碩士 / 國立成功大學 / 水利及海洋工程學系 / 102 / Recently, more and more people realize the importance of Ecology. For river restoration, ecological engineering projects that providing more suitable habitats for fish community are being designed. To sustain fish population and maintain biodiversity, understanding the relationship between fish community and physical habitat of rivers plays an important role.
This study proposes a simplified method to estimate the mesohabitat composition that would favor members of a given set of fish species. Sampling data were collected form HouKu River and WuGouShui River, Taiwan. Using an autecology matrix to identify the critical environmental factors for fish and fuzzy control theory which including depth and velocity as inputs to classify habitats as shallow pool, shallow riffle, deep pool, and deep riffle. Linear regression (LR) and artificial neural networks (ANNs) were used to run the fish habitat models which are based on fish data, abiotic data and an autecology matrix. The result shows that ANNs is an appropriate tool for modeling the relationship between fish and habitat. The models results constitute a reference condition that can be used to guide stream restoration and ecological engineering decisions aimed at maintaining the natural ecological integrity and diversity of rivers.
| Identifer | oai:union.ndltd.org:TW/102NCKU5083115 |
| Date | January 2014 |
| Creators | Huan-HsuanChang, 張桓旋 |
| Contributors | Jian-Ping Suen, 孫建平 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 84 |
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