| 摘要: |
| 为分析环境因子对薇甘菊 Mikania micrantha 分布的影响, 2020—2021 年间以中山市为研究区,
于薇甘菊盛花期进行实地踏查, 收集薇甘菊分布点数据, 定量分析 10 个环境因子对薇甘菊分布的影响,
基于 GAM 模型 (Generalized additive model) 对中山市薇甘菊适生区分布进行预测。 结果显示, (1) 模
型结果拟合精度高, TSS (Total sum of squares) 均值为 0. 87, AUC (Area under the curve) 均值为 0. 93;
(2) 10 个环境因子对薇甘菊分布均有贡献, 贡献率最大的为降水量季节性变化 (18. 63%), 其次为海拔
(17. 90%), 第三为 4 月降水量 (16. 47%); (3) 模型预测结果显示中山市约 89. 23%的地区适宜薇甘菊
分布。 研究构建的 GAM 模型拟合精度高, 并证明了中山市区域尺度下水、 热和海拔为影响薇甘菊分布的
主导因子。 |
| 关键词: GAM 模型 薇甘菊 分布预测 |
| DOI： |
| 分类号: |
| 基金项目:广东省林学会 2021 年度科技计划项目?“薇甘菊预测模型构建技术研究”（2021-GDFS-KJ-04） |
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| Analysis of Environmental Factors and Prediction of Suitable Distribution Areas of Mikania micrantha in Zhongshan City Based on GAM |
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GAO Song1, MA Yingying1, MA Hongli1, XIE Dezhi2
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1.Guangzhou Yanmei Landscape Engineering Design Co., Ltd;2.Guangzhou Carbon Sequestration Forestry Co., Ltd
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| Abstract: |
| To analyze the effects of environmental factors on the distribution of Mikania micrantha, a field
survey was conducted during the peak flowering period of M. micrantha in Zhongshan city from 2020 to 2021.
Data on distribution points of M. micrantha were collected, and the effects of 10 environmental factors on its distribution were quantitatively analyzed. Based on the Generalized Additive Model (GAM), the distribution of
suitable areas for M. micrantha in Zhongshan city was predicted. The results showed that: (1) the model had
high fitting accuracy, with a total sum of squares (TSS) mean of 0. 87 and an area under the curve (AUC)
mean of 0. 93; (2) Ten environmental factors contribute to the distribution of chamomile, with the highest contribution rate being seasonal variation in precipitation (18. 63%), followed by altitude ( 17. 90%), and the
third being precipitation in April (16. 47%); (3) The model prediction results show that about 89. 23% of the
areas in Zhongshan city are suitable for the distribution of M. micrantha. The GAM model constructed in the study has high fitting accuracy and has been proven to be the dominant factor affecting the distribution of
M. micrantha at the regional scale in Zhongshan city, including water, heat, and altitude. |
| Key words: GAM model Mikania micrantha suitability distribution prediction |
