The terrestrial biosphere impacts considerably on the global carbon cycle. In particular, ecosystems contribute to set off anthropogenic induced fossil fuel emissions and hence decelerate the rise of the atmospheric CO₂ concentration. However, the future net sink strength of an ecosystem will heavily depend on the response of the individual processes to a changing climate. Understanding the makeup of these processes and their interaction with the environment is, therefore, of major importance to develop long-term climate mitigation strategies. Mathematical models are used to predict the fate of carbon in the soil-plant-atmosphere system under changing environmental conditions. However, the underlying processes giving rise to the net carbon balance of an ecosystem are complex and not entirely understood at the canopy level. Therefore, carbon exchange models are characterised by considerable uncertainty rendering the model-based prediction into the future prone to error. Observations of the carbon exchange at the canopy scale can help learning about the dominant processes and hence contribute to reduce the uncertainty associated with model-based predictions. For this reason, a global network of measurement sites has been established that provides long-term observations of the CO₂ exchange between a canopy and the atmosphere along with micrometeorological conditions. These time series, however, suffer from observation uncertainty that, if not characterised, limits their use in ecosystem studies. The general objective of this work is to develop a modelling methodology that synthesises physical process understanding with the information content in canopy scale data as an attempt to overcome the limitations in both carbon exchange models and observations. Similar hybrid modelling approaches have been successfully applied for signal extraction out of noisy time series in environmental engineering. Here, simple process descriptions are used to identify relationships between the carbon exchange and environmental drivers from noisy data. The functional form of these relationships are not prescribed a priori but rather determined directly from the data, ensuring the model complexity to be commensurate with the observations. Therefore, this data-led analysis results in the identification of the processes dominating carbon exchange at the ecosystem scale as reflected in the data. The description of these processes may then lead to robust carbon exchange models that contribute to a faithful prediction of the ecosystem carbon balance. This work presents a number of studies that make use of the developed data-led modelling approach for the analysis and interpretation of net canopy CO₂ flux observations. Given the limited knowledge about the underlying real system, the evaluation of the derived models with synthetic canopy exchange data is introduced as a standard procedure prior to any real data employment. The derived data-led models prove successful in several different applications. First, the data-based nature of the presented methods makes them particularly useful for replacing missing data in the observed time series. The resulting interpolated CO₂ flux observation series can then be analysed with dynamic modelling techniques, or integrated to coarser temporal resolution series for further use e.g., in model evaluation exercises. However, the noise component in these observations interferes with deterministic flux integration in particular when long time periods are considered. Therefore, a method to characterise the uncertainties in the flux observations that uses a semi-parametric stochastic model is introduced in a second study. As a result, an (uncertain) estimate of the annual net carbon exchange of the observed ecosystem can be inferred directly from a statistically consistent integration of the noisy data. For the forest measurement sites analysed, the relative uncertainty for the annual sum did not exceed 11 percent highlighting the value of the data. Based on the same models, a disaggregation of the net CO₂ flux into carbon assimilation and respiration is presented in a third study that allows for the estimation of annual ecosystem carbon uptake and release. These two components can then be further analysed for their separate response to environmental conditions. Finally, a fourth study demonstrates how the results from data-led analyses