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ARS Home » Research » Publications at this Location » Publication #153834
Title: APPLICATION OF GPFARM TO SIMULATE FORAGE PRODUCTION AND COW-CALF WEIGHTS

Author
item ANDALES, ALLAN - NEW MEXICO STATE UNIVERSI
item Derner, Justin
item Bartling, Patricia
item Ahuja, Lajpat
item Dunn, Gale
item HART, RICHARD - ARS-RETIRED

Submitted to: Society for Range Management Meeting Abstracts
Publication Type: Abstract Only
Publication Acceptance Date: 8/1/2003
Publication Date: 1/1/2004
Citation: Andales, A.A., Derner, J.D., Bartling, P.N., Ahuja, L.R., Dunn, G.H., Hart, R.H. 2004. Application of gpfarm to simulate forage production and cow-calf weights. Society for Range Management Meeting Abstracts. No. 5.

Interpretive Summary:

Technical Abstract: A modeling approach that assesses impacts of alternative management decisions before field implementation would reduce decision-making risk for rangeland and livestock production system managers. The goal of this study was to evaluate the functionality of the Great Plains Framework for Agricultural Resource Management (GPFARM) model in simulating forage and cattle production in the Central Great Plains. The forage production module was tested in shortgrass prairie using April-October monthly biomass values from 2000-2002 for warm-season grasses, cool-season grasses, shrubs and weeds. The forage module displayed good agreement in tracking functional group growth and senescence trends, but further investigation is needed to determine why simulated warm-season grass biomass peaked earlier than observed biomass. The cattle production module was tested in northern mixed-grass prairie using June-November monthly average cow and calf weights from 1996-2001 for March-calving, moderately stocked Hereford pairs. Overall, GPFARM performed well and tracked cow and calf pre- and post-weaning weights. Further model work should focus on the calf gain algorithm post-weaning as calf weights were under-predicted. The GPFARM model is useful for rangeland and livestock production system managers as a decision support system. Continued developments will focus on expanding this utility by incorporating environmental risk, additional management operations and within-year flexibility.