首页|期刊导航|生态学杂志|基于优化的MaxEnt模型的遵义乡土花椒适生区预测

基于优化的MaxEnt模型的遵义乡土花椒适生区预测OA

Prediction of suitable distribution for Zunyi native Chinese prickly ash based on optimized MaxEnt

中文摘要英文摘要

遵义乡土花椒果皮品质极优,开展适生区分布预测对于遵义乡土花椒的推广种植具有重要意义.本研究基于33个分布点信息和27个生态因子,采用ENMeval优化的最大熵模型(MaxEnt),结合ArcGIS预测遵义乡土花椒的适生区分布,并分析影响其分布的主要生态因子.结果表明:在当前(1970-2000年)和未来气候(2050年)下,训练样品的受试者工作特征曲线下的面积值(AUC)均高于0.9,表明预测结果可靠;影响遵义乡土花椒潜在分布的主要生态因子为最干月降水量、最冷月最低温、等温性和年温度变化范围,累计贡献率为97.3%;当前气候条件下,遵义乡土花椒高、中和低适生区面积分别为1.35×104、0.93×104和0.57×104 km2,高适生区主要集中在遵义北部的赤水、习水北、桐梓和道真等地;与当前气候相比,遵义乡土花椒在未来2050年的RCP26和RCP45两种气候情景下的高适生区面积将减少,主要减少区域为习水、桐梓和道真等地区.

Zunyi native Chinese prickly ash in Guizhou Province has excellent pericarp quality.Predicting the dis-tribution of suitable areas is of great significance for extending the cultivation of this species.Based on the informa-tion of 33 distribution points and 27 ecological factors,we adopted the MaxEnt model optimized by ENMeval com-bined with ArcGIS to predict the distribution of suitable areas for Zunyi native Chinese prickly ash,.and analyzed the main ecological factors affecting its distribution.The results showed that the receiver operating characteristic curve area(AUC)of the training sample under both 1970-2000 and 2050s climate conditions was higher than 0.9,indicating that the prediction result was reliable.The dominant ecological factors affecting the distribution of Zunyi native Chinese prickly ash were the precipitation of the driest month,the lowest temperature of the coldest month,isothermality,and the annual temperature range,with the cumulative contribution of those four factors being 97.3%.The areas of highly,moderately,and lowly suitable distribution of this species under the climate conditions of 1970-2000 were 1.35×104,0.93×104,and 0.57×104 km2,respectively.The highly suitable areas were mainly distributed in Chishui,northern Xishui,Tongzi,and Daozhen in northern Zunyi.The highly suitable area of Zunyi native Chinese prickly ash will decrease in both RCP26 and RCP45 climate scenarios by 2050,with the main re-duction areas being Xishui,Tongzi,and Daozhen.

陈翠萍;王志琴;余红梅;周朝彬;王景燕

四川农业大学林学院,林业生态工程省级重点实验室,成都 611130遵义师范学院,贵州遵义 563006遵义师范学院,贵州遵义 563006中国科学院植物研究所,北京 100093奉节县农业技术服务中心,重庆 404699

花椒最大熵模型ArcGIS潜在适生区气候变化

Chinese prickly ashmaximum entropy modelArcGISpotentially suitable regionclimate change

《生态学杂志》 2026 (1)

276-283,8

贵州省科技厅基础研究计划项目(黔科合基础-ZK[2022]一般579)、贵州省林业局应用基础研究项目(黔林科合[2022]39号)、国家重点研发计划项目(2018YFD1000605和2020YFD1000700)、赤水河流域环境保护与山地农业发展人才基地项目和贵州省教育厅自然科学研究项目(黔教技[2023]043号)资助.

10.13292/j.1000-4890.202601.001

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