林业科学2012，Vol.48Issue(1)：53-59,7.
样本量对MaxEnt模型预测物种分布精度和稳定性的影响
Effects of Sample Sizes on Accuracy and Stability of Maximum Entropy Model in Predicting Species Distribution
摘要
Abstract
Prediction of species distribution and its changes play more and more important roles 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 rare species. Considering that very few species distribution data have been accumulated, employ species distribution model fitting technique is highly necessary in the process of predicting species distribution. Sampling size has an important influence on expense of actual survey and accuracy of model prediction. In terms of accuracy of species distribution model and expense of forest survey, it is necessary to investigate the least sampling size when species distribution models reach the most accuracy. Thirty-four different sampling sizes(5, 6,8, 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, 1 000 and 1 200 ) of four species were used to simulate the influence of different sample sizes on the precision and stability of MaxEnt species distribution model. The results showed that sampling sizes had no obvious influence on MaxEnt. The accuracy of MaxEnt was unstable when sampling size was small, but as sampling size was increasing ( sampling size of training data was about 50, test data was about 120) , the accuracy was more stable.关键词
样本量/最大熵物种分布模型/AUC/预测精度/标准差Key words
sample size/maximum entropy species distribution model( MaxEnt)/AUC/predictive accuracy/standard deviation分类
农业科技引用本文复制引用
陈新美,雷渊才,张雄清,贾宏炎..样本量对MaxEnt模型预测物种分布精度和稳定性的影响[J].林业科学,2012,48(1):53-59,7.基金项目
国家自然科学基金项目(31170588) （31170588）
科技部社会公益研究专项(2005DIB5J142) （2005DIB5J142）
