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中国农学通报 ›› 2016, Vol. 32 ›› Issue (23): 49-54.doi: 10.11924/j.issn.1000-6850.casb16010083

• 植物保护 农药 • 上一篇    下一篇

基于MaxEnt 的农田恶性杂草雀麦的潜在分布预测

谭金妮,李琦,白霜,王金信   

  1. 山东农业大学植物保护学院农药系,山东农业大学植物保护学院农药系,山东农业大学植物保护学院农药系,山东农业大学植物保护学院农药系
  • 收稿日期:2016-01-18 修回日期:2016-02-21 接受日期:2016-02-25 出版日期:2016-08-10 发布日期:2016-08-10
  • 通讯作者: 王金信
  • 基金资助:
    公益性农田杂草防控技术研究与示范项目(201303022)。

Prediction of Potential Distribution of Japanese Brome (Bromus japonicus) Based on MaxEnt

  • Received:2016-01-18 Revised:2016-02-21 Accepted:2016-02-25 Online:2016-08-10 Published:2016-08-10

摘要: 雀麦是我国农田一种恶性杂草,危害作物生长和发育。为进一步控制其扩散蔓延,根据目前雀麦在全球的分布记录和气象数据,利用最大熵模型MaxEnt 和ArcGIS对雀麦在全球和中国的适生区域进行分析和预测。结果表明,雀麦在全球的适生区为非洲西北部、欧洲的中部、西亚、中东、北美中西部及东部部分地区、中国的黄淮海流域及西南零星地区、日本及朝鲜半岛南部;在中国主要在黄淮海平原、关中平原、长江中下游平原、成都平原、湖南、贵州中北部;中风险潜在分布区的范围在高风险区的基础上进一步扩大。对雀麦发生影响较大的是最冷季度平均温度、年平均气温、温度季节性变化标准差、最冷月最低温、最干季度平均温度。本研究的AUC值为0.943,模拟预测准确性极好,模拟结果可以用于雀麦的适生区预测研究。

关键词: 魔芋, 魔芋, 灰霉病菌, 菌丝, 分生孢子, 生理学特性

Abstract: Japanese Brome is a serious weed in farmland, which damages the growth and development of crops. In order to control the spread of Japanese Brome, MaxEnt maximum entropy model and ArcGIS were used to analyze and predict its potential geographical distribution in China and the rest of the world according to its distribution records and the meteorological data. The results showed that areas of western Africa, south central Europe, western and eastern and parts of middle Asia, mid-western and parts of eastern North America had high invasion risk of Japanese Brome. In China, areas of Huang-huai-hai plain, plain in the middle and lower reaches of Yangtze River, Chengdu plain, south central Shaanxi, southern Shanxi, southern Ningxia and Gansu, north central Guizhou, parts of southwest Xinjiang, southwest Tibet and central Qinghai had high invasion risk of Japanese Brome. The scope of secondary risky areas was expanded further on the basis of the high-risky area. The important environmental factors influencing the occurrence of Japanese Brome were mean temperature of the coldest quarter, the annual average temperature, temperature seasonal variation standard deviation, the lowest temperature in the coldest month and the mean temperature of the driest quarter. In this study, the AUC value was 0.943, which indicated that the accuracy of the simulation forecast was good, and the simulation results could be used for the prediction research of the suitable distribution areas of Japanese Brome.

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