Why City Life May Reshape How Animals Learn From Each Other

Cities are among the most demanding environments that animals have ever encountered. Concrete, traffic, artificial light, chemical runoff and constant human disturbance create conditions that differ radically from the habitats in which most species evolved. One of the most intriguing questions in modern behavioural ecology is whether animals coping with these pressures lean more heavily on a particular cognitive shortcut: learning from others. A new review published in the journal Animal Cognition argues that while social learning should, in theory, be especially valuable in urban settings, the relationship between urbanisation and social learning remains strikingly underexplored, with surprisingly little direct empirical evidence to confirm the intuition.

The review, authored by Camille A. Troisi of the Centre d’Étude en Éthologie et Cognition at the Université de Rennes in France, takes a deliberately analytical approach to the problem. Rather than treating social learning as a single, indivisible behaviour, Troisi separates it into two conceptual components: the social component, which concerns the availability and use of information produced by other individuals, and the learning component, which concerns the cognitive machinery that converts observed or transmitted information into lasting behavioural change. This distinction matters because urban factors may act on each component in different, and sometimes opposing, ways.

Social learning is widely predicted to be most useful in novel or variable environments. When an animal faces a new food source, a new predator or a new hazard, copying an experienced individual can be far cheaper and safer than trial-and-error exploration. Urban environments, with their rapid change and abundance of unfamiliar challenges, appear tailor-made for this strategy. Yet, as the review emphasises, whether animals actually rely on social information in cities depends on a chain of conditions: the information must be available, it must be genuinely useful, individuals must be inclined to use it, and they must be capable of learning from it. Disruption at any link in this chain can weaken the whole process.

Pollution emerges as one of the most pervasive urban factors with the potential to interfere with social learning, and Troisi examines it in three distinct forms. Chemical pollution, including heavy metals and endocrine-disrupting compounds, can impair cognition directly, degrading the attention, memory and sensory processing needed to detect and interpret social cues. Noise pollution poses a different problem: acoustic signals are among the most important channels of social information for birds, mammals and other vocal species, and chronic urban noise can mask calls and songs, effectively cutting the bandwidth through which social information flows. Light pollution adds a further layer, altering activity patterns and potentially desynchronising the timing of social interactions between individuals that would otherwise learn from one another.

Food resources represent another pathway with ambiguous consequences. Cities often provide abundant, predictable and clumped food sources, from rubbish bins to bird feeders. On the one hand, such predictability might reduce the need for social learning, since individuals can locate resources through simple routines rather than by following others. On the other hand, concentrated food can increase the frequency of social interactions and produce local traditions, as has been observed in urban birds and mammals that learn novel foraging techniques from conspecifics. The review highlights that the direction of the effect likely depends on how resources are distributed in space and time, and on how competition shapes the willingness of individuals to allow others close enough to be observed.

Temperature is a factor that is easy to overlook but potentially significant. Urban heat islands raise ambient temperatures relative to surrounding rural areas, and temperature influences metabolic rate, activity levels and the timing of behaviour. Because social learning depends on temporal overlap between demonstrators and observers, thermal shifts that alter daily activity patterns could change who meets whom, and when. Warmer nights, for example, may extend or shift activity windows, potentially increasing opportunities for social contact for some species while reducing them for others.

Habitat structure plays an equally complex role. The built environment alters sightlines, creates vertical structures and fragments vegetation, all of which influence how easily animals can observe one another. Dense buildings may block visual transmission of social information, while at the same time creating new vantage points such as ledges, wires and rooftops where animals congregate visibly. Furthermore, structural features of cities can change the value of what is learned: navigating a maze of glass and asphalt may demand entirely new route knowledge, and experienced residents may hold information about safe corridors and hazards that naive individuals cannot easily acquire alone.

Perhaps the most distinctive feature of urban environments is the sheer pace of environmental change. Social learning carries an inherent risk: information can become outdated. In rapidly changing environments, information copied from others may be obsolete by the time it is used, favouring asocial, individual learning instead. Troisi points out that this dynamic could cut against the intuitive prediction that cities should promote social learning. If the urban landscape, traffic patterns or human behaviours that generate rewards and risks change faster than social information can circulate, animals may do better by sampling the environment themselves. The usefulness of social information, in other words, is not a fixed property but a moving target shaped by the rate of change.

Across all of these factors, the review reaches a sobering conclusion. Although there are substantial bodies of research on each individual component — on how pollution affects cognition, on how noise alters communication, on how animals learn socially in laboratory and wild settings — very little empirical work directly examines the relationship between urbanisation and social learning as an integrated whole. Most conclusions about urban social learning are therefore extrapolations rather than demonstrations. The review serves as both a synthesis of what is plausibly known and a roadmap for what remains to be tested, identifying where the logical pathways from urban factors to social information use are strongest and where empirical data are thinnest.

The implications extend beyond academic curiosity. Understanding how animals adapt cognitively to cities is increasingly relevant to conservation, urban planning and the management of human-wildlife conflict. Species that exploit social information effectively may be better equipped to colonise and thrive in urban areas, potentially explaining why some species flourish alongside humans while others retreat. If pollution, noise or the pace of change erode social learning in vulnerable species, cities could be imposing hidden cognitive costs that compound more visible threats. Filling the empirical gap that this review exposes will require targeted experiments comparing social learning performance across urban and rural populations, across gradients of urbanisation, and under controlled manipulations of the specific factors the review identifies. Until such studies accumulate, the question of whether city life makes animals more — or less — reliant on the wisdom of others remains one of behavioural ecology’s compelling open problems.

Subject of Research: The factors in urban environments that influence animals' reliance on and the usefulness of social learning.

Article Title: Factors impacting reliance on, and usefulness of, social learning in urban environments

Article References: Troisi, C. A. (2026). Factors impacting reliance on, and usefulness of, social learning in urban environments. Animal Cognition. https://doi.org/10.1007/s10071-026-02100-1

Image Credits: AI Generated

DOI: 10.1007/s10071-026-02100-1

Keywords: social learning, urbanisation, animal cognition, urban ecology, noise pollution, chemical pollution, light pollution, food resources, habitat structure, environmental change, behavioural ecology, animal behaviour