Stewardship of global collective behavior.

Collective behavior provides a framework for understanding how the actions and properties of groups emerge from the way individuals generate and share information. In humans, information flows were initially shaped by natural selection yet are increasingly structured by emerging communication technologies. Our larger, more complex social networks now transfer high-fidelity information over vast distances at low cost. The digital age and the rise of social media have accelerated changes to our social systems, with poorly understood functional consequences. This gap in our knowledge represents a principal challenge to scientific progress, democracy, and actions to address global crises. We argue that the study of collective behavior must rise to a "crisis discipline" just as medicine, conservation, and climate science have, with a focus on providing actionable insight to policymakers and regulators for the stewardship of social systems.

Individual and collective encoding of risk in animal groups.

The need to make fast decisions under risky and uncertain conditions is a widespread problem in the natural world. While there has been extensive work on how individual organisms dynamically modify their behavior to respond appropriately to changing environmental conditions (and how this is encoded in the brain), we know remarkably little about the corresponding aspects of collective information processing in animal groups. For example, many groups appear to show increased "sensitivity" in the presence of perceived threat, as evidenced by the increased frequency and magnitude of repeated cascading waves of behavioral change often observed in fish schools and bird flocks under such circumstances. How such context-dependent changes in collective sensitivity are mediated, however, is unknown. Here we address this question using schooling fish as a model system, focusing on 2 nonexclusive hypotheses: 1) that changes in collective responsiveness result from changes in how individuals respond to social cues (i.e., changes to the properties of the "nodes" in the social network), and 2) that they result from changes made to the structural connectivity of the network itself (i.e., the computation is encoded in the "edges" of the network). We find that despite the fact that perceived risk increases the probability for individuals to initiate an alarm, the context-dependent change in collective sensitivity predominantly results not from changes in how individuals respond to social cues, but instead from how individuals modify the spatial structure, and correspondingly the topology of the network of interactions, within the group. Risk is thus encoded as a collective property, emphasizing that in group-living species individual fitness can depend strongly on coupling between scales of behavioral organization.

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 (an effect we call stalemate filtering). 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 stalemate filtering for improving the decision-making abilities of group-living animals.

The lateral line is necessary for blind cavefish rheotaxis in non-uniform flow.

When encountering a unidirectional flow, many fish exhibit an unconditioned orienting response known as rheotaxis. This multisensory behavior can reportedly involve visual, vestibular, tactile and lateral line cues. However, the precise circumstances under which different senses contribute are still unclear and there is considerable debate, in particular, about the contributions of the lateral line. In this study, we investigate the rheotactic behavior of blind cavefish under conditions of spatially non-uniform flow (a jet stream), which in theory, should promote reliance on lateral line cues. The behavior of individual lateral line enabled and disabled fish was videorecorded under IR light in a square arena that prevented streamwise biases and that contained a narrow jet stream in the center of the tank. Whereas the stream's peak velocity (8 cm s(-1)) declined very little in the streamwise direction, it declined steeply in the cross-stream direction (∼3-4.5 cm s(-1) cm(-1)). Lateral line enabled fish showed higher levels of orientation to the stream and its source (a 1-cm-wide nozzle) when in the central (jet stream) region of the tank compared with surrounding regions, whereas lateral line disabled fish showed random orientations in all regions of the tank. The results of this study indicate that the spatial characteristics of flow play a role in determining the sensory basis of rheotaxis.

Sedentary behavior as a factor in determining lateral line contributions to rheotaxis.

Rheotaxis is a robust, multisensory behavior with many potential benefits for fish and other aquatic animals. Visual (optic flow) cues appear to be sufficient for rheotaxis, but other sensory cues can clearly compensate for the loss of vision. The role of various non-visual sensory systems, in particular the flow-sensing lateral line, is poorly understood, largely because of widely varying methods and sensory conditions for studying rheotaxis. Here, we examine how sedentary behavior under visually deprived conditions affects the relative importance of lateral line cues in two species: one that is normally sedentary (the three-lined corydoras, Corydoras trilineatus) and one that normally swims continuously along the substrate (the blind cavefish, Astyanax mexicanus). No effect of lateral line disruption on rheotactic performance was found in blind cavefish, which were significantly more mobile than three-lined corydoras. By contrast, rheotaxis was significantly impaired at low, but not high, flow speeds in lateral-line-disabled corydoras. In addition, lateral-line-enabled corydoras were characterized by decreased mobility and increased rheotactic performance relative to lateral-line-disabled fish. Taken together, these results suggest that sedentary behavior is an important factor in promoting reliance on lateral line cues.

Addressing climate change with behavioral science: A global intervention tournament in 63 countries.

