| Summary: | 碩士 === 國立中興大學 === 水土保持學系所 === 97 === Waterfowl is one of the most important ecological bio-indexes and human activities would greatly affect amounts of waterfowl with its environmental habitat by pollution. Air quality probably is one of the key factors for waterfowl secession. Therefore related to this issue, this study focus on following three objectives: (1) to apply time series models to understand temporal variation of waterfowl species in Da-du estuary, at central part of Taiwan, (2) to simulate air pollution data of the habitat by the 26 geostatistical methods and finally (3) to discuss the mechanism of species variation with air quality by multivariate analysis. In time series analysis, a multiplicative decomposition method as well as additive decomposition method has been adapted to determine and evaluate the species secession, including long-term, seasonal, circular, and irregular changes. Geostatistics was applied to estimate air quality data, categorized by 5 groups of methods, including of mathematical, distance, polygon, Arc View and Surfer method. The estimated values were evaluated by error sum of square (ESS). For effectiveness analysis of relationship between air quality and waterfowl species, descriptive statistics, simple regression, multiple regression and principal component analysis were adapted.
In the results of time series models, the two methods indicated similar outcomes: (1) both were shown a long-term trend (T) decreased with time (t), as following equations, T = 61.575586 - 0.04532t for multiplicative decomposition method, T = 61.638312 - 0.046083t for additive decomposition method; (2) both models all indicate there are two seasonal high peaks in April and November each year; and (3) a circular change, every two years. Both methods were reasonable well to present the waterfowl species changes numerically. For geostatistical method selection, the polynomial method in Kriging group exhibited the best result and by this method we estimate the air quality for the study waterfowl habitat. In the results of multivariate analysis, PM10 and NOx are the most related parameters for the mechanism of waterfowl species variation.
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