TY - JOUR
T1 - Ten (mostly) simple rules to future-proof trait data in ecological and evolutionary sciences
AU - Keller, Alexander
AU - Ankenbrand, Markus J.
AU - Bruelheide, Helge
AU - Dekeyzer, Stefanie
AU - Enquist, Brian J.
AU - Erfanian, Mohammad Bagher
AU - Falster, Daniel S.
AU - Gallagher, Rachael V.
AU - Hammock, Jennifer
AU - Kattge, Jens
AU - Leonhardt, Sara D.
AU - Madin, Joshua S.
AU - Maitner, Brian
AU - Neyret, Margot
AU - Onstein, Renske E.
AU - Pearse, William D.
AU - Poelen, Jorrit H.
AU - Salguero-Gomez, Roberto
AU - Schneider, Florian D.
AU - Tóth, Anikó B.
AU - Penone, Caterina
N1 - Funding Information:
The manuscript was drafted during a workshop by participants of the sDiv working group sDevTrait hosted by the German Centre for Integrative Biodiversity Research (iDiv; DFG FZT 118). We appreciate funding (grant number W7.15 to AK and MA) and support before, during and after the workshop by the iDiv, particularly staff members Marten Winter, Carolin Kögler and Doreen Brückner. SD acknowledges additional support from LifeWatch Belgium. Funding to keep the World Register of Marine Species (WoRMS) is currently provided through the LifeWatch Belgium project. WoRMS constitutes a major contribution to the LifeWatch Species Information Backbone. CP acknowledges support from the DFG Priority Program 1374 ‘Biodiversity‐ Exploratories’ (DFG‐193921238). Open Access funding enabled and organized by Projekt DEAL.
Publisher Copyright:
© 2022 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.
PY - 2023/2
Y1 - 2023/2
N2 - Traits have become a crucial part of ecological and evolutionary sciences, helping researchers understand the function of an organism's morphology, physiology, growth and life history, with effects on fitness, behaviour, interactions with the environment and ecosystem processes. However, measuring, compiling and analysing trait data comes with data-scientific challenges. We offer 10 (mostly) simple rules, with some detailed extensions, as a guide in making critical decisions that consider the entire life cycle of trait data. This article is particularly motivated by its last rule, that is, to propagate good practice. It has the intention of bringing awareness of how data on the traits of organisms can be collected and managed for reuse by the research community. Trait observations are relevant to a broad interdisciplinary community of field biologists, synthesis ecologists, evolutionary biologists, computer scientists and database managers. We hope these basic guidelines can be useful as a starter for active communication in disseminating such integrative knowledge and in how to make trait data future-proof. We invite the scientific community to participate in this effort at http://opentraits.org/best-practices.html.
AB - Traits have become a crucial part of ecological and evolutionary sciences, helping researchers understand the function of an organism's morphology, physiology, growth and life history, with effects on fitness, behaviour, interactions with the environment and ecosystem processes. However, measuring, compiling and analysing trait data comes with data-scientific challenges. We offer 10 (mostly) simple rules, with some detailed extensions, as a guide in making critical decisions that consider the entire life cycle of trait data. This article is particularly motivated by its last rule, that is, to propagate good practice. It has the intention of bringing awareness of how data on the traits of organisms can be collected and managed for reuse by the research community. Trait observations are relevant to a broad interdisciplinary community of field biologists, synthesis ecologists, evolutionary biologists, computer scientists and database managers. We hope these basic guidelines can be useful as a starter for active communication in disseminating such integrative knowledge and in how to make trait data future-proof. We invite the scientific community to participate in this effort at http://opentraits.org/best-practices.html.
KW - FAIR principles
KW - data life cycle
KW - data science
KW - good practices
KW - metadata
KW - open science
KW - phenotype
KW - trait data
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U2 - 10.1111/2041-210X.14033
DO - 10.1111/2041-210X.14033
M3 - Review article
AN - SCOPUS:85142620212
SN - 2041-210X
VL - 14
SP - 444
EP - 458
JO - Methods in Ecology and Evolution
JF - Methods in Ecology and Evolution
IS - 2
ER -