abstract: Although many studies have identified environmental factors as primary drivers of bird richness and abundance, there is still uncertainty about the extent to which climate, topography and vegetation influence richness and abundance patterns seen in local extents of the northern Sonoran Desert. I investigated how bird richness and abundance differed between years and seasons and which environmental variables most influenced the patterns of richness and abundance in the Greater Phoenix Metropolitan Area. I compiled a geodatabase of climate, bioclimatic (interactions between precipitation and temperature), vegetation, soil, and topographical variables that are known to influence both richness and abundance and used 15 years of bird point count survey data from urban and non-urban sites established by Central Arizona–Phoenix Long-Term Ecological Research project to test that relationship. I built generalized linear models (GLM) to elucidate the influence of each environmental variable on richness and abundance values taken from 47 sites. I used principal component analysis (PCA) to reduce 43 environmental variables to 9 synthetic factors influenced by measures of vegetation, climate, topography, and energy. I also used the PCA to identify uncorrelated raw variables and modeled bird richness and abundance with these uncorrelated environmental variables (EV) with GLM. I found that bird richness and abundance were significantly different between seasons, but that richness and winter abundance were not significantly different across years. Bird richness was most influenced by soil characteristics and vegetation while abundance was most influenced by vegetation and climate. Models using EV as independent variables consistently outperformed those models using synthetically produced components from PCA. The results suggest that richness and abundance are both driven by climate and aspects of vegetation that may also be influenced by climate such as total annual precipitation and average temperature of the warmest quarter. Annual oscillations of bird richness and abundance throughout the urban Phoenix area seem to be strongly associated with climate and vegetation. / Dissertation/Thesis / Masters Thesis Applied Biological Sciences 2019

Submitted by Valquíria Barbieri (kikibarbi@hotmail.com) on 2018-04-05T22:00:26Z No. of bitstreams: 1 DISS_2014_Luana Aparecida Gomes de Arruda.pdf: 854132 bytes, checksum: e5dce680d3fc443608aec08b5e456321 (MD5) / Approved for entry into archive by Jordan (jordanbiblio@gmail.com) on 2018-04-23T18:21:48Z (GMT) No. of bitstreams: 1 DISS_2014_Luana Aparecida Gomes de Arruda.pdf: 854132 bytes, checksum: e5dce680d3fc443608aec08b5e456321 (MD5) / Made available in DSpace on 2018-04-23T18:21:48Z (GMT). No. of bitstreams: 1 DISS_2014_Luana Aparecida Gomes de Arruda.pdf: 854132 bytes, checksum: e5dce680d3fc443608aec08b5e456321 (MD5) Previous issue date: 2014-12-02 / Pesquisas em campo voltadas para conservação de espécies são necessárias, porém muitas vezes são limitadas, onerosas e trabalhosas. Uma ferramenta que pode ser utilizada para minimizar estes problemas é a Modelagem Preditiva de Distribuição Potencial de Espécies (MPDPE), que permite estimar áreas potenciais de ocorrência atuais e futuras e que vem recebendo destaque em estudos conservacionistas, pois pode ser utilizada com espécies raras ou que estão sofrendo algum grau de ameaça. No presente estudo, a MPDPE foi utilizada para conhecer a distribuição e prever o efeito potencial de mudanças climáticas sobre a distribuição da perereca Phyllomedusa centralis, que possui distribuição conhecida restrita a poucas localidades no estado de Mato Grosso, Brasil. Os modelos foram desenvolvidos com o método de entropia máxima com o auxilio do programa MaxEnt, utilizando variáveis bioclimáticas atuais e futuras. Os modelos de predição de distribuição atual e de cenários futuros obtiveram elevados valores da área sob a curva operador-receptor e a validação apontou alta precisão na qualidade do modelo. Em todos os modelos, a variável ambiental com maior porcentagem de contribuição foi a precipitação. Todos os modelos apresentaram previsão de aumento nas áreas de distribuição potencial em comparação com o modelo atual de distribuição. Apesar de apresentar limitações, o modelo de distribuição potencial é relevante e pode ajudar no planejamento e gestão de reservas, descoberta de novas populações e manejo de espécies, identificação de áreas prioritárias para conservação e definição de onde é necessária a restauração de habitats. / Field surveys aimed at the conservation of species are necessary, but are often limited, costly and onerous. A tool that can be used to minimize these problems is the Predictive Modeling of Potential Species Distribution (PMPSD), which allows estimating current and future areas of potential occurrence and has received attention from conservationists studies, because it can be used with rare species or who are suffering some degree of threat. In the present study PMPSD was used to determine the distribution and predict the potential effect of climate change on the distribution of tree frog Phyllomedusa centralis, which has restricted distribution to a few localities in the state of Mato Grosso, Brazil. The models were developed with maximum entropy method with the aid of the MaxEnt program using current and future bioclimatic variables. The prediction models of current distribution and future scenarios had higher Area Under the receiver-operator Curve values and the validation showed high accuracy of the model quality. In all models the environmental variable with highest percentage of contribution was precipitation. All models showed increased areas of potential distribution compared with the current distribution model. Despite the limitations, the model of potential distribution is important and can help in planning and management of reserves, discovery of new populations, identification of priority areas for conservation, and definitions of regions to habitat restoration.