摘要
结合70个红瘰疣螈的地理分布数据和28个环境因子,运用MaxEnt模型分析其适宜生境分布及主要影响因子。结果表明,影响红瘰疣螈的主要因素为最冷季度降水量、淤泥含量、昼夜温差月均值、最冷月最低气温、年均降水量等。此外,红瘰疣螈高适宜区主要分布在腾冲市、龙陵县、云县、廊沧拉祜族自治县、凤庆县、永德县等地区,中适宜区主要分布在永平县、施甸县、玉龙纳西族自治县、剑川县等地区。高适宜区面积为2.26万km^(2),中适宜区面积为3.85万km^(2),低适宜区面积为8.30万km^(2),非适宜区面积为23.89万km^(2)。ROC曲线分析表明,训练AUC值为0.926,预测结果较好。建议在高适宜区和中适宜区划定适当的保护小区,对红瘰疣螈进行就地保护。
Combined with the geographical distribution data of 70 individuals of Tylototriton shanjing and 28 environmental factors,MaxEnt model was used to analyze its suitable habitat distribution and main influencing factors.The research results showed that the main influencing factors of T.shanjing were the precipitation in the coldest season,silt content,monthly average temperature difference between day and night,the lowest air temperature in the coldest month,average annual precipitation,etc..The highest suitable area of T.shanjing were Tengchong City,Longling County,Yunxian County,Langcang Lahu Autonomous County,Fengqing County,Yongde County,etc..The moderately suitable area of T.shanjing Yongping County,Shidian County,Yulong Naxi Autonomous County,Jianchuan County,etc..The area of the highest suitable area was 22600 km^(2),the area of moderately suitable area was 38500 km^(2),the area of the lowest suitable suitable area was 83000 km^(2),the area of the unsuitable area was 238900 km^(2).ROC curve analysis showed that the training AUC value was 0.926,and the prediction result was good.It was recommended to delineate appropriate protection areas in the highest suitable area and the moderately suitable area,and carry out on-site protection of T.shanjing.
作者
王素霞
杨德宏
冯鸿能
WANG Su-xia;YANG De-hong;FENG Hong-neng(Faculty of Land Resources Engineering,Kunming University of Science and Technology,Kunming,Yunnan 650031;Tianjin Urban Construction Management&Vocation Technology College,Tianjin 300112)
出处
《安徽农业科学》
CAS
2023年第6期73-77,87,共6页
Journal of Anhui Agricultural Sciences
基金
天津市职业院校“十四五”教育教学改革研究项目(2021084)
2021年度天津市高等职业技术教育研究会课题(2021-3226)。
关键词
红瘰疣螈
MaxEnt模型
潜在分布
适宜性评价
云南
Tylototriton shanjing
MaxEnt model
Potential distribution
Suitability evaluation
Yunnan