Η ερευνητική εργασία που ακολουθεί, έχει σαν στόχο, σε πρώτο επίπεδο, να μελετήσει τα διάφορα μοντέλα ηλεκτρομαγνητικής διάδοσης και σε δεύτερο πλάνο, να δωθεί μία εικόνα σχετικά με τις επιπτώσεις της μη ιονίζουσας ακτινοβολίας, που εκπέμπεται από κεραίες και ασύρματα δίκτυα, στον άνθρωπο και στον περιβάλλοντα χώρο. Στα πρώτα κεφάλαια γίνεται μία θεωρητική αναφορά στις βασικές έννοιες της ηλεκτρομαγνητικής ακτινοβολίας και στους μηχανισμούς διάδοσης της, αλλά και στις επιπτώσεις της ακτινοβολίας αυτής στον άνθρωπο. Ακολουθεί, εκτενής παρουσίαση των πιο σημαντικών θεωρητικών μοντέλων διάδοσης ραδιοσήματος εξωτερικών και εσωτερικών χώρων αντίστοιχα. Στη συνέχεια, δίνεται λεπτομερής περιγραφή των πεδιομέτρων που χρησιμοποιήθηκαν για την καταγραφή των μετρήσεων σε διάφορες περιοχές ενδιαφέροντος. Στο τελευταίο κεφάλαιο, γίνεται παρουσίαση των μετρήσεων με συγκριτικά διαγράμματα καθώς και αναφορά για το κατά πόσο οι μετρήσεις βρίσκονται εντός των ορίων ασφαλείας που τίθενται από διεθνείς οργανισμούς. / In the present work, were studied the models of the radio signal distribution at open and close area and the consequences of the non-ionized radiation, which emits from a wide variety of wirelesses systems, on human body. Initially, the basic significances of the electromagnetic radiation, the Maxwell’s equations and the mechanics of RF distribution, were shortly presented. Further emphasis at the models of the radio signal distribution, at open and close area, was given. The consequences of the electromagnetic radiation concerning basic factors of thermal and no-thermal effect were presented. An additional report of the RF safety limits, according to various international organizations, was given. For the experimental process, we used the Narda Broadband Field meter, which recorded all the frequencies of the electromagnetic spectrum and a laptop with a suitable software (NETSTUMBLER 0.40), which allows the operator of the laptop to know the exact received power coming from the specific router of the WLAN, excluding all other signals even if they belong to the same frequency of 2.4 GHz. The comparison of the experimental measurements with the theoretical, reveals the potential of each theoretical model. Furthermore, we came to the conclusion that the experiments are in the limits of RF safety.

O Eragrostis plana Nees (capim-annoni-2 ou capim annoni) é uma gramínea exótica trazida da África do Sul nos anos cinquenta e atualmente tem presença em aproximadamente 10% da área total do bioma Pampa, sendo a espécie mais invasiva desse bioma. Tendo em conta a grande capacidade desta espécie para se estabelecer em uma ampla variedade de condições ambientais, os efeitos ambientais e econômicos negativos envolvidos, bem como sua dificuldade de erradicação, é importante identificar as áreas mais suscetíveis à invasão em um futuro próximo, para assim aprimorar os planos de manejo e evitar a expansão de áreas infestadas. O presente trabalho foi desenvolvido no município de Aceguá – RS, com o objetivo de identificar quais áreas são as mais suscetíveis à invasão. Foram aplicados os modelos de distribuição de espécies MAXENT e GARP tendo como dados de entrada as variáveis ambientais calculadas a partir imagens espectrais, modelo numérico de elevação, mapa de solos e mapa de vias. Como algumas variáveis originalmente têm resolução espacial de 250 m e outras de 30 m, foi feita uma reamostragem tanto a 30 m como a 250 m para comparar os resultados dos modelos nas duas resoluções espaciais. Para diminuir o número de variáveis de entrada foi feita uma análise de correlação para eliminar as variáveis com alta correlação. Também foi feito o teste Jackknife para avaliar quais variáveis contribuem mais na modelagem espacial da distribuição do capim annoni. Os dois modelos, tanto no treinamento como na validação, nas duas resoluções espaciais, apresentam valores médios de ajuste de AUC acima de 0,7, sendo considerado um bom ajuste. Foram empregados três métodos para calcular os limiares ótimos de corte para cada um dos modelos: 1) sensibilidade igual à especificidade; 2) soma entre a sensibilidade e a especificidade máxima; Os limiares obtidos foram 42 para MAXENT_250, 39 para MAXENT_30, 69 para GARP_250 