Genetic diversity and population structure of Brazilian native bovine breeds

Conservation and improvement strategies should be based on the association between genetic and phenotypic characteristics. The objective of this work was to characterize five native Brazilian cattle breeds (Caracu, Crioulo Lageano, Curraleiro, National Polled and Pantaneiro) and two commercial breeds (Holstein and Nellore) using RAPD technique to estimate genetic distances and variability between and within breeds. Genetic relationships were investigated using 22 primers which generated 122 polymorphic bands. Analysis of molecular variance indicated that most of the genetic variation lay among individuals within populations. The genetic variabilities between pairs of breeds were statistically significant. The smallest genetic divergence was between Crioulo Lageano and Curraleiro.The National Polled, although historically considered to be of Bos taurus aquitanicus origin,similar to theCaracu, was grouped together with the other breeds of Bos taurus ibericus origin. Generally, the individual breeds formed distinct clusters except the National Polled. The RAPD technique was capable to distinguish genetically between the breeds studied; the Caracu, Crioulo Lageano, Curraleiro and Pantaneiro may be considered distinct genetic entities thereby proving the uniqueness of the populations; the National Polled has not been able to re-establish itself after its decline in the 1950s, thereby losing its genetic identity.

Genetic and karyotypic structure of a hybrid zone between the chromosomal races Cordon and Valais in the common shrew, Sorex araneus

Hybrid zones between genetically differentiated populations provide material to study evolutionary processes. Since the discovery of chromosomal races in Sorex araneus, contact zones have attracted attention of scientists. So far, studies on genetic markers in Sorex hybrid zones are missing. The acrocentric chromosomal race Cordon and the highly metacentric race Valais meet and hybridize at Les Houches in the Western Alps. On a transect through the hybrid zone, 273 shrews were caught at 15 localities over 4 years. Karyotype as well as the nuclear protein loci Alb and Pg were analyzed. F-st and F-is values were calculated by F-statistics. An analysis on pooled samples revealed the genetical differences between the hybridizing races as the only cause of population structuring. Genetical markers show dines with very strong frequency shifts at a mountain torrent, but behave differently through the zone. The performance of the torrent in maintaining the hybrid zone, selection against hybrids, possible assortative mating and linkage of the Valais Pg allele to a diagnostic chromosome arm, are discussed.

Genetic improvement and population structure of the Nelore breed in Northern Brazil

The objective of this work was to evaluate the population structure and the genetic and phenotypic progress of Nelore cattle in Northern Brazil. Pedigree information concerning animals born between 1942 and 2006 were analyzed. Population structure was performed using the Endog program. Out of the 140,628 animals studied, 67.7, 14.52 and 3.18% had complete pedigree record of the first, second and third parental generation, respectively. Inbreeding and average relatedness coefficients were low: 0.2 and 0.13%, respectively. However, these parameters may have been underestimated, since information on pedigree was incomplete. The effective number of founders was 370 and the genetic contribution of 10, 50 and 448 most influent ancestors explained 13.2, 28 and 50% of the genetic variability in the population, respectively. The genetic variability for growth traits and population structure demonstrates high probability of increasing productivity through selective breeding. Moreover, management strategies to reduce the currently observed age at first calving and generation intervals are important for Nelore cattle genetic improvement.

GENETIC DIVERSITY AND STRUCTURE OF Oenocarpus mapora GERMPLASM CONSERVED AT EASTERN AMAZON

ABSTRACT The aim of this study was to evaluate the genetic diversity and structure in the germoplasm of Oenocarpus mapora conserved at Eastern Amazon. Thus, 88 individuals were genotyped with five microsatellite loci. These individuals belong to 24 accessions that were sampled in eight sample places of three Brazilian Amazon states conserved at the Active Germplasm Bank (AGB) of Embrapa Eastern Amazon. All loci were polymorphic and they generated 85 alleles with an average of 17 alleles per loci. Total genetic diversity (HE) was 0.48. Sample places were considered genetically distinct, with ?p = 0.354. The analysis of molecular variance (AMOVA) identified that the genetic portion among areas was of 36.14% and within 63.86%. The Nei distances varied from 0.091 between Abaetetuba and Santo Antônio do Tauá, both in the state of Pará (PA), to 4.18, between Parintins, AM and Rio Branco, AC. By means of Bayesian analysis, it was identified nine clusters that compose the accessions of the germplasm bank, with different distributions among individuals. The study showed high fixation rates per sample area, which indicates that there may have been significant inbreeding or crossing among parental individuals. It suggests that future samples should be made of different plants in natural populations. Even though, it was verified that there is considerable genetic variation in the germplasm of O. mapora.

