Format: ORAL

Paola G. Santacruz Endara1,2 ;Carlos Rodrigues-Vaz2 ; Denis Bastianelli3; Laurent Bonnal3; Roy R.H. Erkens4; José Eduardo Meireles5;Lily Bennett2;Thomas L.P. Couvreur 1,2

1Pontificia Universidad Católica del Ecuador, Quito. Apartado postal: 17012184 2 DIADE, Université de Montpellier, CIRAD, IRD, Montpellier, France 3 SELMET, Univ Montpellier, CIRAD, INRAE, Institut Agro, Montpellier, France 4 Maastricht Science Programme, Maastricht University, Maastricht, The Netherlands 5 University of Maine, School of Biology and Ecology. Maine, USA.

Leaf reflectance spectra estimated via near-infrared scanning (NIRs) are increasingly used to untangle the intricate complexity of plant diversity and evolution. The variation of these spectra across the tree of life and the impact of the evolution of leaf traits on spectral differentiation between species is still being explored. In this study, we used a framework that combines NIRs of herbarium dried leaves to infer the diversity and evolution of species specific spectra within the most diverse genus of Annonaceae in the Neotropics: Guatteria. We scanned herbarium preserved leaves of 148 out of the ca. 180 known Guatteria species. Spectra were cleaned, normalized, and analyzed using different multivariate approaches. We tested to see if these data could be used to identify species with similar spectra. We then analyzed this dataset within a comparative phylogenetic framework using a large robust species-level dated phylogeny of Guatteria. We tested for the phylogenetic signal of leaf spectra and inferred diversification rates across the evolution of this genus. We tested if changes in spectral diversity when present coincided with shifts in diversification rates within the genus. Our results shed light on the levels of constraint in the different spectral regions, reflecting the evolution of underlying Guatteria-specific leaf traits. Finally, our study underlines the importance of herbarium specimens to understand the evolution of diversity and leaf traits using innovative techniques such as NIRs.