Biodiv Sci ›› 2018, Vol. 26 ›› Issue (2): 171-176. DOI: 10.17520/biods.2017080
Special Issue: 青藏高原生物多样性与生态安全
• Orginal Article • Previous Articles Next Articles
Shaopeng Cui1,2,3#, Xiao Luo1,2#, Chunwang Li1,2, Huijian Hu4, Zhigang Jiang1,2,*()
Received:
2017-03-15
Accepted:
2017-11-16
Online:
2018-02-20
Published:
2018-05-05
Contact:
Jiang Zhigang
About author:
# Co-first authors
Shaopeng Cui, Xiao Luo, Chunwang Li, Huijian Hu, Zhigang Jiang. Predicting the potential distribution of white-lipped deer using the MaxEnt model[J]. Biodiv Sci, 2018, 26(2): 171-176.
编码 Code | 描述 Description | 来源 Source |
---|---|---|
Bio4 | 气温季节变化 Temperature seasonality | WorldClim database Version 1.4 |
Bio12 | 年降水量 Annual precipitation | WorldClim database Version 1.4 |
NDVI_Summer | 夏季归一化植被指数 Normalized difference vegetation index in summer | Chinese Natural Resources Database |
Altitude | 海拔 Altitude | USGS’s Hydro-1K dataset |
Slope | 坡度 Slope | USGS’s Hydro-1K dataset |
HFI | 人类足迹指数 Human footprint influence | Last of the Wild Data Version 2 |
Stocking rate | 放牧强度 Stocking rate | Food and Agriculture Organization |
Table 1 Environmental variables used to model the potential range of the white-lipped deer
编码 Code | 描述 Description | 来源 Source |
---|---|---|
Bio4 | 气温季节变化 Temperature seasonality | WorldClim database Version 1.4 |
Bio12 | 年降水量 Annual precipitation | WorldClim database Version 1.4 |
NDVI_Summer | 夏季归一化植被指数 Normalized difference vegetation index in summer | Chinese Natural Resources Database |
Altitude | 海拔 Altitude | USGS’s Hydro-1K dataset |
Slope | 坡度 Slope | USGS’s Hydro-1K dataset |
HFI | 人类足迹指数 Human footprint influence | Last of the Wild Data Version 2 |
Stocking rate | 放牧强度 Stocking rate | Food and Agriculture Organization |
Fig. 1 The Jackknife test for evaluating the relative importance of environmental variables in the development of the MaxEnt model. The blue bar shows the “total gain” achieved with the given predictor only. The green bar shows the “total gain” resulting from inclusion of all predictors except the given predictor. The bottom red bar shows the gain with all variables. For variable meanings, see Table 1.
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