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

Rachael V. Gallagher; Daniel S. Falster; Brian S. Maitner; Roberto Salguero-Gómez; Vigdis Vandvik; William D. Pearse; Florian D. Schneider; Jens Kattge; Jorrit H. Poelen; Joshua S. Madin; Markus J. Ankenbrand; Caterina Penone; Xiao Feng; Vanessa M. Adams; John Alroy; Samuel C. Andrew; Meghan A. Balk; Lucie M. Bland; Brad L. Boyle; Catherine H. Bravo-Avila; Ian Brennan; Alexandra J.R. Carthey; Renee Catullo; Brittany R. Cavazos; Dalia A. Conde; Steven L. Chown; Belen Fadrique; Heloise Gibb; Aud H. Halbritter; Jennifer Hammock; J. Aaron Hogan; Hamish Holewa; Michael Hope; Colleen M. Iversen; Malte Jochum; Michael Kearney; Alexander Keller; Paula Mabee; Peter Manning; Luke McCormack; Sean T. Michaletz; Daniel S. Park; Timothy M. Perez; Silvia Pineda-Munoz; Courtenay A. Ray; Maurizio Rossetto; Hervé Sauquet; Benjamin Sparrow; Marko J. Spasojevic; Richard J. Telford; Joseph A. Tobias; Cyrille Violle; Ramona Walls; Katherine C.B. Weiss; Mark Westoby; Ian J. Wright; Brian J. Enquist

doi:10.1038/s41559-020-1109-6

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

Rachael V. Gallagher, Daniel S. Falster, Brian S. Maitner, Roberto Salguero-Gómez, Vigdis Vandvik, William D. Pearse, Florian D. Schneider, Jens Kattge, Jorrit H. Poelen, Joshua S. Madin, Markus J. Ankenbrand, Caterina Penone, Xiao Feng, Vanessa M. Adams, John Alroy, Samuel C. Andrew, Meghan A. Balk, Lucie M. Bland, Brad L. Boyle, Catherine H. Bravo-AvilaIan Brennan, Alexandra J.R. Carthey, Renee Catullo, Brittany R. Cavazos, Dalia A. Conde, Steven L. Chown, Belen Fadrique, Heloise Gibb, Aud H. Halbritter, Jennifer Hammock, J. Aaron Hogan, Hamish Holewa, Michael Hope, Colleen M. Iversen, Malte Jochum, Michael Kearney, Alexander Keller, Paula Mabee, Peter Manning, Luke McCormack, Sean T. Michaletz, Daniel S. Park, Timothy M. Perez, Silvia Pineda-Munoz, Courtenay A. Ray, Maurizio Rossetto, Hervé Sauquet, Benjamin Sparrow, Marko J. Spasojevic, Richard J. Telford, Joseph A. Tobias, Cyrille Violle, Ramona Walls, Katherine C.B. Weiss, Mark Westoby, Ian J. Wright, Brian J. Enquist

Ecosystem Processes

Research output: Contribution to journal › Review article › peer-review

133 Scopus citations

Abstract

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.

Original language	English
Pages (from-to)	294-303
Number of pages	10
Journal	Nature Ecology and Evolution
Volume	4
Issue number	3
DOIs	https://doi.org/10.1038/s41559-020-1109-6
State	Published - Mar 1 2020

Funding

Ideas presented stem from initial discussions at three international meetings—the Australian National Climate Change Adaptation Research Facility Roundtable on Species Traits, the iDigBio ALA Traits workshop, and the preliminary Open Traits workshop held at the Ecological Society of America. R.V.G. is supported by an Australian Research Council DECRA Fellowship (DE170100208). D.S.F. is supported by an Australian Research Council Future Fellowship (FT160100113). R.S.-G. is supported by NERC R/142195-11-1. W.D.P. is supported by NSF ABI-1759965, NSF EF-1802605, and USDA Forest Service agreement 18-CS-11046000-041. A.K. received financial support for M.J.A. by the German Research Foundation (DFG KE1743/7-1). C.M.I. was supported by the Biological and Environmental Research program in the United States Department of Energy’s Office of Science. C.P. is supported by the DFG Priority Program 1374. M.J. was supported by the German Research Foundation within the framework of the Jena Experiment (FOR 1451) and by the Swiss National Science Foundation. S.P.-M. was supported by the Benson Fund from the Department of Paleobiology, National Museum of Natural History. S.T.M. is supported by SERDP project RC18-1346. B.J.E. was supported by NSF Grants DEB0133974, HDR1934790 and EF1065844, a Leverhulme Trust Visiting Professorship Grant, and an Oxford Martin School Fellowship.

