The Effects Of Urban Green Space Pattern On Birds Community

Urban green space is one of the important parts of urban ecosystem, it is also significant habitats for birds and other animals, and it plays a vital role in urban biodiversity protection. The function of urban green space was affected by the spatial pattern, but rapid urbanization changed it by reduced the urban green spaces, and this significantly influenced urban birds community. A lot of researches both at home and abroad have been conducted on this subject to explore the influence that the changed urban green space pattern on the bird community. In this thesis, we take the14green space patches which were inside the second road of Jinan city as examples, with the help of RS、GIS and field survey, study the effects of urban green space on birds community.The first chapter was introduction. Illustrated the background and meaning of the thesis, defined the study area and research object, and constructed the research idea and framework. The second chapter was the domestic and foreign literature review. Based on the causes of urban green space pattern, we summarized the effects of urban green space pattern’s non-biological attributes, biological attributes, and human attributes on birds community, and reviewed the domestic and foreign researches. The third chapter was data and research method. The data, research method and technology used in this thesis were presented. The fourth chapter was the analysis of urban green space pattern. Built the indicator system of urban green space pattern, then analysis the urban green space based on it. The fifth chapter was the feature analysis of birds community. Chose the birds survey method based on review, analysis of the avian community’s feature based on the built indicator system. The sixth chapter was the effects of the urban green space pattern on avian community. Make the key factors of urban green space pattern which affecting the birds community clear by using the correlation analysis, based on this, build the regression model among them. The seventh chapter was conclusion and discussion. Summarized the main conclusions and innovations, discussed the shortages in the thesis.Results showed that:(1) There are certain differences in human properties, non-biological properties and biological properties of urban green space pattern.(2) the features of avian community are as follows, surveyed575bird individuals belong to7orders,12families,17species. From the species composition, the numbers of PASSERIFORMES is a large part, and the others such as CICONIFORMES, ANSERIFORMES, PICIFORMES, CHARADRIIFORMES is relative small. From the Flora type, the number of Palaearctic species is the most, the Japan species is second, the Widespread species is the least. From residence type, the Resident species has the largest number, the Summer resident species in the second place, however the Migrant species is relative small, winter resident is no record. Form birds community structure, there was difference in abundance of bird individuals, abundance of bird species, Simpson diversity index, Shannon-Wiener diversity index and Pielou evenness.(3) the relationship between urban green space pattern and birds community shows that:The DIVISION, percentage of construction area, percentage of green area, vegetation diversity, herb diversity, volume and passenger are the main factors influencing avian community. Constructed the multiple linear regression model between the identified key factors of urban green space pattern and Simpson diversity index, Shannon-Wiener diversity index, Pielou evenness, while considering the regression result.In general, the main innovations showed that:(1) Constructed the urban green space pattern evaluation index system creatively from the non-biological properties, biological properties and human properties, it is helpful to analysis of urban green space pattern comprehensive and objectively.(2) Chose patch and landscape two scales when built the biological properties index system, taking the scaling of the landscape index into account. Made up the shortage of the scale deduction in this aspect by using the moving window method and center point value sampling way to connect the patch and landscape scale.(3) Identified the key factors of urban green space affecting the avian community by the Spearman correlation analysis.(4) Constructed the quantitative relation model between factors of urban green space pattern and avian community feature index use the multiple linear regression method based on the identified key factors of urban green space.