Ordination analysis in sedimentology, geochemistry and palaeoenvironment—Background, current trends and recommendations

Or M. Bialik, Emilia Jarochowska, Michal Grossowicz

Research output: Contribution to journalReview articlepeer-review

Abstract

Ordination is the name given to a group of methods used to analyse multiple variables without preceding hypotheses. Over the last few decades, the use of these methods in Earth science in general, and notably in analyses of sedimentary sources, has dramatically increased. However, with limited resources oriented towards Earth scientists on the topic, the application of ordination analysis is at times suboptimal and misuse by authors can occur. This text was written for researchers with little to no experience with ordination with the aim of exposing them to the utility and the pitfalls of this branch of exploratory statistics. To do so, a detailed review of three ordination methods is offered: principal component analysis, non-metric multidimensional scaling and detrended correspondence analysis. A survey of 163 publications in Earth science is presented, in which these ordination methods were used together with a summary of how, why and on what type of data ordination was used. With common mistakes outlined and misuses in those publications identified. Notably, issues were found with reproducibility, documentation, data set dimensions and transformations. Based on this survey, a recommended workflow is offered for Earth scientists who wish to apply ordination. Additionally, this article is accompanied by highly annotated R scripts for novice users to use these methods.

Original languageEnglish
Pages (from-to)541-563
Number of pages23
JournalDepositional Record
Volume7
Issue number3
DOIs
StatePublished - Sep 2021
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2021 The Authors. The Depositional Record published by John Wiley & Sons Ltd on behalf of International Association of Sedimentologists

Keywords

  • clustering
  • DCA
  • dimension reduction
  • exploratory statistics
  • multivariate statistics
  • NMDS
  • PCA

ASJC Scopus subject areas

  • Oceanography
  • Environmental Science (miscellaneous)
  • Geology
  • Stratigraphy
  • Paleontology

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