Article(id=1309565368960639152, tenantId=1146029695717560320, journalId=1308397196074385509, issueId=1309565023480021997, articleNumber=null, orderNo=null, doi=10.11733/j.issn.1007-0435.2026.01.021, pmid=null, cstr=null, oa=null, hot=0, price=null, onlineType=0, articleFormat=0, articleType=null, articleTypeStr=null, receivedDate=1739635200000, receivedDateStr=2025-02-16, revisedDate=1743436800000, revisedDateStr=2025-04-01, acceptedDate=null, acceptedDateStr=null, onlineDate=1790154314508, onlineDateStr=2026-09-23, pubDate=null, pubDateStr=null, doiRegisterDate=null, doiRegisterDateStr=null, onlineIssueDate=1790154314508, onlineIssueDateStr=2026-09-23, onlineJustAcceptDate=null, onlineJustAcceptDateStr=null, onlineFirstDate=null, onlineFirstDateStr=null, sourceXml=null, magXml=null, createTime=1790154314508, creator=13701087609, updateTime=1790154314508, updator=13701087609, issue=Issue{id=1309565023480021997, tenantId=1146029695717560320, journalId=1308397196074385509, year='2026', volume='34', issue='1', pageStart='1', pageEnd='376', issueExtLink='null', onlineDate='null', pubDate='1768406400000', pubDateStr='2026-01-15', beforeIssueId=null, nextIssueId=null, price=null, status=1, issueComplete=1, articleOrder=1, issueType=-1, specialIssue=null, createTime=1790154232139, creator='13701087609', updateTime=1790156721646, updator='13701087609', preIssue=null, nextIssue=null, articleTotal=null, ext={EN=IssueExt(id=1309575465308880991, tenantId=1146029695717560320, journalId=1308397196074385509, issueId=1309565023480021997, language=EN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=), CN=IssueExt(id=1309575465308880992, tenantId=1146029695717560320, journalId=1308397196074385509, issueId=1309565023480021997, language=CN, specialIssueTitle=, coverIllustrator=null, specialIssueEditor=, specialIssueAbout=)}, issueFiles=null, downloadFileDto=null}, startPage=217, endPage=230, ext={EN=ArticleExt(id=1309565369308766386, articleId=1309565368960639152, tenantId=1146029695717560320, journalId=1308397196074385509, language=EN, title=Predicted Distribution Patterns and Spatial Shifts of the Endemic Species Artemisia dalai-lamae under Climate Change, columnId=null, journalTitle=Acta Agrestia Sinica, columnName=null, runingTitle=null, highlight=null, articleAbstract=To investigate the responses of distribution patterns of the endemic species Artemisia dalai-lamae in China to future climate change, this study utilized a parameter-optimized MaxEnt model with specimen data and environmental variables. The distribution patterns and centroid shifts of A. dalai-lamae under current and future (2021—2060) climate scenarios across three representative pathways were predicted. The results indicate that when the Regularization Multiplier (RM) was set to 3 and the Feature Combination (FC) configured as linear, quadratic and hinge (LQH), the model achieved the lowest complexity and overfitting while maintaining high predictive accuracy. The primary environmental factors influencing the distribution of A. dalai-lamae were elevation, annual precipitation, precipitation of warmest quarter, and annual mean temperature. Under current climate conditions, the suitable habitat area for A. dalai-lamae spans 122.93×104 km2, with optimal distribution concentrated between the eastern sections of the Qilian and Kunlun Mountains. Under future climate scenarios, the suitable habitat area is projected to significantly decrease (with a maximum reduction of 43.2%), and the distribution centroid shows a northwestward shift toward higher latitudes and elevations. These findings suggest that future climate warming poses a severe threat to the survival of A. dalai-lamae., authors=HE Wei1, FANG Qiang-en1, SHAN Lin-qian1, WANG Tong1, WANG Zhen1, authorsList=HE Wei, FANG Qiang-en, SHAN Lin-qian, WANG Tong, WANG Zhen, authorCompany=1 College of Prataculture, Gansu Agricultural University/Key Laboratory of Prataculture