碩士 / 國立臺灣大學 / 生物環境系統工程學研究所 / 100 / River ecological engineering is the engineering method to renovate river approaching to nature in recent years. Establishing good simulation model before executing not only provides a direction for river ecological engineering, but improves the benefits of river management. During simulating river habitat, Habitat Suitability Analysis is one of the most important processes. Habitat suitability index (HSI) builds the relationship between target species and environmental factors of habitat and physical habitat model simulate the river section and calculate weighted usable area (WUA). Combining both of them become a crucial analysis tool to river ecosystem.
The previous study in river habitat simulation mostly aims at the fish preference of environmental factors of habitat to build individual model. However, in order to consider different fish ecological demand in various flow conditions, for example, riffle with high oxygen is full of food sources, pool is suitable to be a shelter, it needs diverse standard simulation model for describing fish activities to approach reality. The study area is Datuan Stream located in Tamsui District, New Taipei City and the target species is monk goby (Sicyopterus japonicus). Fish presence probabilities for each velocity and water depth establish HSI. There are three methods: First, establish suitability index (SI) by each factor separately, and then multiple all SIs together to obtain a composite HSI, which called “traditional model”. Second, Search for optimal function in factors by genetic programming (GP), and obtain HSI, which called “modified model”. Third, divide into four flow conditions by velocity 0.32 (m/s) and water depth 0.29(m), and obtain united HSI, which called “classified model”. Finally, simulate river flow and calculate the spatial distribution of WUA, and then compare the result of three models.
The result reveals that the correlation between frequency of monk goby presence and frequency of flow condition is up to 0.96. Therefore, Category II HSI which is the most common method can not reflect favorite environment of fish in reality. In addition, when it comes to the calibration and validation of model, the root mean square error (RMSE) of modified model is better than traditional model by 0.0718, 0.1001, and 0.1215, 0.1289. While taking the relationship between variables into consideration by GP, it has a better predictive effect. On the other hand, the RMSE of classified model is worse than modified model by 0.1127, 0.1316. All in all, the confidence and accuracy of modified model is greater than other two models. In the end, the result of calculating WUA shows that classified model could avoid underestimation or homogeneity, which may occur in other two models. While researching in different activities of fish (ex: spawning, preying), we expect classified model to be practical and valuable in the future.
| Identifer | oai:union.ndltd.org:TW/100NTU05404052 |
| Date | January 2012 |
| Creators | Chen-Huan Wu, 吳承寰 |
| Contributors | 林裕彬 |
| Source Sets | National Digital Library of Theses and Dissertations in Taiwan |
| Language | zh-TW |
| Detected Language | English |
| Type | 學位論文 ; thesis |
| Format | 100 |
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