Rastreabilidade de camarão amazônico proveniente de cultivo e ambiente natural utilizando a técnica de isótopos estáveis

Pós-graduação em Aquicultura - FCAV

The occurrence of UV filters in natural and drinking water in São Paulo State (Brazil)

Ultraviolet (UV) filters are widely used in the formulation of personal care products (PCPs) to prevent damage to the skin, lips, and hair caused by excessive UV radiation. Therefore, large amounts of these substances are released daily into the aquatic environment through either recreational activities or the release of domestic sewage. The concern regarding the presence of such substances in the environment and the exposure of aquatic organisms is based on their potential for bioaccumulation and their potential as endocrine disruptors. Although there are several reports regarding the occurrence and fate of UV filters in the aquatic environment, these compounds are still overlooked in tropical areas. In this study, we investigated the occurrence of the organic UV filters benzophenone-3 (BP-3), ethylhexyl salicylate (ES), ethylhexyl methoxycinnamate (EHMC), and octocrylene (OC) in six water treatment plants in various cities in Southeast Brazil over a period of 6 months to 1 year. All of the UV filters studied were detected at some time during the sampling period; however, only EHMC and BP-3 were found in quantifiable concentrations, ranging from 55 to 101 and 18 to 115 ng L(-1), respectively. Seasonal variation of BP-3 was most clearly noticed in the water treatment plant in Araraquara, São Paulo, where sampling was performed for 12 months. BP-3 was not quantifiable in winter but was quantifiable in summer. The levels of BP-3 were in the same range in raw, treated and chlorinated water, indicating that the compound was not removed by the water treatment process.

Diversity and genetic structure in natural populations of Hancornia speciosa var. speciosa Gomes in northeastern Brazil

Hancornia speciosa Gomes is a fruit tree native from Brazil that belongs to Apocinaceae family, and is popularly known as Mangabeira. Its fruits are widely consumed raw or processed as fruit jam, juices and ice creams, which have made it a target of intense exploitation. The extractive activities and intense human activity on the environment of natural occurrence of H. speciosa has caused genetic erosion in the species and little is known about the ecology or genetic structure of natural populations. The objective of this research was the evaluation of the genetic diversity and genetic structure of H. speciosa var. speciosa. The genetic variability was assessed using 11 allozyme loci with a sample of 164 individuals distributed in six natural populations located in the States of Pernambuco and Alagoas, Northeastern Brazil. The results showed a high level of genetic diversity within the species (e= 0.36) seeing that the most of the genetic variability of H. speciosa var. speciosa is within its natural populations with low difference among populations ( or = 0.081). The inbreeding values within ( = -0.555) and among populations ( =-0.428) were low showing lacking of endogamy and a surplus of heterozygotes. The estimated gene flow ( m ) was high, ranging from 2.20 to 13.18, indicating to be enough to prevent the effects of genetic drift and genetic differentiation among populations. The multivariate analyses indicated that there is a relationship between genetic and geographical distances, which was confirmed by a spatial pattern analysis using Mantel test (r = 0.3598; p = 0.0920) with 1000 random permutations. The high genetic diversity index in these populations indicates potential for in situ genetic conservation.

