A degree day model of sheep grazing influence on alfalfa weevil, Hypera postica
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Date
2009
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Montana State University - Bozeman, College of Agriculture
Abstract
Alfalfa, Medicago sativa (L.), is produced on approximately 720,000 ha in Montana and is the foremost forage crop in many high, semiarid, intermountain states. Two biological stressors (insects and weeds) combined with poor field management are primarily responsible for reduced alfalfa production. In the U.S. alone, arthropods cause an estimated $260 million loss to alfalfa with the alfalfa weevil (AW), Hypera postica Gyllenhal, being the most damaging phytophagous pest in the United States. Using degree days as predictors for initiation and cessation of arthropod IPM programs is a common practice and on-line degree day calculators using regional temperature data are providing equal accuracy as on-site estimates. Grazing is emerging as a legitimate IPM tactic however there is no published literature using degree days to implement an IPM based grazing systems. A degree day predictive model is needed, as a producer decision and support tool, to improve the effectiveness of strategic sheep grazing to manage alfalfa weevil. Grazing treatments exclosures were established in a randomized complete block design at weekly intervals giving each treatment a unique degree day and stocking rate. Degree days calculated from both on-site and near-site data produced the same model accuracy. Therefore, the near-site model was selected to encourage use by producers. Treatments meeting the selection criteria (G3, G4, G5) were 'modeled' together and a simple linear regression (P < 0.01) was calculated predicting AW larval populations based on stocking rate and degree day. Harvest sample treatment DM did not differ (P > 0.16). However, NDF, CP, and Yield differed (P < 0.01) between treatments. Due to an interaction (P < 0.01), ADF and TDN were separated by year and did not differ P = 0.93 during 2008, but did (P < 0.01) during 2009. Based on yield and nutritive differences between treatments, a simple regression (P < 0.01) of plant RGR was calculated to predict when yield and nutritive characteristics of the modeled and less extensively grazed 'alternative' (NG, G1, G2) treatments would equal. The equation predicted that producers would need to wait an average of four days for treatment harvest characteristics to equal.