Funders	Funder number
United States Department of Energy
National Science Foundation	ABI-1759965, EF-1802605
National Science Foundation
Office of Science	FOR 1451
Office of Science
Biological and Environmental Research
National Museum of Natural History
U.S. Forest Service	18-CS-11046000-041
U.S. Forest Service
National Climate Change Adaptation Research Facility
Strategic Environmental Research and Development Program	DEB0133974, RC18-1346, EF1065844, HDR1934790
Strategic Environmental Research and Development Program
Natural Environment Research Council	R/142195-11-1
Natural Environment Research Council
Leverhulme Trust
Australian Research Council	FT160100113, DE170100208
Australian Research Council
Deutsche Forschungsgemeinschaft	DFG KE1743/7-1
Deutsche Forschungsgemeinschaft
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
Oxford Martin School, University of Oxford

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Gallagher, R. V., Falster, D. S., Maitner, B. S., Salguero-Gómez, R., Vandvik, V., Pearse, W. D., Schneider, F. D., Kattge, J., Poelen, J. H., Madin, J. S., Ankenbrand, M. J., Penone, C., Feng, X., Adams, V. M., Alroy, J., Andrew, S. C., Balk, M. A., Bland, L. M., Boyle, B. L., ... Enquist, B. J. (2020). Open Science principles for accelerating trait-based science across the Tree of Life. Nature Ecology and Evolution, 4(3), 294-303. https://doi.org/10.1038/s41559-020-1109-6

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title = "Open Science principles for accelerating trait-based science across the Tree of Life",

abstract = "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.",

author = "Gallagher, {Rachael V.} and Falster, {Daniel S.} and Maitner, {Brian S.} and Roberto Salguero-G{\'o}mez and Vigdis Vandvik and Pearse, {William D.} and Schneider, {Florian D.} and Jens Kattge and Poelen, {Jorrit H.} and Madin, {Joshua S.} and Ankenbrand, {Markus J.} and Caterina Penone and Xiao Feng and Adams, {Vanessa M.} and John Alroy and Andrew, {Samuel C.} and Balk, {Meghan A.} and Bland, {Lucie M.} and Boyle, {Brad L.} and Bravo-Avila, {Catherine H.} and Ian Brennan and Carthey, {Alexandra J.R.} and Renee Catullo and Cavazos, {Brittany R.} and Conde, {Dalia A.} and Chown, {Steven L.} and Belen Fadrique and Heloise Gibb and Halbritter, {Aud H.} and Jennifer Hammock and Hogan, {J. Aaron} and Hamish Holewa and Michael Hope and Iversen, {Colleen M.} and Malte Jochum and Michael Kearney and Alexander Keller and Paula Mabee and Peter Manning and Luke McCormack and Michaletz, {Sean T.} and Park, {Daniel S.} and Perez, {Timothy M.} and Silvia Pineda-Munoz and Ray, {Courtenay A.} and Maurizio Rossetto and Herv{\'e} Sauquet and Benjamin Sparrow and Spasojevic, {Marko J.} and Telford, {Richard J.} and Tobias, {Joseph A.} and Cyrille Violle and Ramona Walls and Weiss, {Katherine C.B.} and Mark Westoby and Wright, {Ian J.} and Enquist, {Brian J.}",

