IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v14y2025i1p140-d1564766.html
   My bibliography  Save this article

Data-Driven Decision Support to Guide Sustainable Grazing Management

Author

Listed:
  • Matthew C. Reeves

    (USDA Forest Service, Rocky Mountain Research Station, Missoula, MT 59801, USA)

  • Joseph Swisher

    (USDA Forest Service, Inyo National Forest, Mammoth Lakes, CA 93546, USA)

  • Michael Krebs

    (USDA Forest Service, Rocky Mountain Research Station, Missoula, MT 59801, USA)

  • Kelly Warnke

    (USDA Forest Service, Enterprise Program, Rapid City, SD 57702, USA)

  • Brice B. Hanberry

    (USDA Forest Service, Rocky Mountain Research Station, Rapid City, SD 57702, USA)

  • Tip Hudson

    (Rangeland & Livestock Management Extension, Washington State University, Ellensburg, WA 98926, USA)

  • Sonia A. Hall

    (Center for Sustaining Agriculture & Natural Resources, Washington State University, Wenatchee, WA 98801, USA)

Abstract

Data-driven decision support can help guide sustainable grazing management by providing an accurate estimate of grazing capacity, in coproduction with managers. Here, we described the development of a decision support model to estimate grazing capacity and illustrated its application on two sites in the western United States. For the Montgomery Pass Wild Horse Territory in California and Nevada, the upper limit estimated in the capacity assessment was 398 horses and the current population was 654 horses. For the Eagle Creek watershed of the Apache–Sitgreaves National Forest of eastern Arizona, the lower end of capacity was estimated at 1560 cattle annually, compared to the current average of 1090 cattle annually. In addition to being spatio-temporally comprehensive, the model provides a repeatable, cost-effective, and transparent process for establishing and adjusting capacity estimates and associated grazing plans that are supported by scientific information, in order to support livestock numbers at levels that are sustainable over time, including levels that are below average forage production during drought conditions. This modeling process acts as a decision support tool because it enables different assumptions to be used and explored to accommodate multiple viewpoints during the planning process.

Suggested Citation

  • Matthew C. Reeves & Joseph Swisher & Michael Krebs & Kelly Warnke & Brice B. Hanberry & Tip Hudson & Sonia A. Hall, 2025. "Data-Driven Decision Support to Guide Sustainable Grazing Management," Land, MDPI, vol. 14(1), pages 1-21, January.
  • Handle: RePEc:gam:jlands:v:14:y:2025:i:1:p:140-:d:1564766
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/14/1/140/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2073-445X/14/1/140/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. repec:ags:weecfo:287312 is not listed on IDEAS
    2. Peck, Dannele & Derner, Justin & Parton, William & Hartman, Melannie & Fuchs, Brian, 2019. "Flexible stocking with Grass-Cast: A new grassland productivity forecast to translate climate outlooks for ranchers," Western Economics Forum, Western Agricultural Economics Association, vol. 17(01), March.
    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. Srinivasagan N. Subhashree & C. Igathinathane & Adnan Akyuz & Md. Borhan & John Hendrickson & David Archer & Mark Liebig & David Toledo & Kevin Sedivec & Scott Kronberg & Jonathan Halvorson, 2023. "Tools for Predicting Forage Growth in Rangelands and Economic Analyses—A Systematic Review," Agriculture, MDPI, vol. 13(2), pages 1-30, February.
    2. Dennis S. Ojima & Rebecca Aicher & Steven R. Archer & Derek W. Bailey & Susan M. Casby-Horton & Nancy Cavallaro & Julian J. Reyes & John A. Tanaka & Robert A. Washington-Allen, 2020. "A climate change indicator framework for rangelands and pastures of the USA," Climatic Change, Springer, vol. 163(4), pages 1733-1750, 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:jlands:v:14:y:2025:i:1:p:140-:d:1564766. 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.