetozoa and at least four that place these taxa within the “crown” of the eukaryote tree. We suggest that ribosomal RNA data should be more closely examined with regard to these questions, and we emphasize the importance of developing multiple sequence data sets.
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Here we study the effect of point mutations in proteins on the redistributions of the conformational substates. We show that regardless of the location of a mutation in the protein structure and of its type, the observed movements of the backbone recur largely at the same positions in the structures. Despite the different interactions that are disrupted and formed by the residue substitution, not only are the conformations very similar, but the regions that move are also the same, regardless of their sequential or spatial distance from the mutation. This observation leads us to conclude that, apart from some extreme cases, the details of the interactions are not critically important in determining the protein conformation or in specifying which parts of the protein would be more prone to take on different local conformations in response to changes in the sequence. This finding further illustrates why proteins manifest a robustness toward many mutational events. This nonuniform distribution of the conformer population is consistently observed in a variety of protein structural types. Topology is critically important in determining folding pathways, kinetics, building block cutting, and anatomy trees. Here we show that topology is also very important in determining which regions of the protein structure will respond to sequence changes, regardless of the sequential or spatial location of the mutation.
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Members of the lipoxygenase multigene family, found widely in eukaryotes, have been proposed to function in nitrogen partitioning and storage in plants. Lipoxygenase gene responses to source-sink manipulations in mature soybean (Glycine max [L.] Merr.) leaves were examined using gene-specific riboprobes to the five vegetative lipoxygenases (vlxA–vlxE). Steady-state levels of all vlx mRNAs responded strongly to sink limitation, but specific transcripts exhibited differential patterns of response as well. During reproductive sink limitation, vlxA and vlxB messages accumulated to high levels, whereas vlxC and vlxD transcript levels were modest. Immunolocalization using peptide-specific antibodies demonstrated that under control conditions, VLXB was present in the cytosol of the paraveinal mesophyll and with pod removal accumulated additionally in the bundle-sheath and adjacent cells. With sink limitation VLXD accumulated to apparent high levels in the vacuoles of the same cells. Segregation of gene products at the cellular and subcellular levels may thus permit complex patterns of differential regulation within the same cell type. Specific lipoxygenase isoforms may have a role in short-term nitrogen storage (VLXC/D), whereas others may simultaneously function in assimilate partitioning as active enzymes (VLXA/B).
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Fructans play an important role in assimilate partitioning and possibly in stress tolerance in many plant families. Sucrose:fructan 6-fructosyltransferase (6-SFT), an enzyme catalyzing the formation and extension of beta-2,6-linked fructans typical of grasses, was purified from barley (Hordeum vulgare L.). It occurred in two closely similar isoforms with indistinguishable catalytic properties, both consisting of two subunits with apparent masses of 49 and 23 kDa. Oligonucleotides, designed according to the sequences of tryptic peptides from the large subunit, were used to amplify corresponding sequences from barley cDNA. The main fragment generated was cloned and used to screen a barley cDNA expression library. The longest cDNA obtained was transiently expressed in Nicotiana plumbaginifolia protoplasts and shown to encode a functional 6-SFT. The deduced amino acid sequence of the cDNA comprises both subunits of 6-SFT. It has high similarity to plant invertases and other beta-fructosyl hydrolases but only little to bacterial fructosyltransferases catalyzing the same type of reaction as 6-SFT.
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Expansins are unusual proteins discovered by virtue of their ability to mediate cell wall extension in plants. We identified cDNA clones for two cucumber expansins on the basis of peptide sequences of proteins purified from cucumber hypocotyls. The expansin cDNAs encode related proteins with signal peptides predicted to direct protein secretion to the cell wall. Northern blot analysis showed moderate transcript abundance in the growing region of the hypocotyl and no detectable transcripts in the nongrowing region. Rice and Arabidopsis expansin cDNAs were identified from collections of anonymous cDNAs (expressed sequence tags). Sequence comparisons indicate at least four distinct expansin cDNAs in rice and at least six in Arabidopsis. Expansins are highly conserved in size and sequence (60-87% amino acid sequence identity and 75-95% similarity between any pairwise comparison), and phylogenetic trees indicate that this multigene family formed before the evolutionary divergence of monocotyledons and dicotyledons. Sequence and motif analyses show no similarities to known functional domains that might account for expansin action on wall extension. A series of highly conserved tryptophans may function in expansin binding to cellulose or other glycans. The high conservation of this multigene family indicates that the mechanism by which expansins promote wall extensin tolerates little variation in protein structure.
