IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i4p1081-d139613.html
   My bibliography  Save this article

Fine-Scale Evaluation of Giant Panda Habitats and Countermeasures against the Future Impacts of Climate Change and Human Disturbance (2015–2050): A Case Study in Ya’an, China

Author

Listed:
  • Jing Zhen

    (Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Xinyuan Wang

    (Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China)

  • Qingkai Meng

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

  • Jingwei Song

    (Centre for Autonomous Systems, University of Technology Sydney, Ultimo, NSW 2007, Australia)

  • Ying Liao

    (Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China)

  • Bo Xiang

    (Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China)

  • Huadong Guo

    (Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China)

  • Chuansheng Liu

    (Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China)

  • Ruixia Yang

    (Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China)

  • Lei Luo

    (Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China)

Abstract

The accelerating impact of climate change on giant panda ( Ailuropoda melanoleuca ) habitats have become an international research topic. Recently, many studies have also focused on medium-sized mountain ranges or entire giant panda habitats to predict how habitats will change as the climate warms, but few say in detail what to do or where to focus efforts. To fill this gap, this paper presents a new method to take comprehensive, fine-scale evaluations incorporating climate change, human disturbance, and current conservation networks and translate them into practical countermeasures in order to help decision-makers set priority regions for conservation. This study looked at the core area of the Sichuan Giant Panda Sanctuaries United Nations Educational, Scientific and Cultural Organisation (UNESCO) World Natural Heritage site, namely Ya’an Prefecture, as a case study. The research employs the Maximum Entropy (MaxEnt) modeling algorithm to analyze how climate change will affect the habitats by 2050 under two scenarios: only considering the influence of climate change, and thinking about the coupled influence of climate change and human disturbance together. The results showed the following: (1) only considering climate change, the overall habitat that can be used by giant pandas in this region will increase, which differs from most of the previous results showing a decrease; (2) the new suitable habitat will shift westward, northward and eastward in this region; (3) conversely, the suitable habitat will be significantly reduced (about 58.56%) and fragmentized when taking into account human disturbance factors; (4) at present, the three small nature reserves are far from each other and cannot cover the present habitat well nor protect the potentially suitable habitats. Based on the comprehensive analysis of habitat shifts and our two field investigations, we suggest two regions that can be expanded into the conservation network to contain more potentially suitable habitats in the future. Furthermore, we used a geographical information system to incorporate high-resolution remote-sensing images from the GF-1 satellite, land-cover maps, and a digital elevation model (DEM) to verify the possibility of our two suggested regions.

