Beyond the visible: The effects of soil water and nitrogen on plant reflectance spectra
Soils and plants help maintain the balance of nutrients and water in Earth’s ecosystems; however, changes in plant populations due to the arrival of invasive species alter the movement of water and nutrients in the environment. Remote sensing is a developing technology that could monitor these ecosystem changes, but it is still uncertain whether remote sensing can be used to discriminate between different sources of plant stress, such as nitrogen leaching and water loss. This study’s aim is to determine (1) whether changes in soil nitrogen and soil moisture will change plant characteristics in the invasive species Dahurian buckthorn (Rhamnus davurica), (2) whether changes in plant characteristics can be observed spectrally, (3) whether we can tease apart spectral differences due to nitrogen stress and water stress, and (4) which analyses of spectral profiles are the most representative of nitrogen and water changes. We investigated these questions by applying weekly water and nitrogen treatments to buckthorn plants at Blandy Experimental Farm, Boyce, VA. We collected weekly and biweekly measurements of LAI, leaf moisture, leaf nitrogen, and stomatal resistance, which we compared to measurements of soil moisture, soil nitrogen and plant reflectance spectra. We also compared plant and leaf characteristics to calculated vegetation indices including NDVI, WBI, EVI, EVI and CCCI to determine if particular analyses could accurately represent specific plant stresses.
We found that leaf properties change in response to changes in soil properties with a one- to two-week time delay. The strongest correlation between soil and leaf properties was between soil moisture and stomatal resistance (p=0.0365). We also found that changes in plant properties can be observed spectrally. Plant nitrogen content, for example, correlated strongely to CCCI. Results indicate that it is possible to determine if stress is related to nitrogen or to water, as well. Complete spectral profiles used to tease apart wavelengths associated with water and nitrogen stress show reflectance differences in the NIR range. Additionally, discriminant analysis correctly identified plot treatments at least half the time for water and nitrogen stress, suggesting that spectra can discern between the two stressors. Finally, CCCI showed strong correlation to plant and soil C:N (p=0.0333, p=0.0221), making it a good indicator of nitrogen stress for both plants and soil. Such results are important for developing more accurate ecosystem monitoring methods, which will provide a better understanding of environmental health and stability.