can be turned into a simple parametric model that is able to predict the carbon exchange of forest ecosystems. Given the global network of measurements available the derived model can now be tested for generality and transferability to other biomes. In summary, this work particularly highlights the potential of the presented data-led methodologies to identify and describe dominant carbon exchange processes at the canopy level contributing to a better understanding of ecosystem functioning. / Der Kohlenstoffhaushalt der Erde wird maßgeblich von der bewachsenen Landoberfläche beeinflusst. Insbesondere tragen terrestrische Ökosysteme dazu bei, den Anstieg der atmosphärischen Kohlenstoffdioxid- (CO₂-) Konzentration durch anthropogen verursachte Emissionen fossiler Brennstoffe zu verlangsamen. Die Intensität der Netto-CO₂-Aufnahme wird allerdings in einem sich verändernden Klima davon abhängen, wie einzelne Prozesse auf Änderungen der sie beeinflussenden Umweltfaktoren reagieren. Fundierte Kenntnisse dieser Prozesse und das Verständnis ihrer Wechselwirkungen mit der Umwelt sind daher für eine erfolgreiche Klimaschutzpolitik von besonderer Bedeutung. Mit Hilfe von mathematischen Modellen können Vorhersagen über den Verbleib des Kohlenstoffs im System Boden-Pflanze-Atmosphäre unter zukünftigen Umweltbedingungen getroffen werden. Die verantwortlichen Prozesse und ihre Wechselwirkungen mit der Umwelt sind jedoch kompliziert und bis heute auf der Ökosystemskala nicht vollkommen verstanden. Entwickelte Modelle und deren Vorhersagen sind deshalb derzeit mit erheblichen Unsicherheiten behaftet. Messungen von CO₂-Austauschflüssen zwischen einem Ökosystem und der Atmosphäre können dabei helfen, Vorgänge besser verstehen zu lernen und die Unsicherheiten in CO₂-Austausch-Modellen zu reduzieren. Allerdings sind auch diese Beobachtungen, wie alle Umweltmessungen, von Unsicherheiten durchsetzt. Ziel dieser Arbeit ist es Methoden zu entwickeln, die physikalisches Prozessverständnis mit dem dennoch großen Informationsgehalt dieser Daten vorteilhaft zu vereinigen. Dabei soll vereinfachtes Prozessverständnis dazu genutzt werden, Zusammenhänge zwischen dem CO₂-Austausch und den umgebenden Umweltbedingungen aus den Beobachtungen abzuleiten. Das Besondere hierbei ist, dass diese Zusammenhänge direkt aus den Daten geschätzt werden, ohne vorher Annahmen über ihre funktionale Form zu machen. Die Daten als Ausgangspunkt der Modellentwicklung zu wählen gewährleistet, dass die Komplexität der Modelle dem Informationsgehalt der Messungen entspricht. Auf diese Weise lassen sich diejenigen Prozesse identifizieren, welche für den CO₂-Austausch mit der Atmosphäre dominant sind. Die gewonnenen Erkenntnisse können dann in robuste CO₂-Austauschmodelle für Ökosysteme überführt werden und zur Vorhersage von Kohlenstoffbilanzen beitragen. In der vorliegenden Arbeit werden diese entwickelten, datenbasierten Methoden zur Analyse und Interpretation von Netto-CO₂-Flüssen eingesetzt. Die erste Studie führt ein datenbasiertes Modell ein, das unvermeidliche Lücken in Messzeitreihen zuverlässig interpoliert. Dies ermöglicht erweiterte Anwendungen der Daten. In einer nächsten Studie wird ein Verfahren vorgestellt, mit dem die Unsicherheiten in den Beobachtungen charakterisiert werden können. Dies ist nötig, um jährliche Kohlenstoffbilanzen von Ökosystemen unter Berücksichtigung der Messungenauigkeiten direkt aus den Daten herzuleiten. Dabei liegt die Unsicherheit in den betrachteten Waldstandorten bei maximal 11% des Jahreswertes. In einer weiteren Studie werden dieselben Modelle genutzt, um die Netto-CO₂-Flüsse in Einzelkomponenten der CO₂-Assimilation und -Abgabe zu bestimmen. Diese Komponenten sowie die Nettobilanz sind zusammen mit ihren Ungenauigkeiten für Vorhersagen über das Kohlenstoffsenkenpotential eines Ökosystems von besonderer Bedeutung und können Abschätzungen des globalen Kohlenstoffhaushaltes maßgeblich unterstützen. Abschließend zeigt die letzte Studie ein Beispiel für die datenbasierte Entwicklung eines Modells, das die dominanten Prozesse des Kohlenstoffaustausches in Waldökosystemen beschreibt und erfolgreich vorhersagen kann. Dies unterstreicht insbesondere das Potenzial des vorgestellten Modellierungsansatzes, vorherrschende Prozesse zu identifizieren, zu beschreiben und damit zum verbesserten Verständnis des CO₂-Austauschs zwischen Ökosystem und Atmosphäre beizutragen.

