Calhoun, GRAD STUDENT
Calhoun, INVESTIGATOR
Agroecosystems cover a significant fraction of the Earth's surface, making their water and nutrient cycles a major component of global cycles across spatial and temporal scales. Most agroecosystems experience seasonality via variations in precipitation, temperature, and radiation, in addition to human activities which also occur seasonally, such as fertilization, irrigation, and harvesting. These seasonal drivers interact with the system in complex ways which are often poorly characterized. Crop models, which are widely used for research, decision support, and prediction of crop yields, are among the best tools available to analyze these systems. Though normally constructed as a set of dynamical equations forced by hydroclimatic variability, they are not often analyzed using dynamical systems theory and methods from stochastic ecohydrology. With the goal of developing this viewpoint and thus elucidating the roles of key feedbacks and forcings on system stability and on optimal fertilization and irrigation strategies, we develop a minimal dynamical system which contains the key components of a crop model, coupled to a carbon and nitrogen cycling model, driven by seasonal fluctuations in water and nutrient availability, temperature, and radiation. External drivers include seasonally varying climatic conditions and random rainfall forcing, irrigation and fertilization as well as harvesting. The model is used to analyze the magnitudes and interactions of the effects of seasonality on carbon and nutrient cycles, crop productivity, nutrient export of agroecosystems, and optimal management strategies with reference to productivity, sustainability and profitability. The impact of likely future climate scenarios on these systems is also discussed.
Pelak, N. F., III; Revelli, R.; Porporato, A. M. (2017): Impact of seasonal variability in water, plant and soil nutrient dynamics in agroecosystems. American Geophysical Union 2017 Fall Meeting, 11-15 Dec. 2017, New Orleans, LA.
This Paper/Book acknowledges NSF CZO grant support.