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A computer simulation of bluebunch wheatgrass (Agropyron spicatum) growth dynamics and implications to integrated management of livestock and wildlife

University of British Columbia

A computer model was developed for bluebunch wheatgrass (Agropyron spicatum (Pursh) Scribn. and Smith) which simulated the growth dynamics of this species in both the presence and absence of grazing. Growth dynamics were mechanistically modeled as functions of soil water potential, soil and air temperatures, rainfall intensity, photoperiod, foliar nitrogen content, and plant maturity. Simulated processes included growth potential, photosynthesis, dark respiration, carbohydrate translocation between aboveground and belowground biomass, dry matter production, shoot and root mortality, and litterfall. Model predictions of herbage production in the absence of grazing agreed closely with measurements obtained from field sampling. However, erroneous simulation of litterfall and inaccurate portrayal of the relationship between soil water potential and growth rate resulted in some discrepancies between predicted and observed values. Sensitivity analysis of climatic driving variables revealed that dry matter production is highly sensitive to soil moisture regimes; consequently, the effect of soil water potential on growth rate particularly warrants further research. Simulation results indicate that dry matter accumulation is primarily limited by low temperatures in early spring, low moisture availability in mid-summer, and a combination of low temperatures, low foliar nitrogen, and short photoperiods in late fall. Simulated carbohydrate movement from the roots to the shoots occurred during both initiation of spring growth and commencement of fall regrowth in one year of simulation, but occurred only during spring inititation in a second year of simulation. Carbohydrates translocated from the root system accounted for approximately 6 to 7 percent of total annual aboveground dry matter production. Photosynthate translocation to the root system occurred primarily before the onset of aestivation, with peak carbohydrate storage coinciding with the stage when approximately two thirds of current annual growth had been completed. Simulated values of regrowth following ground-level defoliation compared favorably with values obtained from field sampling. Quantitative validation of dry matter accumulation following lighter defoliation intensities is precluded by want of suitable data. However, qualitative validation of simulation results support the biological soundness of projected yields. Simulation results indicate that standing crop in the fall is considerably depressed by most grazing regimes; however, they also indicate that spring defoliations at 25% intensity may increase standing crop in the fall by as much as 61%. Total annual dry matter production was strongly affected by defoliation date and defoliation intensity when herbage removal occurred before July. However, the effects of defoliation date and defoliation intensity became minor when herbage removal occurred after mid-July. Simulation results suggest that improvements in crude protein yield following select grazing regimes surpass improvements in forage yield for comparable grazing treatments, since improvements in crude protein yield are promoted by enhanced nitrogen concentrations as well as stimulated foliar production. Thus, defoliation may occur at a higher intensity or at a later date for an improvement in crude protein yield than for an improvement in biomass yield. Simulation results indicate that the effect of herbage removal on dry matter production the year following defoliation closely parallels the effect of herbage removal on root accumulation during the year of treatment. In general, early spring or fall grazing are less damaging than mid-season grazing at comparable defoliation intensities. Simulation results support the contention that judicious grazing management may be used to improve bluebunch wheatgrass forage and crude protein availability to wintering wildlife. However, improved forage quality is predicated on the assumption that the rate of nitrogen loss in regrowth will not exceed the rate of nitrogen loss in spring growth. Additionally, the simulated effect of defoliation on tillering behavior is critical in determining regrowth yield. Currently, simulated tillering behavior is tenuously modeled because of lack of data.

Text

2010-05-09

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http://hdl.handle.net/2429/24537

Plant Science

University of British Columbia

Graduate