POPULATION STRUCTURE AND SPATIAL DISTRIBUTION OF Bauhinia cheilantha (Bong.) Steud. IN TWO FRAGMENTS AT DIFFERENT REGENERATION STAGES IN THE CAATINGA, IN SERGIPE, BRAZIL

ABSTRACTThis study aimed to analyze the vertical and diameter structure and the spatial distribution pattern of Bauhinia cheilantha in two Caatinga fragments in Sergipe, Brazil, at different regeneration stages. Thirty plots were demarcated in area I (Canindé de São Francisco and Poço Redondo), which has vegetation regeneration, and 25 plots in area II (Porto da Folha) with preserved vegetation, both having 400 m2. All B. cheilanthaindividuals had their height and circumference (circumference at breast height > 6 cm) measured. Possible differences in height and diameter at breast height were tested in the two populations by using Student’s T-test. The distribution pattern of species was calculated through Payandeh’s index. We sampled 154 B. cheilantha individuals, equivalent to 33.3% of the plots in area I and in 1,027 individuals in area II, totaling 100% frequency. Height and the diameter of the two populations were statistically different, where AI achieved all values lower than AII. The spatial distribution pattern of B. cheilantha found in both areas was aggregate, with values of 11.85 and 9.00, respectively. Thus, it became clear that the population in AII is at a more advanced successional status than AI, due to its longer conservation time.

Temporal and spatial variations in the structure of macroalgal communities associated with mangrove trees of Ilha do Cardoso, São Paulo state, Brazil

Temporal and spatial variations in species composition and vertical distribution of macroalgal communities growing on mangrove trees were analyzed bimonthly in the Ilha do Cardoso State Park, São Paulo state (25°03'S and 47°55'W), Southeastern Brazil. The macroalgal communities from mangroves of Perequê and Sítio Grande rivers comprised 10 and 18 taxa respectively. Bostrychia radicans (Mont.) Mont. and B. calliptera (Mont.) Mont. were the predominant taxa, present almost throughout the year and in all the sites studied. The species composition of macroalgal communities from both mangroves presented temporal and spatial variations related to environmental factors. The highest number of taxa was observed during colder, drier months, coinciding with the highest means of high water neap and short periods of continuous emersion (April to August). Some mangrove algae such as B. calliptera, Rhizoclonium spp., Caloglossa spp., and Boodleopsis pusilla (Collins) W. Taylor, Joly et Bernatowicz showed a high degree of tolerance to desiccation, being able to tolerate continuous emersion up to six days. The spatial variations in species composition were related to light, as observed in Catenella caespitosa (Withering) L. Irvine, which occurred in well-lit sites. No pattern of vertical zonation was observed, since Rhizoclonium spp., B. radicans, and B. calliptera occur over the entire vertical range. Variations in the range of vertical distribution of macroalgae of Perequê mangrove were mainly related to the variations in the tidal levels (mean high water neap and/or mean high water spring) while those observed in Sítio Grande mangrove were related to salinity variations, except for B. calliptera and Caloglossa spp. related to tidal levels and high irradiance, respectively.

Spatial variation in the structure and floristic composition of "restinga" vegetation in southeastern Brazil

We examined large-scale spatial variation of structural parameters and floristic composition in open Clusia scrub, a vegetation type of the Brazilian "restingas" (sandy coastal plain vegetation). This vegetation is organized in islands separated by sandy stretches with sparse herbaceous vegetation. We located 12 sample areas on three consecutive beach ridges, lying parallel to the coastline and at different distances from the ocean, in close proximity to two lagoons (Cabiúnas and Comprida). Each sample area was divided into three strips. We used the line intercept method to sample all woody plants ³ 50 cm tall. We used nested ANOVA to verify structural variation between different sampling scales. TWINSPAN analysis was performed to examine the variation in floristic composition between areas. The overall diversity index was 3.07. Six species are repeatedly dominant throughout the entire sampling area. There was homogeneity in relation to diversity and species richness between beach ridges but not within beach ridges. Floristic composition and structural parameters did not vary in relation to distance from the sea but floristic composition did vary as a function of proximity to Cabiúnas or Comprida lagoon. Differences in plant cover between sample areas may be related to the paleoformation of this sandy coastal plain.

