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

Alexander Keller, Markus J. Ankenbrand, Helge Bruelheide, Stefanie Dekeyzer, Brian J. Enquist, Mohammad Bagher Erfanian, Daniel S. Falster, Rachael V. Gallagher, Jennifer Hammock, Jens Kattge, Sara D. Leonhardt, Joshua S. Madin, Brian Maitner, Margot Neyret, Renske E. Onstein, William D. Pearse, Jorrit H. Poelen, Roberto Salguero-Gomez, Florian D. Schneider, Anikó B. TóthCaterina Penone

Research output: Contribution to journalReview articlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)444-458
Number of pages15
JournalMethods in Ecology and Evolution
Issue number2
StatePublished - Feb 2023


  • FAIR principles
  • data life cycle
  • data science
  • good practices
  • metadata
  • open science
  • phenotype
  • trait data

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Ecological Modeling


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