Changes in climate, fire regimes, and land use are rapidly altering the structure and function of dryland watersheds. For example, increases in fire activity and elevated atmospheric nitrogen (N) inputs are enhancing rates of N export to streams, which can not only degrade essential water resources, but may also affect how upland plant communities recover. Simulation models are a critical tool for projecting how climate change, wildfire, and N deposition will influence N retention at watershed scales. However, watershed-scale models often simplify belowground patterns and processes that may be essential to capture N dynamics in drylands. For example, they often ignore how N is hydrologically connected with soil microbes and plant roots over space and time. These model deficits may cause large errors associated with N export projections. To improve the way we simulate belowground N dynamics in drylands, we are using field measurements to validate and expand the way we model belowground hot spots and moments using the ecohydrologic model RHESSys.
Results/Conclusions
We find that following fire in drylands, N export is highly sensitive to meteorological conditions and rates of plant recovery. For example, cumulative N export can increase under drought because recovering plants are much more sensitive to desiccation than soil microbes. Thus, mineral N can accumulate over the hot, dry summer following fire and be rapidly flushed from soils upon wetup. In addition, the magnitude of N loss is sensitive to how N is distributed in the soil profile. These findings demonstrate a need to better represent belowground N partitioning and its effects on plant-soil interactions in models.