Bridging the gap between spectral and evolutionary biology

Abstract:

Spectral biology is revolutionizing how we assess plant biodiversity on Earth but it has yet to fully contribute to, and benefit from, the understanding of how biodiversity is generated by evolution. As a consequence, little is known about how genetic variability, selection, and convergence shape leaf spectra and how this, in turn, affects our ability to measure different dimensions of biodiversity. Here I will outline a modeling framework that bridges the gap between spectral and evolutionary biology by explicitly integrating spectroscopic models (empirical and radiative transfer models) with quantitative genetics and phylogenetic theory. I will then discuss empirical and simulation-based studies that explore different aspects of spectral evolution and biodiversity monitoring. First, I will demonstrate how to model the evolution of leaf spectra within species (i.e. at the population level) and between species, scaling up to the entire tree of life. I will show that these models can be used to 1) simulate leaf spectra under different evolutionary dynamics as well as to 2) fit empirical spectral data to draw inferences about leaf evolution. Second, I will outline how leaf spectra are affected by different microevolutionary parameters (such as population size, genetic variability, and heritability) and macroevolutionary processes (such as convergence and rapid radiations). Finally, I will illustrate how macroevolutionary processes, such as convergence and varying rates of evolution, affect the spectral diversity – biodiversity relationship and discuss its implications for biodiversity monitoring.