A Near Real-Time Monitoring and Knowledge Generation System to Visualize Vegetation Dynamics.

The native plant species in the Rush Valley of Utah’s arid central basin face competition from two aggressive, non-native species: cheat grass (Bromus tectorum) and halogeton (Halogeton glomeratus).  Seasonal rainfall patterns and water availability may to favor cheat grass, which germinates in the fall and flowers in the early spring, or halogeton, which bolts in the later summer and has a tap root up to 0.5 m deep. Their presence in this fragile ecosystem increases the risk of fire and reduces forage (halogeton is toxic to many mammals).  The first goal of this study is to quantify the effects of soil water availability on plant growth and inter-species competition under a series of imposed treatment conditions.  An important second goal of the study is to create a seamless knowledge dissemination system that will show essential trends in the data in near real-time to scientists associated with the project as well as interested public. Plots were established that varied native rainfall, excluded rodents, and underwent managed burns.  Cellular-based datalogging systems were installed that measured soil matric potential and water content at two depths in each treatment, above ground reflectance sensors to quantify Normalize Difference Vegetation Index (NDVI), and micro-meteorological data to characterize site-specific weather. Data are collected from a central server and provided to consumers to highlight trends and events that provide knowledge essential to the first goal of the study. Challenges to setting up and maintaining the system will be discussed.