Modeling waterbird diversity in irrigation ponds of Taoyuan, Taiwan using an artificial neural network approach

Wei Ta Fang, Hone Jay Chu, Bai You Cheng

研究成果: 雜誌貢獻文章同行評審

16 引文 斯高帕斯(Scopus)

摘要

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).

原文英語
頁(從 - 到)209-216
頁數8
期刊Paddy and Water Environment
7
發行號3
DOIs
出版狀態已發佈 - 2009 八月 1

ASJC Scopus subject areas

  • Environmental Engineering
  • Agronomy and Crop Science
  • Water Science and Technology

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