关键词：
河北省沧州市
栖息地选择
机器学习
越冬地
大鸨
预测
地理信息系统
野外数据采集
摘要：
Great Bustards(Otis tarda dybowskii)are one of the world’s heaviest flying birds,occupying grassland habitats in Eastern *** study is located at the most eastern Chinese wintering site in Cangzhou,Hebei Province,where approximately 100 individuals are concentrated in a small area(17.53 km2).Solid information is still lacking about the wintering areas for this subspecies in its eastern range and specifically for *** study area consists of intensely used farmland in proximity to humans and is lacking conservation areas and wild,open ***,we present our results from two years of field data collection on habitat *** choose a machine learning model approach based on a rapid assessment methodology for the winter habitat of the Great *** is based on a spatial analysis of the best available environmental data,which were collected relatively *** relatively new methods in ecology are based on an ensemble of decision trees and include algorithms such as TreeNet,Random Forest and CART used in *** this study,we collected bustard droppings(presence only)from 48 locations between December 2011 and January 2012 and used the sites as training *** from 23 locations were collected in November 2012,and those sites were used as test *** used eight environmental variables as predictor layers for the response variable of bustard presence/*** employed a Geographic Information System(ArcGIS 10.1and Geospatial Modelling Environment)and Google *** with the other three models,we found that predictions from Random Forest obtained a significant difference between presence and *** to this model,the three most important factors for wintering Great Bustards are distance to residential area,distance to water pools,and farmland *** model shows that wintering Great Bustards prefer locations that are over 400 m away from residential areas,within 900 m of water pools and on areas of farmland smal
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中文科技期刊
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