BAYESIAN STATISTICAL METHODS IN GENE-ENVIRONMENT AND GENE-GENE INTERACTION STUDIES

Complex diseases such as cancer result from multiple genetic changes and environmental exposures. Due to the rapid development of genotyping and sequencing technologies, we are now able to more accurately assess causal effects of many genetic and environmental factors. Genome-wide association studies have been able to localize many causal genetic variants predisposing to certain diseases. However, these studies only explain a small portion of variations in the heritability of diseases. More advanced statistical models are urgently needed to identify and characterize some additional genetic and environmental factors and their interactions, which will enable us to better understand the causes of complex diseases. In the past decade, thanks to the increasing computational capabilities and novel statistical developments, Bayesian methods have been widely applied in the genetics/genomics researches and demonstrating superiority over some regular approaches in certain research areas. Gene-environment and gene-gene interaction studies are among the areas where Bayesian methods may fully exert its functionalities and advantages. This dissertation focuses on developing new Bayesian statistical methods for data analysis with complex gene-environment and gene-gene interactions, as well as extending some existing methods for gene-environment interactions to other related areas. It includes three sections: (1) Deriving the Bayesian variable selection framework for the hierarchical gene-environment and gene-gene interactions; (2) Developing the Bayesian Natural and Orthogonal Interaction (NOIA) models for gene-environment interactions; and (3) extending the applications of two Bayesian statistical methods which were developed for gene-environment interaction studies, to other related types of studies such as adaptive borrowing historical data. We propose a Bayesian hierarchical mixture model framework that allows us to investigate the genetic and environmental effects, gene by gene interactions (epistasis) and gene by environment interactions in the same model. It is well known that, in many practical situations, there exists a natural hierarchical structure between the main effects and interactions in the linear model. Here we propose a model that incorporates this hierarchical structure into the Bayesian mixture model, such that the irrelevant interaction effects can be removed more efficiently, resulting in more robust, parsimonious and powerful models. We evaluate both of the 'strong hierarchical' and 'weak hierarchical' models, which specify that both or one of the main effects between interacting factors must be present for the interactions to be included in the model. The extensive simulation results show that the proposed strong and weak hierarchical mixture models control the proportion of false positive discoveries and yield a powerful approach to identify the predisposing main effects and interactions in the studies with complex gene-environment and gene-gene interactions. We also compare these two models with the 'independent' model that does not impose this hierarchical constraint and observe their superior performances in most of the considered situations. The proposed models are implemented in the real data analysis of gene and environment interactions in the cases of lung cancer and cutaneous melanoma case-control studies. The Bayesian statistical models enjoy the properties of being allowed to incorporate useful prior information in the modeling process. Moreover, the Bayesian mixture model outperforms the multivariate logistic model in terms of the performances on the parameter estimation and variable selection in most cases. Our proposed models hold the hierarchical constraints, that further improve the Bayesian mixture model by reducing the proportion of false positive findings among the identified interactions and successfully identifying the reported associations. This is practically appealing for the study of investigating the causal factors from a moderate number of candidate genetic and environmental factors along with a relatively large number of interactions. The natural and orthogonal interaction (NOIA) models of genetic effects have previously been developed to provide an analysis framework, by which the estimates of effects for a quantitative trait are statistically orthogonal regardless of the existence of Hardy-Weinberg Equilibrium (HWE) within loci. Ma et al. (2012) recently developed a NOIA model for the gene-environment interaction studies and have shown the advantages of using the model for detecting the true main effects and interactions, compared with the usual functional model. In this project, we propose a novel Bayesian statistical model that combines the Bayesian hierarchical mixture model with the NOIA statistical model and the usual functional model. The proposed Bayesian NOIA model demonstrates more power at detecting the non-null effects with higher marginal posterior probabilities. Also, we review two Bayesian statistical models (Bayesian empirical shrinkage-type estimator and Bayesian model averaging), which were developed for the gene-environment interaction studies. Inspired by these Bayesian models, we develop two novel statistical methods that are able to handle the related problems such as borrowing data from historical studies. The proposed methods are analogous to the methods for the gene-environment interactions on behalf of the success on balancing the statistical efficiency and bias in a unified model. By extensive simulation studies, we compare the operating characteristics of the proposed models with the existing models including the hierarchical meta-analysis model. The results show that the proposed approaches adaptively borrow the historical data in a data-driven way. These novel models may have a broad range of statistical applications in both of genetic/genomic and clinical studies.

On the onset of turbulence in natural convection on inclined plates

The problem of determination of the turbulence onset in natural convection on heated inclined plates in an air environment has been experimentally revisited. The transition has been detected by using hot wire velocity measurements. The onset of turbulence has been considered to take place where velocity fluctuations (measured through turbulence intensity) start to grow. Experiments have shown that the onset depends not only on the Grashof number defined in terms of the temperature difference between the heated plate and the surrounding air. A correlation between dimensionless Grashof and Reynolds numbers has been obtained, fitting quite well the experimental data.

