Predicting the Potential Distribution of Aralia chinensis L. (Wild Vegetable) in China Under Different Climate Change Scenarios

被引:0
|
作者
Liu, Longjiang [1 ]
Liang, Shanshan [1 ]
Xie, Chengshi [1 ]
Liu, Jie [1 ]
Zheng, Yaqiang [1 ]
Xue, Juan [1 ]
机构
[1] Guizhou Univ Tradit Chinese Med, Coll Pharm, Guiyang 550025, Peoples R China
来源
BIOLOGY-BASEL | 2024年 / 13卷 / 11期
关键词
<italic>Aralia chinensis</italic> L; MaxEnt; potential distribution; suitable habitats; SPECIES DISTRIBUTIONS; MODELS;
D O I
10.3390/biology13110937
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
Global climate change has a main impact on the distribution of plants. Aralia chinensis L. is economically valuable, making it necessary to predict the impact of climate change on its distribution. It is important for researching the effects of climate change on A. chinensis distribution to achieve sustainable utilization. Based on 340 occurrence records of A. chinensis covering all known provinces and 58 environmental factor data, we used MaxEnt to simulate the potential distribution of A. chinensis under current and different future climate scenarios, analyzing the key environmental variables affecting its distribution. The results were as follows: (1) Suitable A. chinensis habitats under current and different future climate scenarios were mainly distributed in the southern region of China, east of the Hu Huanyong line. (2) Annual precipitation, minimum temperature during the coldest month, precipitation during the driest month, and slope were the key environmental variables affecting its potential distribution, and annual precipitation was more important. (3) Suitable habitat areas were projected to increase under different future climate scenarios and expand westward and northward while shrinking in the central regions, such as Hubei and Hunan. The results provide a theoretical reference for the conservation and cultivation of A. chinensis.
引用
收藏
页数:14
相关论文
共 50 条
  • [1] Predicting the Potential Geographical Distribution of Rhodiola L. in China under Climate Change Scenarios
    Yang, Meilin
    Sun, Lingxiao
    Yu, Yang
    Zhang, Haiyan
    Malik, Ireneusz
    Wistuba, Malgorzata
    Yu, Ruide
    PLANTS-BASEL, 2023, 12 (21):
  • [2] Predicting the Potential Distribution of Perennial Plant Coptis chinensis Franch. in China under Multiple Climate Change Scenarios
    Zhao, Qian
    Zhang, Yuan
    Li, Wen-Na
    Hu, Bang-Wen
    Zou, Jia-Bin
    Wang, Shi-Qiang
    Niu, Jun-Feng
    Wang, Zhe-Zhi
    FORESTS, 2021, 12 (11):
  • [3] Predicting the Potential Distribution of Quercus oxyphylla in China under Climate Change Scenarios
    Chen, Shuhan
    You, Chengming
    Zhang, Zheng
    Xu, Zhenfeng
    FORESTS, 2024, 15 (06):
  • [4] Potential Distribution Projections for Senegalia senegal (L.) Britton under Climate Change Scenarios
    Fang, Jiaqi
    Shi, Jianfei
    Zhang, Ping
    Shao, Minghao
    Zhou, Na
    Wang, Yongdong
    Xu, Xinwen
    FORESTS, 2024, 15 (02)
  • [5] Predicting Possible Distribution of Tea (Camellia sinensis L.) under Climate Change Scenarios Using MaxEnt Model in China
    Zhao, Yuncheng
    Zhao, Mingyue
    Zhang, Lei
    Wang, Chunyi
    Xu, Yinlong
    AGRICULTURE-BASEL, 2021, 11 (11):
  • [6] Predicting potential habitat suitability of Quercus suber L. in Algeria under climate change scenarios
    Laala, Ahmed
    Alatou, Djamel
    Adimi, Amina
    AFRICAN JOURNAL OF ECOLOGY, 2021, 59 (04) : 976 - 987
  • [7] Lethal yellowing disease: insights from predicting potential distribution under different climate change scenarios
    Aidoo, Owusu Fordjour
    Cunze, Sarah
    Guimapi, Ritter A.
    Arhin, Linda
    Ablormeti, Fred Kormla
    Tettey, Elizabeth
    Dampare, Frank
    Afram, Yayra
    Bonsu, Osei
    Obeng, Joshua
    Lutuf, Hanif
    Dickinson, Matthew
    Yankey, Ndede
    JOURNAL OF PLANT DISEASES AND PROTECTION, 2021, 128 (05) : 1313 - 1325
  • [8] Lethal yellowing disease: insights from predicting potential distribution under different climate change scenarios
    Owusu Fordjour Aidoo
    Sarah Cunze
    Ritter A. Guimapi
    Linda Arhin
    Fred Kormla Ablormeti
    Elizabeth Tettey
    Frank Dampare
    Yayra Afram
    Osei Bonsu
    Joshua Obeng
    Hanif Lutuf
    Matthew Dickinson
    Ndede Yankey
    Journal of Plant Diseases and Protection, 2021, 128 : 1313 - 1325
  • [9] Distribution modeling for predicting habitat suitability for citron (Citrus medica L.) under climate change scenarios
    Maurya, Aakash
    Semwal, Manoj
    Mishra, Bhavya Priyadarshini
    Mohan, Ram
    Rana, Tikam Singh
    Nair, Narayanan K.
    FLORA, 2023, 304
  • [10] Maxent Modeling for Predicting the Potential Geographical Distribution of Castanopsis carlesii under Various Climate Change Scenarios in China
    Zhong, Xiaoru
    Zhang, Lu
    Zhang, Jiabiao
    He, Liren
    Sun, Rongxi
    FORESTS, 2023, 14 (07):