Ecofisiologia, fenologia e adaptação de espécies florestais arbóreas nas condições edafoclimáticas de Viana-ES

A intensa atividade humana devasta grandes extensões de florestas nativas, seja para expansão da agricultura seja para suprir a crescente demanda do mercado por madeira, de uma forma ou de outra os pequenos fragmentos florestais remanescentes sofrem constantes pressões antrópicas, contudo, o uso de espécies arbóreas adaptadas pode contribuir para a proteção desses recursos naturais. Buscou-se neste estudo avaliar os padrões fenológicos de 109 espécies florestais arbóreas pertencentes a 37 famílias e 82 gêneros, dentre nativas e exóticas, com nove anos de idade, para diferenciar as mais adaptadas e com potencial de serem utilizadas em programas de reflorestamento. O estudo foi realizado na Fazenda Experimental do Incaper, em Jucuruaba, município de Viana-ES, (UTM E-345524, N- 7741039). Foram realizadas análises químicas do solo na área plantada e os dados climatológicos obtidos na estação meteorológica de Viana. O estudo baseou-se na observação do número de plantas sobreviventes de cada espécie e da avaliação do seu crescimento. Foram realizadas observações das fenofases de brotação, senescência de folhas, floração e frutificação. As avaliações fenológicas foram realizadas em intervalos mensais, no período de novembro de 2012 a outubro de 2013. Realizou-se a medição da altura das árvores, diâmetro à altura do peito (DAP), índice de enfolhamento, taxa de sobrevivência e cálculo do ICC (Índice Combinado de Crescimento), bem como a determinação das espécies mais adaptadas. Das 109 espécies estudadas, 64,22% apresentaram adaptação funcional e estrutural às condições de solo e clima da região experimental, 42,22 % floresceram e frutificaram e 90% apresentaram senescência e brotação acompanhando a sazonalidade climática. Vinte e nove espécies apresentaram ICC maior do que o ICC médio. A maioria das espécies destacou-se como alternativa para recuperação da cobertura vegetal local, com destaque para Inga uruguensis e Schizolobium amazonicum. As análises de fluorescência da clorofila revelaram que o aparato fotossintético da Schizolobium amazonicum foi capaz de protegê-la da fotoinibição e promover boa conversão da energia luminosa em fotoquímica.

Variabilidade espacial e temporal de atributos químicos do solo em povoamento de eucalipto

Nos anos mais recentes, observa-se aumento na adoção das técnicas de silvicultura de precisão em florestas plantadas no Brasil. Os plantios de eucalipto ocorrem preferencialmente em áreas com baixa fertilidade de solo e consequentemente baixa produtividade. Logo, para otimizar ao máximo a produção, é necessário saber o quanto essa cultura pode produzir em cada local (sítio). Objetivou-se aplicar uma metodologia que utiliza técnicas de estatística, geoestatística e geoprocessamento, no mapeamento da variabilidade espacial e temporal de atributos químicos do solo cultivado com eucalipto, em área de 10,09 ha, situada no sul do estado do Espírito Santo. Os atributos químicos da fertilidade do solo estudados foram: fósforo (P), potássio (K), cálcio (Ca) e magnésio (Mg), no ano da implantação do povoamento do eucalipto, em 2008, e três anos após, em 2011. O solo foi amostrado em duas profundidades, 0-0,2 m e 0,2-0,4 m, nos 94 pontos de uma malha regular, com extensão de 33 x 33 m. Os dados foram analisados pela estatística descritiva e, em seguida, pela geoestatística, por meio do ajuste de semivariogramas. Diferentes métodos de interpolação foram testados para produzir mapas temáticos mais precisos e facilitar as operações algébricas utilizadas. Com o auxílio de índices quantitativos, realizou-se uma análise geral da fertilidade do solo, por meio da álgebra de mapas. A metodologia utilizada neste estudo possibilitou mapear a variabilidade espacial e temporal de atributos químicos do solo. A análise variográfica mostrou que todos os atributos estudados apresentaram-se estruturados espacialmente, exceto para o atributo P, no Ano Zero (camada 0-0,2 m) e no Ano Três (ambas as camadas). Os melhores métodos de interpolação para o mapeamento de cada atributo químico do solo foram identificados com a ajuda gráfica do Diagrama de Taylor. Mereceram destaque, os modelos esférico e exponencial nas interpolações para a maioria dos atributos químicos do solo avaliados. Apesar de a variação espacial e temporal dos atributos estudados apresentar-se, em média, com pequena variação negativa, a metodologia usada mostrou variações positivas na fertilidade do solo em várias partes da área de estudo. Além disso, os resultados demonstram que os efeitos observados são majoritariamente em função da cultura, uma vez que não foram coletadas amostras de solo em locais adubados. A produtividade do sítio florestal apresentou-se com tendências semelhantes às variações ocorridas na fertilidade do solo, exceto para o magnésio, que se mostrou com tendências espaciais para suporte de elevadas produtividades, de até 50 m3 ha-1 ano-1. Além de mostrar claramente as tendências observadas para as variações na fertilidade do solo, a metodologia utilizada confirma um caminho operacional acessível para empresas e produtores florestais para o manejo nutricional em florestas plantadas. O uso dos mapas facilita a mobilização de recursos para melhorar a aplicação de fertilizantes e corretivos necessários.

