Taxonomic bias, sometimes called taxonomic chauvinism, describes the disproportionate research attention lavished on a few groups of organisms while the vast majority of life remains in scientific darkness. Birds and mammals make up less than one percent of animal biodiversity, yet they dominate conservation funding and research output across most subfields of ecology and evolution. The problem extends down to fine taxonomic scales: within entire clades, a handful of genera and species soak up most of the attention. The classic fruit fly Drosophila melanogaster, the lab rat Rattus norvegicus, and the great tit Parus major were each named by more than a dozen participants in the new survey as organisms they had recently worked with, and fewer than two-thirds of all responses represented unique species.

The research team, led by Pietro Pollo and Michael Kasumovic of the University of New South Wales, hypothesised that the choice of study organisms is shaped by factors along three axes: reason, context, and emotion. Rational factors include logistic advantages, unique traits, and applied potential such as economic importance or conservation status. Contextual factors include a species’ reputation as a model organism and taxonomic inheritance from supervisors. Emotional factors include fondness, hobbies, and work-related preferences such as a love of fieldwork. Many of the predictions were preregistered before data collection, a research plan made prior to analysis that strengthens the credibility of the findings.

To test the framework, the team distributed an online survey between May and August 2025, targeting researchers who had directly collected behavioural data from at least one non-human organism and published at least one research output as a result. The recruitment list contained 20,818 unique email addresses extracted from journals publishing ethological and behavioural research, and 946 researchers completed the survey. After careful screening — excluding 77 responses with failed attention checks, dubious veracity, contradictions, or duplication — 868 responses were retained for analysis. Participants were, on average, nearly 43 years old, roughly half identified as men, and about 90 percent held a PhD.

The statistical analysis was technically ambitious. The team fitted generalised linear models with negative binomial and Poisson error distributions to examine how many species and taxonomic groups participants had experienced. Cumulative linked mixed models, a form of ordinal regression, were used to analyse seven-point Likert-scale agreement with statements about the species participants most recently worked with, with genus and participant identity as random factors. Model selection relied on the Akaike Information Criterion corrected for small sample sizes, retaining models within two units of the lowest value. All analyses were conducted in R, with model assumptions verified using residual diagnostics.

The results overturned a common assumption. The most popular organisms — birds and mammals — were rarely perceived as easier to work with than other groups. With some exceptions, mammals were considered as difficult or more difficult to find, observe, rear, or buy than other taxa. Molluscs, which only about six percent of participants had worked with, were largely perceived as easy to study both in the field and in the laboratory. Logistic convenience, it turns out, may explain why certain genera are popular within taxonomic groups, but it does not explain why entire groups such as mammals dominate the field at higher taxonomic levels.

Contextual factors proved more powerful. Within taxonomic groups, the more frequently a genus was mentioned by distinct participants, the more it was perceived as a model organism, as possessing ideal traits, and as economically important. Participants’ perception that their most recent species was a model organism was strongly related to the impression that the behavioural literature on it was extensive, with a Spearman correlation of 0.643, and moderately related to how easy it was to buy, rear, and observe in the laboratory. Strikingly, many participants deemed species such as barn swallows and crab-eating macaques as model organisms even though they are not officially listed as such. The authors argue that the model organism label should be abolished in most spheres of ecology and evolution because it rewards species that have acquired an arbitrary status among researchers.

Taxonomic inheritance emerged as a major bottleneck. Most participants reported working, at multiple career stages, with species suggested by their supervisors, although this pattern weakened after researchers obtained permanent positions. Early-career researchers interact with few senior scientists who can act as mentors, and because few senior researchers work with neglected taxonomic groups, early-career scientists hoping to study such organisms are less likely to find supervisors who can support their interests. The authors recommend that institutions consider the diversity of taxonomic experiences of senior researchers when recruiting them, that senior researchers adopt a flexible approach supporting junior colleagues to engage with diverse taxa, and that funding organisations include criteria favouring neglected taxa in hiring and grant assessments.

