IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v242y2012icp105-115.html
   My bibliography  Save this article

Assessing habitat suitability based on geographic information system (GIS) and fuzzy: A case study of Schisandra sphenanthera Rehd. et Wils. in Qinling Mountains, China

Author

Listed:
  • Lu, Chun Yan
  • Gu, Wei
  • Dai, Ai Hua
  • Wei, Hai Yan

Abstract

Habitat requirements and spatial distribution of species are essential to biological conservation and management as well as ecosystems conservation and restoration. For some wild species, lacking of explicit criteria of suitable habitat condition is a limitation in their preliminary conservation and management. Schisandra sphenanthera Rehd. et Wils., a wild herb plant mainly located in Qinling Mountains has undergone dramatic drop as its growing market demand and exceeded harvesting, is now endangered. In this study, we collected samples of S. sphenanthera in Qinling Mountains by field work, and examined the content of schisantherin A with high efficiency liquid chromatography (HPLC). Combining the fuzzy membership functions, maximum entropy modeling and geographical information system (GIS), we obtained the suitable range of each factor affecting plant growth and spatial distribution of habitat suitability assessment. Moreover, the model we built is applicable to habitats besides Qinling Mountains by validation. The weight of each factor suggested that the amount of available light, temperature of growth period and content ratio of organic carbon played major roles in the habitat suitability of S. sphenanthera. The spatial distribution suggested that overall Qinling Mountains are suitable habitat for S. sphenanthera, where suitable habitat ratio amounts to 70.80%. This research will provide an effective, easy-operating and resources-saving method to determine the species habitat requirements and spatial habitat distribution. The results from this research will be influential in the future ecological conservation and management of S. sphenanthera in Qinling Mountains, and they would be taken as a reference for habitat suitability assessment research of other species.

Suggested Citation

  • Lu, Chun Yan & Gu, Wei & Dai, Ai Hua & Wei, Hai Yan, 2012. "Assessing habitat suitability based on geographic information system (GIS) and fuzzy: A case study of Schisandra sphenanthera Rehd. et Wils. in Qinling Mountains, China," Ecological Modelling, Elsevier, vol. 242(C), pages 105-115.
  • Handle: RePEc:eee:ecomod:v:242:y:2012:i:c:p:105-115
    DOI: 10.1016/j.ecolmodel.2012.06.002
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380012002748
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2012.06.002?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lahdelma, Risto & Salminen, Pekka & Kuula, Markku, 2003. "Testing the efficiency of two pairwise comparison methods in discrete multiple criteria problems," European Journal of Operational Research, Elsevier, vol. 145(3), pages 496-508, March.
    2. Singh, Aditya & Kushwaha, S.P.S., 2011. "Refining logistic regression models for wildlife habitat suitability modeling—A case study with muntjak and goral in the Central Himalayas, India," Ecological Modelling, Elsevier, vol. 222(8), pages 1354-1366.
    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. Zhang, Quanzhong & Wei, Haiyan & Liu, Jing & Zhao, Zefang & Ran, Qiao & Gu, Wei, 2021. "A Bayesian network with fuzzy mathematics for species habitat suitability analysis: A case with limited Angelica sinensis (Oliv.) Diels data," Ecological Modelling, Elsevier, vol. 450(C).
    2. Ziming Song & Yingyue Sun & Peng Chen & Mingming Jia, 2022. "Assessing the Ecosystem Health of Coastal Wetland Vegetation ( Suaeda salsa ) Using the Pressure State Response Model, a Case of the Liao River Estuary in China," IJERPH, MDPI, vol. 19(1), pages 1-14, January.
    3. Xingtao Wei & Oliver Valentine Eboy & Lu Xu & Di Yu, 2023. "Ecological Sensitivity of Urban Agglomeration in the Guanzhong Plain, China," Sustainability, MDPI, vol. 15(6), pages 1-21, March.
    4. 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.
    5. Yanlin Tian & Zongming Wang & Dehua Mao & Lin Li & Mingyue Liu & Mingming Jia & Weidong Man & Chunyan Lu, 2019. "Remote Observation in Habitat Suitability Changes for Waterbirds in the West Songnen Plain, China," Sustainability, MDPI, vol. 11(6), pages 1-21, March.
    6. Quanzhong Zhang & Haiyan Wei & Zefang Zhao & Jing Liu & Qiao Ran & Junhong Yu & Wei Gu, 2018. "Optimization of the Fuzzy Matter Element Method for Predicting Species Suitability Distribution Based on Environmental Data," Sustainability, MDPI, vol. 10(10), pages 1-16, September.
    7. 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.
    8. 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.

    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. Lahdelma, Risto & Salminen, Pekka, 2009. "Prospect theory and stochastic multicriteria acceptability analysis (SMAA)," Omega, Elsevier, vol. 37(5), pages 961-971, October.
    2. Bobrowski, Maria & Weidinger, Johannes & Schwab, Niels & Schickhoff, Udo, 2021. "Searching for ecology in species distribution models in the Himalayas," Ecological Modelling, Elsevier, vol. 458(C).

    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:eee:ecomod:v:242:y:2012:i:c:p:105-115. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    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.