IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i6p5604-d1104623.html
   My bibliography  Save this article

Prediction of Potential Distribution Area of Two Parapatric Species in Triosteum under Climate Change

Author

Listed:
  • Xumin Li

    (College of Eco-Environmental Engineering, Qinghai University, Xining 810016, China)

  • Zhiwen Yao

    (College of Eco-Environmental Engineering, Qinghai University, Xining 810016, China)

  • Qing Yuan

    (College of Eco-Environmental Engineering, Qinghai University, Xining 810016, China)

  • Rui Xing

    (Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China)

  • Yuqin Guo

    (Qinghai National Park Research Monitoring and Evaluation Center, Xining 810000, China)

  • Dejun Zhang

    (College of Eco-Environmental Engineering, Qinghai University, Xining 810016, China
    State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China)

  • Israr Ahmad

    (Department of Botany, Hazara University Mansehra, Mansehra 21300, Pakistan)

  • Wenhui Liu

    (State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China
    Department of Geological Engineering, Qinghai University, Xining 810016, China)

  • Hairui Liu

    (College of Eco-Environmental Engineering, Qinghai University, Xining 810016, China
    State Key Laboratory of Plateau Ecology and Agriculture, Qinghai University, Xining 810016, China)

Abstract

Climate change has a profound impact on global biodiversity and species geographical distribution, especially in alpine regions. The prediction of species’ habitat could help the understanding of species’ responses to potential climate threats. Triosteum L. (1753) is a typical mountain plant with medicinal and ecological value. There are three species of this genus in East Asia. Triosteum Pinnatifidum Maxim. 1888 and Triosteum himalayanum Wall. 1829 are mainly distributed in the Qinghai–Tibet Plateau and its surroundings, and they are sensitive to climate changes. In this study, a MaxEnt model was used to predict the potential distribution of T. Pinnatifidum and T. himalayanum in the present time and at four different time periods in the future under two different Shared Socioeconomic Pathways (SSPs). Topographic factors were taken into account in the prediction. In the present study, the accuracy of the model’s prediction was verified (the AUC values are 0.975 and 0.974), and the results indicate that temperature is the key factor that affects the distribution of these two species. Compared with current distribution, the potential suitable area of T. Pinnatifidum will increase in the future under two types of SSPs (an average increase is 31%), but the potential suitable area of T. himalayanum will decrease significantly (the average area is 93% of what it was before). In addition, the overlap of potential suitable areas of these two species will also expand, potentially affecting their hybridization and interspecific competition. The centroids of T. Pinnatifidum will migrate to the east, but the trajectory of centroids of T. himalayanum is complex. This study could provide basic data for the resource utilization and biogeography research of Triosteum . It will also be helpful for conservation and sustainable use of mountain herbaceous plants under climate change.

