IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v8y2016i8p722-d74972.html
   My bibliography  Save this article

Predicting the Potential Distribution of Olea ferruginea in Pakistan incorporating Climate Change by Using Maxent Model

Author

Listed:
  • Uzma Ashraf

    (College of Earth and Environmental Sciences, University of the Punjab, Lahore 54590, Pakistan)

  • Hassan Ali

    (Department of Zoology, University of the Punjab, Lahore 54590, Punjab Wildlife and Parks Department, Dera Ghazi Khan Region 32200, Pakistan)

  • Muhammad Nawaz Chaudry

    (College of Earth and Environmental Sciences, University of the Punjab, Lahore 54590, Pakistan)

  • Irfan Ashraf

    (College of Earth and Environmental Sciences, University of the Punjab, Lahore 54590, Pakistan
    Strategic Policy Unit, Lahore Development Authority, Lahore 54770, Pakistan)

  • Adila Batool

    (Department of Space Science, University of the Punjab, Lahore 54590, Pakistan)

  • Zafeer Saqib

    (Department of Environmental Science, International Islamic University, Islamabad 44000, Pakistan)

Abstract

The potential distribution of Olea ferruginea was predicted by Maxent model for present and the upcoming hypothetical (2050) climatic scenario. O. ferruginea is an economically beneficial plant species. For predicting the potential distribution of O. ferruginea in Pakistan, Worldclim variables for current and future climatic change scenarios, digital elevation model (DEM) slope, and aspects with the occurrence point were used. Pearson correlation was used to reject highly correlated variables. A total of 219 sighting points were used in the Maxent modeling. The area under curve (AUC) value was higher than 0.98. The approach used in this study is considered useful in predicting the potential distribution of O. ferruginea species, and can be an effective tool in the conservation and restoration planning for human welfare. The results show that there is a significant impact under future bioclimatic scenarios on the potential distribution of O. ferruginea in Pakistan. There is a significant decrease in the overall distribution of O. ferruginea due to loss of habitats under current distribution range, but this will be compensated by gain of habitat at higher altitudes in the future climate change scenario (habitat shift). It is recommended that the areas predicted suitable for the O. ferruginea may be used for plantation of this species while the deforested land should be restored for human welfare.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:8:p:722-:d:74972
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/8/8/722/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/8/8/722/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Sillero, Neftalí, 2011. "What does ecological modelling model? A proposed classification of ecological niche models based on their underlying methods," Ecological Modelling, Elsevier, vol. 222(8), pages 1343-1346.
    2. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaomin Lv & Guangsheng Zhou, 2018. "Climatic Suitability of the Geographic Distribution of Stipa breviflora in Chinese Temperate Grassland under Climate Change," Sustainability, MDPI, vol. 10(10), pages 1-13, October.
    2. Giuseppe Antonio Catalano & Provvidenza Rita D’Urso & Federico Maci & Claudia Arcidiacono, 2023. "Influence of Parameters in SDM Application on Citrus Presence in Mediterranean Area," Sustainability, MDPI, vol. 15(9), pages 1-20, May.
    3. 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.
    4. Ping He & Yu Gao & Longfei Guo & Tongtong Huo & Yuxin Li & Xingren Zhang & Yunfeng Li & Cheng Peng & Fanyun Meng, 2021. "Evaluating the Disaster Risk of the COVID-19 Pandemic Using an Ecological Niche Model," Sustainability, MDPI, vol. 13(21), pages 1-23, October.
    5. Xuhui Zhang & Haiyan Wei & Zefang Zhao & Jing Liu & Quanzhong Zhang & Xiaoyan Zhang & Wei Gu, 2020. "The Global Potential Distribution of Invasive Plants: Anredera cordifolia under Climate Change and Human Activity Based on Random Forest Models," Sustainability, MDPI, vol. 12(4), pages 1-18, February.
    6. Zefang Zhao & Yanlong Guo & Haiyan Wei & Qiao Ran & Wei Gu, 2017. "Predictions of the Potential Geographical Distribution and Quality of a Gynostemma pentaphyllum Base on the Fuzzy Matter Element Model in China," Sustainability, MDPI, vol. 9(7), pages 1-15, July.
    7. 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.

