Robustness of self-organised systems to changes in behaviour: an example from real and simulated self-organised snail aggregations

Group or population level self-organised systems comprise many individuals displaying group-level emergent properties. Current theory indicates that individual-level behaviours have an effect on the final group-level behaviour; that is, self-organised systems are sensitive to small changes in individual behaviour. Here we examine a self-organised behaviour in relation to environmentally-driven individual-level changes in behaviour, using both natural systems and computer simulations. We demonstrate that aggregations of intertidal snails slightly decrease in size when, owing to hotter and more desiccating conditions, individuals forage for shorter periods--a seemingly non-adaptive behaviour for the snails since aggregation reduces desiccation stress. This decrease, however, only occurs in simple experimental systems (and simulations of these systems). When studied in their natural and more complex environment, and simulations of such an environment, using the same reduced foraging time, no difference in aggregation behaviour was found between hot and cool days. These results give an indication of how robust self-organised systems are to changes in individual-level behaviour. The complexity of the natural environment and the interactions of individuals with this environment, therefore, can result in self-organised systems being more resilient to individual-level changes than previously assumed.     

Collective predator evasion: Putting the criticality hypothesis to the test

According to the criticality hypothesis, collective biological systems should operate in a special parameter region, close to so-called critical points, where the collective behavior undergoes a qualitative change between different dynamical regimes. Critical systems exhibit unique properties, which may benefit collective information processing such as maximal responsiveness to external stimuli. Besides neuronal and gene-regulatory networks, recent empirical data suggests that also animal collectives may be examples of self-organized critical systems. However, open questions about self-organization mechanisms in animal groups remain: Evolutionary adaptation towards a group-level optimum (group-level selection), implicitly assumed in the “criticality hypothesis”, appears in general not reasonable for fission-fusion groups composed of non-related individuals. Furthermore, previous theoretical work relies on non-spatial models, which ignore potentially important self-organization and spatial sorting effects. Using a generic, spatially-explicit model of schooling prey being attacked by a predator, we show first that schools operating at criticality perform best. However, this is not due to optimal response of the prey to the predator, as suggested by the “criticality hypothesis”, but rather due to the spatial structure of the prey school at criticality. Secondly, by investigating individual-level evolution, we show that strong spatial self-sorting effects at the critical point lead to strong selection gradients, and make it an evolutionary unstable state. Our results demonstrate the decisive role of spatio-temporal phenomena in collective behavior, and that individual-level selection is in general not a viable mechanism for self-tuning of unrelated animal groups towards criticality.     

Behavioral states help translate dispersal movements into spatial distribution patterns of floaters

Within the field of spatial ecology, it is important to study animal movements in order to better understand population dynamics. Dispersal is a nonlinear process through which different behavioral mechanisms could affect movement patterns. One of the most common approaches to analyzing the trajectories of organisms within patches is to use random-walk models to describe movement features. These models express individual movements within a specific area in terms of random-walk parameters in an effort to relate movement patterns to the distributions of organisms in space. However, only using the movement trajectories of individuals to predict the spatial spread of animal populations may not fit the complex distribution of individuals across heterogeneous environments. When we empirically tested the results from a random-walk model (a residence index) used to predict the spatial equilibrium distribution of individuals, we found that the index severely underestimated the spatial spread of dispersing individuals. We believe this is because random-walk models only account for the effects of environmental conditions on individual movements, completely overlooking the crucial influence of behavior changes over time. In the future, both aspects should be accounted for when predicting general rules of (meta)population abundance, distribution, and dynamics from patterns of animal movements.     

Endocrine mechanisms,behavioral phenotypes and plasticity: known relationships and open questions