Suggested Citation

  • Xumin Li & Zhiwen Yao & Qing Yuan & Rui Xing & Yuqin Guo & Dejun Zhang & Israr Ahmad & Wenhui Liu & Hairui Liu, 2023. "Prediction of Potential Distribution Area of Two Parapatric Species in Triosteum under Climate Change," Sustainability, MDPI, vol. 15(6), pages 1-23, March.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5604-:d:1104623
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/6/5604/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/6/5604/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fahim Arshad & Muhammad Waheed & Kaneez Fatima & Nidaa Harun & Muhammad Iqbal & Kaniz Fatima & Shaheena Umbreen, 2022. "Predicting the Suitable Current and Future Potential Distribution of the Native Endangered Tree Tecomella undulata (Sm.) Seem. in Pakistan," Sustainability, MDPI, vol. 14(12), pages 1-10, June.
    2. Hao Dong & Ningning Zhang & Simin Shen & Shixin Zhu & Saibin Fan & Yang Lu, 2023. "Effects of Climate Change on the Spatial Distribution of the Threatened Species Rhododendron purdomii in Qinling-Daba Mountains of Central China: Implications for Conservation," Sustainability, MDPI, vol. 15(4), pages 1-13, February.
    3. Uzma Ashraf & Hassan Ali & Muhammad Nawaz Chaudry & Irfan Ashraf & Adila Batool & Zafeer Saqib, 2016. "Predicting the Potential Distribution of Olea ferruginea in Pakistan incorporating Climate Change by Using Maxent Model," Sustainability, MDPI, vol. 8(8), pages 1-11, July.
    4. Jia-Min Jiang & Lei Jin & Lei Huang & Wen-Ting Wang, 2022. "The Future Climate under Different CO 2 Emission Scenarios Significantly Influences the Potential Distribution of Achnatherum inebrians in China," Sustainability, MDPI, vol. 14(8), pages 1-15, April.
    5. Anderson, Robert P. & Gonzalez, Israel, 2011. "Species-specific tuning increases robustness to sampling bias in models of species distributions: An implementation with Maxent," Ecological Modelling, Elsevier, vol. 222(15), pages 2796-2811.
    6. Koo, Kyung Ah & Park, Seon Uk & Kong, Woo-Seok & Hong, Seungbum & Jang, Inyoung & Seo, Changwan, 2017. "Potential climate change effects on tree distributions in the Korean Peninsula: Understanding model & climate uncertainties," Ecological Modelling, Elsevier, vol. 353(C), pages 17-27.
    7. Shuai Qi & Wei Luo & Ke-Lin Chen & Xin Li & Huo-Lin Luo & Zai-Qiang Yang & Dong-Mei Yin, 2022. "The Prediction of the Potentially Suitable Distribution Area of Cinnamomum mairei H. Lév in China Based on the MaxEnt Model," Sustainability, MDPI, vol. 14(13), pages 1-13, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Muhammad Waheed & Shiekh Marifatul Haq & Fahim Arshad & Muhammad Azhar Jameel & Manzer H. Siddiqui & Rainer W. Bussmann & Nabeel Manshoor & Saud Alamri, 2023. "Where Will Threatened Aegle marmelos L., a Tree of the Semi-Arid Region, Go under Climate Change? Implications for the Reintroduction of the Species," Land, MDPI, vol. 12(7), pages 1-19, July.
    2. Wiltshire, Kathryn H & Tanner, Jason E, 2020. "Comparing maximum entropy modelling methods to inform aquaculture site selection for novel seaweed species," Ecological Modelling, Elsevier, vol. 429(C).
    3. Wolke Tobón-Niedfeldt & Alicia Mastretta-Yanes & Tania Urquiza-Haas & Bárbara Goettsch & Angela P. Cuervo-Robayo & Esmeralda Urquiza-Haas & M. Andrea Orjuela-R & Francisca Acevedo Gasman & Oswaldo Oli, 2022. "Incorporating evolutionary and threat processes into crop wild relatives conservation," Nature Communications, Nature, vol. 13(1), pages 1-18, December.
    4. Schmidt, Heiko & Radinger, Johannes & Teschlade, Daniel & Stoll, Stefan, 2020. "The role of spatial units in modelling freshwater fish distributions: Comparing a subcatchment and river network approach using MaxEnt," Ecological Modelling, Elsevier, vol. 418(C).
    5. H. Oğuz Çoban & Ömer K. Örücü & E. Seda Arslan, 2020. "MaxEnt Modeling for Predicting the Current and Future Potential Geographical Distribution of Quercus libani Olivier," Sustainability, MDPI, vol. 12(7), pages 1-17, March.
    6. Muhammad Waheed & Shiekh Marifatul Haq & Fahim Arshad & Rainer W. Bussmann & Muhammad Iqbal & Najat A. Bukhari & Ashraf Atef Hatamleh, 2022. "Grasses in Semi-Arid Lowlands—Community Composition and Spatial Dynamics with Special Regard to the Influence of Edaphic Factors," Sustainability, MDPI, vol. 14(22), pages 1-17, November.