e 68 para GARP_30. Após a aplicação dos limiares, verificou-se que o modelo GARP prediz uma área maior que o MAXENT, 33,20% em comparação com 24,60% na resolução espacial de 250 m, e 35,83% contra 27,17% na resolução espacial de 30 m. Verificou-se também que o GARP possui melhor capacidade de generalização, o qual é importante para modelar espécies invasoras. Os dois modelos predizem com presença uma área comum de 21,23% e 23,94% nas resoluções espaciais de 250 m e 30 m respectivamente. As pastagens são as classes de uso que apresentam uma maior suscetibilidade à invasão de capim anonni. Ao cruzar os resultados dos modelos de suscetibilidade à invasão de capim annoni, com resolução espacial de 30 m, e as áreas de pastagens que estão sob alta pressão de pastejo, verificou-se que o modelo MAXENT consegue predizer uma suscetibilidade à invasão em 24,51% das áreas e o modelo GARP prediz 37,95% de suscetibilidade à invasão. As comparações entre as duas resoluções espaciais demonstrou que não há muitas diferenças em termos de quantificação de área, sendo que o principal ganho foi o detalhamento espacial, o qual foi obtido com um alto custo computacional. / The Eragrostis plana Nees (South African lovegrass), is an exotic grassy plant originally from South Africa, introduced in the 50s and is currently present in approximately 10% of the total area of the Pampa biome, being the most invasive species in this biome. Considering the large capacity of the South African lovegrass establishing itself in a wide variety of environmental conditions, the negative effects, both environmental and economical that it involves, as well as its difficulty of eradication, it is important to identify the invasion most susceptible areas in the near future, in order to improve the management to prevent the spread of infested areas. This research was developed in the municipality of Aceguá – RS, with the objective of identifying which areas are most susceptible to invasion. The MAXENT and GARP models of distribution of species were applied, having as input data the environmental variables calculated from spectral images, digital elevation model, soil map and road map. As some variables originally had spatial resolution of 250m and others of 30m, a resample was done at both 30m and 250m in order to compare the models results in these two spatial resolutions. To reduce the input variables amount, a correlation analysis was performed to eliminate the high correlation variables. The Jackknife test was also used to evaluate which variables contribute most to the South African lovegrass distribution spatial modeling. Both models, at the two spatial resolutions, during the training and the validation steps, present mean values of AUC adjustment above 0.7, being considered a good fit. Three methods were used to calculate the optimal thresholds for each model: 1) the sensitivity equals to the specificity; 2) the sum between sensitivity and specificity is the maximum; 3) the distance between the ROC curve and left top corner is minimum. The calculated thresholds were 42 for MAXENT_250, 39 for MAXENT_30, 69 for GARP_250 and 68 for GARP_30. After applying these thresholds, it was verified that the GARP model predicts an area greater than MAXENT, 33.20% compared to 24.60% for the spatial resolution of 250m, and 35.83% against 27.17% in the spatial resolution of 30m. It was also verified that GARP has a better generalization capacity, which is important for modeling invasive species patterns. Both models predict a common area with susceptible to invasion of 21.23% and 23.94% in spatial resolutions of 250m and 30m respectively. The grasslands are the land cover that presents a South African lovegrass invasion greater susceptibility. Cross-referencing the susceptibility invasion models with the overgrazing areas at 30m of spatial resolution, it was verified that the model MAXENT can predict a susceptibility to invasion in 24.51% of the areas and the GARP model predicts 37.95% susceptibility to invasion. Comparisons between the two spatial resolutions showed that there are not many differences in terms of area quantification, where the main gain was spatial detailing, which was obtained with a high computational cost.