Land use modelling and the role of stakeholders in natural protected areas: the case of Doñana national park, Spain

Doñana, a National Park since 1969, a UNESCO site since 1994 among other protected area designations of national and international character, is a coastal dune and marshland ecosystem of outstanding importance for biodiversity and conservation at the mouth of the Guadalaquivir River, Southwest Spain. However, the Doñana natural area is seriously threatened by global change factors such as humanly induced climate change, habitat loss, overexploitation of ecosystem services, and pollution. Not all stakeholders are convinced of the benefits of the national park, and management of Doñana, its environs and watershed are the subject of intense disagreement. This interplay between natural characteristics of great value with intense human pressure makes Doñana a fascinating workshop for the study of global human environment interactions. Here, we discuss the role of stakeholders in the application of a cellular automatabased model to Doñana and its environs and present the results of a series of exercises undertaken with stakeholders to parametrize the model, something often done by researchers without stakeholder engagement. By engaging with stakeholders early in the project, feedback generated from workshops contributes to model development. Stakeholders are therefore contributors of empirical data for the model as well as independent evaluators providing local and specialist knowledge.

Enhanced radon emission in natural CO2 flows in Campo de Calatrava region (central Spain)

Activity of radon gas in natural soils is commonly low (in the order of few thousands of Bq·m-3) due to the fast decay (half-life= 3.8 days in the case of 222Rn) that prevents accumulation in soil pores. Exceptionally, high Rn soil activity (up to 430 KBq·m-3) is found around point sources of deep CO2 fluxes. These fluxes allow the transport of trace gases (including Rn) to long distances in the geosphere leading to a potential hazard as Rn accumulation in buildings. CO2 degassing is common in active or ancient volcanic fields and occurs as free gas fluxes or dissolved in groundwater. In this work, the occurrence of Rnbearing, CO2 fluxes from the Campo de Calatrava region in Central Spain has been studied in order to determine their (1) magnitude, (2) migration paths and (3) potential impact on the environment, and (4) methodologies to best detection and measurement.

Planning and Management of Mobility in Natural Protected Areas

The paper describes some relevant results of an on-going research aiming to elaborate a methodology to help the mobility management in natural parks, compatible with their protection missions: it has been developed a procedure to reproduce the mobility-environment relationships in various operational conditions. The final purpose is the identification of: a) the effects of various choices in transport planning, both at long term and strategic level; b) the most effective policies of mobility management. The work is articulated in the following steps: 1) definition of protected area on the basis of ecological and socio-economic criteria and legislative constraints; 2) analysis of mobility needs in the protected areas; 3) reconstruction of the state of the art of mobility management in natural parks at European level; 4) analysis of used traffic flows measurement methods; 5) analysis of environmental impacts due to transport systems modelling (air pollution and noise only); 6) identification of mitigation measures to be potentially applied. The whole methodology has been tested and validated on Italian case studies: i) the concerned area has been zoned according to the land-use peculiarities; ii) the local situations of transport infrastructure (roads and parking), services (public transport systems) and rules (traffic regulations) have been mapped with references to physical and functional attributes; iii) the mobility, both systematic and touristic, has been represented in an origin-destination matrix. By means of an assignment model the flows have been distributed and the corresponding average speeds to quantify gaseous and noise emissions was calculated, the criticalities in the reference scenario have been highlighted, as well as some alternative scenarios, including both operational and infrastructural measures have been identified. The comparison between projects and reference scenario allowed the quantification of effects (variation of emissions) for each scenario and a selection of the most effective management actions to be taken.

High frequency of sex and equal frequencies of mating types in natural populations of the ciliate Tetrahymena thermophila.

In ciliate protists, sex involves the temporary joining of two cells of compatible mating type, followed by meiosis and exchange of gametic nuclei between conjugants. Reproduction is by asexual binary fission following conjugation. For the many ciliates with fixed multiple mating types, frequency-dependent sex-ratio theory predicts equal frequencies of mating types, if sex is common in nature. Here, we report that in natural populations of Tetrahymena thermophila sexually immature cells, indicative of recent conjugation, are found from spring through fall. In addition, the seven mating types occur in approximately equal frequencies, and these frequencies appear to be maintained by interaction between complex, multiple mat alleles and environmental conditions during conjugation. Such genotype-environment interaction determining mating type frequency is rare among ciliates.

