文献类型：会议论文

英文题名：Effects of sample size on accuracy and stability of species distribution models: A comparison of GARP and Maxent

作者：Chen, Xinmei[1] Lei, Yuancai[1]

第一作者：Chen, Xinmei

通信作者：Lei, Y.|[a0005ffda2d009ee9448b]雷毅;

机构：[1] Research Institute of Forest Resources Information Techniques, Chinese Academy of Forestry, Beijing, 100091, China

会议论文集：Recent Advances in Computer Science and Information Engineering

会议日期：December 16, 2009 - December 18, 2009

会议地点：Sydney, Australia

语种：英文

外文关键词：Climate change - Forecasting - Genetic algorithms - Predictive analytics - Sampling - Surveys

年份：2012

摘要：Prediction of species distribution and its changes play an increasingly important role in the fields of ecological protection and application as well as global climate changes. It is impracticable to survey species distribution in large area, especially for rare species; therefore species distribution models are very useful for predicting species distribution. Sampling size has an essential influence on the cost of actual survey and the accuracy of model prediction. Generally, the larger sample size, the higher accuracy of models, but with the more cost of survey. It is necessary to research species distribution models to get the highest accuracy but with the least sample size. Taking 31 different sample sizes (5, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 90, 100, 120, 150, 180, 200, 220, 250, 300, 350, 400, 450, 500, 550, 600, 650, 700, 800, 900, 1000 and 1200) of 4 species as an example, this study analyzed the influence of different sample sizes on accuracy and stability of both MaxEnt (Maximum Entropy Species Prediction Model) and GARP(Genetic Algorithm for Rule-set Production). The results showed that both the accuracy and stability of two models increased with the sample size. And the two models had different predictive results to different species. The omission values of GARP were always smaller than that of MaxEnt at the same sample size to all species. ? 2012 Springer-Verlag GmbH.