Suggested Citation

  • Jing Zhen & Xinyuan Wang & Qingkai Meng & Jingwei Song & Ying Liao & Bo Xiang & Huadong Guo & Chuansheng Liu & Ruixia Yang & Lei Luo, 2018. "Fine-Scale Evaluation of Giant Panda Habitats and Countermeasures against the Future Impacts of Climate Change and Human Disturbance (2015–2050): A Case Study in Ya’an, China," Sustainability, MDPI, vol. 10(4), pages 1-19, April.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:4:p:1081-:d:139613
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/4/1081/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/4/1081/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fan, Juntao & Li, Junsheng & Xia, Rui & Hu, Lile & Wu, Xiaopu & Li, Guo, 2014. "Assessing the impact of climate change on the habitat distribution of the giant panda in the Qinling Mountains of China," Ecological Modelling, Elsevier, vol. 274(C), pages 12-20.
    2. Jingwei Song & Xinyuan Wang & Ying Liao & Jing Zhen & Natarajan Ishwaran & Huadong Guo & Ruixia Yang & Chuansheng Liu & Chun Chang & Xin Zong, 2014. "An Improved Neural Network for Regional Giant Panda Habitat Suitability Mapping: A Case Study in Ya’an Prefecture," Sustainability, MDPI, vol. 6(7), pages 1-18, June.
    3. Mao-Ning Tuanmu & Andrés Viña & Julie A. Winkler & Yu Li & Weihua Xu & Zhiyun Ouyang & Jianguo Liu, 2013. "Climate-change impacts on understorey bamboo species and giant pandas in China’s Qinling Mountains," Nature Climate Change, Nature, vol. 3(3), pages 249-253, March.
    4. Ling-en Wang & Yuxi Zeng & Linsheng Zhong, 2017. "Impact of Climate Change on Tourism on the Qinghai-Tibetan Plateau: Research Based on a Literature Review," Sustainability, MDPI, vol. 9(9), pages 1-14, August.
    5. Camille Parmesan & Gary Yohe, 2003. "A globally coherent fingerprint of climate change impacts across natural systems," Nature, Nature, vol. 421(6918), pages 37-42, January.
    6. Ying Tang & Julie A Winkler & Andrés Viña & Jianguo Liu & Yuanbin Zhang & Xiaofeng Zhang & Xiaohong Li & Fang Wang & Jindong Zhang & Zhiqiang Zhao, 2018. "Uncertainty of future projections of species distributions in mountainous regions," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-23, January.
    7. Christopher J. Raxworthy & Enrique Martinez-Meyer & Ned Horning & Ronald A. Nussbaum & Gregory E. Schneider & Miguel A. Ortega-Huerta & A. Townsend Peterson, 2003. "Predicting distributions of known and unknown reptile species in Madagascar," Nature, Nature, vol. 426(6968), pages 837-841, December.
    8. Evan P Tanner & Monica Papeş & R Dwayne Elmore & Samuel D Fuhlendorf & Craig A Davis, 2017. "Incorporating abundance information and guiding variable selection for climate-based ensemble forecasting of species' distributional shifts," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-26, September.
    9. Terry L. Root & Jeff T. Price & Kimberly R. Hall & Stephen H. Schneider & Cynthia Rosenzweig & J. Alan Pounds, 2003. "Fingerprints of global warming on wild animals and plants," Nature, Nature, vol. 421(6918), pages 57-60, January.
    10. Gian-Reto Walther & Eric Post & Peter Convey & Annette Menzel & Camille Parmesan & Trevor J. C. Beebee & Jean-Marc Fromentin & Ove Hoegh-Guldberg & Franz Bairlein, 2002. "Ecological responses to recent climate change," Nature, Nature, vol. 416(6879), pages 389-395, March.
    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. Yanzhen Liu & Yunwei Tang & Linhai Jing & Fulong Chen & Ping Wang, 2021. "Remote Sensing-Based Dynamic Monitoring of Immovable Cultural Relics, from Environmental Factors to the Protected Cultural Site: A Case Study of the Shunji Bridge," Sustainability, MDPI, vol. 13(11), pages 1-21, May.

