Leaf-level functional traits important to photosynthetic carbon (C) assimilation vary widely across biomes, between plant functional types, and coinciding with vertical structural variation in the canopy, which necessitates the use of tools capable of mapping this diversity over large scales. Advances in the spectral and spatial resolution in multi- and hyperspectral imagery (HSI) over the past three decades have allowed for increasingly fine resolution mapping of top-of-canopy (TOC) functional traits at the landscape scale from airborne spectrometers (Wang et al. 2020), while lidar data have been shown to effectively quantify structural attributes of forest canopies important to C assimilation (Dahlin et al. 2013; Asner 2015; Kamoske et al. 2019). However, these datasets are seldom spatiotemporally contiguous, thus limited studies have combined these datasets to capture a complete picture of canopy functional diversity. Here, I integrate field and remote sensing data from a mixed deciduous forest in Virginia, USA, to generate estimates of TOC percent and total-canopy (g/mGround2) nitrogen content before comparing the spatial patterns and drivers of these two metrics. Conversely to trends in TOC percent N, we found that evergreen needleleaf canopies had on average higher total nitrogen (gN/m2) and foliar biomass (gLeaf/m2) than broadleaf deciduous canopies. Upon a closer analysis of the spatial trends and environmental drivers of TOC percent and total N between these plant functional types, we found that the change in plant health (i.e., NDVI) during an outbreak of the spring cankerworm (Palecrita vernata) was a strong predictor of total canopy N, suggesting this disturbance perturbs a complete understanding of whole-canopy function in this system. Overall, this thesis highlights the importance of local and regional-scale ecological understanding of plant form and function, as my results reinforce similar studies (e.g., Kamoske et al. 2021) but contradict long held views of differences in productivity between plant functional types.
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