Behavior of wild vertebrate individuals can vary in response to environmental or social factors. Such within-individual behavioral variation is often mediated by hormonal mechanisms. Hormones also serve as a basis for among-individual variations in behavior including animal personalities and the degree of responsiveness to environmental and social stimuli. How do relationships between hormones and behavioral traits evolve to produce such behavioral diversity within and among individuals? Answering questions about evolutionary processes generating among-individual variation requires characterizing how specific hormones are related to variation in specific behavioral traits, whether observed hormonal variation is related to individual fitness and, whether hormonal traits are consistent (repeatable) aspects of an individual's phenotype. With respect to within-individual variation, we need to improve our insight into the nature of the quantitative relationships between hormones and the traits they regulate, which in turn will determine how they may mediate behavioral plasticity of individuals. To address these questions, we review the actions of two steroid hormones, corticosterone and testosterone, in mediating changes in vertebrate behavior, focusing primarily on birds. In the first part, we concentrate on among-individual variation and present examples for how variation in corticosterone concentrations can relate to behaviors such as exploration of novel environments and parental care. We then review studies on correlations between corticosterone variation and fitness, and on the repeatability over time of corticosterone concentrations. At the end of this section, we suggest that further progress in our understanding of evolutionary patterns in the hormonal regulation of behavior may require, as one major tool, reaction norm approaches to characterize hormonal phenotypes as well as their responses to environments.In the second part, we discuss types of quantitative relationships between hormones and behavioral traits within individuals, using testosterone as an example. We review conceptual models for testosterone-behavior relationships and discuss the relevance of these models for within-individual plasticity in behavior. Next, we discuss approaches for testing the nature of quantitative relationships between testosterone and behavior, concluding that again reaction norm approaches might be a fruitful way forward.We propose that an integration of new tools, especially of reaction norm approaches into the field of behavioral endocrinology will allow us to make significant progress in our understanding of the mechanisms, the functional implications and the evolution of hormone–behavior relationships that mediate variation both within and among individuals. This knowledge will be crucial in light of already ongoing habitat alterations due to global change, as it will allow us to evaluate the mechanisms as well as the capacity of wild populations to adjust hormonally-mediated behaviors to altered environmental conditions.     

Levels of selection, altruism, and primate behavior.

Altruistic behaviors seem anomalous from a traditional view of Darwinian natural selection, and evolutionary explanations for them have generated much discussion. The debate centers around four major explanations: classic individual-level selection, reciprocity and game theory, kin selection, and trait-group selection. The historical context and defining criteria of each model must be reviewed before its validity can be assessed. Of these proposed mechanisms, group selection historically has been the most controversial. Although the extent to which empirical data support group selection hypotheses is uncertain, there is evidence for group-level selection among avirulent virus strains and foraging ant queens. Researchers studying mammalian behavior, particularly primatologists, have largely dismissed models of group-level selection. Most discussion of altruism among primates has focused on differences in fitness among individuals within a single group, but students of altruistic behaviors exhibited by primates also need to investigate intergroup variation with respect to these behaviors. Various altruistic behaviors are likely to have evolved through different forms of selection, and each example of apparent altruism therefore needs to be evaluated separately.     

A framework to evaluate whether to pool or separate behaviors in a multilayer network

A multilayer network approach combines different network layers,which are connected by interlayer edges,to create a single mathematical object.These networks can contain a variety of information types and represent different aspects of a system.However,the process for selecting which information to include is not always straightforward.Using data on 2 agonistic behaviors in a captive population of monk parakeets(Myiopsitta monachus),we developed a framework for investigating how pooling or splitting behaviors at the scale of dyadic relationships(between 2 individuals)affects individual-and group-level social properties.We designed 2 reference models to test whether randomizing the number of interactions across behavior types results in similar structural patterns as the observed data.Although the behaviors were correlated,the first reference model suggests that the 2 behaviors convey different information about some social properties and should therefore not be pooled.However,once we controlled for data sparsity,we found that the observed measures corresponded with those from the second reference model.Hence,our initial result may have been due to the unequal frequencies of each behavior.Overall,our findings support pooling the 2 behaviors.Awareness of how selected measurements can be affected by data properties is warranted,but nonetheless our framework disentangles these efforts and as a result can be used for myriad types of behaviors and questions.This framework will help researchers make informed and data-driven decisions about which behaviors to pool or separate,prior to using the data in subsequent multilayer network analyses.     

Adaptive site selection rules and variation in group size of barn swallows: individual decisions predict population patterns

Variation in group size is ubiquitous among socially breeding organisms. An alternative to the traditional examination of average reproductive success in groups of different sizes is to examine individual decision making by determining the cues used for site selection. Once factors used for decision making are known, one can determine whether group-level patterns, such as group size variation, are emergent properties of individual-level decision rules. The advantage of this alternative approach is that it can explain the distribution of group sizes rather than just the occurrence of optimal group sizes. Using barn swallows, I tested, but did not support, the hypothesis that individuals settle at sites based on the previous success of conspecifics (i.e., performance-based conspecific attraction). Instead, I demonstrate that an adaptive site selection decision rule--to breed where it is possible to reuse previously constructed nests--predicts 83% of the variation in the number of breeding pairs at a site. Furthermore, experimental nest removals demonstrated that settlement decisions are also strongly influenced by site familiarity. I discuss the interaction of the cue-based site selection rule with the occurrence of site fidelity and how, more generally, a consideration of individual-level decision rules can improve our understanding of variation in many social behaviors.     

