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基于MaxEnt模型金毛狗(Cibotium barometz)潜在地理分布预测OA

Prediction of Potential Geographical Distribution of Cibotium barometz Based on MaxEnt Model

中文摘要英文摘要

金毛狗(Cibotium barometz)为濒危保护物种,目前其栖息地受到严重威胁,需建立其全球范围内潜在地理分布预测模型,为其资源保护与利用提供参考.基于365条金毛狗有效分布记录和15个环境变量,采用最大熵(MaxEnt)模型预测金毛狗当前和未来(2030s、2050s、2070s和2090s)潜在适生区,分析影响其分布的主要环境因子.结果表明,MaxEnt模型曲线下方面积(AUC)均值为0.975,模型预测精度高;最暖季降水量、最湿月降水量、坡度、温度季节性变化、平均日较差和年均温均为影响金毛狗分布的主要环境因子,其贡献率累计达94.76%.至2090s,金毛狗总适生区面积在SSP126情景下收缩95.86×104 km²,在SSP370和SSP585情景下分别扩张71.11×104和41.09×104 km².金毛狗主要分布在经度90°E~150°E和纬度10°S~30°N范围内;当前至2070s,其分布中心在3种气候情景下均呈向低纬度区域移动的趋势;2070s至2090s,其分布中心在3种气候情景下均呈向高纬度区域移动的趋势.

Cibotium barometz is endangered protected species,and its habitat is under severely threat current-ly,thus it is necessary to establish global prediction model for its potential geographical distribution to provide references for its resource protection and utilization.Based on data of 365 C.barometz effective distribution re-cords and fifteen environmental variables,C.barometz potential suitable regions were predicted at current and future(2030s,2050s,2070s and 2090s)and main environmental factors affecting its distribution were analyzed by Maximum Entropy(MaxEnt)model.Results showed that area under curve(AUC)mean of MaxEnt model reached 0.975,indicating high prediction accuracy.Precipitation of the warmest quarter,precipitation of the wettest month,degree,temperature seasonality,mean diurnal range and annual mean temperature were main environmental factors affecting C.barometz distribution with cumulative contribution rate of 94.76%.By 2090s,area of C.barometz total suitable region would decrease 95.86×104 km² under SSP126 scenario,whereas it would increase 71.11×104 and 41.09×104 km² under SSP370 and SSP585 scenarios respectively.C.barometz mainly distributed in range of 90°E-150°E longitude and 10°S-30°N latitude.Under three climate scenarios,C.barometz distribution centers showed trends of moving to regions with lower latitudes from current to 2070s,and showed trends of moving to regions with higher latitudes from 2070s to 2090s.

庞庆玲;李健玲;秦波;梁圣华;邓诗玲;蒋日红

广西壮族自治区林业科学研究院 广西特色经济林培育与利用重点实验室 广西林业实验室,广西 南宁 530002广西壮族自治区林业科学研究院 广西特色经济林培育与利用重点实验室 广西林业实验室,广西 南宁 530002广西壮族自治区林业科学研究院 广西特色经济林培育与利用重点实验室 广西林业实验室,广西 南宁 530002广西壮族自治区林业科学研究院 广西特色经济林培育与利用重点实验室 广西林业实验室,广西 南宁 530002广西壮族自治区林业科学研究院 广西特色经济林培育与利用重点实验室 广西林业实验室,广西 南宁 530002广西壮族自治区林业科学研究院 广西特色经济林培育与利用重点实验室 广西林业实验室,广西 南宁 530002

农业科技

MaxEnt模型环境因子地理分布金毛狗

MaxEnt modelenvironmental factorgeographical distributionCibotium barometz

《广西林业科学》 2026 (1)

30-40,11

广西科技创新平台计划(桂科LT2504240030)广西林业科技推广示范项目(2023LYKJ04)广西林科院高层次人才项目(桂林研[RC]2302)

10.19692/j.issn.1006-1126.20260104

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