Epilogue

Complex social animal groups behave as self-organized, single structures: they feed together, they defend against predators together, they escape from perturbations and disperse and migrate together and they share information. It is modestly evident that many individuals sharing information about their environment may be more successful in coping with perturbations than solitary individuals gathering information on their own. The group exists for and by means of all the individuals, and these exist for and by means of the group. Social groups have emergent properties that cannot be easily explained by either selection or self-organization. Yet, sociality has been shaped by the two forces. How sociality has evolved by selection is puzzling also because it confronts the benefits of the group versus the benefits of the individual, which is a historically debated theme. There are many other open questions about sociality that I have explored in this book. But in the end, the process that has fascinated me the most is social copying. Despite the sophisticated mechanisms evolved in increasing information in social groups—which has culminated in humans with language and technological interconnections—it is impressive how a simple behaviour such as social copying has maintained its strength when individuals make any kind of decisions, from insignificant to transcendent....

Conclusions and Prospects

Throughout the book, I have been searching for empirical examples and theories dealing with how perturbations trigger behavioural feedback responses in social animals, how these responses affect the decision to disperse between patches, and the consequences of dispersal for complex, nonlinear population dynamics. What seems quite clear is that social feedbacks—and especially runaway dispersal by copying—do play an important role in those responses, compared to solitary species. Although philopatry to the patch has many benefits, perturbations may decrease the suitability of this patch. When a patch is perturbed, do social species show different responses than solitary species? Since evolution has selected for maximizing fitness prospects, individuals living either in groups or in solitary will try to avoid the detrimental effects of the perturbation, for instance by leaving the patch. The behavioural mechanisms triggered by perturbations are similar for both social and solitary species: increase of information gathering to reduce uncertainty and the use of this updated information to make optimal decisions about either staying or leaving. Thus, the answer is that solitary and social species show similar responses to perturbations. Nevertheless, the way those behavioural mechanisms operate is rather different between social and solitary species: in the former, information is shared among individuals, and decisions about when to leave the patch and where to go are made not only using private or personal information, but mostly using social information. Last but not least, there is social copying, a trend to copy in a nonrational way what others have decided before. This social copying, also called conformity, may trigger what I termed runaway dispersal: perturbations may accumulate over time, decreasing resilience of the social group until attaining a tipping point. Once this threshold is surpassed, the decision to disperse is led by a few individuals, and this decision is copied by the rest of the group in an autocatalytic way....

Evolution of Sociality and Nonlinear Population Dynamics

Sociality appears in many life histories during evolution. Some eusocial bees show evolutionary reversions to solitary behaviour, and populations of the same species can be solitary or social, likely depending on local environmental features. Social species need a minimum size to perform adaptive behaviours, such as the search for resources, which is crucial especially under perturbations. This minimum size may become a threshold, setting a phase transition for separating two stable states, from disorganized and maladaptive to organized and adaptive, which also shows hysteresis. The chapter also explores evolution via facilitation or cooperation (e.g. social information) under the theoretical framework of multilevel selection, by which there is likely an effect of the social group’s genes on individual fitness. Perturbations appear as a strong source of evolutionary processes. In humans, warfare acts as a very powerful selective pressure for competition between groups and thus for cooperation. Sociality has also many costs, such as a higher risk for the spread of infectious disease, the appearance of traps by social haunting philopatry, stronger aggression and competition, and a higher risk of being attacked by predators. Finally, the evolution of cultures is explored; optimization of social learning, social copying, and cultural transmission may have nonlinear consequences for population dynamics.

Introductory Remarks on Perturbations, Cognition, Dispersal, Sociality, and Nonlinear Population Dynamics

This chapter defines the different terms and processes that are the main themes of the book. This chapter starts by explaining how perturbations increase uncertainty, which pushes individuals to update and gather information. In social animals, this information is shared through the social network, which is used to make a decision about staying or leaving the patch. Finally, this decision is not going to be made individually but rather based on decisions made by others. Perturbations may accumulate until surpassing a tipping point; then the first individuals may start to disperse and the rest copies this behaviour, which cascade as long as more individuals disperse. This autocatalytic process is termed runaway dispersal, which may result in nonlinear population dynamics, such as hysteresis, critical transitions, and transient phenomena. These dynamics should occur at the local level (e.g. patch collapse) and metapopulation level (e.g. extinction–colonization turnover).