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / Knowing the distributional patterns and the mechanisms that lead to the actual levels of diversity and richness is a challenge given the ecosystems threats. Understanding how the threats coming from the human actions can affect this diversity is the key to protect ecosystems and species. This study toward (i) investigate the richness distribution patterns of the genus Aegla in four freshwater ecoregions in South America, as well as (ii) the mechanisms that lead to that distribution, and (iii) the human influences in these freshwater ecosystems. The study area comprised four freshwater ecoregions: Upper Uruguay, Low Uruguay, Laguna dos Patos, and Tramandaí-Mampituba. Through data from five scientific collections, UFRGS, UFSM, FZB-RS, PUC-RS, and URI-Erechim, we compiled 30 species of Aegla. We associated the species distribution in four ecoregions to the distributional patterns, conservation status, environmental and spatial variables, rugosity, and land cover. The protected area network not effectively protects the aquatic ecosystems. The species richness is associated to average values of rugosity. Finally, the species occurrence areas exhibit land cover categories of agriculture and urban areas. We consider the levels of endemism inside the protected area network are key factor to conservation of aquatic ecosystems. Historic process linked to the river network formation, in a spatial context, is an important approach to understand the distributional pattern of some freshwater groups. These patterns are associated to spatial questions, following the increasing of agriculture and urban lands, are committing the diversity in freshwater environments. / Conhecer os padrões de distribuição e os mecanismos que levam aos níveis de diversidade e riqueza atuais são desafios dado à ameaça dos ecossistemas. Entendermos como as ameaças oriundas das ações do homem podem impactar essa diversidade é a chave para conservarmos ecossistemas e espécies. Esse estudo teve como objetivo (i) investigar os padrões de distribuição da riqueza do gênero Aegla em quatro ecorregiões de água doce da América do Sul, bem como, (ii) quais os mecanismos que levaram a tal distribuição, e por fim, (iii) a influência das ações do homem nos ecossistemas de água doce. A área de estudo compreendeu quatro ecorregiões de água doce: Alto Uruguai, Baixo Uruguai, Laguna dos Patos e Tramandaí-Mampituba. Através de registros de cinco coleções científicas, UFRGS, UFSM, FZB-RS, PUC-RS e URI-Erechim, obtivemos dados de 30 espécies do gênero Aegla. Padrões de distribuição, status de conservação, variáveis ambientais e espaciais, rugosidade e cobertura do solo foram analisadas e associadas à distribuição das espécies nas ecorregiões. Ficou claro que a rede de unidades de conservação não protege efetivamente os ecossistemas aquáticos. Por sua vez, a riqueza de espécies está associada a valores médios de rugosidade do relevo. E, finalmente, as áreas de ocorrência das espécies apresentaram cobertura do solo com áreas agrícolas e urbanas. Considerarmos os níveis de endemismos dos grupos nas redes de unidades de conservação é um fator chave para proteção efetiva dos ecossistemas aquáticos. Processos históricos ligados à formação das redes de rios, no contexto espacial, é a chave para entendermos padrões de distribuição de alguns grupos de água doce. Esses padrões de distribuição associados às questões espaciais, ligados ao crescente aumento das áreas de agricultura e urbana, estão comprometendo a diversidade de ambientes dulcícolas.

O Eragrostis plana Nees (capim-annoni-2 ou capim annoni) é uma gramínea exótica trazida da África do Sul nos anos cinquenta e atualmente tem presença em aproximadamente 10% da área total do bioma Pampa, sendo a espécie mais invasiva desse bioma. Tendo em conta a grande capacidade desta espécie para se estabelecer em uma ampla variedade de condições ambientais, os efeitos ambientais e econômicos negativos envolvidos, bem como sua dificuldade de erradicação, é importante identificar as áreas mais suscetíveis à invasão em um futuro próximo, para assim aprimorar os planos de manejo e evitar a expansão de áreas infestadas. O presente trabalho foi desenvolvido no município de Aceguá – RS, com o objetivo de identificar quais áreas são as mais suscetíveis à invasão. Foram aplicados os modelos de distribuição de espécies MAXENT e GARP tendo como dados de entrada as variáveis ambientais calculadas a partir imagens espectrais, modelo numérico de elevação, mapa de solos e mapa de vias. Como algumas variáveis originalmente têm resolução espacial de 250 m e outras de 30 m, foi feita uma reamostragem tanto a 30 m como a 250 m para comparar os resultados dos modelos nas duas resoluções espaciais. Para diminuir o número de variáveis de entrada foi feita uma análise de correlação para