Biology subjects

Kao, A. B.

Publications and source records attributed to Kao, A. B..

5 recordsLinked to original sources

bioRxiv2025

A tale of two birds: cognitive simplicity drives collective route improvements in homing pigeons

Cognitive abilities are central to how animals navigate complex environments. Beyond individual cognition, group living can also enhance navigation by pooling individually acquired information. One way this may be achieved is by following experienced leaders, which requires recognizing expertise within group members. Alternatively, accurate decisions could also emerge without expert opinions, through simpler mechanisms like the wisdom of crowds principle that average out individual biases. Consequently, collective navigation strategies range from cognitively complex to simple, and yet, the prevalence or interplay of different collective strategies in nature remains unexplored. In this study, we asked: what is the navigation mechanism, requiring minimal cognitive demands, that is necessary and sufficient to quantitatively replicate the experimental results of a 2017 study on homing pigeons (Columba livia), which showed that sequential chains of bird pairs flying home -- similar to a game of telephone -- led to shorter homing routes compared to control birds flying individually or in fixed pairs. Our results show that the experimental data aligns closely with the simplest strategy -- route averaging. Surprisingly, the complex mechanism of selectively propagating the best flight through social learning offered no additional advantage. We further observed that mixed strategies, although not supported by the experimental data, in theory combined advantages from both averaging and active selection of better routes, resulting in even greater performance. Hence, our results highlight the potential for future research to investigate selective pressures shaping the evolution of cultural learning and trade-offs among different decision mechanisms theoretically available to social animals in nature.

animal behavior and cognition↗

bioRxiv2020

Changes in group size during resource shifts reveal drivers of sociality across the tree of life

From biofilms to whale pods, organisms have repeatedly converged on sociality as a strategy to improve individual fitness. Yet, it remains challenging to identify the most important drivers--and by extension, the evolutionary mechanisms--of sociality for particular species. Here, we present a conceptual framework, literature review, and model demonstrating that the direction and magnitude of the response of group size to sudden resource shifts provides a strong indication of the underlying drivers of sociality. We catalog six functionally distinct mechanisms related to the acquisition of resources, and we model these mechanisms effects on the survival of individuals foraging in groups. We find that whether, and to what degree, optimal group size increases, decreases, or remains constant when resource abundance declines depends strongly on the dominant mechanism. Existing empirical data support our model predictions, and we demonstrate how our framework can be used to predict the dominant social benefit for particular species. Together, our framework and results show that a single easily measurable characteristic, namely, group size under different resource abundances, can illuminate the potential drivers of sociality across the tree of life.

animal behavior and cognition↗

bioRxiv2020

The wisdom of stalemates: consensus and clustering as filtering mechanisms for improving collective accuracy

Groups of organisms, from bacteria to fish schools to human societies, depend on their ability to make accurate decisions in an uncertain world. Most models of collective decision-making assume that groups reach a consensus during a decision-making bout, often through simple majority rule. In many natural and sociological systems, however, groups may fail to reach consensus, resulting in stalemates. Here, we build on opinion dynamics and collective wisdom models to examine how stalemates may affect the wisdom of crowds. For simple environments, where individuals have access to independent sources of information, we find that stalemates improve collective accuracy by selectively filtering out incorrect decisions. In complex environments, where individuals have access to both shared and independent information, this effect is even more pronounced, restoring the wisdom of crowds in regions of parameter space where large groups perform poorly when making decisions using majority rule. We identify network properties that tune the system between consensus and accuracy, providing mechanisms by which animals, or evolution, could dynamically adjust the collective decision-making process in response to the reward structure of the possible outcomes. Overall, these results highlight the adaptive potential of stalemale filtering for improving the decision-making abilities of group-living animals.

animal behavior and cognition↗

bioRxiv2018

Counteracting estimation bias and social influence to improve the wisdom of crowds

Aggregating multiple non-expert opinions into a collective estimate can improve accuracy across many contexts. However, two sources of error can diminish collective wisdom: individual estimation biases and information sharing between individuals. Here we measure individual biases and social influence rules in multiple experiments involving hundreds of individuals performing a classic numerosity estimation task. We first investigate how existing aggregation methods, such as calculating the arithmetic mean or the median, are influenced by these sources of error. We show that the mean tends to overestimate, and the median underestimate, the true value for a wide range of numerosities. Quantifying estimation bias, and mapping individual bias to collective bias, allows us to develop and validate three new aggregation measures that effectively counter sources of collective estimation error. In addition, we present results from a further experiment that quantifies the social influence rules that individuals employ when incorporating personal estimates with social information. We show that the corrected mean is remarkably robust to social influence, retaining high accuracy in the presence or absence of social influence, across numerosities, and across different methods for averaging social information. Utilizing knowledge of estimation biases and social influence rules may therefore be an inexpensive and general strategy to improve the wisdom of crowds.

animal behavior and cognition↗

bioRxiv2017

Optimal construction of army ant living bridges

Integrating the costs and benefits of collective behaviors is a fundamental challenge to understanding the evolution of group living. These costs and benefits can rarely be quantified simultaneously due to the complexity of the interactions within the group, or even compared to each other because of the absence of common metrics between them. The construction of living bridges by New World army ants - which they use to shorten their foraging trails - is a unique example of a collective behavior where costs and benefits have been experimentally measured and related to each other. As a result, it is possible to make quantitative predictions about when and how the behavior will be observed. In this paper, we extend a previous mathematical model of these costs and benefits into a general framework for analyzing the optimal formation, and final configuration, of army ant living bridges. We provide experimentally testable predictions of the final bridge position, as well as the optimal formation process for certain cases, for a wide range of scenarios, which more closely resemble common terrain obstacles that ants encounter in nature. As such, our framework offers a rare benchmark for determining the evolutionary pressures governing the evolution of a naturally occurring collective animal behavior.

animal behavior and cognition↗