globalchange  > 气候变化事实与影响
CSCD记录号: CSCD:6535943
论文题名:
基于MaxEnt模型的南酸枣潜在适生区预测
其他题名: Prediction of Potential Suitable Distribution Areas for Choerospondias axillaris besed on MaxEnt Model
作者: 叶学敏1; 陈伏生1; 孙荣喜1; 吴南生2; 刘斌1; 宋玉林3
刊名: 江西农业大学学报
ISSN: 1000-2286
出版年: 2019
卷: 41, 期:3, 页码:86-92
语种: 中文
中文关键词: 南酸枣 ; MaxEnt模型 ; 适生区 ; 气候变化
英文关键词: Choerospondias axillaris ; MaxEnt model ; suitable area ; climate change
WOS学科分类: PLANT SCIENCES
WOS研究方向: Plant Sciences
中文摘要: 为明确南酸枣在中国的适生分布区及其对气候变化的响应,应用MaxEnt模型综合32个环境变量和196个分布记录模拟南酸枣现在和未来的地理分布,检测其主导环境变量。结果表明:南酸枣在中国适生区面积113.25*10~4 km~2,最适分布区位于南岭、幕阜山、罗霄山、大娄山、武夷山、天目山、武陵山、云贵高原等地区。 Jackknife检验表明:主导环境变量为低温和地表霜频率。在未来全球气候变暖的情境下(RCP2.6),南酸枣适生区扩张并北移(西藏东部、云南地区除外),未来气候变化对其种群地理分布格局影响较小,栽植应用潜力较大。
英文摘要: In order to identify the suitable distribution area of Choerospondias axillaris in China and its response to climate change,the current and future geography distribution patterns of C.axillaris were simulated by using MaxEnt model based on 32 environmental variables and 196 distribution records,and the dominant environmental factors were detected by the model.The results showed that the suitable area for C. axillaris was ca.113.25*10~4 km~2,and the most suitable distribution areas was located in Mt. Nanling,Mt. Mufu,Mt. Luoxiao, Mt. Dalou,Mt. Wuyi,Mt. Tianmu,Mt. Wuling and Yungui Plateau. Jackknife Test indicated that low temperature and ground-frost frequency had great contribution to the distribution for C. axillaris.In the context of future global warming(RCP2.6),the suitable area of C. axillaris expanded and moved northward(except in eastern Tibet and Yunnan). We indicate predicted that the future climate change has little effect on the geographical distribution pattern of C. axillaris. Plantation of C. axillaris has great application potential in China.
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/155864
Appears in Collections:气候变化事实与影响

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作者单位: 1.江西农业大学林学院
2.江西省森林培育重点实验室,
3.江西省森林培育重点实验室, 南昌
4.南昌, 江西
5.江西 330045
6.330045, 中国
7.江西农业大学林学院
8.江西农业大学南酸枣研究所,
9., 南昌
10.南昌, 江西
11.江西 330045
12.330045, 中国
13.江西农业大学林学院, 南昌, 江西 330045, 中国

Recommended Citation:
叶学敏,陈伏生,孙荣喜,等. 基于MaxEnt模型的南酸枣潜在适生区预测[J]. 江西农业大学学报,2019-01-01,41(3):86-92
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