eliminar as variáveis com alta correlação. Também foi feito o teste Jackknife para avaliar quais variáveis contribuem mais na modelagem espacial da distribuição do capim annoni. Os dois modelos, tanto no treinamento como na validação, nas duas resoluções espaciais, apresentam valores médios de ajuste de AUC acima de 0,7, sendo considerado um bom ajuste. Foram empregados três métodos para calcular os limiares ótimos de corte para cada um dos modelos: 1) sensibilidade igual à especificidade; 2) soma entre a sensibilidade e a especificidade máxima; Os limiares obtidos foram 42 para MAXENT_250, 39 para MAXENT_30, 69 para GARP_250 e 68 para GARP_30. Após a aplicação dos limiares, verificou-se que o modelo GARP prediz uma área maior que o MAXENT, 33,20% em comparação com 24,60% na resolução espacial de 250 m, e 35,83% contra 27,17% na resolução espacial de 30 m. Verificou-se também que o GARP possui melhor capacidade de generalização, o qual é importante para modelar espécies invasoras. Os dois modelos predizem com presença uma área comum de 21,23% e 23,94% nas resoluções espaciais de 250 m e 30 m respectivamente. As pastagens são as classes de uso que apresentam uma maior suscetibilidade à invasão de capim anonni. Ao cruzar os resultados dos modelos de suscetibilidade à invasão de capim annoni, com resolução espacial de 30 m, e as áreas de pastagens que estão sob alta pressão de pastejo, verificou-se que o modelo MAXENT consegue predizer uma suscetibilidade à invasão em 24,51% das áreas e o modelo GARP prediz 37,95% de suscetibilidade à invasão. As comparações entre as duas resoluções espaciais demonstrou que não há muitas diferenças em termos de quantificação de área, sendo que o principal ganho foi o detalhamento espacial, o qual foi obtido com um alto custo computacional. / The Eragrostis plana Nees (South African lovegrass), is an exotic grassy plant originally from South Africa, introduced in the 50s and is currently present in approximately 10% of the total area of the Pampa biome, being the most invasive species in this biome. Considering the large capacity of the South African lovegrass establishing itself in a wide variety of environmental conditions, the negative effects, both environmental and economical that it involves, as well as its difficulty of eradication, it is important to identify the invasion most susceptible areas in the near future, in order to improve the management to prevent the spread of infested areas. This research was developed in the municipality of Aceguá – RS, with the objective of identifying which areas are most susceptible to invasion. The MAXENT and GARP models of distribution of species were applied, having as input data the environmental variables calculated from spectral images, digital elevation model, soil map and road map. As some variables originally had spatial resolution of 250m and others of 30m, a resample was done at both 30m and 250m in order to compare the models results in these two spatial resolutions. To reduce the input variables amount, a correlation analysis was performed to eliminate the high correlation variables. The Jackknife test was also used to evaluate which variables contribute most to the South African lovegrass distribution spatial modeling. Both models, at the two spatial resolutions, during the training and the validation steps, present mean values of AUC adjustment above 0.7, being considered a good fit. Three methods were used to calculate the optimal thresholds for each model: 1) the sensitivity equals to the specificity; 2) the sum between sensitivity and specificity is the maximum; 3) the distance between the ROC curve and left top corner is minimum. The calculated thresholds were 42 for MAXENT_250, 39 for MAXENT_30, 69 for GARP_250 and 68 for GARP_30. After applying these thresholds, it was verified that the GARP model predicts an area greater than MAXENT, 33.20% compared to 24.60% for the spatial resolution of 250m, and 35.83% against 27.17% in the spatial resolution of 30m. It was also verified that GARP has a better generalization capacity, which is important for modeling invasive species patterns. Both models predict a common area with susceptible to invasion of 21.23% and 23.94% in spatial resolutions of 250m and 30m respectively. The grasslands are the land cover that presents a South African lovegrass invasion greater susceptibility. Cross-referencing the susceptibility invasion models with the overgrazing areas at 30m of spatial resolution, it was verified that the model MAXENT can predict a susceptibility to invasion in 24.51% of the areas and the GARP model predicts 37.95% susceptibility to invasion. Comparisons between the two spatial resolutions showed that there are not many differences in terms of area quantification, where the main gain was spatial detailing, which was obtained with a high computational cost.