    7. Holder, Anna M. & Markarian, Arev & Doyle, Jessie M. & Olson, John R., 2020. "Predicting geographic distributions of fishes in remote stream networks using maximum entropy modeling and landscape characterizations," Ecological Modelling, Elsevier, vol. 433(C).
    8. Schartel, Tyler E. & Cao, Yong, 2024. "Background selection complexity influences Maxent predictive performance in freshwater systems," Ecological Modelling, Elsevier, vol. 488(C).
    9. Duque-Lazo, J. & van Gils, H. & Groen, T.A. & Navarro-Cerrillo, R.M., 2016. "Transferability of species distribution models: The case of Phytophthora cinnamomi in Southwest Spain and Southwest Australia," Ecological Modelling, Elsevier, vol. 320(C), pages 62-70.
    10. Moreno-Amat, Elena & Mateo, Rubén G. & Nieto-Lugilde, Diego & Morueta-Holme, Naia & Svenning, Jens-Christian & García-Amorena, Ignacio, 2015. "Impact of model complexity on cross-temporal transferability in Maxent species distribution models: An assessment using paleobotanical data," Ecological Modelling, Elsevier, vol. 312(C), pages 308-317.
    11. Halvorsen, Rune & Mazzoni, Sabrina & Dirksen, John Wirkola & Næsset, Erik & Gobakken, Terje & Ohlson, Mikael, 2016. "How important are choice of model selection method and spatial autocorrelation of presence data for distribution modelling by MaxEnt?," Ecological Modelling, Elsevier, vol. 328(C), pages 108-118.
    12. Herkt, K. Matthias B. & Barnikel, Günter & Skidmore, Andrew K. & Fahr, Jakob, 2016. "A high-resolution model of bat diversity and endemism for continental Africa," Ecological Modelling, Elsevier, vol. 320(C), pages 9-28.
    13. Seungbum Hong & Inyoung Jang & Daegeun Kim & Suhwan Kim & Hyun Su Park & Kyungeun Lee, 2022. "Predicting Potential Habitat Changes of Two Invasive Alien Fish Species with Climate Change at a Regional Scale," Sustainability, MDPI, vol. 14(10), pages 1-12, May.
    14. Fois, Mauro & Cuena-Lombraña, Alba & Fenu, Giuseppe & Bacchetta, Gianluigi, 2018. "Using species distribution models at local scale to guide the search of poorly known species: Review, methodological issues and future directions," Ecological Modelling, Elsevier, vol. 385(C), pages 124-132.
    15. Muhammad Danish Jamil & Muhammad Waheed & Shamim Akhtar & Nazneen Bangash & Sunbal Khalil Chaudhari & Muhammad Majeed & Mumtaz Hussain & Kishwar Ali & David Aaron Jones, 2022. "Invasive Plants Diversity, Ecological Status, and Distribution Pattern in Relation to Edaphic Factors in Different Habitat Types of District Mandi Bahauddin, Punjab, Pakistan," Sustainability, MDPI, vol. 14(20), pages 1-16, October.
    16. Santiago José Elías Velazco & Franklin Galvão & Fabricio Villalobos & Paulo De Marco Júnior, 2017. "Using worldwide edaphic data to model plant species niches: An assessment at a continental extent," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-24, October.
    17. Pimenta, Mayra & Andrade, André Felipe Alves de & Fernandes, Fernando Hiago Souza & Amboni, Mayra Pereira de Melo & Almeida, Renata Silva & Soares, Ana Hermínia Simões de Bello & Falcon, Guth Berger &, 2022. "One size does not fit all: Priority areas for real world problems," Ecological Modelling, Elsevier, vol. 470(C).
    18. Worthington, Thomas A. & Zhang, Tianjiao & Logue, Daniel R. & Mittelstet, Aaron R. & Brewer, Shannon K., 2016. "Landscape and flow metrics affecting the distribution of a federally-threatened fish: Improving management, model fit, and model transferability," Ecological Modelling, Elsevier, vol. 342(C), pages 1-18.
    19. Boria, Robert A. & Olson, Link E. & Goodman, Steven M. & Anderson, Robert P., 2014. "Spatial filtering to reduce sampling bias can improve the performance of ecological niche models," Ecological Modelling, Elsevier, vol. 275(C), pages 73-77.
    20. Peng Su & Anyu Zhang & Ran Wang & Jing’ai Wang & Yuan Gao & Fenggui Liu, 2021. "Prediction of Future Natural Suitable Areas for Rice under Representative Concentration Pathways (RCPs)," Sustainability, MDPI, vol. 13(3), pages 1-19, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:15:y:2023:i:6:p:5604-:d:1104623. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.