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dc.contributor.authorTorell, L. Allen
dc.contributor.authorMcDaniel, Kirk C.
dc.contributor.authorKoren, Victor
dc.date.accessioned2020-09-05T07:00:18Z
dc.date.available2020-09-05T07:00:18Z
dc.date.issued2011-01-01
dc.identifier.citationTorell, 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.
dc.identifier.issn0022-409X
dc.identifier.doi10.2111/REM-D-09-00107.1
dc.identifier.urihttp://hdl.handle.net/10150/642843
dc.description.abstractTo 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. 
dc.language.isoen
dc.publisherSociety for Range Management
dc.relation.urlhttps://rangelands.org/
dc.rightsCopyright © Society for Range Management.
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/
dc.subjectbiomass prediction model
dc.subjectBouteloua gracilis
dc.subjectclimate
dc.subjectmodified Sacramento soil moisture accounting model
dc.subjectprecipitation
dc.subjectrangeland net primary production (NPP)
dc.subjectsoil water-NPP relationships
dc.titleEstimating Grass Yield on Blue Grama Range From Seasonal Rainfall and Soil Moisture Measurements
dc.typetext
dc.typeArticle
dc.identifier.journalRangeland Ecology & Management
dc.description.collectioninformationThe Rangeland Ecology & Management archives are made available by the Society for Range Management and the University of Arizona Libraries. Contact lbry-journals@email.arizona.edu for further information.
dc.eprint.versionFinal published version
dc.description.admin-noteMigrated from OJS platform August 2020
dc.source.volume64
dc.source.issue1
dc.source.beginpage56-66
refterms.dateFOA2020-09-05T07:00:18Z


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