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Author: Charity M. Walker Title: THE IMPACT OF SHYNESS ON LONELINESS, SOCIAL ANXIETY, AND SCHOOL LIKING IN LATE CHILDHOOD Advisor: Maria T. Riva, Ph.D. Degree Date: August 2011 ABSTRACT Shyness is associated with several emotional, social, and academic problems. While there are multiple difficulties that often accompany shyness, there appear to be some factors that can moderate negative effects of shyness. Research has demonstrated that certain parenting factors affect the adjustment of shy children in early childhood, but there is minimal research illuminating the effect of parenting factors in older age groups. The first purpose of this study was to examine relationships between shyness and loneliness, social anxiety, and school liking. The second purpose was to investigate whether the quality of the relationship between a parent and a 10- to 15-year-olds child influences the amount of loneliness or social anxiety a shy child experiences or how the child feels about school. Parent-child dyads served as participants and were recruited from public and private middle schools and church youth groups in Colorado and Indiana. Child participants completed several self-report surveys regarding their relationship with a parent, shyness, loneliness, social anxiety, and their attitude toward school. Parents completed a survey about their relationship with their child and responded to questions related to their perceptions of their child's shyness. Data was analyzed with a series of correlation and regression analyses. Greater degrees of self-reported shyness were found to be associated with higher levels of loneliness and social anxiety and less positive feelings about school. Due to a problem with multicollinearity during data analysis, this study was not able to explore the effect of the parent-child relationship quality on the associations between shyness and adjustment factors. Overall, these findings imply that shyness remains an important issue as children approach adolescence. Further research is needed to continue learning about the potential importance of parent-child interactions in reducing maladjustment for shy children during late childhood.
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No estudo das comunidades florestais, estabelecer a importância relativa dos fatores que definem a composição e a distribuição das espécies é um desafio. Em termos de gradientes ambientais o estudo das respostas das espécies arbóreas são essenciais para a compreensão dos processos ecológicos e decisões de conservação. Neste sentido, para contribuir com a elucidação dos processos ecológicos nas principais formações florestais do Estado de São Paulo (Floresta Ombrófila Densa de Terras Baixas, Floresta Ombrófila Densa Submontana, Floresta Estacional Semidecidual e Savana Florestada) este trabalho objetivou responder as seguintes questões: (I) a composição florística e a abundância das espécies arbóreas, em cada unidade fitogeográfica, variam conforme o gradiente edáfico e topográfico?; (II) características do solo e topografia podem influenciar na previsibilidade de ocorrência de espécies arbóreas de ampla distribuição em diferentes tipos vegetacionais? (III) existe relação entre o padrão de distribuição espacial de espécies arbóreas e os parâmetros do solo e topografia? O trabalho foi realizado em parcelas alocadas em unidades de conservação (UC) que apresentaram trechos representativos, em termos de conservação e tamanho, das quatro principais formações florestais presentes no Estado de São Paulo. Em cada UC foram contabilizados os indivíduos arbóreos (CAP ≥ 15 cm), topografia, dados de textura e atributos químicos dos solos em uma parcela de 10,24 ha, subdividida em 256 subparcelas. Análises de correspodência canônica foram aplicadas para estabelecer a correspondência entre a abundância das espécies e o gradiente ambiental (solo e topografia). O método TWINSPAN modificado foi aplicado ao diagrama de ordenação da CCA para avaliar a influência das variáveis ambientais (solo e topografia) na composição de espécies. Árvores de regressão \"ampliadas\" (BRT) foram ajustadas para a predição da ocorrência das espécies segundo as variáveis de solo e topografia. O índice de Getis-Ord (G) foi utilizado para determinar a autocorrelação espacial das variáveis ambientais utilizadas nos modelos de predição da ocorrência das espécies. Nas unidades fitogeográficas analisadas, a correspondência entre o gradiente ambiental (solo e topografia) e a abundância das espécies foi significativa, especialmente na Savana Florestada onde observou-se a maior relação. O solo e a topografia também se relacionaram com a semelhança na composição florística das subparcelas, com exceção da Floresta Estacional Semicidual (EEC). As principais variáveis de solo e