Emotion, however, may be the deepest driver of all. Participants declared more favourable perceptions of taxa they had experienced than of other taxa, and the most popular groups — birds and mammals — overwhelmingly elicited positive feelings even from researchers who had never worked with them. The relationship between fondness and experience appears reciprocal: appreciation of a taxonomic group increases the likelihood of working with it, while experience with it enhances appreciation. This self-reinforcing cycle means that familiarity generates affinity, so taxonomic bias may be self-perpetuating as researchers gravitate towards organisms they already like and become even more attached to them, while unfamiliar taxa remain avoided. The pattern echoes societal values in which vertebrates are generally better perceived than invertebrates, perceptions formed in childhood and reinforced by media and textbooks.

The consequences reach far beyond academic curiosity. Insects were perceived as economically important as mammals, yet invertebrates are under severe threat, underrepresented in biodiversity databases, and their conservation remains underfunded. The authors describe this as a taxonomic bias vortex, in which lack of data generates the impression that no problem exists, leading to even less attention. Meta-analyses of animal behaviour that underrepresent invertebrates risk improper generalisations, curbing the power of studies attempting to draw broad conclusions about nature. The authors advocate for a more taxonomically equitable education beginning as early as childcare, outreach programs promoting appreciation of neglected groups, and the use of citizen science data and recent tracking technologies to facilitate research with different species. If ecology and evolution are to develop truly generalisable theories, the field must look beyond the animals it already loves.

Subject of Research: Ecology and Evolution

Article Title: Drivers of Taxonomic Bias in Ecology and Evolution: Insights From Ethologists and Behavioural Ecologists

Article References: Pollo, P., & Kasumovic, M. M. (2026). Drivers of Taxonomic Bias in Ecology and Evolution: Insights From Ethologists and Behavioural Ecologists. Ecology and Evolution, 16(10), Article e74460. https://doi.org/10.1002/ece3.74460

Image Credits: AI Generated

DOI: 10.1002/ece3.74460

Keywords: taxonomic bias, behavioural ecology, ethology, model organisms, biodiversity, conservation, research methods, invertebrates, Drivers, Taxonomic, Bias, Ecology

The research team set out to answer a question that has become increasingly urgent for reef ecologists. Anthropogenic change, from bleaching to storm damage to sedimentation, is rapidly flattening the three-dimensional architecture of coral reefs, and scientists have long suspected that this simplification should impair the spatial abilities of the fish that depend on it. Yet the cognitive consequences of habitat change remain poorly understood, particularly in fishes. To probe the problem experimentally, the researchers reared juvenile humbug damselfish, Dascyllus aruanus, in aquaria containing either high-complexity or low-complexity coral structures. This split-rearing design allowed them to isolate the effect of structural experience on the developing brain, testing whether fish raised amid a labyrinth of branches would become better navigators than those raised in a comparatively barren environment.

The test itself was elegantly simple. Each fish was trained in a T-maze, a classic apparatus in which an animal must choose between a left and a right arm, one of which leads to a reward. Crucially, the maze could be solved in more than one way. A fish could use an egocentric strategy, essentially memorising a motor rule such as turn left at the junction, or an allocentric strategy, using external landmarks to guide its choice. The researchers measured how many trials each fish needed to reach a learning criterion and how long it took to make correct decisions. Then came the critical step: probe trials in which the cues were placed in conflict, forcing the fish to reveal which strategy it had actually been relying on. When a landmark and a turn direction pointed to different arms, the choice the fish made exposed the strategy hidden beneath its training performance.

The most striking result was not about the environment at all. Turn direction emerged as the strongest predictor of performance in the entire study. Fish that had been trained to turn left reached the learning criterion in fewer trials and consistently relied on egocentric, turn-based strategies during probe trials. This pattern, the authors argue, is indicative of a lateralisation bias, the well-documented tendency of animals, including fishes, to favour one side of the body for particular motor actions. In other words, a left turn appears to sit comfortably within the humbug damselfish’s intrinsic behavioural repertoire, making the task feel almost natural. Fish asked to turn against their preferred direction, by contrast, faced a subtle but persistent handicap that showed up in nearly every measure of learning.

