(2014) Storytelling and story testing in domestication. Proceedings of the National Academy of Sciences of the United States of America, Volume 111 (Number 17). pp. 6159-6164. doi:10.1073/pnas.1400425111 ISSN 0027-8424.

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Abstract

Our knowledge of the domestication of animal and plant species comes from a diverse range of disciplines, and interpretation of patterns in data from these disciplines has been the dominant paradigm in domestication research. However, such interpretations are easily steered by subjective biases that typically fail to account for the inherent randomness of evolutionary processes, and which can be blind to emergent patterns in data. The testing of explicit models using computer simulations, and the availability of powerful statistical techniques to fit models to observed data, provide a scientifically robust means of addressing these problems. Here we outline the principles and argue for the merits of such approaches in the context of domestication-related questions.

Item Type:	Journal Article
Divisions:	Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- )
Journal or Publication Title:	Proceedings of the National Academy of Sciences of the United States of America
Publisher:	National Academy of Sciences
ISSN:	0027-8424
Official Date:	21 April 2014
Dates:	Date Event 21 April 2014 Published 18 March 2014 Accepted 30 January 2014 Submitted
Volume:	Volume 111
Number:	Number 17
Page Range:	pp. 6159-6164
DOI:	10.1073/pnas.1400425111
Status:	Peer Reviewed
Publication Status:	Published
Access rights to Published version:	Open Access (Creative Commons)

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