The causal pie model: an epidemiological method applied to evolutionary biology and ecology
Article first published online: 19 APR 2014
© 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
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Ecology and Evolution
Volume 4, Issue 10, pages 1924–1930, May 2014
How to Cite
Ecology and Evolution 2014; 4(10):1924–1930
- Issue published online: 20 MAY 2014
- Article first published online: 19 APR 2014
- Manuscript Accepted: 26 MAR 2014
- Manuscript Revised: 24 MAR 2014
- Manuscript Received: 4 FEB 2014
- Max Planck Digital Library
- Max Planck Society
- Agents of selection;
- causes of mortality;
- correlated traits;
- natural selection;
- semi-neutral mutations;
A general concept for thinking about causality facilitates swift comprehension of results, and the vocabulary that belongs to the concept is instrumental in cross-disciplinary communication. The causal pie model has fulfilled this role in epidemiology and could be of similar value in evolutionary biology and ecology. In the causal pie model, outcomes result from sufficient causes. Each sufficient cause is made up of a “causal pie” of “component causes”. Several different causal pies may exist for the same outcome. If and only if all component causes of a sufficient cause are present, that is, a causal pie is complete, does the outcome occur. The effect of a component cause hence depends on the presence of the other component causes that constitute some causal pie. Because all component causes are equally and fully causative for the outcome, the sum of causes for some outcome exceeds 100%. The causal pie model provides a way of thinking that maps into a number of recurrent themes in evolutionary biology and ecology: It charts when component causes have an effect and are subject to natural selection, and how component causes affect selection on other component causes; which partitions of outcomes with respect to causes are feasible and useful; and how to view the composition of a(n apparently homogeneous) population. The diversity of specific results that is directly understood from the causal pie model is a test for both the validity and the applicability of the model. The causal pie model provides a common language in which results across disciplines can be communicated and serves as a template along which future causal analyses can be made.