Made available in DSpace on 2014-07-29T16:21:18Z (GMT). No. of bitstreams: 1 Dissertacao Nayara P R de Sousa.pdf: 966173 bytes, checksum: 6479d4ecf0e29c925ca2a8e6c8b59c9d (MD5) Previous issue date: 2011-03-27 / The climate can be considered an extremely important factor in vegetation distribution and its characteristics in a global context. Climate changes affect the global distribution of vegetation in the distant past and probably will affect in the future. Spatial distribution models of species (SDMs), also known as niche models are one of the best current tools for predicting climate-induced changes on the distribution of species. In general, studies of the consequences of climate changes on the distribution of biomes include only the geographic distribution of the biome or the species are analyzed individually. The availability of climatic and ecological data on a large scale, in addition to more efficient procedures for obtaining data from geographic information systems, optimization programs and greater computing power favor the process of modeling the potential distribution, and broaden the effectiveness of results available by the SDMS. The main objective of this study is to evaluate whether there is a shift in the hierarchical structure of future distributions of biome, phytoeeological regions and plants species of the biome under the effect of climate changes. Consequently, we evaluate some effects of climate changes on the pattern of species richness and pattern of future distributions of the biome, phytoeeological regions and species. This study shows that there is a hierarchical structure in the response of vegetation distribution faces climate changes predictions for the year 2080 in the Brazilian Cerrado. In general, in the three scales studied their distributions are moving toward to southeast of Brazil, thus this region is replaced by a diversity gain while the rest of the local Cerrado suffers from the impoverishment of their diversity. This study also shows that in the near future, the Cerrado species will show habitat loss, due to both the loss of fragments and area reduction of these. / O clima pode ser considerado um fator extremamente importante na distribuição da vegetação e suas características em um contexto global. Mudanças climáticas afetaram a distribuição global da vegetação em um passado distante e, provavelmente, afetarão no futuro. Os modelos de distribuição geográfica potencial de espécies (spatial distribution model SDM), conhecidos também como modelos de nicho, são uma das melhores ferramentas atuais para predizer mudanças induzidas pelo clima sobre a distribuição das espécies. Em geral, estudos sobre as consequências das mudanças climáticas na redistribuição dos biomas englobam apenas a distribuição geográfica do bioma ou analisam as espécies individualmente. A disponibilidade de dados climáticos e ecológicos em larga escala, além dos procedimentos mais eficientes de obtenção de dados a partir de sistemas de informação geográfica, programas de otimização e maior poder computacional favorecem o processo de modelagem de distribuição potencial, além de ampliarem a eficiência dos resultados disponíveis pelos SDMs. O objetivo principal deste trabalho é avaliar se existe uma estrutura hierárquica no deslocamento das distribuições futuras do bioma Cerrado, das regiões fitoecológicas e das espécies de plantas do bioma, sob o efeito de mudanças climáticas. Consequentemente, pode-se evidenciar alguns efeitos dessas alterações climáticas sob o padrão de riqueza das espécies e o padrão das distribuições geográficas futuras do bioma, das regiões fitoecológicas e das espécies. Este estudo demonstrou que não existe uma estrutura hierárquica na resposta da distribuição vegetacional frente às previsões de mudanças climáticas para o ano de 2080 no Cerrado brasileiro. Em geral, nas três escalas estudadas as respectivas distribuições deslocam-se para o sudeste do Brasil, de modo que essa região passa a ter um ganho de diversidade local enquanto o restante do Cerrado será afetado com o empobrecimento de sua diversidade. Este estudo aponta ainda, que num futuro próximo, as espécies do Cerrado serão afetadas com a perda de habitat, decorrente tanto da perda de fragmentos como da redução de área destes.

