Enhancing a new experimental research facility in the Santa Rita Experimental Range through the incorporation of novel remote sensing techniques

Abstract:

Global change experiments are often spatially and temporally limited because they are time-intensive, labor-intensive, and expensive to maintain. Incorporation of remote-sensing techniques into global change experiments can complement traditional methods and provide new insights into ecosystem processes. Here we present first results from an effort to incorporate cutting-edge remote sensing techniques at a new rainfall manipulation experiment in the Santa Rita Experimental Range (SRER), near the University of Arizona (UA). The location provides novel opportunities to study in depth key aspects of dryland vegetation structure and function. Following anticipated (and already observed) climatic changes, we are initially exploring a summer precipitation treatment designed to quantify the impact of fewer, larger summer storms and longer dry intervals. We describe here newly incorporated remote sensing techniques that enable automated, high-frequency, non-destructive monitoring of key aspects of aboveground vegetation structure and function including 1) high-frequency vegetation spectral indices and plant community classification derived from a network of low-cost, automated Raspberry Pi phenocams; 2) high-resolution vegetation structural indices and structural trait mapping derived from fine-scale structure from motion three dimensional modeling; 3) non-destructive root growth and below-ground phenology characterization derived from a minirhizotron imaging system. We present first year results compared with in situ measurements of vegetation and soil gas flux, destructive above and belowground plant biomass measurements, soil moisture, and soil temperature data. Insights from these relationships can be used to enhance airborne and spaceborne remote sensing of dryland ecosystems for landscape-scale analysis.