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    • Rangeland Ecology & Management, Volume 64 (2011)
    • Rangeland Ecology & Management, Volume 64, Number 1 (January 2011)
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    Estimating Grass Yield on Blue Grama Range From Seasonal Rainfall and Soil Moisture Measurements

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    Author
    Torell, L. Allen
    McDaniel, Kirk C.
    Koren, Victor
    Issue Date
    2011-01-01
    Keywords
    biomass prediction model
    Bouteloua gracilis
    climate
    modified Sacramento soil moisture accounting model
    precipitation
    rangeland net primary production (NPP)
    soil water-NPP relationships
    
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    Citation
    Torell, L. A., McDaniel, K. C., & Koren, V. (2011). Estimating grass yield on blue grama range from seasonal rainfall and soil moisture measurements. Rangeland Ecology & Management, 64(1), 56-66.
    Publisher
    Society for Range Management
    Journal
    Rangeland Ecology & Management
    URI
    http://hdl.handle.net/10150/642843
    DOI
    10.2111/REM-D-09-00107.1
    Additional Links
    https://rangelands.org/
    Abstract
    To estimate annual forage production from moisture conditions it is important to consider the timing and seasonality of precipitation events as well as the past history of storm events. In this study we examined this relationship using 16 yr of annual measurements of herbaceous standing crop recorded at two study sites located on the Corona Range and Livestock Research Center in central New Mexico. Our hypothesis was that end-of-season herbaceous standing crop estimations could be improved using measured soil moisture instead of seasonal accumulations of rainfall as traditionally used for yield prediction. Daily recorded and simulated soil moisture levels were used to estimate the number of days over the growing season when soil moisture by volume was at low (< 20%), intermediate (20% to 30%), or high (> 30%) levels. Defining regression equations to include either simulated or probe-recorded measures of soil moisture improved the adjusted R2 of the regression models from 46% for the rainfall model to over 60% for various soil moisture models. Key variables for explaining annual variation in herbaceous production included seasonal moisture conditions, the amount of broom snakeweed (Gutierrezia sarothrae [Pursh] Britt. Rusby) present on the area, and the degree days of temperature accumulated over the growing season. Diurnal daily temperatures near historical averages were most advantageous for forage production. Simulated soil moisture data improved predictive grass yield estimates to a level equivalent to using onsite moisture probes to categorize daily moisture conditions. Potential exists to better predict forage conditions based on forecast information that uses soil moisture data instead of the traditional input of seasonal rainfall totals. 
    Type
    text
    Article
    Language
    en
    ISSN
    0022-409X
    ae974a485f413a2113503eed53cd6c53
    10.2111/REM-D-09-00107.1
    Scopus Count
    Collections
    Rangeland Ecology & Management, Volume 64, Number 1 (January 2011)

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