CAREER: Old plants show their true colors: Advancing herbarium-based spectral phenotyping to understand the evolution and distribution of plant function across scales

About This Grant

The tropics are home to immense plant diversity in varied habitats, from evergreen rainforests to savannas, deserts, and seasonally dry forests. Different traits enable plants to thrive in these contrasting habitats. Knowledge of these characteristics and how they came to be is essential for understanding plant diversification. However, measuring relevant traits for many different plants using traditional methods is slow and expensive. This research will develop new methods to measure plant traits on museum specimens using leaf spectra, which characterize the way different colors of light reflect off leaves. These methods will significantly speed up trait measurements at a global scale and revolutionize our ability to understand how traits and their combinations enable plants to live in different environments. The project will train the next generation of researchers in the cutting-edge and rapidly growing area of spectroscopy. Graduate and undergraduate students will gain research experience, new course materials will be developed, and workshops on spectral biology and herbaria will provide training to scientists. A partnership with the Master of Fine Arts program at the University of Maine will result in a public exhibit. The methods and software developed will build capacity for study of natural history collections. This research will explicitly assess the evolution of function associated with independent biome shifts in two widely distributed tropical plant lineages, the Brongniartieae (Fabaceae) and Bombacoideae (Malvaceae). The project will use multivariate phylogenetic comparative method approaches to test 1) if plants in different biomes occupy different functional hypervolumes, 2) if biome shifts lead to differences in evolutionary trait dynamics, such as shifts in rates of evolution, and 3) whether plant traits and combinations of traits evolve convergently in different biomes or if certain traits enable biome shifting in the first place. New, highly sampled time-calibrated phylogenies will be generated using phylogenomic data and Bayesian analyses. Functional data will be assessed from herbarium specimens using novel machine learning models for reliably phenotyping material using spectroscopy developed in this research. As part of methods development and assessment, trait, chemical, and spectral data for 200 species will tracked over time in a one-of-a-kind herborization experiment. These data will be used to parameterize Partial Least Squares Regression and Bayesian Model Averaging phenotyping models. This highly integrative project will advance understanding of the evolutionary dynamics underlying functional variation across space and environments, and transform our ability to collect functional data at large scales using herbarium specimens. This project is jointly funded by the Systematics and Biodiversity Science program and the Established Program to Stimulate Competitive Research (EPSCoR). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.