STUDY ON RARE AND ENDANGERED PLANTS UNDER CLIMATE: MAXENT MODELING FOR IDENTIFYING HOT SPOTS IN NORTHWEST CHINA

Detalhes bibliográficos
Autor(a) principal: zhao, haoxiang
Data de Publicação: 2021
Outros Autores: ZHANG, HUA
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Cerne (Online)
Texto Completo: https://cerne.ufla.br/site/index.php/CERNE/article/view/2667
Resumo: Climate warming has caused substantial changes in spatial and temporal environmental patterns. The study on hot spots of rare and endangered plants in northwest china under predicted climate change provides a scientific reference for the restoration and reconstruction of degraded habitats of rare and endangered plants and the construction and improvement of protection system in northwest China. Based on MaxEnt model, based on 813 effective distribution records and 11 environmental factor variables of rare and endangered plants in northwest china, this study identified the changes of hot spots of rare and endangered plants in northwest china under predicted climate change by using MaxEnt model and ArcGIS software. Comprehensive environmental factor variable contribution rate and knife-cutting method were used to examine and evaluate the important factors affecting the hot spots of rare and endangered plants in northwest china. The appropriate range of environmental factor variables was determined by response curve, and the hot spots and areas threatened by rare and endangered plants in northwest china were determined quantitatively. The results show that: (1) the prediction accuracy of MaxEnt model is high, the working curve area (AUC) of subjects is 0.876, and the total suitable area for potential geographical distribution of rare and endangered plants in northwest china is 137.96×104km2, which is mainly located in western and southwestern Xinjiang province, southern Gansu province, sporadic eastern and southern qinghai province, and southern Shaanxi province. (2) the main environmental factors affecting the hot spots of rare and endangered plants in northwest china are altitude, temperature factors (daily range of average temperature and lowest temperature of the coldest month) and precipitation factors (precipitation in the wettest season) (3) in the future four climate change scenarios, with the increase of emission scenarios from low forcing to high forcing, the loss of hot spots of rare and endangered plants in northwest china is the most obvious in Xinjiang province. The increase is most obvious in qinghai province and Gansu province.
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spelling STUDY ON RARE AND ENDANGERED PLANTS UNDER CLIMATE: MAXENT MODELING FOR IDENTIFYING HOT SPOTS IN NORTHWEST CHINAnorthwest region; Rare and Endangered Plants; MaxEnt model; hot spots; climate changeClimate warming has caused substantial changes in spatial and temporal environmental patterns. The study on hot spots of rare and endangered plants in northwest china under predicted climate change provides a scientific reference for the restoration and reconstruction of degraded habitats of rare and endangered plants and the construction and improvement of protection system in northwest China. Based on MaxEnt model, based on 813 effective distribution records and 11 environmental factor variables of rare and endangered plants in northwest china, this study identified the changes of hot spots of rare and endangered plants in northwest china under predicted climate change by using MaxEnt model and ArcGIS software. Comprehensive environmental factor variable contribution rate and knife-cutting method were used to examine and evaluate the important factors affecting the hot spots of rare and endangered plants in northwest china. The appropriate range of environmental factor variables was determined by response curve, and the hot spots and areas threatened by rare and endangered plants in northwest china were determined quantitatively. The results show that: (1) the prediction accuracy of MaxEnt model is high, the working curve area (AUC) of subjects is 0.876, and the total suitable area for potential geographical distribution of rare and endangered plants in northwest china is 137.96×104km2, which is mainly located in western and southwestern Xinjiang province, southern Gansu province, sporadic eastern and southern qinghai province, and southern Shaanxi province. (2) the main environmental factors affecting the hot spots of rare and endangered plants in northwest china are altitude, temperature factors (daily range of average temperature and lowest temperature of the coldest month) and precipitation factors (precipitation in the wettest season) (3) in the future four climate change scenarios, with the increase of emission scenarios from low forcing to high forcing, the loss of hot spots of rare and endangered plants in northwest china is the most obvious in Xinjiang province. The increase is most obvious in qinghai province and Gansu province.CERNECERNE2021-03-18info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://cerne.ufla.br/site/index.php/CERNE/article/view/2667CERNE; Vol 27 No 1 (2021); e-102667CERNE; Vol 27 No 1 (2021); e-1026672317-63420104-7760reponame:Cerne (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAenghttps://cerne.ufla.br/site/index.php/CERNE/article/view/2667/1228Copyright (c) 2021 CERNEinfo:eu-repo/semantics/openAccesszhao, haoxiangZHANG, HUA2022-01-17T17:29:18Zoai:cerne.ufla.br:article/2667Revistahttps://cerne.ufla.br/site/index.php/CERNEPUBhttps://cerne.ufla.br/site/index.php/CERNE/oaicerne@dcf.ufla.br||cerne@dcf.ufla.br2317-63420104-7760opendoar:2024-05-21T19:54:46.914443Cerne (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv STUDY ON RARE AND ENDANGERED PLANTS UNDER CLIMATE: MAXENT MODELING FOR IDENTIFYING HOT SPOTS IN NORTHWEST CHINA