La mise en place d'objectifs de conservation adéquats repose sur la définition d'états de référence appropriés pour la distribution et l'abondance des espèces. Cependant, l'étendue des impacts cumulés de l'homme sur les écosystèmes est aujourd'hui largement sous-estimée. Dans ce projet, je m'intéresse aux opportunités qu'offre l'utilisation de données historiques combinées à différentes méthodes analytiques pour définir ces états de référence ainsi qu'aux défis posés par ce type d'approche. Des données de présence ont été recueillies pour sept espèces de cétacés et trois espèces de pinnipèdes à partir de sources archéologiques, historiques et industrielles, révélant des réductions dans la distribution et l'abondance des espèces depuis la préhistoire à nos jours. Des modèles de distribution d'espèces ont été développés pour cinq espèces de cétacés, combinant des données de chasse baleinière du 19ème siècle à des variables environnementales afin d'estimer la distribution historique des espèces avant qu'elles n'aient été chassées. J'ai obtenu pour la baleine franche de l'Atlantique Nord (Eubalena glacialis) une estimation détaillée de sa distribution et de son abondance avant qu'elle ne soit exploitée, en extrapolant des connaissances sur la distribution et l'abondance d'une espèce congénérique, la baleine franche du Pacifique Nord (E. japonica). Ces résultats suggèrent que la baleine franche de l'Atlantique Nord occupe une portion réduite de sa distribution historique, et que son abondance actuelle ne représente qu'une infime portion (<5%) de son abondance passée. Plus généralement, ces résultats soulignent l'importance de considérer des données historiques pour comprendre le niveau d'impact par l'homme sur les espèces, évaluer leur niveau de déplétion et renseigner leur potentiel de rétablissement dans l'avenir. / Relevant baselines on the historical distribution and abundance of species are needed to support appropriate conservation targets for depleted species, but the full scale of cumulative human impacts on ecosystems is highly underestimated. In this project, I investigated the challenges and opportunities of combining historical data with analytical methods to improve these historical baselines. Occurrence data from archaeological, historical and industrial sources were reviewed for seven cetacean and three pinniped species, revealing range contractions and population depletions from prehistorical times to today. For five whale species, I used species distribution modelling to combine 19th Century whaling records with environmental data, to estimate pre-whaling distributions. For the highly depleted North Atlantic right whale, (Eubalaena glacialis), I obtained a detailed estimate of pre-whaling distribution and abundance by inferring from the historical distribution and abundance of its congeneric North Pacific right whale (E. japonica). These results suggest that the North Atlantic right whale occupies a small fraction of its historical range and that its current population represents <5% of its historical abundance, with implications for the management, monitoring and conservation targets of this species. More generally, these results emphasize the utility of considering historical data to understand the extent to which species have been impacted by humans, assess their current level of depletion, and inform the options available for their future recovery.

This dissertation presents research on the value of using different sources of data to explore the factors determining invasiveness of introduced species. The research draws upon the availability of data on the historical trial plantings of alien species and other sources. The focus of the study is on Australian Acacia species as a taxon introduced into southern Africa (Lesotho, South Africa and Swaziland). The first component of the study focused on understanding the factors determining introduction outcome of species in historical trial plantings and invasion success of Australian Acacia species using Species Distribution Models (SDMs) and classification tree techniques. SDMs were calibrated using the native range occurrence records (Australia) and were validated using results of 150 years of South African government forestry trial planting records and invaded range data from the Southern African Plant Invaders Atlas. To understand factors associated with survival (‘trial success’) or failure to survive (‘trial failure’) of species in historical trial plantings, classification and regression tree analysis was used. The results indicate climate as one of the factors that explains introduction and/or invasion success of Australian Acacia species in southern Africa. However, the results also indicate that for ‘trial failures’ there are factors other than climate that could have influenced the trial outcome. This study emphasizes the need to integrate data on whether the species has been recorded to be invasive elsewhere with climate matching for invasion risk assessment. The second component of the study focused on understanding the distribution patterns of Australian Acacia species that are not known as invasive in southern Africa. The specific aims were to determine which species still exist at previously recorded sites and determine the current invasion status. This was done by collating data from different sources that list species introduced into southern Africa and then conducting revisits. For the purpose of this study, revisits means conducting field surveys based on recorded occurrences of introduced species. The known occurrence data for species on the list were obtained from different data sources and various invasion biology experts. As it was not practical to do revisits for all species on the list, three ornamental species (Acacia floribunda, A. pendula and A. retinodes) were selected as part of the pilot study for the conducted revisits in this study. Acacia retinodes trees were not found during the revisits. The results provided data that could be used to characterize species based on the Blackburn et al., (2011) scheme. However, it is not clear whether observed Acacia pendula or A. floribunda trees will spread away from the sites hence the need to continuously monitor sites for spread. The methods used in this research establish a protocol for future work on conducting revisits at known localities of introduced species to determine their population dynamics and thereby characterize the species according to the scheme for management purposes. / Dissertation (MSc)--University of Pretoria, 2014. / National Research Foundation (NRF) / Zoology and Entomology / MSc (Zoology) / Unrestricted

