STUDY ON RARE AND ENDANGERED PLANTS UNDER CLIMATE: MAXENT MODELING FOR IDENTIFYING HOT SPOTS IN NORTHWEST CHINA
Autor(a) principal: | |
---|---|
Data de Publicação: | 2021 |
Outros Autores: | |
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. |
id |
UFLA-3_1743da9112c3528c95c5a99ac3595d17 |
---|---|
oai_identifier_str |
oai:cerne.ufla.br:article/2667 |
network_acronym_str |
UFLA-3 |
network_name_str |
Cerne (Online) |
repository_id_str |
|
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 |
_version_ |
1799874944229703680 |