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A protocol for reproducible functional diversity analyses

  • Facundo X. Palacio
  • , Corey T. Callaghan
  • , Pedro Cardoso
  • , Emma J. Hudgins
  • , Marta A. Jarzyna
  • , Gianluigi Ottaviani
  • , Federico Riva
  • , Caio Graco-Roza
  • , Vaughn Shirey
  • , Stefano Mammola

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

The widespread use of species traits in basic and applied ecology, conservation and biogeography has led to an exponential increase in functional diversity analyses, with > 10 000 papers published in 2010–2020, and > 1800 papers only in 2021. This interest is reflected in the development of a multitude of theoretical and methodological frameworks for calculating functional diversity, making it challenging to navigate the myriads of options and to report detailed accounts of trait-based analyses. Therefore, the discipline of trait-based ecology would benefit from the existence of a general guideline for standard reporting and good practices for analyses. We devise an eight-step protocol to guide researchers in conducting and reporting functional diversity analyses, with the overarching goal of increasing reproducibility, transparency and comparability across studies. The protocol is based on: 1) identification of a research question; 2) a sampling scheme and a study design; 3–4) assemblage of data matrices; 5) data exploration and preprocessing; 6) functional diversity computation; 7) model fitting, evaluation and interpretation; and 8) data, metadata and code provision. Throughout the protocol, we provide information on how to best select research questions, study designs, trait data, compute functional diversity, interpret results and discuss ways to ensure reproducibility in reporting results. To facilitate the implementation of this template, we further develop an interactive web-based application (stepFD) in the form of a checklist workflow, detailing all the steps of the protocol and allowing the user to produce a final ‘reproducibility report' to upload alongside the published paper. A thorough and transparent reporting of functional diversity analyses ensures that ecologists can incorporate others' findings into meta-analyses, the shared data can be integrated into larger databases for consensus analyses, and available code can be reused by other researchers. All these elements are key to pushing forward this vibrant and fast-growing field of research.
Original languageEnglish
Article numbere06287
Pages (from-to)1-15
Number of pages15
JournalEcography
Volume2022
Issue number11
Early online date30 Aug 2022
DOIs
Publication statusPublished - Nov 2022
Externally publishedYes

Funding

– FXP received partial support from Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). FR acknowledges support by MITACS through an Accelerate Fellowship (IT23330). GO was supported by the long‐term research development project of the Czech Academy of Sciences (RVO 67985939). SM acknowledges support by the European Commission via the Marie Sklodowska‐Curie Individual Fellowships program (H2020‐MSCA‐IF‐2019; project no. 882221). – The reproducible code box (Supporting information) was adapted from Joseph R. Bennett's lab manual (Carleton Univ.; compiled by Jaimie G. Vincent), and heavily influenced by the Open Science Foundation. – FXP received partial support from Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET). FR acknowledges support by MITACS through an Accelerate Fellowship (IT23330). GO was supported by the long-term research development project of the Czech Academy of Sciences (RVO 67985939). SM acknowledges support by the European Commission via the Marie Sklodowska-Curie Individual Fellowships program (H2020-MSCA-IF-2019; project no. 882221).

FundersFunder number
Consejo Nacional de Investigaciones Científicas y Técnicas
Open Science Foundation
Horizon 2020 Framework Programme882221
Akademie Věd České RepublikyRVO 67985939
European CommissionH2020-MSCA-IF-2019
MitacsIT23330

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