Estamos vivenciando o que pode ser considerado como o sexto evento de extinção global da Biodiversidade. Os anfíbios são os vertebrados mais ameaçados do mundo e ainda o número de espécies ameaçadas pode estar subestimado, pois 22% estão classificadas na categoria Dados Insuficientes (DD). O Brasil possui alta riqueza de anfíbios, porém inúmeras lacunas de conhecimento dificultam a elaboração de listas completas e prejudica a avalição do estado de conservação e o planejamento da conservação dos anfíbios brasileiros. Assim, visando contribuir efetivamente no direcionamento das ações de conservação dos anfíbios brasileiros avaliamos a influência da atitude de especialistas na classificação das espécies, e também identificamos e adaptamos ferramentas para melhor explorar os dados de distribuição disponíveis sobre as espécies DD. Foi proposto um framework de modelagem adaptativa para lidar com a escassez de dados de distribuição destas espécies e incluir a capacidade de dispersão nos modelos de distribuição de espécies. Além disso, para preencher lacunas de conhecimento dos aspectos biológicos e ecológicos das espécies de anfíbios da Mata Atlântica considerados como DD foi realizado busca na literatura e em coleções científicas, bem como a indicação de áreas prioritárias para obter informações adicionais sobre essas espécies. Identificamos que a linha de atuação dos avaliadores influencia na determinação da categoria DD, aumentando ou reduzindo a probabilidade de classificar uma espécie nesta categoria. Com isso, ressalta-se a necessidade de compor equipes multidisciplinares para avaliar o estado de conservação das espécies. O framework aqui proposto tem o potencial de inovar o processo de modelagem com poucos dados disponíveis a partir da inclusão de um dos aspectos mais difíceis de mensurar, a capacidade de dispersão da espécie. O conjunto de informações sobre as espécies DD da Mata Atlântica aumentou consideravelmente com o levantamento de dados e os modelos de distribuição de espécies, e ainda foi possível obter áreas prioritárias para aumentar o conhecimento empírico em mais de 180 municípios. Dentre as categorias de unidades de conservação mais frequentes como áreas prioritárias, destacam-se as Reservas Particulares do Patrimônio Natural nas regiões nordeste e sul, e as Áreas de Preservação permanente na região sudeste. Os resultados deste estudo contribuem efetivamente para o processo de avaliação do estado de conservação dos anfíbios brasileiros, especialmente das espécies DD da Mata Atlântica, de modo que possa ser utilizado no planejamento sistemático da conservação deste grupo. As abordagens utilizadas neste estudo podem servir de modelos para outras espécies ou grupos taxonômicos, reduzindo lacunas e incertezas no processo de avaliação do estado de conservação de espécies. / We are experiencing what could be considered as the sixth global biodiversity extinction event. Amphibians are the most threatened vertebrates in the world, and still the number of endangered species might be underestimated because 22% are classified in the category data deficient (DD). Brazil has a high richness of amphibians, but several knowledge gaps make it difficult to compile complete lists and impair the evaluation of the conservation status and the conservation planning of Brazilian amphibians. Thus, in order to contribute effectively in directing conservation actions for Brazilian anphibians we evaluated the influence of experts attitude on species classification, and also identified and adapted tools to better explore the available data on DD species. It was proposed an adaptive modeling framework to deal with the scarcity of these species distribution data and include dispersion capacity in species distribution modeling. In addition, to fill knowledge gaps of biological and ecological aspects of amphibian species of the Atlantic forest considered as DD literature search and in scientific collections were conducted, as well as the indication of priority areas for gathering additional information about these species. We identified that the line of action of the evaluators influences the determination of the DD category, increasing or reducing the probability of classifying a species in this category. Thereby, it`s emphasized the need to compose multidisciplinary teams to assess species conservation status. The framework proposed here has the potential to innovate the modeling process through the inclusion of one of the most difficult aspects to be measured, the species dispersion capacity. The set of information about DD species of the Atlantic forest has increased considerably with the survey and the species distribution models, and it was still possible to obtain priority areas to increase the empirical knowledge in more than 180 municipalities. Among the categories of protected areas most frequent as priority areas, Private Reserves stands out in the Northeast and South regions and Areas of Permanent Preservation the Southeast. Results of this study contribute effectively to the process conservation status assessment of amphibians, especially DD species from the Atlantic forest, so that it could be used in conservation systematic planning of this group. The approaches used in this study could serve as models for other species or taxonomic groups, reducing gaps and uncertainties in the process of evaluation of species conservation status.