Automatic Structure Generation using Genetic Programming and Fractal Geometry

Three dimensional model design is a well-known and studied field, with numerous real-world applications. However, the manual construction of these models can often be time-consuming to the average user, despite the advantages o ffered through computational advances. This thesis presents an approach to the design of 3D structures using evolutionary computation and L-systems, which involves the automated production of such designs using a strict set of fitness functions. These functions focus on the geometric properties of the models produced, as well as their quantifiable aesthetic value - a topic which has not been widely investigated with respect to 3D models. New extensions to existing aesthetic measures are discussed and implemented in the presented system in order to produce designs which are visually pleasing. The system itself facilitates the construction of models requiring minimal user initialization and no user-based feedback throughout the evolutionary cycle. The genetic programming evolved models are shown to satisfy multiple criteria, conveying a relationship between their assigned aesthetic value and their perceived aesthetic value. Exploration into the applicability and e ffectiveness of a multi-objective approach to the problem is also presented, with a focus on both performance and visual results. Although subjective, these results o er insight into future applications and study in the fi eld of computational aesthetics and automated structure design.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and deterministic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel metaheuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS metaheuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Feature Selection and Classification Using Age Layered Population Structure Genetic Programming

The curse of dimensionality is a major problem in the fields of machine learning, data mining and knowledge discovery. Exhaustive search for the most optimal subset of relevant features from a high dimensional dataset is NP hard. Sub–optimal population based stochastic algorithms such as GP and GA are good choices for searching through large search spaces, and are usually more feasible than exhaustive and determinis- tic search algorithms. On the other hand, population based stochastic algorithms often suffer from premature convergence on mediocre sub–optimal solutions. The Age Layered Population Structure (ALPS) is a novel meta–heuristic for overcoming the problem of premature convergence in evolutionary algorithms, and for improving search in the fitness landscape. The ALPS paradigm uses an age–measure to control breeding and competition between individuals in the population. This thesis uses a modification of the ALPS GP strategy called Feature Selection ALPS (FSALPS) for feature subset selection and classification of varied supervised learning tasks. FSALPS uses a novel frequency count system to rank features in the GP population based on evolved feature frequencies. The ranked features are translated into probabilities, which are used to control evolutionary processes such as terminal–symbol selection for the construction of GP trees/sub-trees. The FSALPS meta–heuristic continuously refines the feature subset selection process whiles simultaneously evolving efficient classifiers through a non–converging evolutionary process that favors selection of features with high discrimination of class labels. We investigated and compared the performance of canonical GP, ALPS and FSALPS on high–dimensional benchmark classification datasets, including a hyperspectral image. Using Tukey’s HSD ANOVA test at a 95% confidence interval, ALPS and FSALPS dominated canonical GP in evolving smaller but efficient trees with less bloat expressions. FSALPS significantly outperformed canonical GP and ALPS and some reported feature selection strategies in related literature on dimensionality reduction.

Spatial and Temporal Variation of Microbial Community Structure In Surficial Sediments of Cochin Estuary

This thesis entitled spatial and temporal variarion of microbial community structure in surficial sediments of cochin estuary.In the estuarine and coastal systems, organic matter (OM) is derived not only from autochthonous primary production, but also from allochthonous (terrestrial) organic matter (OM) delivered by river discharge and runoff. A significant portion of the OM sinks through the water column and is ultimately stored in carbon pool in the sediments.Analysis of spatial and temporal variation in benthic microbial community of a tropical estuary was conducted for the first time using non selective measures that affirms that PLFA approach is a sensitive and reliable method in determining microbial community structures of surficial sediments of estuary.The close relationship between the concentrations of the microbial fatty acids and total biomass indicates that bacteria could account for the largest proportion of the biomass in the sediments.This is first study that has documented the changes in microbial community composition linkage to biotic and abiotic variables in benthic estuarine ecosystem. This contemporaneous community will be the backdrop for understanding the response of autochthonous community to increasing anthropogenic stress.

A singular vector perspective of 4DVAR: The spatial structure and evolution of baroclinic weather systems

The extent to which the four-dimensional variational data assimilation (4DVAR) is able to use information about the time evolution of the atmosphere to infer the vertical spatial structure of baroclinic weather systems is investigated. The singular value decomposition (SVD) of the 4DVAR observability matrix is introduced as a novel technique to examine the spatial structure of analysis increments. Specific results are illustrated using 4DVAR analyses and SVD within an idealized 2D Eady model setting. Three different aspects are investigated. The first aspect considers correcting errors that result in normal-mode growth or decay. The results show that 4DVAR performs well at correcting growing errors but not decaying errors. Although it is possible for 4DVAR to correct decaying errors, the assimilation of observations can be detrimental to a forecast because 4DVAR is likely to add growing errors instead of correcting decaying errors. The second aspect shows that the singular values of the observability matrix are a useful tool to identify the optimal spatial and temporal locations for the observations. The results show that the ability to extract the time-evolution information can be maximized by placing the observations far apart in time. The third aspect considers correcting errors that result in nonmodal rapid growth. 4DVAR is able to use the model dynamics to infer some of the vertical structure. However, the specification of the case-dependent background error variances plays a crucial role.