title STUDY ON RARE AND ENDANGERED PLANTS UNDER CLIMATE: MAXENT MODELING FOR IDENTIFYING HOT SPOTS IN NORTHWEST CHINA
spellingShingle STUDY ON RARE AND ENDANGERED PLANTS UNDER CLIMATE: MAXENT MODELING FOR IDENTIFYING HOT SPOTS IN NORTHWEST CHINA
zhao, haoxiang
northwest region; Rare and Endangered Plants; MaxEnt model; hot spots; climate change
title_short STUDY ON RARE AND ENDANGERED PLANTS UNDER CLIMATE: MAXENT MODELING FOR IDENTIFYING HOT SPOTS IN NORTHWEST CHINA
title_full STUDY ON RARE AND ENDANGERED PLANTS UNDER CLIMATE: MAXENT MODELING FOR IDENTIFYING HOT SPOTS IN NORTHWEST CHINA
title_fullStr STUDY ON RARE AND ENDANGERED PLANTS UNDER CLIMATE: MAXENT MODELING FOR IDENTIFYING HOT SPOTS IN NORTHWEST CHINA
title_full_unstemmed STUDY ON RARE AND ENDANGERED PLANTS UNDER CLIMATE: MAXENT MODELING FOR IDENTIFYING HOT SPOTS IN NORTHWEST CHINA
title_sort STUDY ON RARE AND ENDANGERED PLANTS UNDER CLIMATE: MAXENT MODELING FOR IDENTIFYING HOT SPOTS IN NORTHWEST CHINA
author zhao, haoxiang
author_facet zhao, haoxiang
ZHANG, HUA
author_role author
author2 ZHANG, HUA
author2_role author
dc.contributor.author.fl_str_mv zhao, haoxiang
ZHANG, HUA
dc.subject.por.fl_str_mv northwest region; Rare and Endangered Plants; MaxEnt model; hot spots; climate change
topic northwest region; Rare and Endangered Plants; MaxEnt model; hot spots; climate change
description Climate warming has caused substantial changes in spatial and temporal environmental patterns. The study on hot spots of rare and endangered plants in northwest china under predicted climate change provides a scientific reference for the restoration and reconstruction of degraded habitats of rare and endangered plants and the construction and improvement of protection system in northwest China. Based on MaxEnt model, based on 813 effective distribution records and 11 environmental factor variables of rare and endangered plants in northwest china, this study identified the changes of hot spots of rare and endangered plants in northwest china under predicted climate change by using MaxEnt model and ArcGIS software. Comprehensive environmental factor variable contribution rate and knife-cutting method were used to examine and evaluate the important factors affecting the hot spots of rare and endangered plants in northwest china. The appropriate range of environmental factor variables was determined by response curve, and the hot spots and areas threatened by rare and endangered plants in northwest china were determined quantitatively. The results show that: (1) the prediction accuracy of MaxEnt model is high, the working curve area (AUC) of subjects is 0.876, and the total suitable area for potential geographical distribution of rare and endangered plants in northwest china is 137.96×104km2, which is mainly located in western and southwestern Xinjiang province, southern Gansu province, sporadic eastern and southern qinghai province, and southern Shaanxi province. (2) the main environmental factors affecting the hot spots of rare and endangered plants in northwest china are altitude, temperature factors (daily range of average temperature and lowest temperature of the coldest month) and precipitation factors (precipitation in the wettest season) (3) in the future four climate change scenarios, with the increase of emission scenarios from low forcing to high forcing, the loss of hot spots of rare and endangered plants in northwest china is the most obvious in Xinjiang province. The increase is most obvious in qinghai province and Gansu province.
publishDate 2021
dc.date.none.fl_str_mv 2021-03-18
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://cerne.ufla.br/site/index.php/CERNE/article/view/2667
url https://cerne.ufla.br/site/index.php/CERNE/article/view/2667
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://cerne.ufla.br/site/index.php/CERNE/article/view/2667/1228
dc.rights.driver.fl_str_mv Copyright (c) 2021 CERNE
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 CERNE
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv CERNE
CERNE
publisher.none.fl_str_mv CERNE
CERNE
dc.source.none.fl_str_mv CERNE; Vol 27 No 1 (2021); e-102667
CERNE; Vol 27 No 1 (2021); e-102667
2317-6342
0104-7760
reponame:Cerne (Online)
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Cerne (Online)
collection Cerne (Online)
repository.name.fl_str_mv Cerne (Online) - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv cerne@dcf.ufla.br||cerne@dcf.ufla.br
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