Functional Vegetation Trait Trends between Five Vegetation Types and Environmental Covariations in the East River Watershed, CO

Abstract:

Studying species’ traits is imperative to understand ecosystem functioning and the relationship to evolutionary history. Although plant traits have been studied in small scale experiments and across global datasets, large scale, spatially explicit, field studies are needed. Here we consider how intra- and interspecific trait variations are related to abiotic factors using trait data acquired from over 400 sites across a headwater catchment of the Colorado River (East River Watershed, CO), in 2018. We conducted an analysis of field and spatial data to analyze plant functional traits and identify topographic and geologic factors that correlate with or cause variations in these observations at the watershed scale. We verified that trait relationships associated with the leaf economic spectrum, a widely accepted theory which nevertheless has exceptions, holds across this system within and between vegetation classes. Several other significant trait differences, especially between conifers and other vegetation types, were found in d¹³C and leaf water content. We explored the relationship between the traits and environmental factors such as elevation, topographic metrics, and geology based on remote sensing and spatial data layers, including airborne LiDAR and hyperspectral data. Specifically, d¹³C was also found to be positively correlated with elevation and negatively correlated with LWC in conifers. When determining trait correlations, interspecific trait variations are noted and analyzed. These findings give insight to possible effects of climate change, drought, and future land use on the East River Watershed and the vegetation traits and dynamics contained within.