This thesis is written as a cumulative dissertation. It presents methods and results which contribute to an improved understanding of the spatio-temporal variability of fog and fog deposition. The questions to be answered are: When is there how much fog, and where and how much fog is deposited on the vegetation as fog precipitation? Freely available data sets serve as a database. The meteorological input data are obtained from the Climate Data Center (CDC) of the German Meteorological Service (DWD). Station data for temperature, relative humidity and wind speed in hourly resolution are used. In addition, visibility data are used for validation purposes. Furthermore, Global Forest Heights (GFH) data from the National Aeronautics and Space Administration (NASA) are used as vegetation height data. The data from NASA’s Shuttle Radar Topography Mission (SRTM) is used as a digital elevation model. The first publication deals with gap filling and data compression for further calculations. This is necessary since the station density for hourly data is relatively low, especially before the 2000s. In addition, there are more frequent gaps in hourly data than in, for instance, daily data, which can thus be filled. It is shown that gradient boosting (gb) enables high quality gap filling in a short computing time. The second publication deals with the determination of the fog, especially with the liquid water content (lwc). Here the focus is on the correction of measurement errors of the relative humidity as well as methods of spatial interpolation are dealt with. The resulting lwc data for Germany with a temporal resolution of one hour and a spatial resolution of one kilometre, are validated against measured lwc data as well as visibility data of the DWD. The last publication uses the data and methods of the two previous publications. The vegetation and wind speed data are also used to determine fog precipitation from the lwc data. This is validated using data from other publications and water balance calculations. In addition to the measured precipitation, the fog precipitation data are used as an input variable for the modelling. This is also one of the possible applications: To determine precipitation from fog, which is not recorded by standard measuring methods, and thus to make water balance modelling more realistic.:1 MOTIVATION 6 2 PROBLEM DEFINITION AND TARGET SETTING 6 3 STRUCTURE 7 4 MODEL LIMITS 9 5 PUBLICATIONS 9 6 OUTLOOK 29

Fires occur extensively across Zambia every year, a problem recognized as a major threat to biodiversity. Yet, basic tools for mapping at a spatial and temporal scale that provide useful information for understanding and managing this problem are not available. The objectives of this research were: to develop a method to map the spatio-temporal seasonal fire occurrence using satellite imagery, to develop a technique for estimating missing data in the satellite imagery considering the possibility of change in land cover over time, and to demonstrate applicability of these new tools by analyzing the fine-scale seasonal patterns of landscape fires in eastern Zambia. A new approach for mapping burned areas uses multitemporal image analysis with a fuzzy clustering algorithm to automatically select spectral-temporal signatures that are then used to classify the images to produce the desired spatio-temporal burned area information. Testing with Landsat data (30m resolution) in eastern Zambia showed accuracies in predicting burned areas above 92%. The approach is simple to implement, data driven, and can be automated, which can facilitate quicker production of burned area information. A profile-based approach for filling missing data uses multitemporal imagery and exploits the similarity in land cover temporal profiles and spatial relationships to reliably estimate missing data even in areas with significant changes. Testing with simulated missing data from an 8-image spectral index sequence showed highly correlated (R2 of 0.78-0.92) and precise estimates (deviations 4-7%) compared to actual values. The profile-based approach overcomes the common requirement of gap-filling methods that there is gradual or no change in land cover, and provides accurate gap-filling under conditions of both gradual and abrupt changes. The spatio-temporal progression of landscape burning was evaluated for the 2009 and 2012 fire seasons (June-November) using Landsat data. Results show widespread burning (~ 60%) with most fires occurring late (August-October) in the season. Fire occurrence and burn patch sizes decreased with increasing settlement density and landscape fragmentation reflecting human influences and fuel availability. Small fires (< 5ha) are predominant and were significantly under-detected (>50%) by a global dataset (MODIS Burned Area Product (500m resolution)), underscoring the critical need of higher geometric resolution imagery such as Landsat imagery for mapping such fine-scale fire activity. / Ph. D.

