A simulation model of Bouteloua gracilis biomass dynamics on the North American shortgrass prairie

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Abstract
A grassland primary producer model for simulating intraseasonal biomass dynamics as a function of temperature, moisture, light, and nitrogen was developed for Bouteloua gracilis (H.B.K.) Lag., the dominant C4 grass of the North American shortgrass prairie. Plant state variables included young and mature leaves, crowns, and roots from three depth categories while simulated processes included spring regrowth, photosynthesis, respiration, photosynthate allocation, death, and litterfall. Sensitivity analyses revealed the model was most sensitive to changes in photosynthesis and photosynthate allocation and least sensitive to changes in initial values of state variables, leaf dark respiration rates, and rate of spring regrowth. An abiotic submodel driven by observed weather data was used in conjunction with the primary producer model to simulate plant biomass dynamics under a variety of conditions including untreated controls (C), nitrogen fertilization (F), irrigation (I), and irrigation plus fertilization (IF). Model predictions of life shoot biomass (B s) and annual aboveground net primary production (NPP A) followed the same trends as field measurements with B sand NPP Aof IF>I>F>C. Failure of the model to accurately predict measured declines in peak B sand NPP Aafter several years of irrigation may have been caused by failure to account for growth lags following water stress, inadequate simulation of interspecific competition, or failure to simulate response to some mineral nutrients which had become limiting after several years of this treatment. A simulated annual carbon budget for plants in the four treatments suggests that from 61% (IF) to 80% (C) of the net carbon fixed above ground is ultimately translocated and utilized below ground.