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Seasonal temperature and precipitation effects on cow–calf production in northern mixed-grass prairie

Reeves, Justin L., Derner, Justin D., Sanderson, Matt A., Petersen, Mark K., Vermeire, Lance T., Hendrickson, John R., Kronberg, Scott L.
Livestock science 2013 v.155 no.2-3 pp. 355
Agricultural Research Service, Charolais, Hereford, Red Angus, Salers, atmospheric precipitation, beef, beef cattle, business enterprises, climate change, cow-calf operations, crossbreds, decision support systems, grazing, growing season, herds, prairies, ranchers, rangelands, risk, seasonal variation, spring, springs (water), stocking rate, summer, temperature, winter, Wyoming
Quantifying the effects of seasonal temperature and precipitation on cow–calf production on rangelands is challenging, as few long-term (>20yrs) studies have been reported. However, an understanding of how seasonal weather inconsistency affects beef production is needed for beef producers to better manage their herds on native rangelands to minimize enterprise risk with respect to climatic variability. Cow–calf beef production data collected at the USDA-ARS High Plains Grasslands Research Station near Cheyenne, WY, USA from 1975 to 2012 were tested using model averaging for effects of spring (April–June) and summer (July–September) temperature and precipitation, as well as prior winter (October–March) and prior growing season (April–September) precipitation on beef production. Two breeds were used at different times during the study period (Herefords from 1975 to 2001 and a Red Angus×Charolais×Salers cross from 2003 to 2012; there was no grazing in 2002) and examined separately to test for differential effects of seasonal weather by breed. Herefords were more sensitive to seasonal weather patterns than the crossbreds, with Hereford pair total beef production showing the largest effect sizes and Hereford cows showing the highest R2 value (0.66) among models. Wet springs and wet winters particularly increased Hereford beef production in this northern mixed-grass prairie, whereas beef production from the crossbreds did not show any weather effect patterns. The model structure used maximizes utility of these data to be built into decision support tools to help ranchers optimize stocking rates and minimize enterprise risk in advance of the grazing season.