Socioeconomics and biogeography jointly drive geographic biases in our knowledge of plant traits: a global assessment of the Raunkiærian shortfall in plants

Abstract

SummaryThe traits of plants determine how they interact with each other and their environment, constituting key knowledge for diverse fields. The lack of comprehensive knowledge of plant traits (the “Raunkiærian shortfall”) poses a major, cross-disciplinary, barrier to scientific advancement. Spatial biases in trait coverage may also lead to erroneous conclusions affecting ecosystem management and conservation planning. Thus, there is an urgent need to assess the spatial completeness of plant trait data, understand drivers of geographic biases, and to identify solutions for filling regional gaps. Here, we leverage a comprehensive set of regional species checklists for vascular plants and trait data for 2,027 traits and 128,929 plant species from the TRY database to assess trait data completeness across the globe. We show that trait data availability in TRY is associated with socioeconomic and biological factors influencing sampling likelihood: trait completeness was positively associated with mean species range size, research expenditure, and human population density and negatively associated with endemism and vascular plant species richness. Integration of a second, regional trait database (AusTraits) more than doubled trait completeness for the continent covered, indicating that the creation and integration of regional databases can rapidly expand trait completeness.Plain Language SummaryThe traits of plants determine how they interact with each other and their environment. Our knowledge of plant traits is incomplete, limiting scientific advancement as well as our ability to manage ecosystems and plan conservation actions. We show that there are large biases in trait data availability which are associated with both biological factors (range size, endemism, species richness) and socioeconomic factors (research expenditure, human population density). We also show how regionally-focused efforts can help rapidly expand trait data availability.