Spatial pattern as an adaptive phenotype

Spatial patterns are common in nature across a broad range of scales, from body coloration patterns of animals to clustering of vegetation. The ultimate causes of these patterns are viewed very differently depending on whether they are traits of individuals or properties of aggregations. Traits of individuals are usually considered to be shaped directly by selection, while patterns of aggregation are typically viewed as incidental side effects of some other underlying processes or environmental heterogeneity. However, given the powerful influence that spatial structure can have on the susceptibility of a population to a dispersal-limited predator or pathogen, it may be useful to consider the possibility that spatial structure per se could serve as an anti-enemy adaptive phenotype. This group-level trait could evolve only if selection at the individual level does not overwhelm higher-level selection. To explore the plausibility of spatial structure as an adaptive phenotype, I consider the specific case of a spatially-explicit, evolutionary host–pathogen model. This model demonstrates the evolution of reproductive restraint, resulting in a low-density, poorly-connected landscape of host clusters that is resistant to the spread of the pathogen. Reimagining spatial structure as an adaptive phenotype may generate new insights of both theoretical and practical significance.     

Heritable differences in schooling behavior among threespine stickleback populations revealed by a novel assay

Identifying the proximate and ultimate mechanisms of social behavior remains a major goal of behavioral biology. In particular, the complex social interactions mediating schooling behavior have long fascinated biologists, leading to theoretical and empirical investigations that have focused on schooling as a group-level phenomenon. However, methods to examine the behavior of individual fish within a school are needed in order to investigate the mechanisms that underlie both the performance and the evolution of schooling behavior. We have developed a technique to quantify the schooling behavior of an individual in standardized but easily manipulated social circumstances. Using our model school assay, we show that threespine sticklebacks (Gasterosteus aculeatus) from alternative habitats differ in behavior when tested in identical social circumstances. Not only do marine sticklebacks show increased association with the model school relative to freshwater benthic sticklebacks, they also display a greater degree of parallel swimming with the models. Taken together, these data indicate that marine sticklebacks exhibit a stronger tendency to school than benthic sticklebacks. We demonstrate that these population-level differences in schooling tendency are heritable and are shared by individuals within a population even when they have experienced mixed-population housing conditions. Finally, we begin to explore the stimuli that elicit schooling behavior in these populations. Our data suggest that the difference in schooling tendency between marine and benthic sticklebacks is accompanied by differential preferences for social vs. non-social and moving vs. stationary shelter options. Our study thus provides novel insights into the evolution of schooling behavior, as well as a new experimental approach to investigate the genetic and neural mechanisms that underlie this complex social behavior.     

Deciphering Interactions in Moving Animal Groups

Collective motion phenomena in large groups of social organisms have long fascinated the observer, especially in cases, such as bird flocks or fish schools, where large-scale highly coordinated actions emerge in the absence of obvious leaders. However, the mechanisms involved in this self-organized behavior are still poorly understood, because the individual-level interactions underlying them remain elusive. Here, we demonstrate the power of a bottom-up methodology to build models for animal group motion from data gathered at the individual scale. Using video tracks of fish shoal in a tank, we show how a careful, incremental analysis at the local scale allows for the determination of the stimulus/response function governing an individual''s moving decisions. We find in particular that both positional and orientational effects are present, act upon the fish turning speed, and depend on the swimming speed, yielding a novel schooling model whose parameters are all estimated from data. Our approach also leads to identify a density-dependent effect that results in a behavioral change for the largest groups considered. This suggests that, in confined environment, the behavioral state of fish and their reaction patterns change with group size. We debate the applicability, beyond the particular case studied here, of this novel framework for deciphering interactions in moving animal groups.     

Socialized medicine: Individual and communal disease barriers in honey bees

Honey bees are attacked by numerous parasites and pathogens toward which they present a variety of individual and group-level defenses. In this review, we briefly introduce the many pathogens and parasites afflicting honey bees, highlighting the biology of specific taxonomic groups mainly as they relate to virulence and possible defenses. Second, we describe physiological, immunological, and behavioral responses of individual bees toward pathogens and parasites. Third, bees also show behavioral mechanisms for reducing the disease risk of their nestmates. Accordingly, we discuss the dynamics of hygienic behavior and other group-level behaviors that can limit disease. Finally, we conclude with several avenues of research that seem especially promising for understanding host–parasite relationships in bees and for developing breeding or management strategies for enhancing honey bee health. We discuss how human efforts to maintain healthy colonies intersect with similar efforts by the bees, and how bee management and breeding protocols can affect disease traits in the short and long term.     

