A global growth-form database for 143,616 vascular plant species.

Abstract

For the majority of plant species in the world, we know little about their functional ecology, and not even one of the most basic traits-the species' growth habit. To fill the gap in availability of compiled plant growth-form data, we have assembled what is, to our knowledge, the largest global database on growth-form as a plant trait. We have, with extensive error checking and data synthesis, assembled a growth-form database from 163 data sources for 143,616 vascular plant species from 445 different plant families. This is 38.6% of the currently accepted vascular plant diversity. For our database, we have chosen seven categories to cover the majority of the diversity in plant growth forms: aquatic plants, epiphytes, hemiepiphytes, climbing plants, parasitic plants, holo-mycoheterotrophs, and freestanding plants. These categories were used because we were able to reconcile the wealth of existing definitions and types of growth-form information available globally to them clearly and unequivocally, and because they are complementary with existing databases. Plants in the database were designated into a category if their adult growth form fit the criterion. We make available two databases: first, the complete data set, including species for which there is currently conflicting information, and second, a consensus data set, where all available information supports one categorization. Of the plant species for which we found information, 103,138 (72%) are freestanding, 21,110 (15%) are epiphytes, and 4,046 (3%) are parasites. Our growth-form data can be used to produce useful summary statistics by clade. For example, current data suggests that half of pteridophytes are epiphytic, that all hemiepiphytes are eudicots, and that there are no parasitic monocots, gymnosperms, or pteridophytes. Growth form is a crucial piece of fundamental plant-trait data with implications for each species' ecology, evolution, and conservation, and thus this data set will be useful for a range of basic and applied questions across these areas of research. No copyright or proprietary restrictions are associated with the use of this data set, other than citation of the present Data Paper. A static version of this dataset is provided as Supporting Information, and a living and updating version of the dataset is available in a GitHub repository.