Modeling waterbird diversity in irrigation ponds of Taoyuan, Taiwan using an artificial neural network approach |
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Authors: | Wei-Ta Fang Hone-Jay Chu Bai-You Cheng |
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Institution: | (1) Department of Leisure and Recreation Management, Chung Hua University, HsingChu, 300, Taiwan;(2) Bioenvironmental Systems Engineering Department, National Taiwan University, 1, Sec. 4, Roosevelt Rd., Da-an District, Taipei City, 106, Taiwan |
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Abstract: | The study develops an approach adopted by artificial neural networks (ANN) to model the relationship between pondscape and
waterbird diversity. Study areas with thousands of irrigation ponds are unique geographic features from the original functions
of irrigation converted to waterbird refuges. The model considers pond shape and size, neighboring farmlands, and constructed
areas in calculating parameters pertaining to the interactive influences on avian diversity, among them the Shannon–Wiener
diversity index. Results indicate that irrigation ponds adjacent to farmland benefited waterbird diversity. On the other hand,
urban development leads to the reduction of pond numbers, which reduces waterbird diversity. By running the ANN model, the
resulting index shows a good-fit prediction of bird diversity against pond size, shape, neighboring farmlands, and neighboring
developed areas with a correlation coefficient (r) of 0.72, in contrast to the results from a linear regression model (r < 0.28). |
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Keywords: | Artificial neural network (ANN) Irrigation pond Waterbird Landscape ecology Taiwan |
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