Orchestration of gene expression across the seasons : Hypothalamic gene expression in natural photoperiod throughout the year in the Siberian hamster

Funding for work in the laboratory of PB was supported by Scottish Government Rural and Environment Science and Analytical Services Division, BBSRC (grant BB/M001504/1), British Society for Neuroendocrinology (research visit grant to IP). Work in the laboratory of SS was supported by a grant from the DFG (Ste 331/8-1). We thank Siegried Hilken, Marianne Brüning, Dr. Esther Lipokatic-Takacs and Dr. Frank Scherbarth at UVMH for technical assistance. We thank Graham Horgan of Bioinformatics, Statistics Scotland for assistance with some of statistical tests.

Direct quantification of rare earth element concentrations in natural waters by ICP-MS

A direct quadrupole ICP-MS technique has been developed for the analysis of the rare earth elements and yttrium in natural waters. The method has been validated by comparison of the results obtained for the river water reference material SLRS-4 with literature values. The detection limit of the technique was investigated by analysis of serial dilutions of SLRS-4 and revealed that single elements can be quantified at single-digit fg/g concentrations. A coherent normalised rare earth pattern was retained at concentrations two orders of magnitude below natural concentrations for SLRS-4, demonstrating the excellent inter-element accuracy and precision of the method. The technique was applied to the analysis of a diluted mid-salinity estuarine sample, which also displayed a coherent normalised rare earth element pattern, yielding the expected distinctive marine characteristics. (c) 2006 Published by Elsevier Ltd.

Environmental and nature conservation : a facet study of concern for the quality of the natural environment

A multi-variate descriptive model of environmental and nature conservation attitudes and values is proposed and empirically supported. A mapping sentence is developed out of analysis of data from a series of Repertory Grid interviews addressing conservation employees' attitudes towards their profession's activities. The research is carried out within the meta-theoretical framework of Facet Theory. A mapping sentence is developed consisting of 9 facets. From the mapping sentence 3 questionnaires were constructed viewing the selective orientations towards environmental concern. A mapping sentence and facet model is developed for each study. Once the internal structure of this model had been established using Similarity Structure Analysis, the elements of the facets are subjected to Partial Order Scalogram Analysis with base coordinates. A questionnaire was statistically analysed to assess the relationship between facet elements and 4 measures of attitudes towards, and involvement with, conservation. This enabled the comparison of the relative strengths of attitudes associated with each facet element and each measure of conservation attitude. In general, the relationship between the social value of conservation and involvement pledges to conservation were monotonic; perceived importance of a conservation issue appearing predictive of personal involvement. Furthermore, the elements of the life area and scale facets were differentially related to attitude measures. The multi-variate descriptive model of environmental conservation values and attitudes is discussed in relation to its implications for psychological research into environmental concern and for environmental and nature conservation.

Online solid phase extraction liquid chromatography tandem mass spectrometry (SPE-LC-MS/MS) method for the determination of sucralose in reclaimed and drinking waters and its photo degradation in natural waters from South Florida

