Simulation Model for Studying Dynamics of Water Flow and Water Status in Plants
- C. J. Fernández and
- K. J. McCree
Models are useful for visualizing the many complex interactions that occur in plants, and for investigating effects of morphological and physiological attributes on plant performance. Plant Water Dynamics simulates the dynamic variations of plant water status that occur while a plant interacts with the environment. The modeling approach was based on the idea that plant water status depends on the balance of three fluxes: uptake of water from soil, storage of water in plant tissue, and loss of water by transpiration. All three fluxes are calculated directly or indirectly as functions of plant water status, as defined by leaf water potential. At any given time, the sum of all water fluxes is balanced to zero. The model is based on water transport theory and uses the concepts of capacitance, effective leaf area, and morphological homeostasis to calculate the change in organ water fraction per unit change of organ water potential, the leaf area that effectively intercepts radiation, and the increase in xylem cross-sectional area in proportion to the increase in effective leaf area, respectively. Stress responses control the flow of water through the plant by affecting the conductances of roots, xylem, and leaves. These stress responses are triggered as the water status of soil and plant deteriorate. Original features of the model include the introduction of a storage term into the flux balance, the inclusion of stress effects on xylem as well as root conductances, and the ability to modify stress responses as the plant osmotically adjusts. A sample run simulating transpiration and leaf water potential data for sorghum plants [Sorghum bicolor (L.) Moench] during a single water deficit cycle under controlled environmental conditions showed that the model is a reliable simulation tool. Analysis of each of the model's new features demonstrated that the approach used in Plant Water Dynamics is an improvement over previous models.
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