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ARS Home » Plains Area » Fort Collins, Colorado » Center for Agricultural Resources Research » Rangeland Resources & Systems Research » Research » Publications at this Location » Publication #313492

Title: Seasonal weather-related decision making for cattle production in the Northern Great Plains

Author
item Reeves, Justin
item Derner, Justin
item Sanderson, Matt
item Kronberg, Scott
item Hendrickson, John
item Vermeire, Lance
item Petersen, Mark
item IRISARRI, GONZALO - University Of Wyoming

Submitted to: Rangelands
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/10/2019
Publication Date: 6/12/2015
Publication URL: http://handle.nal.usda.gov/10113/60971
Citation: Reeves, J.L., Derner, J.D., Sanderson, M.A., Kronberg, S.L., Hendrickson, J.R., Vermeire, L.T., Petersen, M.K., Irisarri, G. 2015. Seasonal weather related decision making for cattle production in the Northern Great Plains. Rangelands. 37(3):119-124.

Interpretive Summary: Ranching is a risky business, with cattle production (and associated enterprise income) largely being dependent upon seasonal weather patterns and corresponding forage production. To help reduce this risk, the USDA-Agricultural Research Service performed a multi-site study of seasonal weather effects on cattle production across the Northern Great Plains (Wyoming, North Dakota, and Montana). Cool, wet springs and longer, cooler growing seasons increase cattle production across the Northern Great Plains. Knowledge of these seasonal weather influences on cattle production is important for management decision-making, but practical application of this knowledge remains somewhat problematic. Increasing enterprise flexibility for dealing with variable forage production can be achieved by utilizing seasonal weather forecasts, as well as reducing base cow-calf herd numbers to less than 100% of typical ranch carrying capacity. Yearlings can then be used to increase grazing to utilize additional forage in good years. Recently launched USDA Regional Climate Hubs (http://climatehubs.oce.usda.gov) will deliver science-based knowledge, practical information, management and conservation strategies, and decision tools to ranchers that will help them adapt to weather variability and changing climatic conditions.

Technical Abstract: High inter-annual variability of seasonal weather patterns can greatly affect forage and therefore livestock production in the Northern Great Plains. This variability can make it difficult for ranchers to set yearly stocking rates, particularly in advance of the grazing season. To better understand seasonal weather effects on beef cattle production in the Northern Great Plains, the USDA-Agricultural Research Service has performed a multi-site collaboration using long-term (30-96 year) cattle production datasets from Wyoming, North Dakota, and Montana. Data were analyzed using weighted AICc model averaging 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 prior fall/winter (prior October–March) precipitation on cattle production. Across sites, cool, wet springs, and longer, cooler growing seasons increased cattle production, with remaining weather effects being plant-community specific. It was also found that higher stocking rates increase cattle production sensitivity to seasonal weather patterns. Management implications and suggestions from these analyses include reducing base cow-calf stocking rates, and utilizing yearling steers to adjust overall stocking rates in times of ample forage production. Seasonal weather forecasts such as those produced by National Weather Service that are available up to a year in advance can also be paired with our model results to help predict forage production and begin making stocking rate decisions in advance of the grazing season. To assist in this process, recently launched USDA Regional Climate Hubs will deliver science-based knowledge, practical information, management and conservation strategies, and decision tools.