Quantitative analysis of spore shapes improves identification of fungi

Abstract

Morphology of organisms is an important source of evidence for biodiversity assessment, taxonomic decisions, and understanding of evolution. Shape information about zoological and botanical objects is often treated quantitatively and in this form improves species identification. In studies of fungi, quantitative shape analysis was almost ignored. The disseminated propagules of fungi, the spores, are crucial for their taxonomy – currently in the form of linear measurements or subjectively defined shape categories. It remains unclear how much quantifying spore shape information can improve species identification. In this study, we tested the hypothesis that shape, as a richer source of information, overperforms size when performing automated identification of fungal species. We used the fungi of the genus Subulicystidium (Agaricomycetes, Basidiomycota) as a study object. We analysed 2D spore shape data via elliptic Fourier and Principal Component analyses. With flexible discriminant analysis, we achieved a slightly higher species identification success rate for shape predictors (61.5%) than for size predictors (59.1%). However, we achieved the highest rate for a combination of both (64.7%). We conclude that quantifying fungal spore shapes is worth the effort. We provide an open access protocol which, we hope, will stimulate a broader use of quantitative shape analysis in fungal taxonomy. We also discuss the challenges of such analyses that are specific to fungal spores.