首页|基于MaxEnt模型预测梅的潜在适生区分布

基于MaxEnt模型预测梅的潜在适生区分布

Prediction of Potential Distribution of Prunus mume Based on MaxEnt Model

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目的:确定影响梅分布的主要环境因子,并预测当前与未来条件下梅的适生区.方法:收集172份梅分布点的32个环境因子数据,构建MaxEnt模型,筛选影响梅生长的主导环境因子,结合地理信息系统(ArcGIS10.8)绘制梅目前与未来的适生区分布预测图.结果:影响梅分布的主要环境因子有5个(最冷月最低气温、年降水量、最暖季降水量、年温差与最干燥月降水量);其中最冷月最低气温对梅生存概率影响最大,当最冷月最低气温约10.1℃时梅适生概率最大,达到71.47%.模拟当前气候环境下,梅的高适生区、中适生区和低适生区面积分别占全国总面积的7.78%、17.01%与7.73%.目前高适宜区主要分布在广东、广西、四川、云南、贵州、重庆、浙江与台湾等省,在SSP1-2.6与SSP5-8.5下,梅适宜面积(潜在高适生与中适生区)在2021至2060年期间,呈现波浪式增加和北移的趋势,分别为当前的101.85%和102.28%.结论:本研究结果可为梅资源的可持续利用,以及梅人工种植的合理布局与区划研究提供科学依据.
Objective:To determine the dominant environmental factors shaping the distribution of Prunus mume.To predict the distribution areas of P.mume under current and future climatic environ-ments.Methods:A total of 172 distribution points and corresponding 32 environmental factors of P.mume were collected,and the MaxEnt model was constructed accordingly.The dominant environmen-tal factors affecting the growth were identified,and the current and future distribution map of P.mume was drawn by ArcGIS.Results:There were five main environmental as dominant factors affecting the distribution of P.mume:min temperature of coldest month(bio6),annual precipitation(bio12),pre-cipitation of warmest quarter(bio18),annual temperature difference(bio7)and precipitation of driest Month(bio14),among which bio6 had the greatest effect on the survival probability.When the lowest temperature in the coldest month was 10.1℃,P.mume reached the highest living probability of 71.47%;Under the current climatic environment,the areas of high,medium and low suitable areas ac-counted for 7.78%,17.01%and 7.73%,respectively,in China.And the high suitable areas were main-ly distributed in Guangdong,Guangxi,Sichuan,Guizhou,Yunnan,Chongqing,Zhejiang and Taiwan provinces.Under SSP1-2.6 and SSP5-8.5,the suitable area of P.mume(potential high and medium suitable area)moved north and increased wavelike of 101.85%and 102.28%,respectively.Conclu-sion:The present result could provide basic data not only for the sustainable utilization of P.mume re-sources,but also for its rational distribution of artificial planting.

Prunus mumeMaximum modelEnvironmental factorsPotential distributionFuture climate

陈伊能、刘志刚、于婷、廖海、周嘉裕

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西南交通大学 生命科学与工程学院,四川 成都 610031

马边彝族自治县林业局,四川 乐山 614600

最大熵模型 环境因子 潜在分布 未来气候

成都市科技局项目中央高校医工结合项目四川省中医药管理局项目

2022-YF05-01357-SN2682022ZTPY0532021MS116

2024

中国野生植物资源
中华全国供销合作总社南京野生植物综合利用研究院

中国野生植物资源

影响因子:0.667
ISSN:1006-9690
年,卷(期):2024.43(1)
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