Temperature and Precipitation Affect Steer Weight Gains Differentially by Stocking Rate in Northern Mixed-Grass Prairie

Abstract Cattle weight gain responses to seasonal weather variability are difficult to predict for rangelands because few long-term (>20 yr) studies have been conducted. However, an increased understanding of temperature and precipitation influences on cattle weight gains is needed to optimize stocking rates and reduce enterprise risk associated with climatic variability. Yearling steer weight gain data collected at the USDA-ARS High Plains Grasslands Research Station at light, moderate, and heavy stocking rates for 30 years (1982–2011) were used to examine the effects of spring (April–June) and summer (July–September) temperature and precipitation, as well as prior-growing-season (prior April–September) and fall/winter (October–March) precipitation, on beef production (kg · ha−1). At heavier stocking rates, steer production was more sensitive to seasonal weather variations. A novel finding was that temperature (relatively cool springs and warm summers) played a large predictive role on beef production. At heavier stocking rates, beef production was highest during years with cool, wet springs and warm, wet summers, corresponding to optimum growth conditions for this mixed C3–C4 plant community. The novelty and utility of these findings may increase the efficacy of stocking rate decision support tools. The parsimonious model structure presented here includes three-month seasonal clusters that are forecasted and freely available from the US National Oceanic and Atmospheric Administration up to a year in advance. These seasonal weather forecasts can provide ranchers with an increased predictive capacity to adjust stocking rates (in advance of the grazing season) according to predicted seasonal weather conditions, thereby reducing enterprise risk.

[1]  L. Vermeire,et al.  Effect of weather patterns on preweaning growth of beef calves in the Northern Great Plains. , 2012 .

[2]  Lajpat R. Ahuja,et al.  Opportunities for Increasing Utility of Models for Rangeland Management , 2012 .

[3]  G. Likens,et al.  Value of long-term ecological studies , 2012 .

[4]  Nathaniel A. Brunsell,et al.  Timing of climate variability and grassland productivity , 2012, Proceedings of the National Academy of Sciences.

[5]  O. Ramírez,et al.  Economics of Flexible Versus Conservative Stocking Strategies to Manage Climate Variability Risk , 2010 .

[6]  C. Bastian,et al.  Optimal Rangeland Stocking Decisions Under Stochastic and Climate‐Impacted Weather , 2010 .

[7]  Matthew A. Diersen,et al.  Long-Term Production and Profitability From Grazing Cattle in the Northern Mixed Grass Prairie , 2010 .

[8]  Haiying Wang,et al.  Frequentist model averaging estimation: a review , 2009, J. Syst. Sci. Complex..

[9]  T. Mader,et al.  Potential climate change effects on warm-season livestock production in the Great Plains , 2009 .

[10]  J. Craine,et al.  Consequences of climate variability for the performance of bison in tallgrass prairie , 2009 .

[11]  J. W. Waggoner,et al.  Long-term cattle gain responses to stocking rate and grazing systems in northern mixed-grass prairie , 2008 .

[12]  J. Derner,et al.  Grazing-Induced Modifications to Peak Standing Crop in Northern Mixed-grass Prairie , 2007 .

[13]  L. Ahuja,et al.  Strategic and Tactical Prediction of Forage Production in Northern Mixed-Grass Prairie , 2006 .

[14]  J. Y. King,et al.  Elevated CO2 and defoliation effects on a shortgrass steppe: Forage quality versus quantity for ruminants , 2005 .

[15]  J. D. Hanson,et al.  Evaluation of GPFARM for Simulation of Forage Production and Cow–Calf Weights , 2005 .

[16]  David R. Anderson,et al.  Multimodel Inference , 2004 .

[17]  R. Barbehenn,et al.  C3 grasses have higher nutritional quality than C4 grasses under ambient and elevated atmospheric CO2 , 2004 .

[18]  Osvaldo E. Sala,et al.  Inter-annual variation in primary production of a semi-arid grassland related to previous-year production , 2001 .

[19]  David R. Anderson,et al.  Null Hypothesis Testing: Problems, Prevalence, and an Alternative , 2000 .

[20]  James C. Ascough,et al.  Object-oriented simulation of integrated whole farms : GPFARM framework , 2000 .

[21]  R. H. Hart,et al.  Grazing intensities, vegetation, and heifer gains: 55 years on shortgrass. , 1998 .

[22]  P. Nyren,et al.  GRAZING INTENSITY AND ECOSYSTEM PROCESSES IN A NORTHERN MIXED-GRASS PRAIRIE, USA , 1998 .

[23]  J. W. Waggoner,et al.  Vegetation, cattle, and economic responses to grazing strategies and pressures , 1997 .

[24]  D. Ganskopp,et al.  Response of cattle to cured reproductive stems in a caespitose grass. , 1992 .

[25]  R. H. Hart,et al.  Cattle, vegetation, and economic responses to grazing systems and grazing pressure. , 1988 .

[26]  S. Smoliak.  Influence of climatic conditions on production of Stipa-Bouteloua prairie over a 50-year period. , 1986 .

[27]  G. B. Schaalje,et al.  Cattle weight gains in relation to stocking rate on rough fescue grassland. , 1986 .

[28]  J. Singh,et al.  The structure and function of ten Western North American grasslands: III. Net primary production, turnover and efficiencies of energy capture and water use , 1978 .

[29]  G. Williams.  Photosynthetic adaptation to temperature in c(3) and c(4) grasses: a possible ecological role in the shortgrass prairie. , 1974, Plant physiology.

[30]  David R. Anderson,et al.  Understanding AIC and BIC in Model Selection , 2004 .

[31]  B. Baker,et al.  Comparison of the effects of different climate change scenarios on rangeland livestock production , 1993 .

[32]  J. Holechek,et al.  Range Management: Principles and Practices , 1989 .