Simulation and social network analysis provide insight into the acquisition of tool behaviour in hybrid macaques.
Proc Biol Sci
; 290(1995): 20222276, 2023 03 29.
Article
en En
| MEDLINE
| ID: mdl-36987645
The pathways through which primates acquire skills are a central focus of cultural evolution studies. The roles of social and genetic inheritance processes in skill acquisition are often confounded by environmental factors. Hybrid macaques from Koram Island (Thailand) provide an opportunity to examine the roles of inheritance and social learning to skill acquisition within a single ecological setting. These hybrids are a cross between tool-using Burmese long-tailed (Macaca fascicularis aurea) and non-tool-using common long-tailed macaques (Macaca fascicularis fascicularis). This population provides an opportunity to explore the roles of social learning and inheritance processes while being able to exclude underlying ecological factors. Here, we investigate the roles of social learning and inheritance in tool use prevalence within this population using social network analysis and simulation. Agent-based modelling (ABM) is used to generate expectations for how social/asocial learning and inheritance structure the patterning in a social network. The results of the simulation show that various transmission mechanisms can be differentiated based on associations between individuals in a social network. The results provide an investigative framework for discussing tool use transmission pathways in the Koram social network. By combining ABM, network analysis, and behavioural data from the field we can investigate the roles social learning and inheritance play in tool acquisition of wild primates.
Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Comportamiento del Uso de la Herramienta
/
Aprendizaje Social
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Aspecto:
Determinantes_sociais_saude
Límite:
Animals
País/Región como asunto:
Asia
Idioma:
En
Revista:
Proc Biol Sci
Asunto de la revista:
BIOLOGIA
Año:
2023
Tipo del documento:
Article
País de afiliación:
Alemania
Pais de publicación:
Reino Unido