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.

The convergence of three young scientific disciplines (ecology, geospatial sciences, and remote sensing) has generated unique advancements in wildlife research by connecting ecological data with remote sensing data through the application of geospatial techniques. Ecological datasets may contain spatial and sampling biases. By using geospatial techniques, datasets may be useful in revealing landscape scale (e.g., statewide) trends for wildlife populations, such as population recovery and human-wildlife interactions. Specifically, black bear populations across North America vary greatly in their degree of distribution stability. The black bear population in Michigan may be considered stable or secure, whereas the population in Missouri is currently recolonizing. The focus of the research in this dissertation is to examine the ecological and anthropogenic impacts 1) on human-black bear interactions in Michigan (see Chapter 2) and 2) on black bear presence in Missouri (see Chapter 3), through the use of black bear reports provided by the public to the state wildlife agencies. By using generalized linear modeling (GLM) and maximum entropy (MaxEnt), I developed spatial distribution models of probability of occurrence/presence for the 2 study areas (Michigan and Missouri). For the Missouri study, I quantified the spatiotemporal shifts in the probability of bear presence statewide. The results from my statewide studies corroborate previous local-scale research based on rigorous data collection. Overall, human-black bear interactions (e.g., wildlife sightings, conflicts), while very dynamic, appear greatest in forested and rural areas where the preferred habitat for black bears (i.e., forest) intersects with low density anthropogenic activities. As both human and black bear populations continue to expand, it is reasonable to expect human-black bear interactions to spatiotemporally increase across both study areas. The results from my studies provide wildlife managers with information critical to management decisions such as harvest regulations and habitat conservation actions across the landscape and through time. The ability to detect and monitor ecological changes through the use of geospatial techniques can lead to insights about the stressors and drivers of population-level change, further facilitating the development of proactive causeocused management strategies.