Bounding species distribution models

作     者：Thomas J. STOHLGREN Catherine S. JARNEVICH Wayne E. ESAIAS Jeffrey T. MORISETTE 

作者机构：Fort Collins Science Center U.S. Geological Survey 2150 Centre Avenue Fort Collins CO 80526USA Code 614.5. NASA/Goddard Space Flight Center. Greenbelt MD 20771 USA 

出 版 物：《Current Zoology》 (动物学报（英文版）)

年 卷 期：2011年第57卷第5期

页      面：642-647页

核心收录：

学科分类：02[经济学] 07[理学] 09[农学] 071007[理学-遗传学] 070103[理学-概率论与数理统计] 090102[农学-作物遗传育种] 0710[理学-生物学] 0202[经济学-应用经济学] 020208[经济学-统计学] 0905[农学-畜牧学] 0906[农学-兽医学] 0901[农学-作物学] 0714[理学-统计学（可授理学、经济学学位）] 0701[理学-数学] 

基　　金：NASA grant for funding Supported by U.S. Geological Survey Invasive Species Program USGS Fort Collins Science Program USDA CSREES 

主　　题：分布模型 物种管理 欧洲核子研究中心 地理信息系统 环境预测 模型映射 物种分布 CART 

摘      要：Species distribution models are increasing in popularity for mapping suitable habitat for species of management concern. Many investigators now recognize that extrapolations of these models with geographic information systems (GIS) might be sensitive to the environmental bounds of the data used in their development, yet there is no recommended best practice for “clamping model extrapolations. We relied on two commonly used modeling approaches: classification and regression tree (CART) and maximum entropy (Maxent) models, and we tested a simple alteration of the model extrapolations, bounding extrapolations to the maximum and minimum values of primary environmental predictors, to provide a more realistic map of suitable habitat of hybridized Africanized honey bees in the southwestern United States. Findings suggest that multiple models of bounding, and the most conservative bounding of species distribution models, like those presented here, should probably replace the unbounded or loosely bounded techniques currently used.