Macquarie University
Browse

Data from: How much of the world is woody?

dataset
posted on 2022-06-10, 03:10 authored by Richard G. FitzJohn, Matt W. Pennell, Amy E. Zanne, Peter F. Stevens, David C. Tank, William K. Cornwell, Matthew W. Pennell
1.The question posed by the title of this paper is a basic one, and it is surprising that the answer is not known. Recently assembled trait datasets provide an opportunity to address this, but scaling these datasets to the global scale is challenging because of sampling bias. Although we currently know the growth form of tens of thousands of species, these data are not a random sample of global diversity; some clades are exhaustively characterised, while others we know little–to–nothing about. 2.Starting with a database of woodiness for 39,313 species of vascular plants (12% of taxonomically resolved species, 59% of which were woody), we estimated the status of the remaining taxonomically resolved species by randomisation. To compare the results of our method to conventional wisdom, we informally surveyed a broad community of biologists. No consensus answer to the question existed, with estimates ranging from 1% to 90% (mean: 31.7%). 3.After accounting for sampling bias, we estimated the proportion of woodiness among the world's vascular plants to be between 45% and 48%. This was much lower than a simple mean of our dataset and much higher than the conventional wisdom. 4.Synthesis: Alongside an understanding of global taxonomic diversity (i.e., number of species globally), building a functional understanding of global diversity is an important emerging research direction. This approach represents a novel way to account for sampling bias in functional trait datasets and to answer basic questions about functional diversity at a global scale

Usage Notes

Results-woodinessAll results from the analyses conducted in the paper and results from our survey of researcherswood-supporting.tar.gz

History

FAIR Self Assessment Rating

  • Unassessed

Data Sensitivity

  • General

Source

Dryad

Usage metrics

    Macquarie University Research Data Repository

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC