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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
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    References listed on IDEAS

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    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.
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