    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. Wesley R. Brooks & Stephen C. Newbold, 2013. "Ecosystem damages in integrated assessment models of climate change," NCEE Working Paper Series 201302, National Center for Environmental Economics, U.S. Environmental Protection Agency, revised Mar 2013.
    2. Víctor Rincón & Javier Velázquez & Derya Gülçin & Aida López-Sánchez & Carlos Jiménez & Ali Uğur Özcan & Juan Carlos López-Almansa & Tomás Santamaría & Daniel Sánchez-Mata & Kerim Çiçek, 2023. "Mapping Priority Areas for Connectivity of Yellow-Winged Darter ( Sympetrum flaveolum , Linnaeus 1758) under Climate Change," Land, MDPI, vol. 12(2), pages 1-39, January.
    3. Lucie Kuczynski & Mathieu Chevalier & Pascal Laffaille & Marion Legrand & Gaël Grenouillet, 2017. "Indirect effect of temperature on fish population abundances through phenological changes," PLOS ONE, Public Library of Science, vol. 12(4), pages 1-13, April.
    4. Sang-Don Lee, 2017. "Global Warming Leading to Phenological Responses in the Process of Urbanization, South Korea," Sustainability, MDPI, vol. 9(12), pages 1-27, November.
    5. Brooks, Wesley R. & Newbold, Stephen C., 2014. "An updated biodiversity nonuse value function for use in climate change integrated assessment models," Ecological Economics, Elsevier, vol. 105(C), pages 342-349.
    6. Dissanayake, Sahan T.M. & Önal, Hayri & Westervelt, James D. & Balbach, Harold E., 2012. "Incorporating species relocation in reserve design models: An example from Ft. Benning GA," Ecological Modelling, Elsevier, vol. 224(1), pages 65-75.
    7. Kato, E., 2009. "Soil and water conservation technologies: a buffer against production risk in the face of climate change?: insights from the Nile Basin in Ethiopia," IWMI Working Papers H042477, International Water Management Institute.
    8. Omann, Ines & Stocker, Andrea & Jäger, Jill, 2009. "Climate change as a threat to biodiversity: An application of the DPSIR approach," Ecological Economics, Elsevier, vol. 69(1), pages 24-31, November.
    9. V. P. Khanduri & C. M. Sharma & S. P. Singh, 2008. "The effects of climate change on plant phenology," Environment Systems and Decisions, Springer, vol. 28(2), pages 143-147, June.
    10. Guanjie Jiao & Xiawei Shentu & Xiaochen Zhu & Wenbo Song & Yujia Song & Kexuan Yang, 2022. "Utility of Deep Learning Algorithms in Initial Flowering Period Prediction Models," Agriculture, MDPI, vol. 12(12), pages 1-17, December.
    11. Gregorio Moreno-Rueda & Juan Pleguezuelos & Esmeralda Alaminos, 2009. "Climate warming and activity period extension in the Mediterranean snake Malpolon monspessulanus," Climatic Change, Springer, vol. 92(1), pages 235-242, January.
    12. Karyn Tabor & Jennifer Hewson & Hsin Tien & Mariano González-Roglich & David Hole & John W. Williams, 2018. "Tropical Protected Areas Under Increasing Threats from Climate Change and Deforestation," Land, MDPI, vol. 7(3), pages 1-14, July.
    13. Mayeul Dalleau & Stéphane Ciccione & Jeanne A Mortimer & Julie Garnier & Simon Benhamou & Jérôme Bourjea, 2012. "Nesting Phenology of Marine Turtles: Insights from a Regional Comparative Analysis on Green Turtle (Chelonia mydas)," PLOS ONE, Public Library of Science, vol. 7(10), pages 1-13, October.
    14. Richard Tol, 2011. "Regulating knowledge monopolies: the case of the IPCC," Climatic Change, Springer, vol. 108(4), pages 827-839, October.
    15. Anne Goodenough & Adam Hart, 2013. "Correlates of vulnerability to climate-induced distribution changes in European avifauna: habitat, migration and endemism," Climatic Change, Springer, vol. 118(3), pages 659-669, June.
    16. Fabina, Nicholas S. & Abbott, Karen C. & Gilman, R.Tucker, 2010. "Sensitivity of plant–pollinator–herbivore communities to changes in phenology," Ecological Modelling, Elsevier, vol. 221(3), pages 453-458.
    17. Ye, Qing & Yang, Xiaoguang & Dai, Shuwei & Chen, Guangsheng & Li, Yong & Zhang, Caixia, 2015. "Effects of climate change on suitable rice cropping areas, cropping systems and crop water requirements in southern China," Agricultural Water Management, Elsevier, vol. 159(C), pages 35-44.
    18. John H Matthews & Bart AJ Wickel & Sarah Freeman, 2011. "Converging Currents in Climate-Relevant Conservation: Water, Infrastructure, and Institutions," PLOS Biology, Public Library of Science, vol. 9(9), pages 1-4, September.
    19. Brandt, Laura A. & Benscoter, Allison M. & Harvey, Rebecca & Speroterra, Carolina & Bucklin, David & Romañach, Stephanie S. & Watling, James I. & Mazzotti, Frank J., 2017. "Comparison of climate envelope models developed using expert-selected variables versus statistical selection," Ecological Modelling, Elsevier, vol. 345(C), pages 10-20.
    20. Zhang, Jiarui & Jørgensen, Sven E. & Lu, Jianjian & Nielsen, Søren N. & Wang, Qiang, 2014. "A model for the contribution of macrophyte-derived organic carbon in harvested tidal freshwater marshes to surrounding estuarine and oceanic ecosystems and its response to global warming," Ecological Modelling, Elsevier, vol. 294(C), pages 105-116.

    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:10:y:2018:i:4:p:1081-:d:139613. 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.