Global root traits (GRooT) database

Nathaly R. Guerrero-Ramirez; Liesje Mommer; Gregoire T. Freschet; Colleen M. Iversen; M. Luke McCormack; Jens Kattge; Hendrik Poorter; Fons van Der Plas; Joana Bergmann; Thom W. Kuyper; Larry M. York; Helge Bruelheide; Daniel C. Laughlin; Ina C. Meier; Catherine Roumet; Marina Semchenko; Christopher J. Sweeney; Jasper van Ruijven; Oscar J. Valverde-Barrantes; Isabelle Aubin; Jane A. Catford; Peter Manning; Adam Martin; Rubén Milla; Vanessa Minden; Juli G. Pausas; Stuart W. Smith; Nadejda A. Soudzilovskaia; Christian Ammer; Bradley Butterfield; Joseph Craine; Johannes H. C. Cornelissen; Franciska T. de Vries; Marney E. Isaac; Koen Kramer; Christian Koenig; Eric G. Lamb; Vladimir G. Onipchenko; Josep Peñuelas; Peter B. Reich; Matthias C. Rillig; Lawren Sack; Bill Shipley; Leho Tedersoo; Fernando Valladares; Peter van Bodegom; Patrick Weigelt; Justin P. Wright; Alexandra Weigelt

doi:10.1111/geb.13179

Global root traits (GRooT) database

Nathaly R. Guerrero-Ramirez
, Liesje Mommer
, Gregoire T. Freschet
, Colleen M. Iversen
, M. Luke McCormack
, Jens Kattge
, Hendrik Poorter
, Fons van Der Plas
, Joana Bergmann
, Thom W. Kuyper
, Larry M. York
, Helge Bruelheide
, Daniel C. Laughlin
, Ina C. Meier
, Catherine Roumet
, Marina Semchenko
, Christopher J. Sweeney
, Jasper van Ruijven
, Oscar J. Valverde-Barrantes
, Isabelle Aubin

Jane A. Catford, Peter Manning, Adam Martin, Rubén Milla, Vanessa Minden, Juli G. Pausas, Stuart W. Smith, Nadejda A. Soudzilovskaia, Christian Ammer, Bradley Butterfield, Joseph Craine, Johannes H. C. Cornelissen, Franciska T. de Vries, Marney E. Isaac, Koen Kramer, Christian Koenig, Eric G. Lamb, Vladimir G. Onipchenko, Josep Peñuelas, Peter B. Reich, Matthias C. Rillig, Lawren Sack, Bill Shipley, Leho Tedersoo, Fernando Valladares, Peter van Bodegom, Patrick Weigelt, Justin P. Wright, Alexandra Weigelt

German Center for Integrative Biodiversity Research Halle-Jena-Leipzig
University of Göttingen
Wageningen University & Research
Université Paul Sabatier Toulouse III
Oak Ridge National Laboratory
Morton Arboretum
Jülich Research Centre
Max Planck Institute of Biochemistry
Leipzig University
Free University of Berlin
Berlin-Brandenburg Institute of Advanced Biodiversity Research
Noble Research Institute LLC
Martin Luther University Halle-Wittenberg
University of Wyoming
Université Paul-Valéry Montpellier III
University of Manchester
Florida International University
Canadian Forest Service
King's College London
Senckenberg Biodiversity and Climate Research Centre
University of Toronto
Universidad Rey Juan Carlos
University of Oldenburg
Vrije Universiteit Brussel
CSIC - Centro de Investigaciones sobre Desertificación (Spain)
Norwegian University of Science and Technology
Nanyang Technological University
Leiden University
Northern Arizona University
Jonah Ventures
Vrije Universiteit Amsterdam
University of Amsterdam
Humboldt University of Berlin
University of Saskatchewan
Lomonosov Moscow State University
Centre for Ecological Research and Forestry Applications
University of Minnesota
Western Sydney University
University of California at Los Angeles
Université de Sherbrooke
University of Tartu
National Museum of Natural Sciences
Duke University

Research output: Contribution to journal › Article › peer-review

Abstract

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.

Original language	English
Pages (from-to)	25-37
Journal	Global Ecology and Biogeography
Volume	30
Issue number	1
DOIs	https://doi.org/10.1111/geb.13179
Publication status	Published - 9 Sept 2020
Externally published	Yes

Keywords

Belowground ecology
Functional biogeography
Macroecological studies
Plant form and function
Publicly-available database
Root traits

Access to Document

10.1111/geb.13179Licence: CC BY

Cite this

Guerrero-Ramirez, N. R., Mommer, L., Freschet, G. T., Iversen, C. M., McCormack, M. L., Kattge, J., Poorter, H., van Der Plas, F., Bergmann, J., Kuyper, T. W., York, L. M., Bruelheide, H., Laughlin, D. C., Meier, I. C., Roumet, C., Semchenko, M., Sweeney, C. J., van Ruijven, J., Valverde-Barrantes, O. J., ... Weigelt, A. (2020). Global root traits (GRooT) database. Global Ecology and Biogeography, 30(1), 25-37. https://doi.org/10.1111/geb.13179

