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Global root traits (GRooT) database
Author(s) -
GuerreroRamírez Nathaly R.,
Mommer Liesje,
Freschet Grégoire T.,
Iversen Colleen M.,
McCormack M. Luke,
Kattge Jens,
Poorter Hendrik,
Plas Fons,
Bergmann Joana,
Kuyper Thom W.,
York Larry M.,
Bruelheide Helge,
Laughlin Daniel C.,
Meier Ina C.,
Roumet Catherine,
Semchenko Marina,
Sweeney Christopher J.,
Ruijven Jasper,
ValverdeBarrantes Oscar J.,
Aubin Isabelle,
Catford Jane A.,
Manning Peter,
Martin Adam,
Milla Rubén,
Minden Vanessa,
Pausas Juli G.,
Smith Stuart W.,
Soudzilovskaia Nadejda A.,
Ammer Christian,
Butterfield Bradley,
Craine Joseph,
Cornelissen Johannes H. C.,
Vries Franciska T.,
Isaac Marney E.,
Kramer Koen,
König Christian,
Lamb Eric G.,
Onipchenko Vladimir G.,
Peñuelas Josep,
Reich Peter B.,
Rillig Matthias C.,
Sack Lawren,
Shipley Bill,
Tedersoo Leho,
Valladares Fernando,
Bodegom Peter,
Weigelt Patrick,
Wright Justin P.,
Weigelt Alexandra
Publication year - 2021
Publication title -
global ecology and biogeography
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.164
H-Index - 152
eISSN - 1466-8238
pISSN - 1466-822X
DOI - 10.1111/geb.13179
Subject(s) - trait , biome , root (linguistics) , biology , subspecies , database , ecology , ecosystem , computer science , linguistics , philosophy , programming language
Motivation Trait data are fundamental to the quantitative description of plant form and function. Although root traits capture key dimensions related to plant responses to changing environmental conditions and effects on ecosystem processes, they have rarely been included in large‐scale comparative studies and global models. For instance, root traits remain absent from nearly all studies that define the global spectrum of plant form and function. Thus, to overcome conceptual and methodological roadblocks preventing a widespread integration of root trait data into large‐scale analyses we created the Global Root Trait (GRooT) Database. GRooT provides ready‐to‐use data by combining the expertise of root ecologists with data mobilization and curation. Specifically, we (a) determined a set of core root traits relevant to the description of plant form and function based on an assessment by experts, (b) maximized species coverage through data standardization within and among traits, and (c) implemented data quality checks. Main types of variables contained GRooT contains 114,222 trait records on 38 continuous root traits. Spatial location and grain Global coverage with data from arid, continental, polar, temperate and tropical biomes. Data on root traits were derived from experimental studies and field studies. Time period and grain Data were recorded between 1911 and 2019. Major taxa and level of measurement GRooT includes root trait data for which taxonomic information is available. Trait records vary in their taxonomic resolution, with subspecies or varieties being the highest and genera the lowest taxonomic resolution available. It contains information for 184 subspecies or varieties, 6,214 species, 1,967 genera and 254 families. Owing to variation in data sources, trait records in the database include both individual observations and mean values. Software format GRooT includes two csv files. A GitHub repository contains the csv files and a script in R to query the database.