topografia relacionadas a flora em cada UC foram: (1) Na Floresta Ombrófila Densa de Terras Baixas (PEIC) - teor de alumínio na camada profunda (Al (80-100 cm)) que pode refletir os teor de Al na superfície, acidez do solo (pH(H2O) (5-25 cm)) e altitude, que delimitou as áreas alagadas; (2) Na Floresta Ombrófila Densa Submontana (PECB) - altitude, fator que, devido ao relevo acidentado, influencia a temperatura e incidência de sol no sub-bosque; (3) Na Savana Florestada (EEA) - fertilidade, tolerância ao alumínio e acidez do solo. Nos modelos de predição BRT, as variáveis químicas dos solos foram mais importantes do que a textura, devido à pequena variação deste atributo no solo nas áreas amostradas. Dentre as variáveis químicas dos solos, a capacidade de troca catiônica foi utilizada para prever a ocorrência das espécies nas quatro formações florestais, sendo particularmente importante na camada mais profunda do solo da Floresta Ombrófila Densa de Terras Baixas (PEIC). Quanto à topografia, a altitude foi inserida na maioria dos modelos e apresentou diferentes influências sobre as áreas de estudo. De modo geral, para presença das espécies de ampla distribuição observou-se uma mesma tendência quando à associação com os atributos dos solos, porém com amplitudes dos descritores edáficos que variaram de acordo com a área de estudo. A ocorrência de Guapira opposita e Syagrus romanzoffiana, cujo padrão variou conforme a escala, foi explicada por variáveis com padrões espaciais agregados que somaram entre 30% e 50% de importância relativa no modelo BRT. A presença de A. anthelmia, cujo padrão também apresentou certo nível de agregação, foi associada apenas a uma variável com padrão agregado, a altitude (21%), que pode ter exercido grande influência na distribuição da espécie ao delimitar áreas alagadas. T. guianensis se associou a variáveis ambientais preditoras com padrão espacial agregado que somaram cerca de 70% de importância relativa, o que deve ter sido suficiente para estabelecer o padrão agregado em todas as escalas. No entanto, a influência dos fatores ambientais no padrão de distribuição da espécie não depende apenas do ótimo ambiental da espécie, mas um resultado da interação espécie-ambiente. Concluiu-se que: (I) características edáficas e topográficas explicaram uma pequena parcela da composição florística, em cada unidade fitogeográfica, embora a ocorrência de algumas espécies tenha se associado ao gradiente edáfico e topográfico; (II) a partir de características dos solos e da topografia foi possível prever a presença de espécies arbóreas, que apresentaram particularidades em relação a sua associação com o solo de cada fitofisionomia; (III) a partir de associações descritivas o solo e a topografia influenciam o padrão de distribuição espacial das espécies, na proporção em que contribuem para a presença das mesmas.
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One of the main challenges in biological conservation has been to understand species distribution across space and time. Over the last decades, many diversity and conservation surveys have been conducted that have revealed that habitat heterogeneity acts as a major factor that determines saproxylic assemblages. However, temporal dynamics have been poorly studied, especially in Mediterranean forests. We analyzed saproxylic beetle distribution at inter and intra-annual scales in a “dehesa” ecosystem, which is a traditional Iberian agrosilvopastoral ecosystem that is characterized by the presence of old and scattered trees that dominate the landscape. Significant differences in effective numbers of families/species and species richness were found at the inter-annual scale, but this was not the case for composition. Temperature and relative humidity did not explain these changes which were mainly due to the presence of rare species. At the intra-annual scale, significant differences in the effective numbers of families/species, species richness and composition between seasons were found, and diversity partitioning revealed that season contributed significantly to gamma-diversity. Saproxylic beetle assemblages exhibited a marked seasonality in richness but not in abundance, with two peaks of activity, the highest between May and June, and the second between September and October. This pattern is mainly driven by the seasonality of the climate in the Mediterranean region, which influences ecosystem dynamics and imposes a marked seasonality on insect assemblages. An extended sampling period over different seasons allowed an overview of saproxylic dynamics, and revealed which families/species were restricted to particular seasons. Recognizing that seasons act as a driver in modelling saproxylic beetle assemblages might be a valuable tool in monitoring and for conservation strategies in Mediterranean forests.