La biologie des systèmes intègre données et connaissances par des méthodes bioinformatiques, afin de mieux appréhender la physiologie des organismes. Une problématique est l’applicabilité de ces techniques aux organismes non modèles, au centre de plus en plus d’études, grâce aux avancées de séquençage et à l’intérêt croissant de la recherche sur les microbiotes. Cette thèse s’intéresse à la modélisation du métabolisme par des réseaux, et de sa fonctionnalité par diverses sémantiques basées sur les graphes et les contraintes stoechiométriques. Une première partie présente des travaux sur la complétion de réseaux métaboliques pour les organismes non modèles. Une méthode basée sur les graphes est validée, et une seconde, hybride, est développée, en programmation par ensembles réponses (ASP). Ces complétions sont appliquées à des réseaux métaboliques d’algues en biologie marine, et étendues à la recherche de complémentarité métabolique entre Ectocarpus siliculosus et une bactérie symbiotique. En s’appuyant sur les méthodes de complétion, la seconde partie de la thèse vise à proposer et implémenter une sélection de communautés à l’échelle de grands microbiotes. Une approche en deux étapes permet de suggérer des symbiotes pour l’optimisation d’un objectif donné. Elle supporte la modélisation des échanges et couvre tout l’espace des solutions. Des applications sur le microbiote intestinal humain et la sélection de bactéries pour une algue brune sont présentées. Dans l’ensemble, cette thèse propose de modéliser, développer et appliquer des méthodes reposant sur des sémantiques de graphe pour élaborer des hypothèses sur le métabolisme des organismes. / Systems biology relies on computational biology to integrate knowledge and data, for a better understanding of organisms’ physiology. Challenges reside in the applicability of methods and tools to non-model organisms, for instance in marine biology. Sequencing advances and the growing importance of elucidating microbiotas’ roles, have led to an increased interest into these organisms. This thesis focuses on the modeling of the metabolism through networks, and of its functionality using graphs and constraints semantics. In particular, a first part presents work on gap-filling metabolic networks in the context of non-model organisms. A graph-based method is benchmarked and validated and a hybrid one is developed using Answer Set Programming (ASP) and linear programming. Such gap-filling is applied on algae and extended to decipher putative interactions between Ectocarpus siliculosus and a symbiotic bacterium. In this direction, the second part of the thesis aims at proposing formalisms and implementation of a tool for selecting and screening communities of interest within microbiotas. It enables to scale to large microbiotas and, with a two-step approach, to suggest symbionts that fit the desired objective. The modeling supports the computation of exchanges, and solving can cover the whole solution space. Applications are presented on the human gut microbiota and the selection of bacterial communities for a brown alga. Altogether, this thesis proposes modeling, software and biological applications using graph-based semantics to support the elaboration of hypotheses for elucidating the metabolism of organisms.

Submitted by Gabriela Lopes (gmachadolopesufpel@gmail.com) on 2017-03-07T16:57:14Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) DISSERTAÇÃO_Gisele_Machado.pdf: 3307276 bytes, checksum: 592c96eced3ac21eaba699361b81eed0 (MD5) / Approved for entry into archive by Aline Batista (alinehb.ufpel@gmail.com) on 2017-03-09T20:39:48Z (GMT) No. of bitstreams: 2 DISSERTAÇÃO_Gisele_Machado.pdf: 3307276 bytes, checksum: 592c96eced3ac21eaba699361b81eed0 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) / Made available in DSpace on 2017-03-09T20:39:48Z (GMT). No. of bitstreams: 2 DISSERTAÇÃO_Gisele_Machado.pdf: 3307276 bytes, checksum: 592c96eced3ac21eaba699361b81eed0 (MD5) license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Previous issue date: 2015-03-31 / O Estado do Rio Grande do Sul tem