Les modifications environnementales qui affectent aujourd'hui les milieux marins recouvrent des problématiques scientifiques et sociétales majeures, d'autant que ces changements devraient s'accélérer au cours du 21ème siècle. Comprendre et anticiper la réponse de la biodiversité marine à ces changements représente un enjeu scientifique d'actualité. Les approches biogéographiques et macroécologiques constituent un cadre scientifique dans lequel il est possible d'étudier, de décrire, et de comprendre les motifs de distribution des espèces à large échelle et d'estimer leur évolution possible face aux changements environnementaux. C'est notamment le cas dans l'océan Austral où les effets du changement climatique se font déjà sentir et où les modifications environnementales associées pourraient avoir des effets profonds sur la structure et le fonctionnement des écosystèmes. Malgré de récents efforts d'échantillonnage, nos connaissances sur la distribution des espèces dans l’océan Austral comptent encore de nombreuses lacunes attribuables au caractère récent des découvertes, à l'isolement et à l'éloignement de cet océan d'accès difficiles. Dans ce contexte, les objectifs de cette thèse consistaient à mieux comprendre les motifs de distribution d'espèces à l’échelle de l’océan Austral, à mettre en évidence les facteurs qui en sont à l’origine et enfin, à évaluer l’impact du changement climatique sur leur distribution. Pour cela, différents types de modèles de niche écologique (MNE) ont été employés. Les échinides (oursins), organismes communs des communautés benthiques de l’océan Austral ont servi de modèle d'étude pour ce travail. / Current environmental changes, which impact marine environments, cover major scientific and societal issues, especially as these environmental changes are expected to accelerate along the 21st century. Understanding and forecasting the response of marine biodiversity to these changes is a pregnant scientific issue. Biogeographic and macroecological approaches provide a scientific framework for that purpose. They allow describing and understanding species distribution patterns at large spatial scale as well as estimating their potential shift with regards to environmental change. This is particularly true in the Southern Ocean, where the effects of climate change are already occurring and where environmental changes could have a deep and manifold impact on the structure and functioning of marine ecosystems. Despite recent sampling efforts, our knowledge of the Southern Ocean species distributions still faces many shortcomings due to the rather recent discovery of this ocean, its isolation and remoteness along with difficult access conditions. In this context, the aims of this thesis are to better understand the factors that drive species distribution patterns at the Southern Ocean scale, and to assess the impact of climate change on their distribution. For this purpose, different types of Species Distribution Models (SDM) have been used. Echinoids (sea urchins), which are common organisms of benthic communities in the Southern Ocean, have been used as a biological model for this work.

What explains the geographic distribution of pathogens? Better understanding and characterising disease patterns will help scientists to identify areas likely to host future epidemics and epizootics and to prioritise surveillance and intervention. However, the use of disease surveillance data to assess the risk of transmission and generate risk maps raises conceptual and methodological issues. Indeed, pathogens and more particularly viruses aren't ”species” like others that live in the open environment and must be studied with methods and concepts of their own. Avian influenza (AI), a disease caused by a virus infecting bird populations, has been selected to study these issues. AI has a major economic impact on the poultry industry in many countries, raises concerns of livelihood in low and middle-income countries, and represents a major concern for human health. The aim of this PhD thesis was to improve the knowledge on the spatial epidemiology of AI in different settings and conditions (i). For this, recent epizootics caused by the subtypes A (H5N1) and A (H7N9) were selected as case studies. First, highly pathogenic subtypes of the A (H5N1) virus have been studied in poultry farms (ducks and chickens) at different spatial scales: at the continental scale and the regional scale in the Mekong (Cambodia, Laos, Vietnam, Thailand) and the Nile Delta in Egypt. All these cases occurred between 2003, the date on which the virus starts to spread outside China, and 2015; the HPAI A (H5N1) subtypes are still reported today in many countries. Human infections caused by the A (H7N9) virus in China from March 2013 to 2017 were also studied. Studied different AI subtypes at different spatial scales within different host species also allowed to develop a conceptual model of AI transmission and to discuss the issue of the transferability of results in epidemiology (ii). Lastly, this PhD thesis leads to a discussion about the transfer of methods and concepts from ecology to spatial epidemiology, with a particular emphasis on their possible limitations (iii). / Doctorat en Sciences agronomiques et ingénierie biologique / info:eu-repo/semantics/nonPublished