Background Sucralose has gained popularity as a low calorie artificial sweetener worldwide. Due to its high stability and persistence, sucralose has shown widespread occurrence in environmental waters, at concentrations that could reach up to several μg/L. Previous studies have used time consuming sample preparation methods (offline solid phase extraction/derivatization) or methods with rather high detection limits (direct injection) for sucralose analysis. This study described a faster and sensitive analytical method for the determination of sucralose in environmental samples. Results An online SPE-LC–MS/MS method was developed, being capable to quantify sucralose in 12 minutes using only 10 mL of sample, with method detection limits (MDLs) of 4.5 ng/L, 8.5 ng/L and 45 ng/L for deionized water, drinking and reclaimed waters (1:10 diluted with deionized water), respectively. Sucralose was detected in 82% of the reclaimed water samples at concentrations reaching up to 18 μg/L. The monthly average for a period of one year was 9.1 ± 2.9 μg/L. The calculated mass loads per capita of sucralose discharged through WWTP effluents based on the concentrations detected in wastewaters in the U. S. is 5.0 mg/day/person. As expected, the concentrations observed in drinking water were much lower but still relevant reaching as high as 465 ng/L. In order to evaluate the stability of sucralose, photodegradation experiments were performed in natural waters. Significant photodegradation of sucralose was observed only in freshwater at 254 nm. Minimal degradation (<20%) was observed for all matrices under more natural conditions (350 nm or solar simulator). The only photolysis product of sucralose identified by high resolution mass spectrometry was a de-chlorinated molecule at m/z 362.0535, with molecular formula C12H20Cl2O8. Conclusions Online SPE LC-APCI/MS/MS developed in the study was applied to more than 100 environmental samples. Sucralose was frequently detected (>80%) indicating that the conventional treatment process employed in the sewage treatment plants is not efficient for its removal. Detection of sucralose in drinking waters suggests potential contamination of surface and ground waters sources with anthropogenic wastewater streams. Its high resistance to photodegradation, minimal sorption and high solubility indicate that sucralose could be a good tracer of anthropogenic wastewater intrusion into the environment.

Increasing the power of genome wide association studies in natural populations using repeated measures : evaluation and implementation

1. Genomewide association studies (GWAS) enable detailed dissections of the genetic basis for organisms' ability to adapt to a changing environment. In long-term studies of natural populations, individuals are often marked at one point in their life and then repeatedly recaptured. It is therefore essential that a method for GWAS includes the process of repeated sampling. In a GWAS, the effects of thousands of single-nucleotide polymorphisms (SNPs) need to be fitted and any model development is constrained by the computational requirements. A method is therefore required that can fit a highly hierarchical model and at the same time is computationally fast enough to be useful. 2. Our method fits fixed SNP effects in a linear mixed model that can include both random polygenic effects and permanent environmental effects. In this way, the model can correct for population structure and model repeated measures. The covariance structure of the linear mixed model is first estimated and subsequently used in a generalized least squares setting to fit the SNP effects. The method was evaluated in a simulation study based on observed genotypes from a long-term study of collared flycatchers in Sweden. 3. The method we present here was successful in estimating permanent environmental effects from simulated repeated measures data. Additionally, we found that especially for variable phenotypes having large variation between years, the repeated measurements model has a substantial increase in power compared to a model using average phenotypes as a response. 4. The method is available in the R package RepeatABEL. It increases the power in GWAS having repeated measures, especially for long-term studies of natural populations, and the R implementation is expected to facilitate modelling of longitudinal data for studies of both animal and human populations.

Influence of the natural environment on health: evaluation of different environmental contexts (urban, green spaces) and intervention proposals

Urbanization has grown during the last decades, with an increase in population concentrated in cities. Cities are usually relatively nature-poor, and the loss of green urban space likely leads to less contact with the natural world for urban dwellers. It is known that the natural environment could provide important advantages, and the loss of contact with this type of environment has potential negative impacts on the quality of life. The use of green urban space demonstrated stronger benefits for mental health and stress reduction. In general, exposure to green urban space is linked to a reduction in mortality rates, due to the promotion of a healthy lifestyle. Green urban space could be an optimal environment in which to perform physical activity. Undertaking regular physical activity is one of the major determinants of health. The benefits of exercise have been widely demonstrated through a wide range of studies. Benefits are linked to the treatment and prevention of most chronic and non-communicable diseases, that are not contagious, but they are usually long-lasting. Regular physical activity could reduce mental health problems, such as anxiety. The World Health Organization proposed to improve physical activity programs through the implementation of interventions in green urban spaces. Green urban space provides a safe, accessible, and attractive place to perform physical activity. All the interventions aimed to promote the practice of physical activity and to reduce sedentary behavior are important. It is well known that physical activity has several positive effects, a great amount of the population remains inactive. A good strategy could be to show people how integrated physical activity into their all-day life, for example through the use of green urban space or active commuting. The results in the present thesis showed the effectiveness of performing physical activity in a natural environment and of active commuting.