Biting activity of Aedes scapularis (Rondani) and Haemagogus mosquitoes in Southern Brazil (Diptera: Culicidae)

The biting activity of a population of Aedes scapularis (Rondani), Haemagogus capricornii Lutz and Hg. leucocelaenus (Dyar and Shannon) in Southern Brazil was studied between March 1980 and April 1983. Data were obtained with 25-hour human bait catches in three areas with patchy residual forests, named "Jacaré-Pepira", "Lupo" Farm, and "Sta. Helena" Farm, in the highland region of S. Paulo State (Brazil). Data obtained on Ae. scapularis were compared with those formerly gathered in the "Ribeira'' Valley lowlands, and were similar, except in the "Lupo" Farm study area, where a precrepuscular peak was observed, not recorded at the "Jacaré-Pepira" site or in the "Ribeira" Valley. In all the areas this mosquito showed diurnal and nocturnal activity, but was most active during the evening crepuscular period. These observations support the hypothesis about the successful adaptation of Ae. scapularis to man-made environments and have epidemiological implications that arise from it. As for Haemagogus, results obtained on the "Lupo" and "Sta. Helena" regions agree with previous data obtained in several other regions and show its diurnal activity. The proximity of "Lupo" Farm, where Hg. capricornii and Hg. leucocelaenus showed considerable activity, to "Araraquara" city where Aedes aegypti was recently found, raises some epidemiological considerations about the possibility of urban yellow fever resurgence.

Studies on mosquitoes (Diptera: Culicidae) and anthropic environment: 8- Survey of adult behaviour of Spissipes Section species of Culex (Melanoconion) in South-Eastern Brazil

A study of Spissipes Section of Culex (Melanoconion) adults behaviour was carried out from August 1992 through December 1993 in human dominated (anthropic) environment in the Ribeira Valley, S.Paulo State, Brazil. By sampling at several sites it the dominance of Culex ribeirensis and Cx. sacchettae became evident even through a total number of ten species was recorded. Those two mosquitoes showed a clear tendency to frequent the domiciliary environment where they were caught, both indoor and outdoor, through the use of the human bait. In the outside environments, the residual patchy forests seems to display a concentration role, from which these adults spread to the open land and reach the dwellings. As their vector competence has been demonstrated through the virus isolations in natural conditions, it is advisable to pay attention to the presence of these mosquitoes in the man-made environment.

Studies on mosquitoes (Diptera: Culicidae) and anthropic environment: 9- Synanthropy and epidemiological vector role of Aedes scapularis in South-Eastern Brazil

Behaviour comparisons of Aedes scapularis and Ae. serratus are presented. Results were obtained by sampling Aedes adult mosquitoes at several places in the rural anthropic environment in the Ribeira Valley region of S. Paulo State, Brazil. Aedes dominance was shared by those two species, but Ae. scapularis Sshowed a clear tendency to frequent the modified environment, while Ae. serratus was to be found in the more preserved ones, here represented by the vestigial patchy forests. Regarding the open cultivated land and the dwelling environments, Ae. scapularis preponderates. Considering the regional developmental phases, this mosquito showed a remarkable increase in the modified environment differently from Ae. serratus that underwent a considerable decrease in migrating from the forest to the anthropic environment. As a consequence of these results it is reasonable to conclude that Ae. scapularis may be considered as an epidemiologically efficient vector and that it quite probably played this role in the Rocio encephalitis and other arbovirus epidemics.

QSAR modeling of antitubercular activity of diverse organic compounds

Tuberculosis (TB) is a worldwide infectious disease that has shown over time extremely high mortality levels. The urgent need to develop new antitubercular drugs is due to the increasing rate of appearance of multi-drug resistant strains to the commonly used drugs, and the longer durations of therapy and recovery, particularly in immuno-compromised patients. The major goal of the present study is the exploration of data from different families of compounds through the use of a variety of machine learning techniques so that robust QSAR-based models can be developed to further guide in the quest for new potent anti-TB compounds. Eight QSAR models were built using various types of descriptors (from ADRIANA.Code and Dragon software) with two publicly available structurally diverse data sets, including recent data deposited in PubChem. QSAR methodologies used Random Forests and Associative Neural Networks. Predictions for the external evaluation sets obtained accuracies in the range of 0.76-0.88 (for active/inactive classifications) and Q(2)=0.66-0.89 for regressions. Models developed in this study can be used to estimate the anti-TB activity of drug candidates at early stages of drug development (C) 2011 Elsevier B.V. All rights reserved.

Phlebotomine fauna in a rural area of the Brazilian Pantanal

The aim of the study was to identify among the phlebotomine fauna potential leishmaniasis vectors. The study was carried out in Corumbá county, State of Mato Grosso do Sul, Mid-West Brazil (18º59'S, 56º39'W). Sand fly captures were undertaken fortnightly with automatic light traps at 11 sites in forested environments and anthropic areas from April 2001 to July 2003. A total of only 41 specimens were captured. Thirty-one percent of the specimens were captured in forests and 68.3% in anthropic areas. The predominance of non-anthropophilic groups and the low density of N. whitmani, a known cutaneous leishmaniasis vector, does not seem to indicate any actual risk of the transmission of this disease in the study area.

