Multi-scalar analysis of spring phenology in a northern mixed forest

This dissertation investigates three important topics related to the spring phenology of a mixed temperate forest in northern Wisconsin. First, this dissertation seeks to understand the dynamic relationships amongst climate, phenology, and the surface-atmosphere exchange of carbon dioxide (CO 2). This investigation used measures of microclimate, forest phenology, and CO2 exchange to understand the separate and coupled effects of climate and phenology on CO2 exchange. Second, this dissertation examines the relationship between surface and satellite observations of spring forest phenology. Surface and satellite measurements of light interception by forest canopies were used with visual phenology observations to delineate the species and growth stages that contributed the most to variation in the satellite observations. Finally, a statistical model of spring forest phenology was created using satellite observations of leaf area and land surface temperature (LST). After creating and validating the model, it was used with future projections of air temperature to predict how spring forest phenology may be influenced by future climate change.;A detailed study of the three aforementioned topics yielded findings that contribute to the existing literature. With regard to surface-atmosphere CO2 exchange during the spring, the findings indicate that spring forest phenology is responsible for a positive trend in CO 2 assimilation by the land surface and fluctuations in the amount of incident photosynthetically active radiation (PAR) are responsible for daily variability in CO2 assimilation. The results of investigating the second topic suggest that satellite measurements of the forest during the spring largely reflect the phenology of deciduous broadleaf species in the mixed forest. Lastly, the effort to create a forest phenology model using satellite-derived estimates of leaf area and LST was largely successful. The results convey that an asymmetric dose-response function predicts the spring growth of the canopy from the onset of growth to maturity with a high degree of accuracy. Using the model with future estimates of daily air temperature suggested that the spring onset of forest growth and the onset of maturity could potentially advance due to climate change by as much as 0.29 days per year and 0.28 days per year, respectively.