IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v10y2018i5p1643-d147941.html
   My bibliography  Save this article

Characterizing Drought Effects on Vegetation Productivity in the Four Corners Region of the US Southwest

Author

Listed:
  • Mohamed Abd Salam EL-Vilaly

    (International Food Policy Research Institute, 2033 K St, NW, Washington, DC 20006-1002, USA)

  • Kamel Didan

    (Department of Biosystems Engineering, The University of Arizona, 1177 E. 4th Street, Tucson, AZ 85721, USA)

  • Stuart E. Marsh

    (Arizona Remote Sensing Center, School of Natural Resources and the Environment, The University of Arizona, 1311 E. 4th Street, BioSciences East 325, Tucson, AZ 85721, USA)

  • Michael A. Crimmins

    (Department of Soils, Water and Environmental Science, The University of Arizona, Tucson, AZ 85721, USA)

  • Armando Barreto Munoz

    (Department of Biosystems Engineering, The University of Arizona, 1177 E. 4th Street, Tucson, AZ 85721, USA)

Abstract

The droughts striking the Colorado Plateau, where the Hopi Tribe and Navajo Nation Native American reservation lands are located, and their impacts have appeared slowly and relatively unnoticed in conventional national drought monitoring efforts like the National Drought Monitor. To understand the effect of drought-based drivers on vegetation productivity in the Hopi Tribe and Navajo Nation reservation lands, an assessment approach was developed integrating climate, land cover types, and topographical data with annual geospatially explicit normalized difference vegetation index (NDVI)-related productivity from 1989 to 2014 derived from 15-day composite multi-sensor NDVI time series data. We studied vegetation–environment relationships by conducting multiple linear regression analysis to explain the driver of vegetation productivity changes. Our results suggest that the interannual change of vegetation productivity showed high variability in middle elevations where needleleaf forest is the dominant vegetation cover type. Our analysis also shows that the spatial variation in interannual variability of vegetation productivity was more driven by climate drivers than by topography ones. Specifically, the interannual variability in spring precipitation and fall temperature seems to be the most significant factor that correlated with the interannual variability in vegetation productivity during the last two and a half decades.

Suggested Citation

  • Mohamed Abd Salam EL-Vilaly & Kamel Didan & Stuart E. Marsh & Michael A. Crimmins & Armando Barreto Munoz, 2018. "Characterizing Drought Effects on Vegetation Productivity in the Four Corners Region of the US Southwest," Sustainability, MDPI, vol. 10(5), pages 1-16, May.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:5:p:1643-:d:147941
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/10/5/1643/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/10/5/1643/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Guangsheng Chen & Hanqin Tian & Chi Zhang & Mingliang Liu & Wei Ren & Wenquan Zhu & Arthur Chappelka & Stephen Prior & Graeme Lockaby, 2012. "Drought in the Southern United States over the 20th century: variability and its impacts on terrestrial ecosystem productivity and carbon storage," Climatic Change, Springer, vol. 114(2), pages 379-397, September.
    Full references (including those not matched with items on IDEAS)

    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. Tianjie Lei & Jianjun Wu & Jiabao Wang & Changliang Shao & Weiwei Wang & Dongpan Chen & Xiangyu Li, 2022. "The Net Influence of Drought on Grassland Productivity over the Past 50 Years," Sustainability, MDPI, vol. 14(19), pages 1-20, September.
    2. Zhang, Chi & Wu, Jianguo & Grimm, Nancy B. & McHale, Melissa & Buyantuyev, Alexander, 2013. "A hierarchical patch mosaic ecosystem model for urban landscapes: Model development and evaluation," Ecological Modelling, Elsevier, vol. 250(C), pages 81-100.
    3. Hanqin Tian & Guangsheng Chen & Chaoqun Lu & Xiaofeng Xu & Daniel Hayes & Wei Ren & Shufen Pan & Deborah Huntzinger & Steven Wofsy, 2015. "North American terrestrial CO 2 uptake largely offset by CH 4 and N 2 O emissions: toward a full accounting of the greenhouse gas budget," Climatic Change, Springer, vol. 129(3), pages 413-426, April.
    4. Ryan Nedd & Aavudai Anandhi, 2022. "Land Use Changes in the Southeastern United States: Quantitative Changes, Drivers, and Expected Environmental Impacts," Land, MDPI, vol. 11(12), pages 1-25, December.

    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:5:p:1643-:d:147941. 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.