Understanding ‘it depends’ in ecology: a guide to hypothesising, visualising and interpreting statistical interactions

Spake, Rebecca; Bowler, Diana E. ORCID: https://orcid.org/0000-0002-7775-1668; Callaghan, Corey T.; Blowes, Shane A.; Doncaster, C. Patrick; Antão, Laura H.; Nakagawa, Shinichi; McElreath, Richard; Chase, Jonathan M.. 2023 Understanding ‘it depends’ in ecology: a guide to hypothesising, visualising and interpreting statistical interactions. Biological Reviews, 98 (4). 983-1002. https://doi.org/10.1111/brv.12939

Before downloading, please read NORA policies.

Preview

Text
N534719JA.pdf - Published Version
Available under License Creative Commons Attribution 4.0.
Download (3MB) | Preview

Official URL: http://dx.doi.org/10.1111/brv.12939

Abstract/Summary

Ecologists routinely use statistical models to detect and explain interactions among ecological drivers, with a goal to evaluate whether an effect of interest changes in sign or magnitude in different contexts. Two fundamental properties of interactions are often overlooked during the process of hypothesising, visualising and interpreting interactions between drivers: the measurement scale – whether a response is analysed on an additive or multiplicative scale, such as a ratio or logarithmic scale; and the symmetry – whether dependencies are considered in both directions. Overlooking these properties can lead to one or more of three inferential errors: misinterpretation of (i) the detection and magnitude (Type-D error), and (ii) the sign of effect modification (Type-S error); and (iii) misidentification of the underlying processes (Type-A error). We illustrate each of these errors with a broad range of ecological questions applied to empirical and simulated data sets. We demonstrate how meta-analysis, a widely used approach that seeks explicitly to characterise context dependence, is especially prone to all three errors. Based on these insights, we propose guidelines to improve hypothesis generation, testing, visualisation and interpretation of interactions in ecology.

Item Type:	Publication - Article
Digital Object Identifier (DOI):	https://doi.org/10.1111/brv.12939
UKCEH and CEH Sections/Science Areas:	Biodiversity (Science Area 2017-)
ISSN:	1464-7931
Additional Information. Not used in RCUK Gateway to Research.:	Open Access paper - full text available via Official URL link.
Additional Keywords:	antagonistic, effect size, generalised linear models, Hedges' g, log response ratio, meta-regression, statistical interaction, synergistic, synthesis, transformation
NORA Subject Terms:	Ecology and Environment Mathematics Data and Information
Date made live:	31 Oct 2023 09:59 +0 (UTC)
URI:	https://nora.nerc.ac.uk/id/eprint/534719

Item Type:

Publication - Article

Digital Object Identifier (DOI):

https://doi.org/10.1111/brv.12939

UKCEH and CEH Sections/Science Areas:

Biodiversity (Science Area 2017-)

ISSN:

1464-7931

Additional Information. Not used in RCUK Gateway to Research.:

Open Access paper - full text available via Official URL link.

Additional Keywords:

antagonistic, effect size, generalised linear models, Hedges' g, log response ratio, meta-regression, statistical interaction, synergistic, synthesis, transformation

NORA Subject Terms:

Ecology and Environment
Mathematics
Data and Information

Date made live:

31 Oct 2023 09:59 +0 (UTC)

URI:

https://nora.nerc.ac.uk/id/eprint/534719