生态学报2017，Vol.37Issue(13)：4476-4482,7.DOI:10.5846/stxb201602020243
基于物种分布模型的精确采样提高目标物种发现率——以黑颈鹤(Grus nigricollis),白头鹤(Grus monacha)为例
摘要
Abstract
The identification of the geographic distribution of wildlife is fundamental in applied ecology,since 1t provides important information for subsequent analyses.However,the investigation of wildlife is often expensive and time consuming,especially for rare species and when using inefficient sampling designs.To determine target species more efficiently,we tried to apply model-based sampling using predictions from species distribution models (SDMs).We used black-necked (Grus nigricollis) and hooded (Grus monacha) cranes as two examples,and used the Random Forest algorithm combining the breeding location and environmental information to model the breeding geographic distribution of the two crane species.We extracted the relative index of occurrence (RIO) for the breeding locations (testing points,model-based sampling method),random point locations (random sampling method),and regular point locations (regular sampling method) from the prediction map.Then,we used boxplots and ANOVA to analyze these data;the results indicated breeding locations with higher RIOs,and a significant difference was found between the other two methods.Therefore,the model-based sampling method helped to reduce the size of the investigated areas and determine target species more effectively.To conclude,a species distribution model-based sampling method for fieldwork would help to increase our knowledge of rare species distributions.More generally,we recommend using this approach to support conservation plans.关键词
物种分布模型/随机森林/精确采样/黑颈鹤/白头鹤Key words
species distribution model (SDM)/Random Forest/sampling method/black-necked crane/hooded crane引用本文复制引用
宓春荣,郭玉民,Huettmann Falk,韩雪松..基于物种分布模型的精确采样提高目标物种发现率——以黑颈鹤(Grus nigricollis),白头鹤(Grus monacha)为例[J].生态学报,2017,37(13):4476-4482,7.基金项目
国家自然科学基金(31570532) （31570532）
