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

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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.


Recent Publications

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:

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)


Corsica Field Trip 2019



NSF Grant – Characterization and dissection of DNA
methylation and animal color changes in an African cichlid

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We’ll soon be on some more fishing trips! Along with the Alvarado Lab at Queens College CUNY, we’ll be visiting Lake Tanganyika even more often in the coming years as part of an NSF funded project examining the mechanisms of colour and behavioural change in polyphenic and polymorphic cichlids.



Well that’s certainly not a fish… Along with an awesome team from the Peleg and Meroz labs, we’ve just been awarded the fancy HFSP Young Investigator’s Grant (no but seriously, HFSP here). Here’s the press wrap-up:

The structure of networks can have massive impacts on how information moves. From the viral spread of fake news, to power blackouts, to crowd funding, the ways individual systems connect and influence one another shapes much of modern life. A broad goal across disciplines is to understand and design optimal network structures, but understanding the multitude of ways individuals in these systems affect one another presents a massive challenge to researchers.

To address this issue, Alex Jordan, leader of the Integrative Field Biology Group in the Max Planck Department of Collective Behaviour and University of Konstanz, has teamed up with computer scientist Orit Peleg (University of Colorado Boulder) and plant physiologist Yasmine Meroz (Tel Aviv University) to understand how information moves through massive networks of plants, aiming to create models of optimal network structure that can be employed in areas from computer science to public transport. Their HFSP grant is one of only nine 2019 Young Investigator Grants, which are awarded to researchers within five years of establishing their independent research group and no more than ten years from their doctoral degree.

Because they can move their leaves and flowers to track the sun, by maximizing their own exposure, sunflowers in turn throw shade on their social partners. These plants must then in turn move to avoid being shaded themselves, creating large network cascades of cause and response in these plant communities.

“I have long been studying the ways animals interact and affect one another’s behaviour in social groups,” says Jordan. “But animals are incredibly complex – interacting with one another through sight, sound, touch and smell. The complexity of these interactions, coupled with the fact that animals often move around in space, means a complete understanding of social network interactions in these systems is close to impossible.”

“In contrast, with the sunflower system we have the ability to measure and manipulate every aspect of interaction, from reduced photosynthesis from shading, to spatial arrangement of individuals, and even to prevent movement in response to light at all. As such, we can capture all the information that flows in the system.”

Bodensee Slippers

We’ve been embracing the Konstanz winter by partaking in (sports?) that require various forms of sliding around, as well as dressing up for Fasnacht.




Tanganyika 2018

In the deep heart of Africa once again. Good photos by Jakob and Paul, bad ones and drone ones by Alex!



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