IDEAS home Printed from https://ideas.repec.org/a/eee/ecolec/v181y2021ics0921800919312431.html
   My bibliography  Save this article

Rangeland condition assessment in the Gobi Desert: A quantitative approach that places stakeholder evaluations front and Centre

Author

Listed:
  • Sinclair, Steve J.
  • Avirmed, Otgonsuren
  • White, Matthew D.
  • Batpurev, Khorloo
  • Griffioen, Peter A.
  • Liu, Canran
  • Jambal, Sergelenkhuu
  • Sime, Hayley
  • Olson, Kirk A.

Abstract

There is widespread concern that the condition of rangelands in the Gobi Desert is declining. Opinions differ about how to translate these concerns into a defensible assessment of condition. Finding common ground is essential because condition measurements influence land-use decisions on large scales.

Suggested Citation

  • Sinclair, Steve J. & Avirmed, Otgonsuren & White, Matthew D. & Batpurev, Khorloo & Griffioen, Peter A. & Liu, Canran & Jambal, Sergelenkhuu & Sime, Hayley & Olson, Kirk A., 2021. "Rangeland condition assessment in the Gobi Desert: A quantitative approach that places stakeholder evaluations front and Centre," Ecological Economics, Elsevier, vol. 181(C).
  • Handle: RePEc:eee:ecolec:v:181:y:2021:i:c:s0921800919312431
    DOI: 10.1016/j.ecolecon.2020.106891
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0921800919312431
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolecon.2020.106891?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. Kocev, Dragi & Džeroski, Sašo & White, Matt D. & Newell, Graeme R. & Griffioen, Peter, 2009. "Using single- and multi-target regression trees and ensembles to model a compound index of vegetation condition," Ecological Modelling, Elsevier, vol. 220(8), pages 1159-1168.
    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. Virginia Anne Kowal & Julian Ahlborn & Chantsallkham Jamsranjav & Otgonsuren Avirmed & Rebecca Chaplin-Kramer, 2021. "Modeling Integrated Impacts of Climate Change and Grazing on Mongolia’s Rangelands," Land, MDPI, vol. 10(4), pages 1-28, April.

    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. Jeongsub Choi & Mengmeng Zhu & Jihoon Kang & Myong K. Jeong, 2024. "Convolutional neural network based multi-input multi-output model for multi-sensor multivariate virtual metrology in semiconductor manufacturing," Annals of Operations Research, Springer, vol. 339(1), pages 185-201, August.
    2. Moung-Jin Lee & Wonkyong Song & Saro Lee, 2015. "Habitat Mapping of the Leopard Cat ( Prionailurus bengalensis ) in South Korea Using GIS," Sustainability, MDPI, vol. 7(4), pages 1-21, April.
    3. Crisci, C. & Ghattas, B. & Perera, G., 2012. "A review of supervised machine learning algorithms and their applications to ecological data," Ecological Modelling, Elsevier, vol. 240(C), pages 113-122.
    4. Wen Song & Wei Song & Haihong Gu & Fuping Li, 2020. "Progress in the Remote Sensing Monitoring of the Ecological Environment in Mining Areas," IJERPH, MDPI, vol. 17(6), pages 1-17, March.
    5. Yujing Zhou & Dubo He, 2024. "Multi-Target Feature Selection with Adaptive Graph Learning and Target Correlations," Mathematics, MDPI, vol. 12(3), pages 1-24, January.
    6. Shijie Li & Zuoqin Qian & Ji Liu, 2024. "Multi-Output Regression Algorithm-Based Non-Dominated Sorting Genetic Algorithm II Optimization for L-Shaped Twisted Tape Insertions in Circular Heat Exchange Tubes," Energies, MDPI, vol. 17(4), pages 1-22, February.
    7. Mannan Karim & Jiqiu Deng & Muhammad Ayoub & Wuzhou Dong & Baoyi Zhang & Muhammad Shahzad Yousaf & Yasir Ali Bhutto & Muhammad Ishfaque, 2023. "Improved Cropland Abandonment Detection with Deep Learning Vision Transformer (DL-ViT) and Multiple Vegetation Indices," Land, MDPI, vol. 12(10), pages 1-24, October.
    8. Everaert, Gert & Boets, Pieter & Lock, Koen & Džeroski, Sašo & Goethals, Peter L.M., 2011. "Using classification trees to analyze the impact of exotic species on the ecological assessment of polder lakes in Flanders, Belgium," Ecological Modelling, Elsevier, vol. 222(14), pages 2202-2212.
    9. Holguin-Gonzalez, Javier E. & Boets, Pieter & Alvarado, Andres & Cisneros, Felipe & Carrasco, María C. & Wyseure, Guido & Nopens, Ingmar & Goethals, Peter L.M., 2013. "Integrating hydraulic, physicochemical and ecological models to assess the effectiveness of water quality management strategies for the River Cuenca in Ecuador," Ecological Modelling, Elsevier, vol. 254(C), pages 1-14.
    10. Choi, Jong-Kuk & Oh, Hyun-Joo & Koo, Bon Joo & Ryu, Joo-Hyung & Lee, Saro, 2011. "Crustacean habitat potential mapping in a tidal flat using remote sensing and GIS," Ecological Modelling, Elsevier, vol. 222(8), pages 1522-1533.
    11. Jagannath Aryal & Chiranjibi Sitaula & Sunil Aryal, 2022. "NDVI Threshold-Based Urban Green Space Mapping from Sentinel-2A at the Local Governmental Area (LGA) Level of Victoria, Australia," Land, MDPI, vol. 11(3), pages 1-21, February.
    12. Meyer, Angela, 2021. "Multi-target normal behaviour models for wind farm condition monitoring," Applied Energy, Elsevier, vol. 300(C).
    13. Meenakshi Sharma & Prashant Kaushik & Aakash Chawade, 2021. "Frontiers in the Solicitation of Machine Learning Approaches in Vegetable Science Research," Sustainability, MDPI, vol. 13(15), pages 1-14, August.
    14. Kocev, Dragi & Naumoski, Andreja & Mitreski, Kosta & Krstić, Svetislav & Džeroski, Sašo, 2010. "Learning habitat models for the diatom community in Lake Prespa," Ecological Modelling, Elsevier, vol. 221(2), pages 330-337.
    15. Schmid, Lena & Gerharz, Alexander & Groll, Andreas & Pauly, Markus, 2023. "Tree-based ensembles for multi-output regression: Comparing multivariate approaches with separate univariate ones," Computational Statistics & Data Analysis, Elsevier, vol. 179(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:ecolec:v:181:y:2021:i:c:s0921800919312431. 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.elsevier.com/locate/ecolecon .

    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.