Adversity magnifies the importance of social information in decision-making

Social copying drives a tipping point for nonlinear population collapse

Sudden changes in populations are ubiquitous in ecological systems, especially under perturbations. The agents of global change may increase the frequency and severity of anthropogenic perturbations, but complex populations' responses hamper our understanding of their dynamics and resilience. Furthermore, the long-term environmental and demographic data required to study those sudden changes are rare. Fitting dynamical models with an artificial intelligence algorithm to population fluctuations over 40 y in a social bird reveals that feedback in dispersal after a cumulative perturbation drives a population collapse. The collapse is well described by a nonlinear function mimicking social copying, whereby dispersal made by a few individuals induces others to leave the patch in a behavioral cascade for decision-making to disperse. Once a threshold for deterioration of the quality of the patch is crossed, there is a tipping point for a social response of runaway dispersal corresponding to social copying feedback. Finally, dispersal decreases at low population densities, which is likely due to the unwillingness of the more philopatric individuals to disperse. In providing the evidence of copying for the emergence of feedback in dispersal in a social organism, our results suggest a broader impact of self-organized collective dispersal in complex population dynamics. This has implications for the theoretical study of population and metapopulation nonlinear dynamics, including population extinction, and managing of endangered and harvested populations of social animals subjected to behavioral feedback loops.

Diversity of opinions promotes herding in uncertain crowds

Classic and recent studies demonstrate how we fall for the 'tyranny of the majority' and conform to the dominant trend when uncertain. However, in many social interactions outside of the laboratory, there is rarely a clearly identified majority and discerning who to follow might be challenging. Here, we asked whether in such conditions herding behaviour depends on a key statistical property of social information: the variance of opinions in a group. We selected a task domain where opinions are widely variable and asked participants (N = 650) to privately estimate the price of eight anonymous paintings. Then, in groups of five, they discussed and agreed on a shared estimate for four paintings. Finally, they provided revised individual estimates for all paintings. As predicted (https://osf.io/s89w4), we observed that group members converged to each other and boosted their confidence following social interaction. We also found evidence supporting the hypothesis that the more diverse groups show greater convergence, suggesting that the variance of opinions promotes herding in uncertain crowds. Overall, these findings empirically examine how, in the absence of a clear majority, the distribution of opinions relates to subjective feelings of confidence and herding behaviour.

Modeling human migration driven by changing mindset, agglomeration, social ties, and the environment

Migration is an adaptation strategy to unfavorable conditions and is governed by a complex set of socio-economic and environmental drivers. Here we identified important drivers relatively underrepresented in many migration models-CHanging mindset, Agglomeration, Social ties, and the Environment (CHASE)-and asked: How does the interplay between these drivers influence transient dynamics and long-term outcomes of migration? We addressed this question by developing and analyzing a parsimonious Markov chain model. Our findings suggest that these drivers interact in nonlinear and complex ways. The system exhibits legacy effects, highlighting the importance of including migrants' changing priorities. The increased characteristic population size of the system counter-intuitively leads to fewer surviving cities, and this effect is mediated by how fast migrants change their mindsets and how strong the social ties are. Strong social ties result in less diverse populations across cities, but this effect is influenced by how many cities remain. To our knowledge, this is the first time that these drivers are incorporated in one coherent, mechanistic, parsimonious model and the effects of their interplay on migration systematically studied. The complex interplay underscores the need to incorporate these drivers into mechanistic migration models and implement such models for real-world cases.

Dominating lengthscales of zebrafish collective behaviour

Collective behaviour in living systems is observed across many scales, from bacteria to insects, to fish shoals. Zebrafish have emerged as a model system amenable to laboratory study. Here we report a three-dimensional study of the collective dynamics of fifty zebrafish. We observed the emergence of collective behaviour changing between ordered to randomised, upon adaptation to new environmental conditions. We quantify the spatial and temporal correlation functions of the fish and identify two length scales, the persistence length and the nearest neighbour distance, that capture the essence of the behavioural changes. The ratio of the two length scales correlates robustly with the polarisation of collective motion that we explain with a reductionist model of self-propelled particles with alignment interactions.

