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Ten (mostly) simple rules to future-proof trait data in ecological and evolutionary sciences

delete2022-11-22
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OA
AI
A
Alexander Keller *
M
Markus J. Ankenbrand
H
Helge Bruelheide
S
Stefanie Dekeyzer
B
Brian J. Enquist
M
Mohammad Bagher Erfanian
D
Daniel S. Falster
R
Rachael V. Gallagher
J
Jennifer Hammock
J
Jens Kattge
S
Sara D. Leonhardt
J
Joshua S. Madin
B
Brian Maitner
M
Margot Neyret
R
Renske E. Onstein
W
William D. Pearse
J
Jorrit H. Poelen
R
Roberto Salguero‐Gómez
F
Florian D. Schneider
A
Anikó B. Tóth
C
Caterina Penone *
DOI:10.1111/2041-210X.14033delete
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Abstract

Abstract

En 中文
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 .
Keywords:
data life cycle
data science
FAIR principles
good practices
metadata
open science
phenotype
trait data
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Methods in Ecology and Evolution cover
Methods in Ecology and Evolution
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