note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Limited.",

year = "2020",

month = mar,

day = "1",

doi = "10.1038/s41559-020-1109-6",

language = "English",

volume = "4",

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Gallagher, RV, Falster, DS, Maitner, BS, Salguero-Gómez, R, Vandvik, V, Pearse, WD, Schneider, FD, Kattge, J, Poelen, JH, Madin, JS, Ankenbrand, MJ, Penone, C, Feng, X, Adams, VM, Alroy, J, Andrew, SC, Balk, MA, Bland, LM, Boyle, BL, Bravo-Avila, CH, Brennan, I, Carthey, AJR, Catullo, R, Cavazos, BR, Conde, DA, Chown, SL, Fadrique, B, Gibb, H, Halbritter, AH, Hammock, J, Hogan, JA, Holewa, H, Hope, M, Iversen, CM, Jochum, M, Kearney, M, Keller, A, Mabee, P, Manning, P, McCormack, L, Michaletz, ST, Park, DS, Perez, TM, Pineda-Munoz, S, Ray, CA, Rossetto, M, Sauquet, H, Sparrow, B, Spasojevic, MJ, Telford, RJ, Tobias, JA, Violle, C, Walls, R, Weiss, KCB, Westoby, M, Wright, IJ & Enquist, BJ 2020, 'Open Science principles for accelerating trait-based science across the Tree of Life', Nature Ecology and Evolution, vol. 4, no. 3, pp. 294-303. https://doi.org/10.1038/s41559-020-1109-6

TY - JOUR

T1 - Open Science principles for accelerating trait-based science across the Tree of Life

AU - Gallagher, Rachael V.

AU - Falster, Daniel S.

AU - Maitner, Brian S.

AU - Salguero-Gómez, Roberto

AU - Vandvik, Vigdis

AU - Pearse, William D.

AU - Schneider, Florian D.

AU - Kattge, Jens

AU - Poelen, Jorrit H.

AU - Madin, Joshua S.

AU - Ankenbrand, Markus J.

AU - Penone, Caterina

AU - Feng, Xiao

AU - Adams, Vanessa M.

AU - Alroy, John

AU - Andrew, Samuel C.

AU - Balk, Meghan A.

AU - Bland, Lucie M.

AU - Boyle, Brad L.

AU - Bravo-Avila, Catherine H.

AU - Brennan, Ian

AU - Carthey, Alexandra J.R.

AU - Catullo, Renee

AU - Cavazos, Brittany R.

AU - Conde, Dalia A.

AU - Chown, Steven L.

AU - Fadrique, Belen

AU - Gibb, Heloise

AU - Halbritter, Aud H.

AU - Hammock, Jennifer

AU - Hogan, J. Aaron

AU - Holewa, Hamish

AU - Hope, Michael

AU - Iversen, Colleen M.

AU - Jochum, Malte

AU - Kearney, Michael

AU - Keller, Alexander

AU - Mabee, Paula

AU - Manning, Peter

AU - McCormack, Luke

AU - Michaletz, Sean T.

AU - Park, Daniel S.

AU - Perez, Timothy M.

AU - Pineda-Munoz, Silvia

AU - Ray, Courtenay A.

AU - Rossetto, Maurizio

AU - Sauquet, Hervé

AU - Sparrow, Benjamin

AU - Spasojevic, Marko J.

AU - Telford, Richard J.

AU - Tobias, Joseph A.

AU - Violle, Cyrille

AU - Walls, Ramona

AU - Weiss, Katherine C.B.

AU - Westoby, Mark

AU - Wright, Ian J.

AU - Enquist, Brian J.

PY - 2020/3/1

Y1 - 2020/3/1

N2 - 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.

AB - 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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U2 - 10.1038/s41559-020-1109-6

DO - 10.1038/s41559-020-1109-6

M3 - Review article

C2 - 32066887

AN - SCOPUS:85079725318

SN - 2397-334X

VL - 4

SP - 294

EP - 303

JO - Nature Ecology and Evolution

JF - Nature Ecology and Evolution

IS - 3

ER -

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

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