TY - JOUR

T1 - Storytelling and story testing in domestication

AU - Gerbault, Pascale

AU - Allaby, Robin G

AU - Boivin, Nicole

AU - Rudzinski, Anna

AU - Grimaldi, Ilaria M

AU - Pires, J. Chris

AU - Climer Vigueira, Cynthia

AU - Dobney, Keith

AU - Gremillion, Kristen J

AU - Barton, Loukas

AU - Arroyo-Kalin, Manuel

AU - Purugganan, Michael D.

AU - Rubio de Casas, Rafael

AU - Bollongino, Ruth

AU - Burger, Joachim

AU - Fuller, Dorian Q.

AU - Bradley, Daniel G.

AU - Balding, David J.

AU - Richerson, Peter J.

AU - Gilbert, M. Thomas P.

AU - Larson, Greger

AU - Thomas, Mark G.

PY - 2014

Y1 - 2014

N2 - The domestication of plants and animals marks one of the most significant transitions in human, and indeed global, history. Traditionally, study of the domestication process was the exclusive domain of archaeologists and agricultural scientists; today it is an increasingly multidisciplinary enterprise that has come to involve the skills of evolutionary biologists and geneticists. Although the application of new information sources and methodologies has dramatically transformed our ability to study and understand domestication, it has also generated increasingly large and complex datasets, the interpretation of which is not straightforward. In particular, challenges of equifinality, evolutionary variance, and emergence of unexpected or counter-intuitive patterns all face researchers attempting to infer past processes directly from patterns in data. We argue that explicit modeling approaches, drawing upon emerging methodologies in statistics and population genetics, provide a powerful means of addressing these limitations. Modeling also offers an approach to analyzing datasets that avoids conclusions steered by implicit biases, and makes possible the formal integration of different data types. Here we outline some of the modeling approaches most relevant to current problems in domestication research, and demonstrate the ways in which simulation modeling is beginning to reshape our understanding of the domestication process.

AB - The domestication of plants and animals marks one of the most significant transitions in human, and indeed global, history. Traditionally, study of the domestication process was the exclusive domain of archaeologists and agricultural scientists; today it is an increasingly multidisciplinary enterprise that has come to involve the skills of evolutionary biologists and geneticists. Although the application of new information sources and methodologies has dramatically transformed our ability to study and understand domestication, it has also generated increasingly large and complex datasets, the interpretation of which is not straightforward. In particular, challenges of equifinality, evolutionary variance, and emergence of unexpected or counter-intuitive patterns all face researchers attempting to infer past processes directly from patterns in data. We argue that explicit modeling approaches, drawing upon emerging methodologies in statistics and population genetics, provide a powerful means of addressing these limitations. Modeling also offers an approach to analyzing datasets that avoids conclusions steered by implicit biases, and makes possible the formal integration of different data types. Here we outline some of the modeling approaches most relevant to current problems in domestication research, and demonstrate the ways in which simulation modeling is beginning to reshape our understanding of the domestication process.

KW - Animals

KW - Animals, Domestic

KW - Crops, Agricultural

KW - Humans

KW - Hybridization, Genetic

KW - Models, Biological

KW - Narration

U2 - 10.1073/pnas.1400425111

DO - 10.1073/pnas.1400425111

M3 - Journal article

C2 - 24753572

VL - 111

SP - 6159

EP - 6164

JO - Proceedings of the National Academy of Sciences of the United States of America

JF - Proceedings of the National Academy of Sciences of the United States of America

SN - 0027-8424

IS - 17

ER -