| Literature DB >> 30232162 |
Jonathan N Pruitt1,2, Andrew Berdahl3,4, Christina Riehl5, Noa Pinter-Wollman6, Holly V Moeller7, Elizabeth G Pringle8, Lucy M Aplin9,10, Elva J H Robinson11, Jacopo Grilli4, Pamela Yeh6, Van M Savage6, Michael H Price4, Joshua Garland4, Ian C Gilby12, Margaret C Crofoot13, Grant N Doering7,2, Elizabeth A Hobson4.
Abstract
Animal social groups are complex systems that are likely to exhibit tipping points-which are defined as drastic shifts in the dynamics of systems that arise from small changes in environmental conditions-yet this concept has not been carefully applied to these systems. Here, we summarize the concepts behind tipping points and describe instances in which they are likely to occur in animal societies. We also offer ways in which the study of social tipping points can open up new lines of inquiry in behavioural ecology and generate novel questions, methods, and approaches in animal behaviour and other fields, including community and ecosystem ecology. While some behaviours of living systems are hard to predict, we argue that probing tipping points across animal societies and across tiers of biological organization-populations, communities, ecosystems-may help to reveal principles that transcend traditional disciplinary boundaries.Entities:
Keywords: collapse; complex system; cooperation; critical point; hysteresis; social network
Mesh:
Year: 2018 PMID: 30232162 PMCID: PMC6170811 DOI: 10.1098/rspb.2018.1282
Source DB: PubMed Journal: Proc Biol Sci ISSN: 0962-8452 Impact factor: 5.349
Figure 1.A hysteresis window between an environmental condition (e.g. temperature) and group behaviour (e.g. degree of infighting). This figure is modelled after a study on within-group conflict in response to heat stress in social spiders. Groups that have been in an agitated state (red) tend to remain agitated, whereas calm groups (blue) tend to remain calm. Therefore, there exists a set of intermediate environmental conditions (T1 < T < T2) where a group can be either calm or agitated depending on its historical dynamics. In the lower panel, solid lines represent stable equilibria states and the shaded regions show their basins of attraction. The dashed line is an unstable equilibrium, which demarks the boundary between the basins of attraction. The upper panels (A–E) provide an alternate abstraction of this system: for a given environmental condition, the group response tends to a low point on the ‘landscape’. The bottoms of the troughs in the upper panels are therefore stable equilibria and correspond to the locations of the solid red and blue lines in the lower panel (see ‘Y’ label for an example). Tipping points occur when a stable equilibrium (solid line/trough) collides with an unstable equilibrium (dashed line/peak) and is eliminated—at this point the system transitions suddenly to the alternate remaining equilibrium. In this system the tipping points are at T1 (when the system is in the agitated state and temperature is decreasing) and at T2 (when the system is in the calm state and temperature is increasing).
Figure 2.Social tipping points are characterized by an abrupt change in behaviour state caused by small changes in environmental parameters. Here, groups of territorial damselfish (brown fishes) may respond with vigilance and inspection (top image) towards intruders or not (bottom image) depending on whether food is limited. One sign of a possible tipping point is a change point in the data, where the data suddenly appear to be nonstationary. In the plot, this is depicted as a sudden change in the mean of aggressiveness (y-axis). If a model for aggressiveness is built for conditions where food supply is low, but then applied to cases where food supply is high, the model will have very large error. This reinforces the point that the old model is no longer valid for the new data if a tipping point has occurred. The three functions fitted to the identical data above have all been used to estimate the position of tipping points along environmental gradients, though the centre panel reinforces the point that entirely new models may be required to explain system properties before versus after a tipping point.
Figure 3.A hysteresis window depicting the relationship between group activity level (y-axis) in association with contrasting levels of predation risk (x-axis). At low levels of predation groups engage in social interactions that heighten group activity (1) but also distract groups from detecting small to moderate levels of predation risk (2). However, at some increased level of predation risk groups decrease activity and become vigilant (3), and extreme levels of risk will cause groups to go into hiding and cease activity (4). As risk dissipates, groups require a much lower level of risk to resume social activity (5).