The Spectral Ecology of a Highly Polymorphic Tree Species

Remote sensing, with its capacity to capture continuous, high spatial and spectral resolution data, has emerged as an invaluable tool for ecological research and addressing conservation challenges. To fully harness the potential of remote sensing, spectral ecology has emerged as a field that investigates the interactions between the electromagnetic spectrum and biological processes. This dissertation capitalizes on a model system to explore the spectral ecology of a dominant, highly polymorphic, keystone, and endemic tree species (Metrosideros polymorpha). M. polymorpha not only serves as a model organism for studying adaptive radiation and intraspecific variation but also presents a critical conservation challenge. The recent introduction of the fungal disease Ceratocystis lukuohia has resulted in millions of M. polymorpha mortalities. This dissertation employs leaf-level spectroscopy data and canopy-level imaging spectroscopy data. Imaging spectroscopy captures reflectance across the visible to short-wave infrared (VSWIR) spectrum to provide high-spectral resolution data that enable canopy trait retrievals, species classifications, disease resistance detection, and genotype differentiation. Chapter 1 serves as an introduction, framing the subsequent chapters by presenting an overview of spectral ecology, imaging spectroscopy, and M. polymorpha. Chapter 2 explores M. polymorpha trait and spectra variation across environmental gradients. This chapter concludes that intraspecific variation follows the leaf economic spectrum and that elevation is a dominant driver of M. polymorpha trait and spectral variation. In Chapter 3, leaf-level spectroscopy was able to discriminate between sympatric, conspecific varieties of M. polymorpha and their hybrids as well as individuals resistant and susceptible to Ceratocystis wilt. Together, Chapters 2 and 3 support the concept of “genetic turnover,” akin to species turnover, wherein environmental conditions filter M. polymorpha genotypes present in a given region. Chapter 4 classifies M. polymorpha across the over 10,000 km2 of Hawai'i Island to aid in conservation efforts, demonstrating the potential of imaging spectroscopy to classify vegetation on large geographic scales. The final chapter builds on the prior chapters to present a M. polymorpha genetic diversity map for Hawai'i Island. In conclusion, this dissertation examines the spectral ecology of a model system to advance the understanding of ecological dynamics and address a pressing conservation challenge.