acumulado perdas na produção agropecuária e econômica, em função da ocorrência de eventos de seca. Apesar de todo o avanço tecnológico, a agricultura ainda depende das condições climáticas e meteorológicas e, por isso, estudos devem ser realizados com o intuito de auxiliar na investigação do comportamento da seca, nas mais diversas regiões. Um passo importante para o entendimento dos eventos de seca é a utilização de índices, que fazem um levantamento da situação, conforme uma escala de intensidade, que objetiva dar um panorama do comportamento hídrico da região.Assim, o presente trabalho tem como objetivo identificar e caracterizar o comportamento da seca, utilizando índices meteorológicos, em diferentes escalas temporais para 40 estações, compostas por uma série de dados de precipitação de 90 anos (1913-2002), localizadas no Estado do Rio Grande do Sul, obtidas através do banco de dados do Instituto Nacional de Meteorologia e da Agência Nacional de Águas.Para tanto, foram utilizados dois índices de seca: Índice Padronizado de Precipitação, nas escalas temporais de 1, 3, 6, 9, 12 e 24 meses, nas intensidades severa e extrema,e o Índice de Moreno,em escala trimestral e semestral,nas intensidades intensa e severa, bem como a contagem do número total de dias secos e análise da sequência de dias secos.Para o preenchimento de dados das séries de precipitação diária, foi utilizada a modelagem estocástica Cadeia de Markov de dois estados. Os resultados mostraram que para o Índice de Moreno, a escala trimestral, comparativamente à escala semestral, apresentou maior concentração de eventos de seca. Para o Índice Padronizado de Precipitação,as maiores sequências de meses secos foram encontradas na intensidade extrema; a maior ocorrência de eventos de seca severa coincidiu em 85% com os períodos de La Niña e a maior incidência de eventos de seca severa e intensa ocorreu na década de 1943 a 1952. Quantoà espacialização do Índice Padronizado de Precipitação, nas escalas 6, 12 e 24 meses, esta representou adequadamente os resultados obtidos nas sequências de períodos secos. / Due to the occurrence of drought events, the state of Rio Grande do Sul has accumulated losses in the agricultural and economic production. Despite the technological advances, agriculture still depends on climatic and weather conditions and, therefore, studies should be conducted in order to help the investigation of drought behavior in various regions. An important step in the understanding of drought events is the use of indexes, which survey the situation, according to an intensity scale, which aims to give an overview of the water behavior in the region. Thus, this study aims to identify and characterize drought behavior by using meteorological indexes, at different time scales for 40 seasons, consisting of a series of rainfall data from 1913 to 2002, located in the state of Rio Grande do Sul, obtained from the database of the National Institute of Meteorology (INMET) and the National Water Agency (ANA). Therefore, two drought indexes were used: Standardized Precipitation Index, in the time scales of 1, 3, 6, 9, 12 and 24 months, in severe and extreme intensities, and the Moreno Index, a quarterly and half-yearly scale, in intense to severe intensities, as well as the count of the total number and sequence analysis of dry days. For data filling of daily precipitation series, the stochastic model was used applying the Markov chain from two states. The results indicated that for the Moreno Index, the quarterly level, compared to the half-yearly scale, showed a higher concentration of drought events. For the Standardized Precipitation Index, the main sequences of dry months were found in extreme intensity; the higher incidence of severe drought events coincided in 85% with periods of La Niña and the higher incidence of severe and intense drought events occurred from 1943 to 1952. As for the spatial distribution of the Standardized Precipitation Index, in the scales 6, 12 and 24 months, it adequately represented the results obtained in the sequences of dry periods.

No description available.