Right-turning fish told a different and equally revealing story. Rather than grinding through the maze with an uncomfortable motor rule, these individuals increasingly shifted their reliance toward landmark cues during probe trials, and they made faster decisions when doing so. The researchers interpret this as evidence that allocentric strategies reduced the cost of acting against an intrinsic turn bias. Instead of forcing a right turn against their natural inclination, the fish appear to have outsourced the decision to external landmarks, effectively sidestepping the conflict between the task and their own bodies. It is a remarkable example of cognitive flexibility in a fish barely a few centimetres long, and it suggests that animals may actively choose navigation strategies not just because of what they learned, but because of what their own laterality makes easy.

What about the environment? Here the results defied expectations. Contrary to the prediction that fish raised in structurally rich aquaria would learn the maze faster overall, environmental complexity did not affect the number of trials required to reach the learning criterion. The headline measure of learning was, in effect, blind to rearing conditions. But complexity was not without consequence. Fish from the high-complexity treatment located the reward faster during early training, suggesting that experience with intricate structure confers an advantage in the earliest phase of spatial familiarisation, when an animal is first mapping a novel environment. The benefit faded as training progressed, hinting that complexity accelerates the initial acquisition of spatial information rather than raising the ceiling of eventual performance.

Complexity also left its mark on the probe trials in a subtler way. High-complexity fish showed longer decision latencies when cues conflicted, a pattern the authors suggest reflects greater sensitivity to landmark information. When the landmark and the turn direction disagreed, these fish appeared to pause, weighing the conflicting sources of information rather than defaulting immediately to a motor rule. That hesitation may represent a form of cognitive depth: an animal that has grown up navigating complex, landmark-rich environments may be more attuned to spatial cues in the world around it, and more reluctant to ignore them when they contradict a learned habit. In a degraded reef, where landmarks vanish and structure collapses, such sensitivity could become a liability rather than an asset.

The broader significance of the study lies in its challenge to how scientists interpret spatial cognition experiments. If turn biases and strategy use can dominate performance measures, then studies that ignore laterality risk misattributing differences in learning to environmental effects when the real driver is an intrinsic behavioural constraint. A population of fish with a different mix of left- and right-turners might appear cognitively superior or inferior for reasons that have nothing to do with their habitat. The authors highlight the importance of considering these intrinsic factors when evaluating how animals cope with environmental change, a caution that extends well beyond damselfish to any species tested in mazes or navigation tasks.

For coral reefs, the stakes are concrete. As climate change and local stressors strip away the branching corals that humbug damselfish call home, the fish will face environments where landmark-based navigation, the strategy that helped right-turning individuals overcome their biases, may become less reliable. Understanding how turn preference, strategy choice and habitat structure interact offers a more nuanced picture of which individuals and populations are likely to cope with simplification, and which will struggle. The study, conducted under Macquarie University animal ethics approval and supported by a DAAD PROMOS fellowship and an International Macquarie Research Excellence Scholarship, was published open access, allowing researchers and reef managers alike to examine the full dataset and analysis code. In the end, the humble humbug damselfish delivers a lesson that resonates far beyond the T-maze: the mind that navigates the world is shaped both by the world it inhabits and by the body it brings to the task, and neither can be understood alone.

Subject of Research: Turn bias, habitat complexity and spatial learning strategies in humbug damselfish

Article Title: Leaning left: how turn bias and habitat complexity shape spatial cognition in a coral-reef fish

Article References: von Drenkmann, H., Klinke, A., & Brown, C. (2026). Leaning left: how turn bias and habitat complexity shape spatial cognition in a coral-reef fish. Animal Cognition. https://doi.org/10.1007/s10071-026-02116-7

Image Credits: AI Generated

DOI: 10.1007/s10071-026-02116-7

Keywords: spatial cognition, humbug damselfish, coral reef fish, lateralisation, turn bias, egocentric navigation, allocentric navigation, T-maze, habitat complexity, landmark cues, animal cognition, behavioural ecology

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