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TRY plant trait database – enhanced coverage and open access

Nutrient Network; Kattge, Jens; Bönisch, Gerhard; Díaz, Sandra; Lavorel, Sandra; Prentice, Iain Colin; Leadley, Paul; Tautenhahn, Susanne; Werner, Gijsbert D. A.; Aakala, Tuomas; Abedi, Mehdi; Acosta, Alicia T. R.; Adamidis, George C.; Adamson, Kairi; Aiba, Masahiro; Albert, Cécile H.; Alcántara, Julio M.; Alcázar C, Carolina; Aleixo, Izabela; ... mehr

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’. ... mehr


Verlagsausgabe §
DOI: 10.5445/IR/1000104735
Veröffentlicht am 10.01.2020
Originalveröffentlichung
DOI: 10.1111/gcb.14904
Scopus
Zitationen: 1170
Web of Science
Zitationen: 1037
Dimensions
Zitationen: 1332
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Geographie und Geoökologie (IFGG)
KIT-Zentrum Klima und Umwelt (ZKU)
Publikationstyp Zeitschriftenaufsatz
Publikationsmonat/-jahr 01.2020
Sprache Englisch
Identifikator ISSN: 1354-1013, 1365-2486
KITopen-ID: 1000104735
Erschienen in Global change biology
Verlag John Wiley and Sons
Band 26
Heft 1
Seiten 119–188
Vorab online veröffentlicht am 31.12.2019
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