Skip to main content
Seeing herbaria in a new light: leaf reflectance spectroscopy unlocks predictive trait and classification modeling in plant biodiversity collections

Seeing herbaria in a new light: leaf reflectance spectroscopy unlocks predictive trait and classification modeling in plant biodiversity collections

This is a Preprint and has not been peer reviewed. This is version 2 of this Preprint.

Add a Comment

You must log in to post a comment.


Comments

There are no comments or no comments have been made public for this article.

Downloads

Download Preprint

Supplementary Files

Authors

Dawson M White , Jeannine Cavender-Bares , Charles Davis , J. Antonio Guzmán Q., Shan Kothari, Jorge Robles, Jose Eduardo Meireles

Abstract

Reflectance spectroscopy is a rapid method for estimating traits and discriminating species. Spectral libraries from herbarium specimens represent an untapped resource for generating broad phenomic datasets across space, time, and taxa. We conducted a proof-of-concept study using trait data and spectra from herbarium specimens up to 179 years old alongside data from recently dried, pressed leaves. We validated model accuracy and transferability for trait prediction and taxonomic discrimination. Trait models from herbarium spectra predicted leaf mass per area (LMA) with R2 = 0.94 and %RMSE = 4.86%, and discriminated 25 species with 74% accuracy. Models for LMA prediction were transferable between herbarium and pressed spectra, achieving R2 = 0.88, %RMSE = 8.76% for herbarium to pressed spectra, and R2 = 0.76, %RMSE = 10.5% for the reverse transfer. We also found correlations among classification probabilities with several herbarium specimen quality predictor variables. The results validate herbarium spectral data for trait prediction and taxonomic discrimination, and demonstrate trait modeling can benefit from the complementary use of pressed-leaf and herbarium-leaf spectral datasets. These promising methodological advancements help to justify the spectral digitization of plant biodiversity collections and support their application in broad ecological and evolutionary investigations.

DOI

https://doi.org/10.32942/X29P8B

Subjects

Biodiversity, Bioinformatics, Botany, Ecology and Evolutionary Biology, Integrative Biology, Life Sciences

Keywords

Herbarium spectroscopy, Biodiversity Digitization, Leaf functional traits, Extended specimen, Plant Phenomics, plant diversity, taxonomy

Dates

Published: 2025-02-10 20:34

Last Updated: 2025-05-17 01:12

Older Versions

License

CC BY Attribution 4.0 International

Additional Metadata

Conflict of interest statement:
None

Data and Code Availability Statement:
All analysis codes used in this study are publicly available at GitHub (github.org/Erythroxylum/herbarium-spectra).

Language:
English