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题名: Looking below the ground: Prediction of Tuber indicum habitat using the Weights of Evidence method
作者: Yang, Xue-Qing2; Kodikara, Gayantha R. L.3; Luedeling, Eike4; null(杨雪飞)5; He, Jun1; Liu, Pei-gui5; null(许建初)1
刊名: ECOLOGICAL MODELLING
关键词: Weights of Evidence model ; Potential distribution ; Tuber indicum ; Species conservation
英文摘要: The under-ground mushroom Tuber indicum is renowned for its economic, nutritional, ethnobotanical and ecological importance. For the development of sustainable harvest and conservation practices, better knowledge about the mushroom's habitat is indispensable. However, few approaches allow monitoring T. indicum's distribution on a large geographic scale. Apart from the difficulty to directly monitor them by Remote Sensing and GIS technology, a particular challenge arises from the sampling limitations for this seasonal mushroom. This problem is common in geology, where underground mineral resources must be mapped without direct observations. Geologists apply the 'Weights of Evidence' method for such situations, and this approach may have potential for underground mushrooms as well. We thus constructed potential habitat maps for T. indicum using the Weights of Evidence method. Based on field survey and published sources, ten influential indicators associated with T. indicum were selected and mapped for Longyang district in southwestern Yunnan, China. Two predictive models were established from independent environmental layers. In order to build better understanding of the models' predictive ability, apart from the Receiver Operating Characteristic (ROC) curve, the Area Adjusted Frequency (AAF) approach was also applied for model evaluation. For the final map, the best-performing model was selected. The resulting habitat map could provide guidance for future conservation activities. (C) 2012 Elsevier B.V. All rights reserved.
出版日期: 2012-12-01
卷号: 247, 页码:27-39
语种: 英语
收录类别: SCI
Citation statistics:
内容类型: 期刊论文
URI标识: http://ir.kib.ac.cn/handle/151853/20393
Appears in Collections:资源植物与生物技术所级重点实验室_期刊论文

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作者单位: 1.China & E Asia Off Co Kunming Inst Bot, World Agroforestry Ctr, Kunming 650201, Yunnan, Peoples R China
2.Chinese Acad Sci, Kunming Inst Bot, Ctr Mt Ecosyst Studies, Kunming 650201, Peoples R China
3.Arthur C Clarke Inst Modern Technol, Space Applicat Div, Katubedda, Moratuwa, Sri Lanka
4.World Agroforestry Ctr ICRAF, Nairobi, Kenya
5.Chinese Acad Sci, Kunming Inst Bot, Key Lab Biodivers & Biogeog, Kunming 650201, Peoples R China
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