    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. Gengping Zhu & Matthew J Petersen & Wenjun Bu, 2012. "Selecting Biological Meaningful Environmental Dimensions of Low Discrepancy among Ranges to Predict Potential Distribution of Bean Plataspid Invasion," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-9, September.
    2. Phillips, Sierra J. & Pasternack, Gregory B. & Larrieu, Kenneth, 2025. "Development and testing of a mechanistic potential niche model of riparian tree seedling recruitment," Ecological Modelling, Elsevier, vol. 501(C).
    3. Gabriel Fernando Cardoza-Martínez & Jorge Luis Becerra-López & Citlalli Edith Esparza-Estrada & José Luis Estrada-Rodríguez & Alexander Czaja & Muhammad Ehsan & Eduardo Baltierra-Trejo & Ulises Romero, 2019. "Shifts in Climatic Niche Occupation in Astrophytum Coahuilense (H. Möller) Kayser and Its Potential Distribution in Mexico," Sustainability, MDPI, vol. 11(4), pages 1-13, February.
    4. Zeng, Yiwen & Low, Bi Wei & Yeo, Darren C.J., 2016. "Novel methods to select environmental variables in MaxEnt: A case study using invasive crayfish," Ecological Modelling, Elsevier, vol. 341(C), pages 5-13.
    5. Sillero, Neftalí & Campos, João Carlos & Arenas-Castro, Salvador & Barbosa, A.Márcia, 2023. "A curated list of R packages for ecological niche modelling," Ecological Modelling, Elsevier, vol. 476(C).
    6. 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.
    7. Rajendra K. Meena & Maneesh S. Bhandari & Pawan Kumar Thakur & Nitika Negi & Shailesh Pandey & Rama Kant & Rajesh Sharma & Netrananda Sahu & Ram Avtar, 2024. "MaxEnt-Based Potential Distribution Mapping and Range Shift under Future Climatic Scenarios for an Alpine Bamboo Thamnocalamus spathiflorus in Northwestern Himalayas," Land, MDPI, vol. 13(7), pages 1-18, June.
    8. Sillero, Neftalí & Arenas-Castro, Salvador & Enriquez‐Urzelai, Urtzi & Vale, Cândida Gomes & Sousa-Guedes, Diana & Martínez-Freiría, Fernando & Real, Raimundo & Barbosa, A.Márcia, 2021. "Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling," Ecological Modelling, Elsevier, vol. 456(C).
    9. Rodrigues, Lucas dos Santos & Daudt, Nicholas Winterle & Cardoso, Luis Gustavo & Kinas, Paul Gerhard & Conesa, David & Pennino, Maria Grazia, 2023. "Species distribution modelling in the Southwestern Atlantic Ocean: A systematic review and trends," Ecological Modelling, Elsevier, vol. 486(C).
    10. Beaumont, Linda J. & Graham, Erin & Duursma, Daisy Englert & Wilson, Peter D. & Cabrelli, Abigail & Baumgartner, John B. & Hallgren, Willow & Esperón-Rodríguez, Manuel & Nipperess, David A. & Warren, , 2016. "Which species distribution models are more (or less) likely to project broad-scale, climate-induced shifts in species ranges?," Ecological Modelling, Elsevier, vol. 342(C), pages 135-146.
    11. Zhao, Jiongchao & Wang, Chong & Shi, Xiaoyu & Bo, Xiaozhi & Li, Shuo & Shang, Mengfei & Chen, Fu & Chu, Qingquan, 2021. "Modeling climatically suitable areas for soybean and their shifts across China," Agricultural Systems, Elsevier, vol. 192(C).
    12. Robin Lines & Dimitrios Bormpoudakis & Panteleimon Xofis & Joseph Tzanopoulos, 2021. "Modelling Multi-Species Connectivity at the Kafue-Zambezi Interface: Implications for Transboundary Carnivore Conservation," Sustainability, MDPI, vol. 13(22), pages 1-15, November.
    13. Mateo, Rubén G. & Arellano, Gabriel & Gómez-Rubio, Virgilio & Tello, J. Sebastián & Fuentes, Alfredo F. & Cayola, Leslie & Loza, M. Isabel & Cala, Victoria & Macía, Manuel J., 2022. "Insights on biodiversity drivers to predict species richness in tropical forests at the local scale," Ecological Modelling, Elsevier, vol. 473(C).
    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. Sutton, G.F. & Martin, G.D., 2022. "Testing MaxEnt model performance in a novel geographic region using an intentionally introduced insect," Ecological Modelling, Elsevier, vol. 473(C).
    16. 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.
    17. Fernandez, Marc & Sillero, Neftali & Yesson, Chris, 2022. "To be or not to be: the role of absences in niche modelling for highly mobile species in dynamic marine environments," Ecological Modelling, Elsevier, vol. 471(C).
    18. Cesar A Marchioro, 2016. "Global Potential Distribution of Bactrocera carambolae and the Risks for Fruit Production in Brazil," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-16, November.
    19. Yuncheng Zhao & Mingyue Zhao & Lei Zhang & Chunyi Wang & Yinlong Xu, 2021. "Predicting Possible Distribution of Tea ( Camellia sinensis L.) under Climate Change Scenarios Using MaxEnt Model in China," Agriculture, MDPI, vol. 11(11), pages 1-18, November.
    20. Urtzi Enriquez-Urzelai & Nicola Bernardo & Gregorio Moreno-Rueda & Albert Montori & Gustavo Llorente, 2019. "Are amphibians tracking their climatic niches in response to climate warming? A test with Iberian amphibians," Climatic Change, Springer, vol. 154(1), pages 289-301, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:8:y:2016:i:8:p:722-:d:74972. 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.