Multi-network-based diffusion analysis reveals vertical cultural transmission of sponge tool use within dolphin matrilines

Abstract

Behavioural differences among social groups can arise from differing ecological conditions, genetic predispositions and/or social learning. In the past, social learning has typically been inferred as responsible for the spread of behaviour by the exclusion of ecological and genetic factors. This ‘method of exclusion’ was used to infer that ‘sponging’, a foraging behaviour involving tool use in the bottlenose dolphin ( Tursiops aduncus ) population in Shark Bay, Western Australia, was socially transmitted. However, previous studies were limited in that they never fully accounted for alternative factors, and that social learning, ecology and genetics are not mutually exclusive in causing behavioural variation. Here, we quantified the importance of social learning on the diffusion of sponging, for the first time explicitly accounting for ecological and genetic factors, using a multi-network version of ‘network-based diffusion analysis'. Our results provide compelling support for previous findings that sponging is vertically socially transmitted from mother to (primarily female) offspring. This research illustrates the utility of social network analysis in elucidating the explanatory mechanisms behind the transmission of behaviour in wild animal populations.

Wild primates copy higher-ranked individuals in a social transmission experiment

“…NBDA 39,41,59 assumes that the rate of social transmission between individuals is proportional to the network connection between them and its aim is twofold: (1) to detect and to quantify social transmission and (2) to establish the typical pathways of social transmission. We used a multi-network NBDA 8,48 allowing us to input multiple networks, each scaled by a different s parameter, which estimates the rate of transmission per observation through each network 39 . We used the order of acquisition (OADA) variant of NBDA 40 , which takes as data only the order in which individuals acquire the target behavior and not the times of acquisition.…”

“…The study of social learning has been recently enriched by the integration of social networks analysis and associated statistical methodologies 5 . Such complementary approaches allow researchers to test for social transmission in wild freely interacting populations of animals and track the diffusion of behavioral innovations across social networks such as the spread of "lobtail feeding" in humpback whales 6 , new tool use in chimpanzees 7 and bottlenose dolphins 8 or new foraging techniques in great tits 9 . Social network structure has been found to shape the diffusion of socially learned behaviors; association of individuals in close proximity can be used to predict innovation spread 10 .…”

“…We record the exact time of each manipulation and the identity of observers allowing us to have fine-grained observation data to construct a dynamic observation network, and to quantify the "per observation" social effect between different classes of individual. While association networks 6,[35][36][37] , genetic networks 8 , and static observation networks 11 have been used so far in modeling social transmission, very few studies used a dynamic observation network 7,28 . We aim here to challenge the notion of a single best strategy or a strategy associating several biases while previous studies on vervet monkeys reported a "copy adult females" strategy [23][24][25] .…”

Estimating heritability of social phenotypes from social networks

“…I present the basic latent variable model first, and then discuss expansions of the model to account for edge and node specific covariates, and spatial and temporal effects. I illustrate this modelling framework with an example analysis with Stan-a Bayesian general purpose inference library (Carpenter et al, 2017)-using a publicly available dataset on bottlenose dolphins (Wild et al, 2019a)…”

The importance of individual-to-society feedbacks in animal ecology and evolution

“…Information state can also determine the maintenance of social bonds-having similar social traits can facilitate cohesion among individuals by allowing them to synchronise and coordinate their activities(Coussi-Korbel & Fragaszy 1995). For example, populations of bottlenose dolphins are often divided into social communities assorted by learnt foraging tactics(Mann et al 2012;Machado et al 2019;Wild et al 2019), illustrating the idea that the more individuals interact, the more opportunities they have for copying each other, thus highlighting how social decisions can reinforce behavioural homogeny. Models have shown that the feedback between information transmission and social decision-making can stimulate the formation of stable groups within otherwise unstructured, well-mixed, populations with(Cantor et al 2015) and without any complex decision-making(Cantor & Farine 2018).…”