Follow the straggler: zebrafish use a simple heuristic for collective decision-making

Animal groups often make decisions sequentially, from the front to the back of the group. In such cases, individuals can use the choices made by earlier ranks, a form of social information, to inform their own choice. The optimal strategy for such decisions has been explored in models which differ on, for example, whether or not agents take into account the sequence of observed choices. The models demonstrate that choices made later in a sequence are more informative, but it is not clear if animals use this information or rely instead on simpler heuristics, such as quorum rules. We show that a simple rule 'copy the last observed choice', gives similar predictions to those of optimal models for most likely sequences. We trained groups of zebrafish to choose one arm of a Y-maze and used them to demonstrate various sequences to naive fish. We show that the naive fish appear to use a simple rule, most often copying the choice of the last demonstrator, which results in near-optimal choices at a fraction of the computational cost.

Decrease in social cohesion in a colonial seabird under a perturbation regime

Social interactions, through influence on behavioural processes, can play an important role in populations’ resilience (i.e. ability to cope with perturbations). However little is known about the effects of perturbations on the strength of social cohesion in wild populations. Long-term associations between individuals may reflect the existence of social cohesion for seizing the evolutionary advantages of social living. We explore the existence of social cohesion and its dynamics under perturbations by analysing long-term social associations, in a colonial seabird, the Audouin’s gull Larus audouinii, living in a site experiencing a shift to a perturbed regime. Our goals were namely (1) to uncover the occurrence of long-term social ties (i.e. associations) between individuals and (2) to examine whether the perturbation regime affected this form of social cohesion. We analysed a dataset of more than 3500 individuals from 25 years of monitoring by means of contingency tables and within the Social Network Analysis framework. We showed that associations between individuals are not only due to philopatry or random gregariousness but that there are social ties between individuals over the years. Furthermore, social cohesion decreased under the perturbation regime. We sustain that perturbations may lead not only to changes in individuals’ behaviour and fitness but also to a change in populations’ social cohesion. The consequences of decreasing social cohesion are still not well understood, but they can be critical for the population dynamics of social species.

Quorums enable optimal pooling of independent judgements in biological systems

Collective decision-making is ubiquitous, and majority-voting and the Condorcet Jury Theorem pervade thinking about collective decision-making. Thus, it is typically assumed that majority-voting is the best possible decision mechanism, and that scenarios exist where individually-weak decision-makers should not pool information. Condorcet and its applications implicitly assume that only one kind of error can be made, yet signal detection theory shows two kinds of errors exist, 'false positives' and 'false negatives'. We apply signal detection theory to collective decision-making to show that majority voting is frequently sub-optimal, and can be optimally replaced by quorum decision-making. While quorums have been proposed to resolve within-group conflicts, or manage speed-accuracy trade-offs, our analysis applies to groups with aligned interests undertaking single-shot decisions. Our results help explain the ubiquity of quorum decision-making in nature, relate the use of sub- and super-majority quorums to decision ecology, and may inform the design of artificial decision-making systems.

Editorial note

This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).

Collective decision making by rational individuals

The patterns and mechanisms of collective decision making in humans and animals have attracted both empirical and theoretical attention. Of particular interest has been the variety of social feedback rules and the extent to which these behavioral rules can be explained and predicted from theories of rational estimation and decision making. However, models that aim to model the full range of social information use have incorporated ad hoc departures from rational decision-making theory to explain the apparent stochasticity and variability of behavior. In this paper I develop a model of social information use and collective decision making by fully rational agents that reveals how a wide range of apparently stochastic social decision rules emerge from fundamental information asymmetries both between individuals and between the decision makers and the observer of those decisions. As well as showing that rational decision making is consistent with empirical observations of collective behavior, this model makes several testable predictions about how individuals make decisions in groups and offers a valuable perspective on how we view sources of variability in animal, and human, behavior.