Assessing the influence of abiotic factors and leaf-level properties on the stability of growing-season canopy greenness in a deciduous forest

Maps depicting spatial pattern in the stability of summer greenness could advance understanding of how forest ecosystems will respond to global changes such as a longer growing season. Declining summer greenness, or “greendown”, is spectrally related to declining near-infrared reflectance and is observed in most remote sensing time series to begin shortly after peak greenness at the end of spring and extend until the beginning of leaf coloration in autumn,. Understanding spatial patterns in the strength of greendown has recently become possible with the advancement of Landsat phenology products, which show that greendown patterns vary at scales appropriate for linking these patterns to proposed environmental forcing factors. This study tested two non-mutually exclusive hypotheses for how leaf measurements and environmental factors correlate with greendown and decreasing NIR reflectance across sites. At the landscape scale, we used linear regression to test the effects of maximum greenness, elevation, slope, aspect, solar irradiance and canopy rugosity on greendown. Secondly, we used leaf chemical traits and reflectance observations to test the effect of nitrogen availability and intrinsic water use efficiency on leaf-level greendown, and landscape-level greendown measured from Landsat. The study was conducted using Quercus alba canopies across 21 sites of an eastern deciduous forest in North America between June and August 2014. Our linear model explained greendown variance with an R2=0.47 with maximum greenness as the greatest model effect. Subsequent models excluding one model effect revealed elevation and aspect were the two topographic factors that explained the greatest amount of greendown variance. Regression results also demonstrated important interactions between all three variables, with the greatest interaction showing that aspect had greater influence on greendown at sites with steeper slopes. Leaf-level reflectance was correlated with foliar δ13C (proxy for intrinsic water use efficiency), but foliar δ13C did not translate into correlations with landscape-level variation in greendown from Landsat. Therefore, we conclude that Landsat greendown is primarily indicative of landscape position, with a small effect of canopy structure, and no measureable effect of leaf reflectance. With this understanding of Landsat greendown we can better explain the effects of landscape factors on vegetation reflectance and perhaps on phenology, which would be very useful for studying phenology in the context of global climate change

DISSOLVED AND GASEOUS FLUXES OF CARBON AND NITROGEN FROM URBAN WATERSHEDS OF THE CHESAPEAKE BAY

Carbon and nitrogen loading to streams and rivers contributes to eutrophication as well as greenhouse gas (GHG) production in streams, rivers and estuaries. My dissertation consists of three research chapters, which examine interactions and potential trade-offs between water quality and greenhouse gas production in urban streams of the Chesapeake Bay watershed. My first research project focused on drivers of carbon export and quality in an urbanized river. I found that watershed carbon sources (soils and leaves) contributed more than in-stream production to overall carbon export, but that periods of high in-stream productivity were important over seasonal and daily timescales. My second research chapter examined the influence of urban storm-water and sanitary infrastructure on dissolved and gaseous carbon and nitrogen concentrations in headwater streams. Gases (CO2, CH4, and N2O) were consistently super-saturated throughout the course of a year. N2O concentrations in streams draining septic systems were within the high range of previously published values. Total dissolved nitrogen concentration was positively correlated with CO2 and N2O and negatively correlated with CH4. My third research chapter examined a long-term (15-year) record of GHG emissions from soils in rural forests, urban forest, and urban lawns in Baltimore, MD. CO2, CH4, and N2O emissions showed positive correlations with temperature at each site. Lawns were a net source of CH4 + N2O, whereas forests were net sinks. Gross CO2 fluxes were also highest in lawns, in part due to elevated growing-season temperatures. While land cover influences GHG emissions from soils, the overall role of land cover on this flux is very small (< 0.5%) compared with gases released from anthropogenic sources, according to a recent GHG budget of the Baltimore metropolitan area, where this study took place.