Group behaviour in physical,chemical and biological systems

Groups exhibit properties that either are not perceived to exist, or perhaps cannot exist, at the individual level. Such ‘emergent’ properties depend on how individuals interact, both among themselves and with their surroundings. The world of everyday objects consists of material entities. These are, ultimately, groups of elementary particles that organize themselves into atoms and molecules, occupy space, and so on. It turns out that an explanation of even the most commonplace features of this world requires relativistic quantum field theory and the fact that Planck’s constant is discrete, not zero. Groups of molecules in solution, in particular polymers (‘sols’), can form viscous clusters that behave like elastic solids (‘gels’). Sol-gel transitions are examples of cooperative phenomena. Their occurrence is explained by modelling the statistics of inter-unit interactions: the likelihood of either state varies sharply as a critical parameter crosses a threshold value. Group behaviour among cells or organisms is often heritable and therefore can evolve. This permits an additional, typically biological, explanation for it in terms of reproductive advantage, whether of the individual or of the group. There is no general agreement on the appropriate explanatory framework for understanding group-level phenomena in biology.     

Navigating Over Space and Time: Fishing Effort Allocation and the Development of Customary Norms in an Open-Access Mangrove Estuary in Ecuador

Fisheries are increasingly understood as complex adaptive systems; but the cultural, behavioral, and cognitive factors that explain spatial and temporal dynamics of fishing effort allocation remain poorly understood. Using Geographic Information Systems (GIS) as a visualization tool, this paper combines catch-per-unit-effort (CPUE) and ethnographic data on the Ecuadorian mangrove cockle fishery to explore patterns in fishing effort and the social production of fishing space. I argue that individual decisions about where, when, and how to fish result in spatial and temporal patterns in effort allocation, ultimately regulating open-access fisheries that typically operate on a first-come, first-served basis. These emergent patterns in the fishing effort are explained by individual-level preferences and adaptations; the development of knowledge and customary norms through the habitual use of resource space by individuals and groups; ecological conditions; and access. New adaptive challenges threaten to undermine such self-organization of open-access systems on larger spatial and temporal scales prompting a likely re-allocation of the fishing effort in the future.     

Modeling collective animal behavior with a cognitive perspective: a methodological framework

The last decades have seen an increasing interest in modeling collective animal behavior. Some studies try to reproduce as accurately as possible the collective dynamics and patterns observed in several animal groups with biologically plausible, individual behavioral rules. The objective is then essentially to demonstrate that the observed collective features may be the result of self-organizing processes involving quite simple individual behaviors. Other studies concentrate on the objective of establishing or enriching links between collective behavior researches and cognitive or physiological ones, which then requires that each individual rule be carefully validated. Here we discuss the methodological consequences of this additional requirement. Using the example of corpse clustering in ants, we first illustrate that it may be impossible to discriminate among alternative individual rules by considering only observational data collected at the group level. Six individual behavioral models are described: They are clearly distinct in terms of individual behaviors, they all reproduce satisfactorily the collective dynamics and distribution patterns observed in experiments, and we show theoretically that it is strictly impossible to discriminate two of these models even in the limit of an infinite amount of data whatever the accuracy level. A set of methodological steps are then listed and discussed as practical ways to partially overcome this problem. They involve complementary experimental protocols specifically designed to address the behavioral rules successively, conserving group-level data for the overall model validation. In this context, we highlight the importance of maintaining a sharp distinction between model enunciation, with explicit references to validated biological concepts, and formal translation of these concepts in terms of quantitative state variables and fittable functional dependences. Illustrative examples are provided of the benefits expected during the often long and difficult process of refining a behavioral model, designing adapted experimental protocols and inversing model parameters.     

Insights on bias and information in group-level studies

Ecological and aggregate data studies are examples of group-level studies. Even though the link between the predictors and outcomes is not preserved in these studies, inference about individual-level exposure effects is often a goal. The disconnection between the level of inference and the level of analysis expands the array of potential biases that can invalidate the inference from group-level studies. While several sources of bias, specifically due to measurement error and confounding, may be more complex in group-level studies, two sources of bias, cross-level and model specification bias, are a direct consequence of the disconnection. With the goal of aligning inference from individual versus group-level studies, I discuss the interplay between exposure and study design. I specify the additional assumptions necessary for valid inference, specifically that the between- and within-group exposure effects are equal. Then cross-level inference is possible. However, all the information in the group-level analysis comes from between-group comparisons. Models where the group-level analysis provides even a small percentage of information about the within-group exposure effect are most susceptible to model specification bias. Model specification bias can be even more serious when the group-level model isn't derived from an individual-level model.     

