From patterns to causal understanding: Structural equation modeling (SEM) in soil ecology

Nico Eisenhauer, Matthew A. Bowker, James B. Grace, Jeff R. Powell

Research output: Contribution to journalArticlepeer-review

265 Scopus citations


In this perspectives paper we highlight a heretofore underused statistical method in soil ecological research, structural equation modeling (SEM). SEM is commonly used in the general ecological literature to develop causal understanding from observational data, but has been more slowly adopted by soil ecologists. We provide some basic information on the many advantages and possibilities associated with using SEM and provide some examples of how SEM can be used by soil ecologists to shift focus from describing patterns to developing causal understanding and inspiring new types of experimental tests. SEM is a promising tool to aid the growth of soil ecology as a discipline, particularly by supporting research that is increasingly hypothesis-driven and interdisciplinary, thus shining light into the black box of interactions belowground.

Original languageEnglish (US)
Pages (from-to)65-72
Number of pages8
Issue number2-3
StatePublished - Mar 1 2015


  • Aboveground-belowground interactions
  • Hypothesis testing
  • Mechanistic understanding
  • Path analysis
  • Soil processes

ASJC Scopus subject areas

  • Ecology, Evolution, Behavior and Systematics
  • Soil Science


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