Modeling the Effects of Climate Change on the Current and Future Potential Distribution of Berberis vulgaris L. with Machine Learning

被引:0
|
作者
Sarikaya, Ayse Gul [1 ]
Uzun, Almira [2 ]
机构
[1] Bursa Tech Univ, Fac Forestry, TR-16310 Bursa, Turkiye
[2] Bursa Tech Univ, Grad Sch, TR-16310 Bursa, Turkiye
关键词
Berberis vulgaris; climate change; maxent; machine learning; sustainability; distribution; SPECIES DISTRIBUTIONS; HABITAT SUITABILITY; MAXENT; PREDICTION; SURFACES; IMPACTS;
D O I
10.3390/su16031230
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Species of the Berberis genus, which are widely distributed naturally throughout the world, are cultivated and used for various purposes such as food, medicinal applications, and manufacturing dyes. Model-based machine learning is a language for specifying models, allowing the definition of a model using concise code, and enabling the automatic creation of software that implements the specified model. Maximum entropy (MaxEnt 3.4.1) is an algorithm used to model the appropriate distribution of species across geographical regions and is based on the species distribution model that is frequently also used in modeling the current and future potential distribution areas of plant species. Therefore, this study was conducted to estimate the current and future potential distribution areas of Berberis vulgaris in T & uuml;rkiye for the periods 2041-2060 and 2081-2100, according to the SSP2 4.5 and SSP5 8.5 scenarios based on the IPSL-CM6A-LR climate change model. For this purpose, the coordinates obtained in the WGS 84 coordinate system were marked using the 5 m high spatial resolution Google Satellite Hybrid base maps, which are readily available in the 3.10.4 QGIS program, the current version of QGIS (Quantum GIS). The CM6A-LR climate model, the latest version of the IPSL climate models, was used to predict the species' future distribution area. The area showed a high correlation with the points representing B. vulgaris, which is generally distributed in the Mediterranean and the central and eastern Black Sea regions of T & uuml;rkiye, and the very suitable areas encompassed 45,413.82 km(2). However, when the SSP2 4.5 scenario was considered for the period 2041-2060, the areas very suitable for Berberis vulgaris comprised 59,120.05 km(2), and in the SSP2 4.5 scenario, very suitable areas were found to encompass 56,730.46 km(2) in the 2081-2100 period. Considering the SSP5 8.5 scenario for the period 2041-2060, the area most suitable for the B. vulgaris species is 66,670.39 km(2). In the SSP5 8.5 scenario, very suitable areas were found to cover 20,108.29 km(2) in the 2081-2100 period. Careful consideration of both the potential positive and negative impacts of climate change is essential, and these should be regarded as opportunities to implement appropriate adaptation strategies. The necessary conditions for the continued existence and sustainability of B. vulgaris-that is, areas with ecological niche potential-have been determined.
引用
收藏
页数:16
相关论文
共 50 条
  • [21] Distribution of rose hip (Rosa canina L.) under current and future climate conditions
    E. Seda Arslan
    Ayhan Akyol
    Ömer K. Örücü
    Ayşe Gül Sarıkaya
    Regional Environmental Change, 2020, 20
  • [22] Modeling the climate suitability of tea [Camellia sinensis(L.) O. Kuntze] in Sri Lanka in response to current and future climate change scenarios
    Jayasinghe, Sadeeka Layomi
    Kumar, Lalit
    AGRICULTURAL AND FOREST METEOROLOGY, 2019, 272 : 102 - 117
  • [23] Potential effects of climate change on future distribution of an endangered tree species, Acer mazandaranicum, in the Hyrcanian forest
    Yousefzadeh, Hamed
    Walas, Lukasz
    Amirchakhmaghi, Narjes
    Alipour, Shirin
    Pouramin, Mansour
    Song, Yi-Gang
    Kozlowski, Gregor
    FOREST ECOLOGY AND MANAGEMENT, 2024, 555
  • [24] Modeling coffee (Coffea arabica L.) climate suitability under current and future scenario in Jimma zone, Ethiopia
    Benti, Fedhasa
    Diga, Girma Mamo
    Feyisa, Gudina Legessie
    Tolesa, Alemayehu Regassa
    ENVIRONMENTAL MONITORING AND ASSESSMENT, 2022, 194 (04)
  • [25] The past, current, and future distribution modeling of four water lilies (Nymphaea) in Africa indicates varying suitable habitats and distribution in climate change
    Nzei, John M.
    Ngarega, Boniface K.
    Mwanzia, Virginia M.
    Musili, Paul M.
    Wang, Qing-Feng
    Chen, Jin-Ming
    AQUATIC BOTANY, 2021, 173
  • [26] Study on Taiwania cryptomerioides under climate change: MaxEnt modeling for predicting the potential geographical distribution
    Zhao, Haoxiang
    Zhang, Hua
    Xu, Cungang
    GLOBAL ECOLOGY AND CONSERVATION, 2020, 24
  • [27] Assessment of Climate Change and Land Use Effects on Water Lily (Nymphaea L.) Habitat Suitability in South America
    Nzei, John M.
    Ngarega, Boniface K.
    Mwanzia, Virginia M.
    Kurauka, Joseph K.
    Wang, Qing-Feng
    Chen, Jin-Ming
    Li, Zhi-Zhong
    Pan, Cheng
    DIVERSITY-BASEL, 2022, 14 (10):
  • [28] Modeling the current land suitability and future dynamics of global soybean cultivation under climate change scenarios
    Feng, Lu
    Wang, Hongyan
    Ma, Xiaowei
    Peng, Hongbo
    Shan, Jianrong
    FIELD CROPS RESEARCH, 2021, 263
  • [29] Predicting the potential global distribution of Ageratina adenophora under current and future climate change scenarios
    Changjun, Gu
    Yanli, Tu
    Linshan, Liu
    Bo, Wei
    Yili, Zhang
    Haibin, Yu
    Xilong, Wang
    Zhuoga, Yangjin
    Binghua, Zhang
    Bohao, Cui
    ECOLOGY AND EVOLUTION, 2021, 11 (17): : 12092 - 12113
  • [30] The Ginkgo biloba L. in China: Current Distribution and Possible Future Habitat
    Zhang, Ying
    Zhang, Jinbing
    Tian, Li
    Huang, Yaohui
    Shao, Changliang
    FORESTS, 2023, 14 (12):