Effectively reducing climate change requires marked, global behavior change. However, it is unclear which strategies are most likely to motivate people to change their climate beliefs and behaviors. Here, we tested 11 expert-crowdsourced interventions on four climate mitigation outcomes: beliefs, policy support, information sharing intention, and an effortful tree-planting behavioral task. Across 59,440 participants from 63 countries, the interventions' effectiveness was small, largely limited to nonclimate skeptics, and differed across outcomes: Beliefs were strengthened mostly by decreasing psychological distance (by 2.3%), policy support by writing a letter to a future-generation member (2.6%), information sharing by negative emotion induction (12.1%), and no intervention increased the more effortful behavior-several interventions even reduced tree planting. Last, the effects of each intervention differed depending on people's initial climate beliefs. These findings suggest that the impact of behavioral climate interventions varies across audiences and target behaviors.

The spatiotemporal dynamics of rheotactic behavior depends on flow speed and available sensory information.

Rheotaxis is a robust, multisensory behavior with many potential benefits for fish and other aquatic organisms. Visual (optic flow) cues appear to be sufficient for rheotaxis, but other sensory cues can clearly compensate for the loss of vision. Nevertheless, the nature of multisensory interactions and the relative contributions of different senses under varying conditions are poorly understood - largely because there is so little description of the actual behavior. Here, we examined the effects of different flow speeds and different sensory conditions on the spatiotemporal dynamics of rheotaxis. Although the overall ability of giant danio (Devario aequipinnatus) to head upstream is largely unaffected by either unimodal or bimodal deprivation of visual and/or lateral line senses, the spatiotemporal form of the behavior is altered in subtle ways. When deprived of vision, fish move further upstream, but the angular accuracy of the upstream heading is reduced. In addition, visually deprived fish exhibit left/right sweeping movements near the upstream barrier at low flow speeds. Sweeping movements are abolished when these fish are additionally deprived of lateral line information. These results indicate that fish adopt different sensorimotor strategies to compensate for the loss of one or more senses and that the nature of multisensory interactions is a complex function of flow speed.

Combining interventions to reduce the spread of viral misinformation.

Misinformation online poses a range of threats, from subverting democratic processes to undermining public health measures. Proposed solutions range from encouraging more selective sharing by individuals to removing false content and accounts that create or promote it. Here we provide a framework to evaluate interventions aimed at reducing viral misinformation online both in isolation and when used in combination. We begin by deriving a generative model of viral misinformation spread, inspired by research on infectious disease. By applying this model to a large corpus (10.5 million tweets) of misinformation events that occurred during the 2020 US election, we reveal that commonly proposed interventions are unlikely to be effective in isolation. However, our framework demonstrates that a combined approach can achieve a substantial reduction in the prevalence of misinformation. Our results highlight a practical path forward as misinformation online continues to threaten vaccination efforts, equity and democratic processes around the globe.

Both prey and predator features predict the individual predation risk and survival of schooling prey.

Predation is one of the main evolutionary drivers of social grouping. While it is well appreciated that predation risk is likely not shared equally among individuals within groups, its detailed quantification has remained difficult due to the speed of attacks and the highly dynamic nature of collective prey response. Here, using high-resolution tracking of solitary predators (Northern pike) hunting schooling fish (golden shiners), we not only provide insights into predator decision-making, but show which key spatial and kinematic features of predator and prey predict the risk of individuals to be targeted and to survive attacks. We found that pike tended to stealthily approach the largest groups, and were often already inside the school when launching their attack, making prey in this frontal 'strike zone' the most vulnerable to be targeted. From the prey's perspective, those fish in central locations, but relatively far from, and less aligned with, neighbours, were most likely to be targeted. While the majority of attacks were successful (70%), targeted individuals that did manage to avoid being captured exhibited a higher maximum acceleration response just before the attack and were further away from the pike's head. Our results highlight the crucial interplay between predators' attack strategy and response of prey underlying the predation risk within mobile animal groups.

Vortex phase matching as a strategy for schooling in robots and in fish.

It has long been proposed that flying and swimming animals could exploit neighbour-induced flows. Despite this it is still not clear whether, and if so how, schooling fish coordinate their movement to benefit from the vortices shed by others. To address this we developed bio-mimetic fish-like robots which allow us to measure directly the energy consumption associated with swimming together in pairs (the most common natural configuration in schooling fish). We find that followers, in any relative position to a near-neighbour, could obtain hydrodynamic benefits if they exhibit a tailbeat phase difference that varies linearly with front-back distance, a strategy we term 'vortex phase matching'. Experiments with pairs of freely-swimming fish reveal that followers exhibit this strategy, and that doing so requires neither a functioning visual nor lateral line system. Our results are consistent with the hypothesis that fish typically, but not exclusively, use vortex phase matching to save energy.

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. Using knowledge of estimation biases and social influence rules may therefore be an inexpensive and general strategy to improve the wisdom of crowds.