Our lab uses quantitative approaches to study the evolution of animal social behaviour in natural ecological and social contexts. We translate the computational techniques developed in lab settings for model systems like Drosophila and Zebrafish, including machine vision, automated tracking, and behavioural decomposition, and employ these in more complex field environments like Lake Tanganyika and the Coral Reef. We seek to understand how social and collective interactions are modified by current context, how animals perceive and process social cues, and how environments – both social and physical – are changed as a consequence of animal behaviour. We take a broad approach, combining proximate neurobiological and genetic mechanisms of social behaviour with large-scale ecological studies of social influence and collective behaviour. Here are some of our current projects.
The evolution of social behaviour
When complex social structures evolve, what needs to change in terms of the behaviour animals express? Do social animals need to do more, that is, must a richer or more complex behavioural repertoire evolve? Are we as human observers able to detect the potentially subtle ways that behaviour may differ in what appear to be similar contexts? And can machine learning approaches help us in this endeavour?
We ask these questions across a range of systems, from the explosive adaptive radiation in Tanganyikan cichlids, damselfish on Jamaican coral reefs, Trinidadian guppies, and spiders in the Latin American rainforests.
The interaction between physical and social spaces
“We shape our buildings; thereafter they shape us” – Winston Churchill
Animals affect, and are affected by, their environments. This simple relationship means that it is difficult to assess how removing animals from their natural contexts might influence their behavioural expression. We aim to quantify the natural structures in which animals live and interact, and manipulate attributes of these structures to experimentally test their effects.
Sexual selection, mate choice, and parental care in complex social conditions
Payoffs of reproductive strategies vary depending on the social context in which they are employed, but quantifying how social conditions change can be difficult. With spiders and fish, we manipulate elements of the social context, track all interactions among individuals, and measure the fitness payoffs of varying strategies.
The evolution of social competence and cognition
Living in groups potentially imposes cognitive challenges that solitary animals do not face. Memory of past interactions, inference of unknown relationships, and recognition of individuals may be required to maintain functional social groups. Using a blend of virtual and traditional approaches, we try to understand the range of cognitive abilities that have evolved along with social living, along with how these differences may be encoded in the brain itself.
Francisco F, Nührenberg, Jordan A. 2019. A low-cost, open-source framework for tracking and behavioural analysis of animals in aquatic ecosystems. Submitted to Movement Ecology
Kohda M, Hotta T, Takeyama T, Yoshimura N, Jordan A. 2019. If a fish can pass the mark test, what are the implications for consciousness and self-awareness testing in animals? PLOS Biology February 7, 2019
Beekman M, Jordan LA. 2017. Does the field of animal personality provide any new insights for behavioural ecology?. Behavioural Ecology (2017) 28 (3): 617-623. DOI: https://doi.org/10.1093/beheco/arx022
Jordan LA, Maguire S, Hofmann, HA, Kohda M. 2016. The social and ecological consequences of an ‘over-extended’ phenotype. Proceedings of the Royal Society B 283 (1822)