Nesta tese investigou-se os padrões microclimáticos, de fluxos de energia e CO2 em uma floresta em planície de inundação da Ilha do Bananal, com ênfase nos efeitos da inundação sazonal nas variáveis atmosféricas e na produtividade do ecossistema, além de estimativas de fluxos aquáticos evasivos de CO2 e CH4. Para tanto, foram utilizadas técnicas micrometeorológicas de vórtices turbulentos, estimativas de armazenamento vertical de CO2 e dados medidos em uma torre micrometeorológica no período de 2004 a 2014, além de campanhas específicas para medidas de fluxos evasivos. Embora existam ciclos sazonais bem definidos de precipitação, temperatura do ar e umidade na região, controlados pela oferta radiativa, esta não explica diretamente as variações na evapotranspiração quando se busca explicá-la pelo aumento da disponibilidade energética. O particionamento da energia disponível aponta para um domínio do calor latente em comparação ao sensível durante períodos de decaimento do saldo de radiação, configurando um padrão peculiar não reportado na literatura. Os dados de temperatura do ar, precipitação pluviométrica, fluxos turbulentos de CO2 e fluxos energéticos (LE e H) mostraram uma possível influência das secas que ocorreram no lado oeste da região, também neste sítio experimental do leste. Os anos de 2005 e 2010 foram mais quentes, pouco chuvosos e mais secos que os demais anos da série de dados, e em 2010 ocorreu a menor produtividade líquida da estação seca. A inundação mostrou ter um papel importante nos fluxos de CO2, fazendo com que a produtividade bruta, a respiração do ecossistema e a produtividade líquida diminuam, somando-se os efeitos esperados pelo controle radiativo. A produtividade líquida respondeu aos efeitos da inundação semanas antes desta iniciar na torre, persistindo seus efeitos até algumas semanas depois, com a diminuição da produtividade. Já a respiração do ecossistema e a produtividade primária bruta mostraram ser mais sensíveis ao início da estação seca, com uma interrupção no declínio atribuído à inundação, provavelmente devido ao favorecimento da decomposição de matéria orgânica suspensa na água. Os resultados dos fluxos de carbono sugerem uma alta assimilação de CO2 pela floresta, o que requer corroboração através de medidas biométricas, não sendo, contudo, descartada a confiabilidade dos resultados. Os resultados da campanha para medidas de fluxos evasivos mostraram que o rio é uma fonte de CO2 para a atmosfera, e tanto o rio quanto a superfície vegetada atuam como fonte de CH4 para a atmosfera, com maior contribuição da superfície vegetada. As concentrações de metano e carbono na água foram superiores ás amostragens da atmosfera, o que já era esperado conforme os estudos existentes na literatura. / This thesis investigated the microclimate, CO2 and energy fluxes patterns at a forest in floodplain of Bananal Island, with emphasis on the seasonal flooding effects in atmospheric variables and ecosystem productivity, as well as estimates of evasive water CO2 and CH4 fluxes. To carry it out, micrometeorological eddy covariance technique was associated, vertical storage CO2 estimates and measured data in a micrometeorological tower from 2004 to 2014, as well as specific campaigns for evasive fluxes measures. Although there are welldefined seasonal cycles of precipitation, air temperature and humidity in the area controlled by the radiative offer, it does not directly explain the variations in evapotranspiration when seeking for explain it by the increase in energy availability. Partitioning of the available energy points to a latent heat flux domain compared to sensible heat flux during net radiation decay periods, showing a peculiar pattern not reported in the literature. The data air temperature, rainfall, eddy CO2 and energy fluxes (LE and H) showed a possible influence of droughts that occurred on the west side of the region, in this experimental site from the east. The years 2005 and 2010 were warmer, little rainy and drier than the other years of the data series, and in 2010 had the lowest net productivity of the dry season. The flood was shown to have an important role in CO2 streams, causing the gross productivity, ecosystem respiration and the net productivity decrease, adding to the effects expected by the radiative control. The net productivity responded to the effects of flooding weeks before this start in the tower, continuing its effects until a few weeks later, with decreasing productivity. Already ecosystem respiration and gross primary productivity proved to be more sensitive to early dry season, with an interruption in the decline attributed to flooding, probably due to favoring the decomposition of organic matter suspended in the water. The results of the carbon fluxes suggest a high CO2 assimilation by forest, which requires corroboration through biometric measurements and are not, however, ruled out the reliability of the results. The results of the campaign to evasive flux measurements showed that the river is a CO2 source to the atmosphere, and both the river and the vegetated surface act as a CH4 source to the atmosphere, with a greater contribution of the vegetated surface. Methane and carbon concentrations in the water were higher ace sampling the atmosphere, which was expected as existing studies in the literature.

