Animal social networks

PictureFrom: Dugatkin & Hasenjager (2015)
Social groups can be conceptualized as networks in which the connections between individuals represent some form of social relationship [1]. These patterns of connectivity and how they change over time can have important ecological and evolutionary consequences. For example, when populations are subdivided into tightly knit communities (as in the dolphin network shown here), this can constrain the spread of behavioral innovations across communities, while facilitating rapid transmission within them [2]. My recent research has focused on the behavioral and ecological factors that shape social network structure and the resulting consequences for how individuals learn about their environment.

1. Hasenjager MJ, Dugatkin LA. 2015. Social network analysis in behavioral ecology.  Advances in the Study of Behavior 47, 39-114. doi: 10.1016/bs.asb.2015.02.003

2. Dugatkin LA, Hasenjager M. 2015. The Networked Animal.  Scientific American, June 2015, pp. 50-55. doi: 10.1038/scientificamerican0615-50

Social and ecological drivers of network structure and function

PictureEl Cedro River, Arima, Trinidad
Social network structure emerges from the patterning of interactions among individuals. For my doctoral work, I manipulated the social and environmental conditions experienced by shoals of Trinidadian guppies (Poecilia reticulata) and investigated how this impacted the structure of their social networks and the spread of foraging information within them. Key findings included: (i) that foraging information spread more rapidly through mixed shoals of familiar and unfamiliar fish, resulting from disruption of relationships following introduction of the latter [1]; (ii) high perceived predation risk generated networks that were strongly assorted by body size and drove individuals to explore their environment in the company of preferred social partners [2]; and (iii) that how individuals learned was contingent not only on their own risk-taking tendency, but on that of their group mates [3].

1. Hasenjager MJ, Dugatkin LA. 2017. Familiarity affects network structure and information flow in guppy (Poecilia reticulata) shoals. Behavioral Ecology 28, 233-242. doi: 10.1093/beheco/arw152

2. Hasenjager MJ, Dugatkin LA. 2017. Fear of predation shapes social network structure and the acquisition of foraging information in guppy shoals. Proceedings of the Royal Society B 284, 20172020. doi: 10.1098/rspb.2017.2020

3. Hasenjager MJ, Hoppitt W, Dugatkin LA. 2020. Personality composition determines social learning pathways within shoaling fish. Proceedings of the Royal Society B 287, 20201871. doi: 10.1098/rspb.2020.1871

The adaptive value of honeybee communication networks

Picture
Nectar exchange during trophallaxis
The honeybee (Apis mellifera) waggle dance is a marvel of collective behavior, whereby successful foragers can transmit the location of profitable resources to colony members. Yet recent work has called the functional relevance of this remarkable ability into question, as disrupting dances often has little impact on the amount of food that a colony is able to collect. The solution may reside in that fact that foragers have access to alternative social information sources alongside the dance [1], and that the dance itself can simultaneously serve multiple functions. As a postdoctoral researcher with Dr. Elli Leadbeater, I aimed to elucidate how different information networks (e.g. dance-following, food-sharing interactions) were integrated under different foraging conditions by combining social network analyses [2] with experimental manipulations of feeder arrays. For instance, I compared the contribution of dance and non-dance interactions during forager recruitment to novel locations and reactivation to previously visited sites. I found that dances were key for recruitment, but that reactivation (which is far more common during daily foraging) was driven primarily by non-dance interactions [3]. These findings help to explain why disrupting dances often has a limited impact on foraging and sheds light on the selective pressures that have shaped the evolution of the waggle dance.

1. Leadbeater E, Hasenjager MJ. 2019. Honeybee communication: There's more on the dancefloor. Current Biology 29, R285-R287. doi: 10.1016/j.cub.2019.03.009

2. Hasenjager MJ, Leadbeater E, Hoppitt W. 2021. Detecting and quantifying social transmission using network-based diffusion analysis. Journal of Animal Ecology, 90, 8-26. doi: 10.1111/1365-2656.13307

3. Hasenjager MJ, Hoppitt W, Leadbeater E. 2020. Network-based diffusion analysis reveals context-specific dominance of dance communication in foraging honeybees. Nature Communications 11, 625. doi: 10.1038/s41467-020-14410-0

Bio-inspired design of supply networks

Ants and other social insects have evolved behavioral algorithms that allow them to rapidly respond to shifts in supply or demand and efficiently distribute key resources throughout the colony, all without any form of central control. As a postdoctoral researcher with Dr. Nina Fefferman at the National Institute for Mathematical and Biological Synthesis, I aim to identify such algorithms and adapt them for human use to improve the robustness and resilience of our supply networks.