Prediction of the potentially suitable areas of Litsea cubeba in China based on future climate change using the optimized MaxEnt model

被引:40
|
作者
Shi, Xiaodeng [1 ]
Wang, Jiawei [2 ]
Zhang, Li [2 ]
Chen, Shangxing [3 ]
Zhao, Anlin [4 ]
Ning, Xiaodan [2 ,3 ]
Fan, Guorong [3 ]
Wu, Nansheng [2 ]
Zhang, Ling [2 ]
Wang, Zongde [3 ]
机构
[1] Zhejiang Acad Forestry, Hangzhou 310023, Peoples R China
[2] Jiangxi Agr Univ, Coll Forestry, Jiangxi Key Lab Silviculture, Nanchang 330045, Peoples R China
[3] Jiangxi Agr Univ, Coll Forestry, Camphor Engn Res Ctr NFGA, East China Woody Fragrance & Flavor Engn Res Ctr,N, Nanchang 330045, Peoples R China
[4] East China Survey & Planning Inst, Hangzhou 310019, Peoples R China
关键词
Climate change; Litsea cubeba; MaxEnt; Potentially suitable area; Species distribution models; Woody oil plant; SPECIES DISTRIBUTION; ESSENTIAL OIL; COMPLEXITY; ACCURACY; REGION; FRUITS; GIS;
D O I
10.1016/j.ecolind.2023.110093
中图分类号
X176 [生物多样性保护];
学科分类号
090705 ;
摘要
Litsea cubeba is an important woody oil plant. The essential oils (EOs) can be extracted from its flowers, leaves and peels and, by volume, it is the most exported natural EOs from China. Thus, L. cubeba has important economic and medicinal value. Although there is demand for the rapid expansion of L. cubeba production, there has been a sharp reduction in natural resources. Therefore, determining the potentially suitable area for L. cubeba and expanding its cultivation will help meet the growing demand for volatile oil. Based on 453 distribution records of L. cubeba in China and 16 major environmental factors, we simulated the distribution pattern of the potentially suitable area of L. cubeba under three different climate change scenarios (SSP126, SSP370 and SSP585) in three time periods: the current period, 2050 s, and 2070 s. The analysis was implemented using the MaxEnt model, optimized using the ENMeval package. The jackknife test, percent contribution and response curve were used to determine the most important environmental factors and response intervals affecting the distribution of L. cubeba. We found that the parameter settings of the optimal model were RM = 2.5 and FC = LQH. The results of the MaxEnt model exhibited a high prediction accuracy and a low degree of overfitting. Precipitation of the driest quarter, annual precipitation, temperature annual range and minimum temperature of the coldest month were the dominant factors affecting the distribution of L. cubeba, and their thresholds were >= 36.21 mm, >= 905.95 mm, <= 32.44 degrees C and >= -3.73 degrees C, respectively. The results showed that the total potentially suitable area of L. cubeba in China was 208.19 x 104 km2 under current climate conditions. The predicted potentially suitable area was mainly concentrated in the 19 provinces and cities in the Yangtze River Basin and its southern area. Under future climate change conditions, the predicted potentially suitable area of L. cubeba increased with time, and the centroid of the predicted potentially suitable area of each grade moved northward. The results of this study can be used to guide the selection of future introductions, as well as the development, artificial cultivation and resource conservation of L. cubeba.
引用
收藏
页数:13
相关论文
共 50 条
  • [31] The influence of climate change on the future distribution of two Thymus species in Iran: MaxEnt model-based prediction
    Hosseini, Naser
    Ghorbanpour, Mansour
    Mostafavi, Hossein
    BMC PLANT BIOLOGY, 2024, 24 (01)
  • [32] Predicting the Impact of Climate Change on the Future Distribution of Paederus fuscipes Curtis, 1826, in China Based on the MaxEnt Model
    Gao, Hui
    Wei, Xinju
    Peng, Yaqin
    Zhuo, Zhihang
    INSECTS, 2024, 15 (06)
  • [33] Predicting the Potential Distribution of Hylomecon japonica in China under Current and Future Climate Change Based on Maxent Model
    Cao, Zhen
    Zhang, Lei
    Zhang, Xinxin
    Guo, Zengjun
    SUSTAINABILITY, 2021, 13 (20)
  • [34] Prediction of Chinese suitable habitats of Panax notoginseng under climate change based on MaxEnt and chemometric methods
    Guo Y.
    Zhang S.
    Ren L.
    Tian X.
    Tang S.
    Xian Y.
    Wu X.
    Zhang Z.
    Scientific Reports, 14 (1)
  • [35] Predictive Modeling of Suitable Habitats for Cinnamomum Camphora (L.) Presl Using Maxent Model under Climate Change in China
    Zhang, Lei
    Jing, Zhinong
    Li, Zuyao
    Liu, Yang
    Fang, Shengzuo
    INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, 2019, 16 (17)
  • [36] Prediction of the Current and Future Distribution of Tomato Leafminer in China Using the MaxEnt Model
    Yang, Hangxin
    Jiang, Nanziying
    Li, Chao
    Li, Jun
    INSECTS, 2023, 14 (06)
  • [37] Current and future distribution of Forsythia suspensa in China under climate change adopting the MaxEnt model
    Wang, En
    Lu, Zongran
    Rohani, Emelda Rosseleena
    Ou, Jinmei
    Tong, Xiaohui
    Han, Rongchun
    FRONTIERS IN PLANT SCIENCE, 2024, 15
  • [38] Predicting the current and future distributions of Pennisetum alopecuroides (L.) in China under climate change based on the MaxEnt model
    Xu, Yuandong
    Zhu, Ruifen
    Gao, Lifang
    Huang, Dejun
    Fan, Yan
    Liu, Chang
    Chen, Jishan
    PLOS ONE, 2023, 18 (04):
  • [39] Assessing the suitable cultivation areas for Scutellaria baicalensis in China using the Maxent model and multiple linear regression
    Xu, Ning
    Meng, Fanyun
    Zhou, Guofu
    Li, Yunfeng
    Wang, Bo
    Lu, Heng
    BIOCHEMICAL SYSTEMATICS AND ECOLOGY, 2020, 90
  • [40] PREDICTING SUITABLE HABITAT FOR CHINA'S ENDANGERED PLANT CYCAS SEGMENTIFIDA USING MAXENT UNDER CLIMATE CHANGE
    Wei, Lijuan
    Chen, Xinyue
    Yang, Honglan
    Sun, Weina
    Pan, Yang
    Wang, Guohai
    PAKISTAN JOURNAL OF BOTANY, 2024, 56 (05) : 1881 - 1888