The global spectrum of plant form and function: enhanced species-level trait dataset
CERABOLINI, Bruno
Universitá degli Studi dell’Insubria = University of Insubria [Varese] [Uninsubria]
Universitá degli Studi dell’Insubria = University of Insubria [Varese] [Uninsubria]
CASANOVES, Fernando
Centro Agronómico Tropical de Investigación y Enseñanza - Tropical Agricultural Research and Higher Education Center [CATIE]
Centro Agronómico Tropical de Investigación y Enseñanza - Tropical Agricultural Research and Higher Education Center [CATIE]
FOREY, Estelle
Département écologie et biodiversité des milieux forestiers, prairiaux et aquatiques [ECODIV]
< Réduire
Département écologie et biodiversité des milieux forestiers, prairiaux et aquatiques [ECODIV]
Langue
en
Article de revue
Ce document a été publié dans
Scientific Data. 2022-12-07, vol. 9, n° 1, p. 755
Nature Publishing Group
Résumé en anglais
Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per ...Lire la suite >
Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date.< Réduire
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