Ecosystem of Ministry of Education/China-US Research Center for Sustainable Development of Grassland Animal Husbandry, Lanzhou, Gausu Province 730070, China, correspAuthors=null, authorNote=null, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, articleAbsUrl=null, sourceXml=null, magXml=null, pdfUrl=null, pdf=null, pdfFileSize=null, pdfExtLink=null, richHtmlUrl=null, mobilePdfUrl=null, reviewReport=null, pdfFirstPage=null, abstractGraph=null, abstractGraphContent=null, abstractVideo=null, citation=null, cebUrl=null, magXmlContent=null, mapNumber=null, fund=null), CN=ArticleExt(id=1309565369208103089, articleId=1309565368960639152, tenantId=1146029695717560320, journalId=1308397196074385509, language=CN, title=气候变化背景下特有种米蒿的分布格局及其空间迁移预测, columnId=1309565024058835950, journalTitle=草地学报, columnName=研究论文, runingTitle=null, highlight=null, articleAbstract=为探究我国特有种米蒿(Artemisia dalai-lamae)的分布格局对未来气候变化的响应,本研究基于标本数据与环境变量数据,通过参数优化后的MaxEnt模型,预测当前及未来(2021—2060年)时期三种气候情景下米蒿的分布格局与质心变化趋势。结果表明:当模型调控倍率(Regularization multiplier, RM)为3,特征组合(Feature combination, FC)为线性加二次型加分段化(LQH)时,模型复杂度和过拟合程度最低,预测准确性高;影响米蒿分布的主要环境因子是海拔、年均降水量、暖季降水量和年平均气温;在当前气候条件下,米蒿的适生区面积为122.93×10⁴ km²,最适分布区主要集中在祁连山和昆仑山东段之间;在未来气候条件下,米蒿的适生面积将显著缩减(最大降幅达43.2%),质心有向西北方向高纬度高海拔区域迁移的趋势,表明未来气候变暖将对米蒿生存构成极大威胁。, authors=何伟1, 方强恩1, 单麟茜1, 王彤1, 王振1, authorsList=何伟, 方强恩, 单麟茜, 王彤, 王振, authorCompany=1 甘肃农业大学草业学院/草业生态系统教育部重点实验室/中-美草地畜牧业可持续发展研究中心, 甘肃 兰州 730070, correspAuthors=null, authorNote=何伟(2001-),男,回族,浙江瑞安人,硕士研究生,主要从事草种质资源评价与利用研究,E-mail:863273202@qq.com, correspAuthorsNote=null, copyrightStatement=null, copyrightOwner=null, extLink=null, 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Predicted Distribution Patterns and Spatial Shifts of the Endemic Species Artemisia dalai-lamae under Climate Change
HE Wei1, FANG Qiang-en1, SHAN Lin-qian1, WANG Tong1, WANG Zhen1
Affiliations
1 College of Prataculture, Gansu Agricultural University/Key Laboratory of Prataculture Ecosystem of Ministry of Education/China-US Research Center for Sustainable Development of Grassland Animal Husbandry, Lanzhou, Gausu Province 730070, China
To investigate the responses of distribution patterns of the endemic species Artemisia dalai-lamae in China to future climate change, this study utilized a parameter-optimized MaxEnt model with specimen data and environmental variables. The distribution patterns and centroid shifts of A. dalai-lamae under current and future (2021—2060) climate scenarios across three representative pathways were predicted. The results indicate that when the Regularization Multiplier (RM) was set to 3 and the Feature Combination (FC) configured as linear, quadratic and hinge (LQH), the model achieved the lowest complexity and overfitting while maintaining high predictive accuracy. The primary environmental factors influencing the distribution of A. dalai-lamae were elevation, annual precipitation, precipitation of warmest quarter, and annual mean temperature. Under current climate conditions, the suitable habitat area for A. dalai-lamae spans 122.93×104 km2, with optimal distribution concentrated between the eastern sections of the Qilian and Kunlun Mountains. Under future climate scenarios, the suitable habitat area is projected to significantly decrease (with a maximum reduction of 43.2%), and the distribution centroid shows a northwestward shift toward higher latitudes and elevations. These findings suggest that future climate warming poses a severe threat to the survival of A. dalai-lamae.
Key words
MaxEnt model
/
Climate change
/
Suitable distribution area
/
Artemisia dalai-lamae
/
Endemic species
HE Wei, FANG Qiang-en, SHAN Lin-qian, WANG Tong, WANG Zhen.
Predicted Distribution Patterns and Spatial Shifts of the Endemic Species Artemisia dalai-lamae under Climate Change[J].
Acta Agrestia Sinica,
2026
, 34
(1)
: 217
-230
.
DOI: 10.11733/j.issn.1007-0435.2026.01.021
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