Genotypic variability enhances the reproducibility of an ecological study

Nat Ecol Evol. 2018 Feb;2(2):279-287. doi: 10.1038/s41559-017-0434-x. Epub 2018 Jan 15.

Abstract

Many scientific disciplines are currently experiencing a 'reproducibility crisis' because numerous scientific findings cannot be repeated consistently. A novel but controversial hypothesis postulates that stringent levels of environmental and biotic standardization in experimental studies reduce reproducibility by amplifying the impacts of laboratory-specific environmental factors not accounted for in study designs. A corollary to this hypothesis is that a deliberate introduction of controlled systematic variability (CSV) in experimental designs may lead to increased reproducibility. To test this hypothesis, we had 14 European laboratories run a simple microcosm experiment using grass (Brachypodium distachyon L.) monocultures and grass and legume (Medicago truncatula Gaertn.) mixtures. Each laboratory introduced environmental and genotypic CSV within and among replicated microcosms established in either growth chambers (with stringent control of environmental conditions) or glasshouses (with more variable environmental conditions). The introduction of genotypic CSV led to 18% lower among-laboratory variability in growth chambers, indicating increased reproducibility, but had no significant effect in glasshouses where reproducibility was generally lower. Environmental CSV had little effect on reproducibility. Although there are multiple causes for the 'reproducibility crisis', deliberately including genetic variability may be a simple solution for increasing the reproducibility of ecological studies performed under stringently controlled environmental conditions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Brachypodium / genetics*
  • Brachypodium / growth & development
  • Environment
  • Europe
  • Genotype*
  • Medicago truncatula / genetics*
  • Medicago truncatula / growth & development
  • Reproducibility of Results
  • Research Design* / statistics & numerical data