Elevation Control on Vegetation Organization in a Semiarid Ecosystem in Central New Mexico

Monday, 14 December 2015
Poster Hall (Moscone South)
Sai Siddhartha Nudurupati1, Erkan Istanbulluoglu2, Jordan Marie Adams3, Daniel E. J. Hobley4, Nicole M Gasparini3, Gregory E Tucker5 and Eric W.H. Hutton6, (1)University of Washington, Seattle, WA, United States, (2)University of Washington Seattle Campus, Seattle, WA, United States, (3)Tulane University of Louisiana, New Orleans, LA, United States, (4)Univ of Colorado, Boulder, CO, United States, (5)University of Colorado at Boulder, Boulder, CO, United States, (6)Community Surface Dynamics Modeling System, Boulder, CO, United States
Many semiarid and desert ecosystems are characterized by patchy and dynamic vegetation. Topography plays a commanding role on vegetation patterns. It is observed that plant biomes and biodiversity vary systematically with slope and aspect, from shrublands in low desert elevations, to mixed grass/shrublands in mid elevations, and forests at high elevations. In this study, we investigate the role of elevation dependent climatology on vegetation organization in a semiarid New Mexico catchment where elevation and hillslope aspect play a defining role on plant types. An ecohydrologic cellular automaton model developed within Landlab (component based modeling framework) is used. The model couples local vegetation dynamics (that simulate biomass production based on local soil moisture and potential evapotranspiration) and plant establishment and mortality based on competition for resources and space. This model is driven by elevation dependent rainfall pulses and solar radiation. The domain is initialized with randomly assigned plant types and the model parameters that couple plant response with soil moisture are systematically changed. Climate perturbation experiments are conducted to examine spatial vegetation organization and associated timescales. Model results reproduce elevation and aspect controls on observed vegetation patterns indicating that this model captures necessary and sufficient conditions that explain these observed ecohydrological patterns.