Please use this identifier to cite or link to this item: http://hdl.handle.net/11455/88088
標題: 樣本數量對最大熵物種分布模式(MaxEnt)準確度之影響:以臺灣水青岡為例
Effects of Sample Size on Accuracy of MaxEnt: A Case Study of “Fagus hayatae”
作者: 江鴻猷
曾喜育
邱清安
曾彥學
Hong-You Jiang
Hsy-Yu Tzeng
Ching-An Chiu
Yen-Hsueh Tseng
關鍵字: species distribution modeling (SDM);Fagus hayatae;MaxEnt;sample size;accuracy;prevalence;物種分布模擬;臺灣水青岡;樣本數量;準確度;普及率
Project: 林業研究季刊, Volume 36, Issue 2, Page(s) 101-113.
摘要: 
The accuracy of species distribution modeling (SDM) is affected not only by species, modeling method and scale, and environmental predictor, but also by sample size. In this study, we extracted gradually the occurrence data of "Fagus hayatae" together with 8 environmental predictors to evaluate the effect of sample size on MaxEnt through AUC, TSS and Kappa index. The results showed that there are 1~8,014 occurrence points extracted gradually from "F. hayatae" distribution area through 40 m arithmetic series of sampling scale. The accuracy of MaxEnt increased with enlarging sample size gradually, accompanied by decreasing uncertainty, until it reached the maximum value of AUC, TSS and Kappa indices. However, based on AUC index, the exaggerated sample size such as 2,008 and 8,014 points led to a lightly reduction of MaxEnt accuracy. On the other hand, some cases using small sample size (less than 10 points) for SDM also performed well. The result represented that small sample size from a specific sampling condition could provide a reliable modeling. In the case study for modeling "F. hayatae" distribution, 35~99 occurrence points unbiased spatially of sample size was appropriate. AUC, TSS and Kappa were inconsistent for evaluating the SDM performance. Because Kappa was sensitive to the prevalence, it was not an applicable index to evaluate the effect of sample size on SDM accuracy.

物種分布模擬的準確度除了因物種、模擬方法、解釋變數和研究尺度等因子而有所差異外,亦受到樣本數量的影響。本研究以不同樣本數量之臺灣水青岡(Fagus hayatae)分布點及8項環境預測變數為材料,以MaxEnt為物種分布模擬方法,利用AUC、TSS、Kappa評估模擬成效,藉以比較不同樣本數量所建構之模擬的差異。結果顯示以40 m間距對臺灣水青岡分布區等距取樣,可獲取1~8,014個樣本點。隨著樣本數量增加,MaxEnt模擬準確度也隨之增加,直至達到最大準確度後趨於緩和,其原因為建構模擬的環境變數估計值會隨樣本數量的增加而減少其不確定性;但根據AUC指標顯示,過量的樣本(如2,008、8,014點)會使模擬準確度略為下降,另一方面本研究也顯示部分小樣本(10點以下) 建構的模擬亦表現良好,證實小樣本在特定的取樣條件下,仍可建立具有可信度的模擬;以本文模擬臺灣水青岡分布為例,35~99個無空間偏差之物種出現點應是合宜的樣本數量。評估模擬表現之3種指標並不一致,其中Kappa明顯受到普及率之影響,並不適用於評估樣本數量對物種分布模擬之影響。
URI: http://hdl.handle.net/11455/88088
Appears in Collections:第36卷 第02期

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