INVESTIGATING GEOCHEMICAL CONTROLS ON VEGETATION COVER IN THE NORTHERN COLORADO FRONT RANGE

There are various anecdotal observations of vegetation patterns controlled by the underlying lithologic units, yet surprisingly few detailed studies have investigated what drives these patterns. In the Sierra Nevada, Hahm et al. (2014) found geochemistry differences of granitic rocks control vegetation patterns. In another extreme, serpentine soil geochemistry is known to limit vegetation growth except in cases of specialized species because of high concentration of metals such as Fe, Cr, Ni, Mn and Co (Oze et al., 2008). In Southeastern Utah, Neff et al. (2006) found soil nutrients and cycling to depend on sedimentary bedrock type in Canyonlands National Park (Neff et al., 2006). These examples demonstrate the influence of lithology on soil development and thus vegetation growth patterns, however, there are still many unstudied lithologies and geographic areas. To address these unknowns, we took advantage of observed forested (Ponderosa dominant) versus unforested (herbaceous dominant) areas in Proterozoic metamorphic rocks of the northern Colorado Front Range. Here, amphibolite regions lack forested cover, whereas quartz-rich metasedimentary schists are forested. We collected and compiled geochemistry data of bedrock samples (amphibolite n = 12, schist n = 7) and also verified a statistical difference in vegetation cover using the Normalized Difference Vegetation Index (NDVI). NDVI was lower for amphibolite regions (<120) and higher (>120) for metasedimentary regions. Rock and soil geochemistry shows large differences in primary and secondary elements that are relevant to vegetation growth. For example, the amphibolites contained a higher percentage of Mg, Ca, and P compared to the metasedimentary samples. The Mg:Ca ratios were very different between the rocks types, with an average ratio of 0.7 for amphibolite compared to 3.7 for the metasedimentary units. The metasedimentary units also had higher K values. These geochemical patterns might help explain the observed vegetation patterns. We are exploring additional chemical analyses of collected soil samples in hopes that the soil data will provide a clearer picture of why there is a distinct vegetation difference in the two regions.