Page Banner

United States Department of Agriculture

Agricultural Research Service

Title: Spring precipitation as a predictor for peak standing crop of mixed-grass prairie

Authors
item Wiles, Lori
item Dunn, Gale
item Printz, Jeff - USDA-NRCS
item Patton, Robert - NORTH DAKOTA STATE UNIV
item Nyren, Anne - NORTH DAKOTA STATE UNIV

Submitted to: Rangeland Ecology and Management
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: December 6, 2011
Publication Date: March 1, 2011
Citation: Wiles, L., Dunn, G.H., Printz, J., Patton, R., Nyren, A. 2011. Spring precipitation as a predictor for peak standing crop of mixed-grass prairie. Rangeland Ecology and Management. 64(2):215-222.

Interpretive Summary: Ranchers and range managers in the West are at the mercy of climatic conditions that determine the amount of annual forge available on rangeland. Typically, stocking or de-stocking decisions need to be made before the final annual forage production level is known. Since erroneous stocking rate decisions can have dire economic and environmental consequences, a decision support tool is needed that uses easily obtained information to provide a reasonably accurate prediction of forage growth potential as early as possible in the coming growing/grazing season. Our hypothesis was that rainfall during certain periods of the year (annual, growing season, and with-in growing season) would be highly correlated with peak standing crop and could, therefore, be used in a decision support tool. We analyzed the relationships between grazed and un-grazed peak standing crop (PSC) and precipitation using a non-linear regression, Akaike’s information criterion for model selection, and data from three locations: Streeter, ND, Miles City, MT, and Cheyenne, WY. Predictor variables included annual and growing season precipitation and several variables based on spring precipitation. We found that grazing did not affect the relationship between PSC and precipitation, nor were annual or growing season precipitation good predictor variables. The best predictor variable was total precipitation in April and May for MT, May and June for ND and April, May and June for WY, with r2 ranging from 0.50 to 0.64. These results indicate that spring precipitation is useful information for stocking or destocking decisions and can potentially be used to develop a decision support tool.

Technical Abstract: Ranchers and range managers in the West are at the mercy of climatic conditions that determine the amount of annual forge available on rangeland. Typically, stocking or de-stocking decisions need to be made before the final annual forage production level is known. Since erroneous stocking rate decisions can have dire economic and environmental consequences, a decision support tool is needed that uses easily obtained information to provide a reasonably accurate prediction of forage growth potential as early as possible in the coming growing/grazing season. Our goal was to identify such a potential predictor. We analyzed the relationships between grazed and un-grazed peak standing crop (PSC) and precipitation using a non-linear regression, Akaike’s information criterion for model selection, and data from three locations: Streeter, ND, Miles City, MT, and Cheyenne, WY. Predictor variables included annual and growing season precipitation and several variables based on spring precipitation. Both the response and predictor variables were normalized. We found that grazing did not affect the relationship between PSC and precipitation, nor were annual or growing season precipitation good predictor variables. The best predictor variable was total precipitation in April and May for MT, May and June for ND and April, May and June for WY, with r2 ranging from 0.50 to 0.64. These results indicate that spring precipitation is useful information for stocking or destocking decisions and can potentially be used to develop a decision support tool.

Last Modified: 4/17/2014
Footer Content Back to Top of Page