@article{f7270f8f72b54f5b81e89411674dd468,

title = "Global root traits (GRooT) database",

abstract = "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.",

keywords = "Belowground ecology, Functional biogeography, Macroecological studies, Plant form and function, Publicly-available database, Root traits",

author = "Guerrero-Ramirez, \{Nathaly R.\} and Liesje Mommer and Freschet, \{Gregoire T.\} and Iversen, \{Colleen M.\} and McCormack, \{M. Luke\} and Jens Kattge and Hendrik Poorter and \{van Der Plas\}, Fons and Joana Bergmann and Kuyper, \{Thom W.\} and York, \{Larry M.\} and Helge Bruelheide and Laughlin, \{Daniel C.\} and Meier, \{Ina C.\} and Catherine Roumet and Marina Semchenko and Sweeney, \{Christopher J.\} and \{van Ruijven\}, Jasper and Valverde-Barrantes, \{Oscar J.\} and Isabelle Aubin and Catford, \{Jane A.\} and Peter Manning and Adam Martin and Rub{\'e}n Milla and Vanessa Minden and Pausas, \{Juli G.\} and Smith, \{Stuart W.\} and Soudzilovskaia, \{Nadejda A.\} and Christian Ammer and Bradley Butterfield and Joseph Craine and Cornelissen, \{Johannes H. C.\} and \{de Vries\}, \{Franciska T.\} and Isaac, \{Marney E.\} and Koen Kramer and Christian Koenig and Lamb, \{Eric G.\} and Onipchenko, \{Vladimir G.\} and Josep Pe{\~n}uelas and Reich, \{Peter B.\} and Rillig, \{Matthias C.\} and Lawren Sack and Bill Shipley and Leho Tedersoo and Fernando Valladares and \{van Bodegom\}, Peter and Patrick Weigelt and Wright, \{Justin P.\} and Alexandra Weigelt",

year = "2020",

month = sep,

day = "9",

doi = "10.1111/geb.13179",

language = "English",

volume = "30",

pages = "25--37",

journal = "Global Ecology and Biogeography",

issn = "1466-822X",

number = "1",

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Guerrero-Ramirez, NR, Mommer, L, Freschet, GT, Iversen, CM, McCormack, ML, Kattge, J, Poorter, H, van Der Plas, F, Bergmann, J, Kuyper, TW, York, LM, Bruelheide, H, Laughlin, DC, Meier, IC, Roumet, C, Semchenko, M, Sweeney, CJ, van Ruijven, J, Valverde-Barrantes, OJ, Aubin, I, Catford, JA, Manning, P, Martin, A, Milla, R, Minden, V, Pausas, JG, Smith, SW, Soudzilovskaia, NA, Ammer, C, Butterfield, B, Craine, J, Cornelissen, JHC, de Vries, FT, Isaac, ME, Kramer, K, Koenig, C, Lamb, EG, Onipchenko, VG, Peñuelas, J, Reich, PB, Rillig, MC, Sack, L, Shipley, B, Tedersoo, L, Valladares, F, van Bodegom, P, Weigelt, P, Wright, JP & Weigelt, A 2020, 'Global root traits (GRooT) database', Global Ecology and Biogeography, vol. 30, no. 1, pp. 25-37. https://doi.org/10.1111/geb.13179

TY - JOUR

T1 - Global root traits (GRooT) database

AU - Guerrero-Ramirez, Nathaly R.

AU - Mommer, Liesje

AU - Freschet, Gregoire T.

AU - Iversen, Colleen M.

AU - McCormack, M. Luke

AU - Kattge, Jens

AU - Poorter, Hendrik

AU - van Der Plas, Fons

AU - Bergmann, Joana

AU - Kuyper, Thom W.

AU - York, Larry M.

AU - Bruelheide, Helge

AU - Laughlin, Daniel C.

AU - Meier, Ina C.

AU - Roumet, Catherine

AU - Semchenko, Marina

AU - Sweeney, Christopher J.

AU - van Ruijven, Jasper

AU - Valverde-Barrantes, Oscar J.

AU - Aubin, Isabelle

AU - Catford, Jane A.

AU - Manning, Peter

AU - Martin, Adam

AU - Milla, Rubén

AU - Minden, Vanessa

AU - Pausas, Juli G.

AU - Smith, Stuart W.

AU - Soudzilovskaia, Nadejda A.

AU - Ammer, Christian

AU - Butterfield, Bradley

AU - Craine, Joseph

AU - Cornelissen, Johannes H. C.

AU - de Vries, Franciska T.

AU - Isaac, Marney E.

AU - Kramer, Koen

AU - Koenig, Christian

AU - Lamb, Eric G.

AU - Onipchenko, Vladimir G.

AU - Peñuelas, Josep

AU - Reich, Peter B.

AU - Rillig, Matthias C.

AU - Sack, Lawren

AU - Shipley, Bill

AU - Tedersoo, Leho

AU - Valladares, Fernando

AU - van Bodegom, Peter

AU - Weigelt, Patrick

AU - Wright, Justin P.

AU - Weigelt, Alexandra

PY - 2020/9/9

Y1 - 2020/9/9

N2 - 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.

AB - 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.

KW - Belowground ecology

KW - Functional biogeography

KW - Macroecological studies

KW - Plant form and function

KW - Publicly-available database

KW - Root traits

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U2 - 10.1111/geb.13179

DO - 10.1111/geb.13179

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SN - 1466-822X

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JO - Global Ecology and Biogeography

JF - Global Ecology and Biogeography

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ER -

Global root traits (GRooT) database

Abstract

Keywords

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