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A dynamic framework for the study of optimal birth intervals reveals the importance of sibling competition and mortality risks

Lookup NU author(s): Dr Daryl Shanley, Alex Houston, Emeritus Professor Thomas Kirkwood


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Human reproductive patterns have been well studied, but the mechanisms by which physiology, ecology and existing kin interact to affect the life history need quantification. Here, we create a model to investigate how age-specific interbirth intervals adapt to environmental and intrinsic mortality, and how birth patterns can be shaped by competition and help between siblings. The model provides a flexible framework for studying the processes underlying human reproductive scheduling. We developed a state-based optimality model to determine age-dependent and family-dependent sets of reproductive strategies, including the state of the mother and her offspring. We parameterized the model with realistic mortality curves derived from five human populations. Overall, optimal birth intervals increase until the age of 30 after which they remain relatively constant until the end of the reproductive lifespan. Offspring helping each other does not have much effect on birth intervals. Increasing infant and senescent mortality in different populations decreases interbirth intervals. We show that sibling competition and infant mortality interact to lengthen interbirth intervals. In lower-mortality populations, intense sibling competition pushes births further apart. Varying the adult risk of mortality alone has no effect on birth intervals between populations; competition between offspring drives the differences in birth intervals only when infant mortality is low. These results are relevant to understanding the demographic transition, because our model predicts that sibling competition becomes an important determinant of optimal interbirth intervals only when mortality is low, as in post-transition societies. We do not predict that these effects alone can select for menopause.

Publication metadata

Author(s): Thomas MG, Shanley DP, Houston AI, McNamara JM, Mace R, Kirkwood TBL

Publication type: Article

Publication status: Published

Journal: Journal of Evolutionary Biology

Year: 2015

Volume: 28

Issue: 4

Pages: 885-895

Print publication date: 01/04/2015

Online publication date: 17/03/2015

Acceptance date: 25/02/2015

ISSN (print): 1010-061X

ISSN (electronic): 1420-9101

Publisher: Wiley-Blackwell Publishing Ltd.


DOI: 10.1111/jeb.12613


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Funder referenceFunder name
250209European Research Council
249347European Research Council