Article Dans Une Revue Nature Ecology & Evolution Année : 2020

Open Science principles for accelerating trait-based science across the Tree of Life

1 Macquarie University [Sydney]
2 UNSW - University of New South Wales [Sydney]
3 University of Arizona
4 University of Oxford
5 UQ [All campuses : Brisbane, Dutton Park Gatton, Herston, St Lucia and other locations] - The University of Queensland
6 MPIDR - Max Planck Institute for Demographic Research
7 UiB - University of Bergen
8 BCCR - Bjerknes Centre for Climate Research
9 USU - Utah State University
10 Auteur indépendant
11 MPI-BGC - Max Planck Institute for Biogeochemistry
12 iDiv - German Centre for Integrative Biodiversity Research
13 HIMB - Hawaii Institute of Marine Biology
14 Biocenter University of Würzburg = Biozentrum der Universität Würzburg
15 University Hospital of Würzburg
16 Institute of Plant Sciences
17 UTAS - University of Tasmania [Hobart]
18 CSIRO - Commonwealth Scientific and Industrial Research Organisation [Australia]
19 BIO5 Institute
20 Deakin University [Burwood]
21 University of Miami
22 ANU - Australian National University
23 ISU - Iowa State University
24 SDU - University of Southern Denmark
25 Monash University [Melbourne]
26 La Trobe University
27 National Museum of Natural History [Washington]
28 FIU - Florida International University [Miami]
29 ORNL - Oak Ridge National Laboratory [Oak Ridge]
30 Institute of Biology [Leipzig]
31 University of Melbourne
32 USD - University of South Dakota [Vermillion]
33 SBiK-F - Senckenberg Biodiversity and Climate Research Centre
34 The Morton Arboretum
35 UBC - University of British Columbia [Canada]
36 Harvard University
37 Georgia Institute of Technology [Atlanta]
38 ASU - Arizona State University [Tempe]
39 Royal Botanic Gardens [Kew]
40 ESE - Ecologie Systématique et Evolution
41 University of Adelaide
42 UC Riverside - University of California [Riverside]
43 Imperial College London
44 CEFE - Centre d’Ecologie Fonctionnelle et Evolutive
Daniel Falster
Brian Maitner
William Pearse
Florian D Schneider
Jorrit Poelen
Joshua Madin
Caterina Penone
Xiao Feng
Vanessa Adams
John Alroy
Meghan Balk
  • Fonction : Auteur
Brad Boyle
  • Fonction : Auteur
Catherine Bravo-Avila
Ian Brennan
Alexandra Carthey
Dalia Conde
Steven Chown
Heloise Gibb
  • Fonction : Auteur
Sean Michaletz
Daniel Park
Joseph Tobias
Katherine Weiss
Mark Westoby
Ian Wright
Brian Enquist

Résumé

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles—open data, open source and open methods—is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.
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hal-04391250 , version 1 (10-12-2024)

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Rachael Gallagher, Daniel Falster, Brian Maitner, Roberto Salguero-Gómez, Vigdis Vandvik, et al.. Open Science principles for accelerating trait-based science across the Tree of Life. Nature Ecology & Evolution, 2020, 4 (3), pp.294-303. ⟨10.1038/s41559-020-1109-6⟩. ⟨hal-04391250⟩
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