关键词: 样本量, 最大熵物种分布模型, AUC, 预测精度, 标准差

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.

Key words: sample size, maximum entropy species distribution model(MaxEnt), AUC, predictive accuracy, standard deviation