Prologue

The idea of combining social species, information, perturbations, and nonlinear responses related to dispersal originated naively a long time ago, in the Gulf of Roses in the western Mediterranean. As a kid, I used to spend holidays in a tiny village nearby the ruins of Empuries, a magical place where an ancient Greek colony was founded in 575 BC, later occupied by the Romans. I remember going to the beach where I would place my towel sheltered from the wind behind a large section of the ancient Greek dock built on huge stones. More than 2100 years later, one can still enjoy the mosaics, the temple columns, and the large walls protecting the Roman city from the outside. Once, while visiting this place with my parents, I asked them why that magnificent settlement was abandoned, vanished, and was buried by dust, but I did not get a convincing answer (even now, I would not be able to answer this question if asked by my own kids). Archaeologists believe that the collapse of Empuries was caused by a combination of factors, namely the appearance of other flourishing communities (Barcino and Tarraco, or Barcelona and Tarragona as they are known today) and a perturbed environmental regime, caused by an accumulation of sediments resulting from a nearby river, which disabled the use of the harbour. These factors likely contributed to dispersal, which ended up in the abandonment of the city. In any case, my wonderings about Empuries remained dormant for the next 40 years. But these questions slowly awakened when one of my fieldwork studies monitoring Audouin’s gulls at the Ebro Delta was unexpectedly affected by a perturbation that began in the mid-1990s. This breeding patch, which came to hold almost 75% of the total world population of this once endangered species, has collapsed in recent times, but strikingly it remained apparently resilient for many years (Figure P1). The Ebro Delta shared with Empuries the characteristic of being an exceptionally suitable habitat allowing a population to flourish, prior to eventual collapse. Empuries and the Ebro Delta represent all of the issues I have come to be interested in as a researcher: a social group thriving in a favourable patch, perturbations generating dispersal, and a nonlinear response leading to patch extinction (as a form of a new stable state). Some years ago a reading of Marten Scheffer’s book about critical transitions was also very inspiring. Understanding why Empuries and the Ebro Delta collapsed has intrigued my curiosity over the past several years, and has led me to take the leap in writing this book....

Runaway Dispersal in Social Species

Local populations are in most cases open and connected with other populations through dispersal. Dispersal, aside from its multiplicative nature, has a demographic additive effect for the spatiotemporal dynamics and extinction–colonization turnover of the donor and the receiver populations. Population dynamics are more sensitive to dispersal under perturbations, because dispersing is a resilience mechanism to avoid or reduce novel mortality risk. Furthermore, dispersing individuals carry information, a process that may create dynamic landscape information networks. In social species, the decision to stay or to disperse is made based on decisions made by others. When perturbations accumulate and jeopardize survival or fecundity, leading individuals may decide to disperse, and this decision is copied by others, generating a runaway dispersal to other patches. The decision trade-off between staying and dispersing depends on the dynamic spatiotemporal heterogeneity in patch quality. What matters for making a decision is not the difference in patch quality, but the ratio between the patch currently occupied and the rest of the patches. Decision-making in social animals for dispersing is explored under the frameworks of the prospect theory, the neoclassical economic theory, and the hypercycle theory. It is also shown how runaway dispersal may occur from a theoretical point of view due to a very simple mechanism of copying others in a density-dependent manner. This simple mechanism overruns a rational scenario when making decisions in social animals. This chapter ends by assessing the potential consequences of runaway dispersal for nonlinear responses in communities and entire ecosystems.

The Case of Audouin’s Gulls at Punta de la Banya

To illustrate the argument of the book, this chapter discusses the case study of the collapse of the world’s largest local population of the Audouin’s gull, a social bird. This bird was considered the world’s most endangered gull at the end of the 1960s. Its population was estimated at only 1,000 breeding pairs scattered in tiny colonies on remote rocky islets in the Mediterranean, where the species was confined. In 1981 the gulls established a colony at Punta de la Banya peninsula, and only 14 years after colonization, the patch held more than 10,000 breeding females and almost 75% of the total world population. Lack of competition and predation and a large number of resources determined a patch of high quality, which attracted immigrant gulls from the outside and allowed gulls to reproduce at very high rates. A perturbation regime caused by the arrival of carnivores caused the local population to crash due to runaway dispersal to other patches. The link between the social process of collective dispersal and the nonlinear collapse is demonstrated by a population model that uses optimization methods. Before the onset of dispersal by social copying, the population showed a long transient phase during which resilience mechanisms were activated.

Extinction, Nonlinear Dynamics, and Sociality

This chapter assesses how social feedbacks, and particularly runaway dispersal resulting from social copying, influence population extinction. Several forms of the logistic model are built to assess the role of density-dependent and cooperation mechanisms in the generation of nonlinearities in the path to extinction. Interestingly, transience to an extinction stable state may be delayed and may result in quasi-extinction population queues. Some empirical examples of quasi-extinction stable states are shown, including human populations. It is also explained how social sunk-cost effects—when individuals are trapped in a patch due to its momentum of suitability, social copying, or emotional drivers—can influence these quasi-extinction dynamics. The chapter also reviews several statistical tools for anticipating critical transitions and other nonlinear behaviours in populations. These tools include the early warning signals, which quantify when a critical threshold is approaching.

Population Dynamics of Social Species under Perturbations

The detection of abrupt changes in natural populations of social and nonsocial animals as a result of perturbations is challenging. This chapter highlights some empirical examples from the literature and the author’s own studies, and the responses of populations of species with different degree of sociality are compared. To overcome the difficulties of obtaining field population data, theoretical approaches can be very useful for simulating these responses from social feedbacks. These models show the influence of social information and social copying to generate nonlinear population dynamics, such as bifurcations and cascades. The chapter’s final section explores the stability properties of populations subjected to perturbations and the role of social feedbacks for resilience. These properties depend on the time of occupation of the patch, its suitability compared to other patches, and the type of perturbation (e.g. pulsed, in regime, or in combination). This section ends by exploring how social copying influences collective cultural innovations of social populations under perturbations. For instance, the American Pueblo tribe colonized riverine habitats and changed their way of living following the collapse of their original habitat due to droughts and tribal fights.