Abstract
Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
Highlights
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants measurable at the individual plant level (Violle et al, 2007)—reflect the outcome of evolutionary and community assembly processes responding to abiotic and biotic environmental constraints (Valladares, Gianoli, & Gomez, 2007)
The TRY database provides an unprecedented number of consolidated plant trait data, which have become accessible at the TRY Data Portal under an open access data policy
The TRY database is well accepted by the scientific community and has facilitated progress in different aspects of research, for example in global vegetation modelling from static PFTs to a more continuous representation of biodiversity (e.g. Peaucelle, Bellassen, Ciais, Peñuelas, & Viovy, 2016; Sakschewski et al, 2015, 2016; Verheijen et al, 2013, 2015), extending macroecology and biodiversity by functional aspects (e.g. Bjorkman, Myers-Smith, Elmendorf, Normand, Rüger, et al, 2018; Bruelheide et al, 2018; Craven et al, 2018; Newbold et al, 2015), linking soil characteristics to vegetation attributes (e.g. Boeddinghaus et al, 2019; de Vries et al, 2012; Delgado-Baquerizo et al, 2018) and providing data for global maps of plant traits (e.g. Butler et al, 2017; Moreno-Martínez et al, 2018)
Summary
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants measurable at the individual plant level (Violle et al, 2007)—reflect the outcome of evolutionary and community assembly processes responding to abiotic and biotic environmental constraints (Valladares, Gianoli, & Gomez, 2007). During 12 years of development, versions 1–5 of the TRY database have been released with an increasing number of contributed data sets and trait records (Tables 1 and 2; Figure 1a). Coverage and availability of trait data in TRY stimulate trait-based research, which often leads to the identification of unexpected data gaps This motivates data mobilization and/or new measurements, which improve the availability of plant trait data for the research community, and—if contributed to TRY—help the database grow. Examples for such a ‘feed-forward data integration loop’ are provided in Box 1. We discuss ways forward and the potential future role of the TRY initiative for the research community
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