College Park, MD 20740
ABSTRACT: Models of soil organic matter (SOM) dynamics are used for predicting the effects of management and climate change on soil carbon stabilization and soil nutrient availability. Current models are based on a few conceptual SOM pools that are not measurable. Each SOM pool is associated with a specific turnover time that represents the stability of the material transformed or respired. However, there is ample evidence that the physical aggregation of soil has a significant effect on SOM dynamics. It has been shown that these physical aggregations and their dynamics can be measured directly in the laboratory and in the field, but they have not been explicitly incorporated in models. Here, I present a simulation model that integrates soil aggregate dynamics with SOM dynamics. In the model I consider unaggregated and microaggregated soil that can exist within or external to macroaggregated soil. The organic matter inside of each aggregate class is divided into particulate organic matter, mineral-associated organic matter fraction and an inert organic matter pool. I used empirical data from laboratory and field experiments to estimate the biological and environmental effects on the rate of formation and breakdown of macroaggregates and microaggregates, and the organic matter dynamics within these different aggregate classes. The simulation model was validated with long-term field data. The advantage of a model that is based on measurable SOM fractions is that its internal structure can be validated by field data. Furthermore, models that are based on mechanistic processes have the potential advantage of being more robust and, therefore, providing predictions to a larger array of scenarios, including scenarios that cannot be manipulated in field conditions.
BIOGRAPHY: Dr. Moran Segoli, PhD, is a post-doctoral fellow at the agroecology lab at the University of California in Davis. Dr. Segoli received his Ph.D. in Desert Studies from the department of ecology, Ben-Gurion University of the Negev, Israel. His research focused on patch and landscape scale effects of anthropogenic disturbances on woody vegetation, and the cascading effect on herbaceous vegetation, soil dwelling arthropods and soil nutrients. He used large scale field manipulations and observations to examine the available ecosystem-based management options that increase productivity for livestock and maintain biodiversity and ecosystem resilience. During his post-graduate studies, Dr. Segoli has used computational modeling to examine the effects of increased monocultural crop field size on the resulting density of herbivorous pests. Currently, Dr. Segoli is modifying the Environment Policy Integrated Climate (EPIC) model to include a hierarchical representation of soil nutrient dynamics within soil aggregate dynamics. This model will be the first field scale model that uses measurable soil fractions (as opposed to conceptual pools used in existing models) that can be validated by field data.