From the bottom of their roots to the tops of their canopies, forests provide benefits for all of Earth’s inhabitants including cultural and spiritual significance, economic opportunities, clean air and water, habitat for flora and fauna, and recreation and aesthetic values. Yet these important ecosystems are being lost at an alarming rate due to resource extraction and urbanization. With forests’ irreplaceable services to humans, flora, and fauna alike, and their central role in carbon mitigation strategies, forest loss could have severe impacts on Earth’s biodiversity and humanity. However, not all forests are the same. Instead, they consist of a diversity of species, ages, and structures which directly impact the processes that drive carbon sequestration. For example, light use efficiency, photosynthetic capacity, and trace gas exchange are affected by within-canopy radiation regimes and turbulence environments which are directly and indirectly regulated by the horizontal and vertical distribution of foliage within the canopy. Functional traits (e.g., leaf mass per area and foliar nitrogen content) and structural traits (e.g., leaf area density) drive these processes while showing significant variation between and within plant functional types and vertically through forest canopies. These plant functional types and forest traits also appear in different locations across the landscape due to soils, topography, climate, historic landscape conditions, and management activities which directly impacts forest biodiversity.To improve our estimates of processes related to carbon cycling and biodiversity, a better understanding of the three-dimensional variation of forest canopy traits is needed. Airborne remote sensing platforms that make use of hyperspectral and lidar data have recently been operationalized, which provide an opportunity to examine forest functional and structural traits across spatial extents not possible by field surveys alone. This dissertation utilizes these airborne platforms and explicit field testing to estimate three-dimensional forest traits across ecosystems while quantifying the effects of biodiversity, topography, and biogeography on the spatial variation and distribution of these traits.Chapter 1 introduces the concepts and questions raised in this dissertation. Chapter 2 addresses the impacts of spatial scale, pulse density, and canopy penetration on forest structure estimates from two airborne lidar systems, while offering solutions to enhance the accuracy of these estimates by standardizing spatial grains, limiting understory inflation, and utilizing Beer-Lambert coefficients. Chapter 3 assesses the influence of lidar derived forest structure, abiotic gradients, and management regions on the spatial patterns of remotely sensed top-of-canopy and total canopy nitrogen showing that total canopy estimates correspond to different ecological processes and exhibit unique spatial patterns than traditional top-of-canopy nitrogen estimates. Chapter 4 examines how taxonomic, functional, and phylogenetic diversity vary across eastern US forests, while assessing to what degree remotely sensed metrics are correlated with in situ biodiversity measures concluding that canopy structure is a critical predictor of forest biodiversity when combined with forest functional and topographic metrics. Chapter 5 summarizes the results and charts a path forward for research on forest structure, function, and diversity. Overall, this dissertation shows that it is critical to consider forest structural and functional traits together to accurately estimate the spatial distribution and variation of canopy processes and biodiversity, while helping to paint a clearer picture of how forests function in a time of rapid global change.
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