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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
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    Cited by:

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    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.

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