Bryophytes distribution along an altitudinal gradient of native forest in Pico island (Azores): preliminary results of epiphytic genera

MOVECLIM, Mid Course Meeting, 2-6 September 2013, Réunion (Mascarenes).

New mitochondrial and nuclear evidences support recent demographic expansion and an atypical phylogeographic pattern in the Spittlebug Philaenus spumarius (Hemiptera, Aphrophoridae)

Copyright: © 2014 Rodrigues et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Preliminary observations on the benthic marine algae of the Gorringe seabank (northeast Atlantic Ocean)

Copyright © Springer-Verlag Berlin Heidelberg and AWI 2014.

Towards systematic conservation planning in the Azores

Several field methodologies, analytical measures and theoretical patterns have been explored for conservation planning for arthropods in native forests of the Azores archipelago. Here, the outcomes are assembled to make recommendations on practical strategies to assess arthropod diversity and to select and manage protected native forests in the Azores. Suggestions are made on how to apply similar plans for conservation of other plant and animal groups in these forests. Potential threats to the Azorean native forest are described and measures to minimize them are proposed. Future studies are also suggested that would improve the present knowledge of arthropod diversity and distribution in Azorean native forests and could assist in the identification of suitable conservation strategies.

Growth responses of Macrocystis pyrifera (Laminariales), Southern Chile, juvenile sporophytes to nutrient limitation

1st Mares Conference on Marine Ecosystems Health and Conservation. Olhão, Portugal 17-21 November 2014.

Rede de monitorização ambiental em tempo- real com sistemas móveis

A compreensão das interacções entre os oceanos, a linha de costa, a qualidade do ar e as florestas só será possível através do registo e análise de informação geo-temporalmente referenciada. Mas a monitorização de grandes áreas apresenta o problema da cobertura espacial e temporal, e os custos nela envolvidos pela impossibilidade de disseminar a quantidade de estações de monitorização necessários à compreensão do fenómeno. É necessário então definir metodologias de colocação de sensores e recolha de informação de forma robusta, económica e temporalmente útil. Nesta dissertação apresentamos uma estratégia de monitorização ambiental, para meios hídricos, (ou de grande dimensão) que baseada em sistemas móveis e alguns princípios da geoestatística, fornece uma ferramenta de monitorização mais económica, sem prejuízo da qualidade de informação. Os modelos usados na geoestatística assentam na ideia de que medidas mais próximas tendem a serem mais parecidas do que valores observados em locais distantes e fornece métodos para quantificar esta correlação espacial e incorporá-la na estimação. Os resultados obtidos sustentam a convicção do uso de veículos móveis em redes de sensores e que contribuímos para responder à seguinte questão “Qual a técnica que nos permite com poucos sensores monitorizar grandes áreas?”. A solução passará por modelos de estimação de grandezas utilizados na geoestatística associados a sistemas móveis.

Vulnerability of mediterranean watersheds to climate change

Desertification is a critical issue for Mediterranean drylands. Climate change is expected to aggravate its extension and severity by reinforcing the biophysical driving forces behind desertification processes: hydrology, vegetation cover and soil erosion. The main objective of this thesis is to assess the vulnerability of Mediterranean watersheds to climate change, by estimating impacts on desertification drivers and the watersheds’ resilience to them. To achieve this objective, a modeling framework capable of analyzing the processes linking climate and the main drivers is developed. The framework couples different models adapted to different spatial and temporal scales. A new model for the event scale is developed, the MEFIDIS model, with a focus on the particular processes governing Mediterranean watersheds. Model results are compared with desertification thresholds to estimate resilience. This methodology is applied to two contrasting study areas: the Guadiana and the Tejo, which currently present a semi-arid and humid climate. The main conclusions taken from this work can be summarized as follows: • hydrological processes show a high sensitivity to climate change, leading to a significant decrease in runoff and an increase in temporal variability; • vegetation processes appear to be less sensitive, with negative impacts for agricultural species and forests, and positive impacts for Mediterranean species; • changes to soil erosion processes appear to depend on the balance between changes to surface runoff and vegetation cover, itself governed by relationship between changes to temperature and rainfall; • as the magnitude of changes to climate increases, desertification thresholds are surpassed in a sequential way, starting with the watersheds’ ability to sustain current water demands and followed by the vegetation support capacity; • the most important thresholds appear to be a temperature increase of +3.5 to +4.5 ºC and a rainfall decrease of -10 to -20 %; • rainfall changes beyond this threshold could lead to severe water stress occurring even if current water uses are moderated, with droughts occurring in 1 out of 4 years; • temperature changes beyond this threshold could lead to a decrease in agricultural yield accompanied by an increase in soil erosion for croplands; • combined changes of temperature and rainfall beyond the thresholds could shift both systems towards a more arid state, leading to severe water stresses and significant changes to the support capacity for current agriculture and natural vegetation in both study areas.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.