Spatial variance of mobile aquatic organisms: capelin and cod in Newfoundland coastal waters

Spatial variance in the distribution of aquatic mobile organisms differs from that of passive tracers such as phytoplankton or water temperature. On average, spatial variance of phytoplankton scales with sample unit as $L^2$ or equivalently with frequency as $f^{-2}$. Limited evidence suggests that spatial variance in the distribution of mobile organisms is concentrated at relatively small scales, with little increase over larger scales: spatial variance scales as $f^{-1}$ or less. We investigated whether spatial variance in distributions of a mobile predator, Atlantic cod (Gadus morhua), and a schooling prey, capelin (Mallotus villosus), also scale with frequency as $f^{-1}$. Acoustic surveys showed that at short time scales spatial variance in cod and capelin densities, as measured by spectral density, peaked at various scales ranging from 20 m to 10 km. At longer time scales, spatial variance of cod scaled as $f^{-1.08}$ at resolutions finer than 90 m, while scaling as $f^{-0.18}$ at coarser scales. Spatial variance of capelin scaled as $f^{-1.1}$ at resolutions finer than 400 m, while scaling as $f^{-0.21}$ at coarser scales. Spatial variance plots of krill and marine birds showed similar transitions from shallow to steep scaling. Shoaling, schooling and the aggregative response by predators to concentrations of prey were three processes hypothesized to influence spatial variance in distributions of mobile organisms. Numerical experiments showed that shoaling injects variance at large to intermediate scales, resulting in scalings flatter than $f^{-1}$. Additional experiments showed that schooling produces a transition from shallow to steep scaling as frequency increases. Spatial variance patterns in cod density were not due to aggregative responses by the predator to concentrations of capelin: there was no association, on average, at resolution scales from 20 m to 10 km. Exponent values for aquatic or terrestrial mobile organisms are predicted to be approximately two at the scale of an individual organism, 0.2 at scales that contain aggregations, and two at scales larger than that of populations. These findings suggest that relations between mobile organisms and large scale habitat variables will be difficult to detect, that stratified survey designs used to estimate commercial population sizes will be inefficient, and that rates of interaction between predator and prey will be underestimated if local observations are averaged over the spatial scale of the population.     

Modern termites inherited the potential of collective construction from their common ancestor

Animal collective behaviors give rise to various spatial patterns, such as the nests of social insects. These structures are built by individuals following a simple set of rules, slightly varying within and among species, to produce a large diversity of shapes. However, little is known about the origin and evolution of the behavioral mechanisms regulating nest structures. In this study, we discuss the perspective of inferring the evolution of collective behaviors behind pattern formations using a phylogenetic framework. We review the collective behaviors that can be described by a single set of behavioral rules, and for which variations of the environmental and behavioral parameter values produce diverse patterns. We propose that this mechanism could be at the origin of the pattern diversity observed among related species, and that, when they are placed in the proper conditions, species have the behavioral potential to form patterns observed in related species. The comparative analysis of shelter tube construction by lower termites is consistent with this hypothesis. Although the use of shelter tubes in natural conditions is variable among species, most modern species have the potential to build them, suggesting that the behavioral rules for shelter tube construction evolved once in the common ancestor of modern termites. Our study emphasizes that comparative studies of behavioral rules have the potential to shed light on the evolution of collective behaviors.     

A scalar analysis of landscape connectivity

Landscape connectivity is critical to the maintenance of spatially-structured populations and consists of both a structural component, which describes the shape, size and location of landscape features; and a biological component, which consists of both the response of individuals to landscape features, and the patterns of gene flow that result from those individual responses. Traditional studies of landscape connectivity have attempted to discern individual behavioral responses to landscape features, but this methodology is intractable for many species. This paper is an attempt to relate the components of landscape connectivity through the explicit treatment of their spatial and temporal scales. Traditional measures of structural and biological components of connectivity are reviewed and more recently developed methods for the analysis of scale for each are introduced. I then present a framework for the comparison of scalar phenomena based on Watt's unit pattern, describe the potential outcomes of the comparison and discuss the implications of each. Several testable hypotheses emerge from the analysis that may serve as a useful framework for the investigation of landscape connectivity in the future .