Made available in DSpace on 2017-07-21T14:19:32Z (GMT). No. of bitstreams: 1 Ricardo Baba.pdf: 3642224 bytes, checksum: 81e8e78f554cdf870e6f9a554b71f87a (MD5) Previous issue date: 2012-07-31 / Climatic data are more and more important to predict climate phenomena or to evaluate historical data that serve as support for decision making especially for agriculture. Ensuring the quality of these data is crucial. These data are collected by the meteorological stations, during this process some data gaps and data inconsistent may be generated. Identify suspicious or inconsistent data is very important to ensure data quality. This paper presents an approach that uses statistical and geostatistical techniques to identify incorrect and suspicious data and estimate new values to fill gaps and errors. In this research, a spatial database was used to implement these techniques (statistical and geostatistical) and to test and evaluate the weather data. To evaluate these techniques we used data from stations located in Paraná State to evaluate the temperature variable. To check the results of the estimated data, we used the mean absolute error (MAE) and the root mean square error (RMSE). As a result, the uses of these techniques have proved to be suitable to identify basic errors and historical errors. The temporal validation showed a poor performance by overestimating the amount of incorrect data. Regarding the estimation techniques applied Kriging, Inverse of Distance Weighted and Linear Regression, all showed similar performance in the error analysis. / A análise de dados climáticos serve de suporte na previsão de fenômenos relacionados, na avaliação de seus dados históricos e para a tomada de decisões, em especial na área da agricultura. Garantir a sua qualidade é fundamental. O processo de coleta desses dados, através das estações meteorológicas, pode apresentar problemas, onde dados inconsistentes podem ser geridos ou obtidos. A identificação de dados inconsistentes ou suspeitos é de fundamental importância na garantia de qualidade dos dados. Este trabalho apresenta uma abordagem para solução do problema, utilizando técnicas estatísticas e geoestatísticas na identificação de dados inconsistentes e na estimativa de dados a serem corrigidos ou preenchidos. A implementação destas técnicas em um banco de dados espacial apresentou-se como um facilitador na identificação e no preenchimento desses dados. Para avaliação destas técnicas utilizou-se de dados das estações localizadas no Estado do Paraná, para análise da variável temperatura. Para avaliar os resultados, foram utilizados os erros médio e quadrático. Como resultado, destaca-se que as técnicas de identificação de erros mostraram-se adequadas na consistência de erros básicos e históricos. A validação espacial apresentou baixo desempenho por superestimar a quantidade de dados incorretos. Quanto as técnicas utilizadas na estimativa dos dados, Krigagem, Inverso da Distância e Regressão Linear, todas apresentaram desempenho semelhantes com relação à análise dos erros.

Nesta tese investigou-se os padrões microclimáticos, de fluxos de energia e CO2 em uma floresta em planície de inundação da Ilha do Bananal, com ênfase nos efeitos da inundação sazonal nas variáveis atmosféricas e na produtividade do ecossistema, além de estimativas de fluxos aquáticos evasivos de CO2 e CH4. Para tanto, foram utilizadas técnicas micrometeorológicas de vórtices turbulentos, estimativas de armazenamento vertical de CO2 e dados medidos em uma torre micrometeorológica no período de 2004 a 2014, além de campanhas específicas para medidas de fluxos evasivos. Embora existam ciclos sazonais bem definidos de precipitação, temperatura do ar e umidade na região, controlados pela oferta radiativa, esta não explica diretamente as variações na evapotranspiração quando se busca explicá-la pelo aumento da disponibilidade energética. O particionamento da energia disponível aponta para um domínio do calor latente em comparação ao sensível durante períodos de decaimento do saldo de radiação, configurando um padrão peculiar não reportado na literatura. Os dados de temperatura do ar, precipitação pluviométrica, fluxos turbulentos de CO2 e fluxos energéticos (LE e H) mostraram uma possível influência das secas que ocorreram no lado oeste da região, também neste sítio experimental do leste. Os anos de 2005 e 2010 foram mais quentes, pouco chuvosos e mais secos que os demais anos da série de dados, e em 2010 ocorreu a menor produtividade líquida da estação seca. A inundação mostrou ter um papel importante nos fluxos de CO2, fazendo com que a produtividade bruta, a respiração do ecossistema e a produtividade líquida diminuam, somando-se os efeitos esperados pelo controle radiativo. A produtividade líquida respondeu aos efeitos da inundação semanas antes desta iniciar na torre, persistindo seus efeitos até algumas semanas depois, com a diminuição da produtividade. Já a respiração do ecossistema e a produtividade primária bruta mostraram ser mais sensíveis ao início da estação seca, com uma interrupção no