Trait-climate relationships within and among taxa using machine learning and herbarium specimens.

CNNs detected and measured leaves with levels of accuracy useful for trait extraction and analysis and illustrate the potential for machine learning of herbarium specimens to massively increase global leaf trait datasets. Within species relationships were weak, suggesting population history and gene flow have a strong effect at this level. Herbarium specimens and machine learning could expand sampling of trait data within many species, offering new insights into trait evolution. This article is protected by copyright. All rights reserved.