TRY plant trait database – enhanced coverage and open access
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Machine scores (provisional)
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
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- Teacher spread
- 0.208 · how far apart the two teachers sit on this one work
- Validation status
score_only:v0-immature-baseline· verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it
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.
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The record
- Venue
- Global Change Biology
- Topic
- Banana Cultivation and Research
- Field
- Agricultural and Biological Sciences
- Canadian institutions
- University of WinnipegUniversity of CalgaryUniversity of ReginaMcGill UniversityLakehead UniversityUniversité du Québec en Abitibi-TémiscamingueMinistry of ForestsUniversity of TorontoUniversité du Québec à MontréalUniversité de SherbrookeAlgoma UniversityUniversité du Québec en OutaouaisCentre de Géomatique du QuébecUniversité du Québec à Trois-RivièresNatural Sciences and Engineering Research Council of CanadaMinistry of Natural Resources and ForestryUniversity of WaterlooWilfrid Laurier UniversityUniversité LavalUniversity of GuelphNatural Resources CanadaUniversité de MontréalUniversity of SaskatchewanCanadian Forest ServiceUniversity of VictoriaUniversity of British ColumbiaThe Scarborough Hospital
- Funders
- Biological and Environmental ResearchScience and Technology Facilities CouncilOffice of ScienceDeutsches Zentrum für integrative Biodiversitätsforschung Halle-Jena-LeipzigMax-Planck-GesellschaftSight Research UKNederlandse Organisatie voor Wetenschappelijk OnderzoekFondation pour la Recherche sur la BiodiversiteAXA Research FundNatural Environment Research CouncilU.S. Department of Energy
- Keywords
- TraitDatabaseComputer scienceProgramming language
- Has abstract in OpenAlex
- yes