declínio atribuído à inundação, provavelmente devido ao favorecimento da decomposição de matéria orgânica suspensa na água. Os resultados dos fluxos de carbono sugerem uma alta assimilação de CO2 pela floresta, o que requer corroboração através de medidas biométricas, não sendo, contudo, descartada a confiabilidade dos resultados. Os resultados da campanha para medidas de fluxos evasivos mostraram que o rio é uma fonte de CO2 para a atmosfera, e tanto o rio quanto a superfície vegetada atuam como fonte de CH4 para a atmosfera, com maior contribuição da superfície vegetada. As concentrações de metano e carbono na água foram superiores ás amostragens da atmosfera, o que já era esperado conforme os estudos existentes na literatura. / This thesis investigated the microclimate, CO2 and energy fluxes patterns at a forest in floodplain of Bananal Island, with emphasis on the seasonal flooding effects in atmospheric variables and ecosystem productivity, as well as estimates of evasive water CO2 and CH4 fluxes. To carry it out, micrometeorological eddy covariance technique was associated, vertical storage CO2 estimates and measured data in a micrometeorological tower from 2004 to 2014, as well as specific campaigns for evasive fluxes measures. Although there are welldefined seasonal cycles of precipitation, air temperature and humidity in the area controlled by the radiative offer, it does not directly explain the variations in evapotranspiration when seeking for explain it by the increase in energy availability. Partitioning of the available energy points to a latent heat flux domain compared to sensible heat flux during net radiation decay periods, showing a peculiar pattern not reported in the literature. The data air temperature, rainfall, eddy CO2 and energy fluxes (LE and H) showed a possible influence of droughts that occurred on the west side of the region, in this experimental site from the east. The years 2005 and 2010 were warmer, little rainy and drier than the other years of the data series, and in 2010 had the lowest net productivity of the dry season. The flood was shown to have an important role in CO2 streams, causing the gross productivity, ecosystem respiration and the net productivity decrease, adding to the effects expected by the radiative control. The net productivity responded to the effects of flooding weeks before this start in the tower, continuing its effects until a few weeks later, with decreasing productivity. Already ecosystem respiration and gross primary productivity proved to be more sensitive to early dry season, with an interruption in the decline attributed to flooding, probably due to favoring the decomposition of organic matter suspended in the water. The results of the carbon fluxes suggest a high CO2 assimilation by forest, which requires corroboration through biometric measurements and are not, however, ruled out the reliability of the results. The results of the campaign to evasive flux measurements showed that the river is a CO2 source to the atmosphere, and both the river and the vegetated surface act as a CH4 source to the atmosphere, with a greater contribution of the vegetated surface. Methane and carbon concentrations in the water were higher ace sampling the atmosphere, which was expected as existing studies in the literature.

In response to global climate change, many important earth-systems-oriented science programs have been established in the past. One such program, the Fluxnet program, studies the response of world forests and other natural ecosystems by measuring biospheric fluxes of carbon dioxide (CO2), water vapour, and energy with eddy-covariance (EC) techniques to assess the role of world ecosystems in offsetting increases in CO2 emissions and related impacts on global climate. The EC methodology has its limitations particularly when weather is inclement and during system stoppages. These limitations create non-trivial problems by creating data gaps in the monitored data stream, diminishing the integrity of the dataset and increasing uncertainty with data interpretation. This Thesis deals with the development of a parsimonious, semi-empirical approach for gap filling of net ecosystem productivity (NEP) data. The approach integrates the effects of environmental controls on diurnal NEP. The approach, because of its limited number of parameters, can be rapidly optimized when appropriate meteorological, site, and NEP target values are provided. The procedure is verified by applying it to several gap-filling case studies, including timeseries collected over balsam fir (Abies Balsamea (L.) Mill.) forests in New Brunswick (NB), Canada and several other forests along a north-south temperaturemoisture gradient from northern Europe to the Middle East. The evaluation showed that the model performed relatively well for most sites; i.e., r2 ranged from 0.68-0.83 and modelling efficiencies, from 0.89-0.97, demonstrating the possibility of applying the model to forests outside NB. Inferior model performance was associated with sites with less than complete input datasets.