Smart swarms of bacteria-inspired agents with performance adaptable interactions

Collective navigation and swarming have been studied in animal groups, such as fish schools, bird flocks, bacteria, and slime molds. Computer modeling has shown that collective behavior of simple agents can result from simple interactions between the agents, which include short range repulsion, intermediate range alignment, and long range attraction. Here we study collective navigation of bacteria-inspired smart agents in complex terrains, with adaptive interactions that depend on performance. More specifically, each agent adjusts its interactions with the other agents according to its local environment--by decreasing the peers' influence while navigating in a beneficial direction, and increasing it otherwise. We show that inclusion of such performance dependent adaptable interactions significantly improves the collective swarming performance, leading to highly efficient navigation, especially in complex terrains. Notably, to afford such adaptable interactions, each modeled agent requires only simple computational capabilities with short-term memory, which can easily be implemented in simple swarming robots.     

Loglinear models for the robust design in mark-recapture experiments

The robust design is a method for implementing a mark-recapture experiment featuring a nested sampling structure. The first level consists of primary sampling sessions; the population experiences mortality and immigration between primary sessions so that open population models apply at this level. The second level of sampling has a short mark-recapture study within each primary session. Closed population models are used at this stage to estimate the animal abundance at each primary session. This article suggests a loglinear technique to fit the robust design. Loglinear models for the analysis of mark-recapture data from closed and open populations are first reviewed. These two types of models are then combined to analyze the data from a robust design. The proposed loglinear approach to the robust design allows incorporating parameters for a heterogeneity in the capture probabilities of the units within each primary session. Temporary emigration out of the study area can also be accounted for in the loglinear framework. The analysis is relatively simple; it relies on a large Poisson regression with the vector of frequencies of the capture histories as dependent variable. An example concerned with the estimation of abundance and survival of the red-back vole in an area of southeastern Québec is presented.     

Swarming behavior in plant roots

Interactions between individuals that are guided by simple rules can generate swarming behavior. Swarming behavior has been observed in many groups of organisms, including humans, and recent research has revealed that plants also demonstrate social behavior based on mutual interaction with other individuals. However, this behavior has not previously been analyzed in the context of swarming. Here, we show that roots can be influenced by their neighbors to induce a tendency to align the directions of their growth. In the apparently noisy patterns formed by growing roots, episodic alignments are observed as the roots grow close to each other. These events are incompatible with the statistics of purely random growth. We present experimental results and a theoretical model that describes the growth of maize roots in terms of swarming.     

Evolution of Complex Density-Dependent Dispersal Strategies

The question of how dispersal behavior is adaptive and how it responds to changes in selection pressure is more relevant than ever, as anthropogenic habitat alteration and climate change accelerate around the world. In metapopulation models where local populations are large, and thus local population size is measured in densities, density-dependent dispersal is expected to evolve to a single-threshold strategy, in which individuals stay in patches with local population density smaller than a threshold value and move immediately away from patches with local population density larger than the threshold. Fragmentation tends to convert continuous populations into metapopulations and also to decrease local population sizes. Therefore we analyze a metapopulation model, where each patch can support only a relatively small local population and thus experience demographic stochasticity. We investigated the evolution of density-dependent dispersal, emigration and immigration, in two scenarios: adult and natal dispersal. We show that density-dependent emigration can also evolve to a nonmonotone, “triple-threshold” strategy. This interesting phenomenon results from an interplay between the direct and indirect benefits of dispersal and the costs of dispersal. We also found that, compared to juveniles, dispersing adults may benefit more from density-dependent vs. density-independent dispersal strategies.     

Density‐dependent dispersal and the formation of range borders.

Knowledge about the mechanisms of range formation is crucial for scientifically based species conservation strategies in the face of ongoing global climate change. In recent years an increasing amount of studies have focused on the influences of density‐dependent dispersal on demographic and biogeographical patterns. However, it still remains unclear, to what extent and in what ways this strategy would affect the range formation of species. In order to fill this gap, we present a study using individual‐based simulations of a species with discrete generations living along a dispersal mortality gradient. We compare the evolution of range sizes for species following density‐dependent and density‐independent emigration. Furthermore we assess the influence of environmental stochasticity and Allee effects on range formation, as both processes are known to play an important role for dispersal evolution. We find that density‐dependent dispersal always results in much wider ranges than unconditional dispersal. Increasing environmental stochasticity, a predicted consequence of climate change, can remarkably expand the ranges of species living in such connectivity gradients if dispersal decisions are based on local population density. A strong Allee effect causes range contraction for both strategies, but the effect is considerably less dramatic under density‐dependent compared to density‐independent emigration. We strongly recommend accounting for these findings in future attempts to model species’ range shifts due to climate change.     

The evolution of dispersal – the importance of information about population density and habitat characteristics

The evolution of mobility patterns and dispersal strategies depend on different population, habitat and life history characteristics. The ability to perceive and make use of information about the surrounding environment for dispersal decisions will also differ between organisms. To investigate the evolutionary consequences of such differences, we have used a simulation model with nearest-neighbour dispersal in a metapopulation to study how variation in the ability to obtain and make use of information about habitat quality and conspecific density affects the evolution of dispersal strategies. We found a rather strong influence of variation in information on the overall rate of dispersal in a metapopulation. The highest emigration rate evolved in organisms with no information about either density or habitat quality and the lowest rate was found in organisms with information about both the natal and the neighbouring patches. For organisms that can make use of information about conspecific density, positively density-dependent dispersal evolved in the majority of cases, with the strongest density dependence occurring when an individual only has information about density in the natal patch. However, we also identified situations, involving strong local population fluctuations and frequent local extinctions, where negatively density-dependent dispersal evolved.     

Collective motion of bacteria in two dimensions

Collective motion can be observed in biological systems over a wide range of length scales, from large animals to bacteria. Collective motion is thought to confer an advantage for defense and adaptation. A central question in the study of biological collective motion is how the traits of individuals give rise to the emergent behavior at population level. This question is relevant to the dynamics of general self-propelled particle systems, biological self-organization, and active fluids. Bacteria provide a tractable system to address this question, because bacteria are simple and their behavior is relatively easy to control. In this mini review we will focus on a special form of bacterial collective motion, i.e., bacterial swarming in two dimensions. We will introduce some organization principles known in bacterial swarming and discuss potential means of controlling its dynamics. The simplicity and controllability of 2D bacterial behavior during swarming would allow experimental examination of theory predictions on general collective motion.     

Breeding dispersal strategies following reproductive failure explain low apparent survival of immigrant Temminck's stints

In some animal populations, immigrants have lower survival than philopatric individuals. Costs of dispersal or low phenotypic quality of dispersers may explain the pattern. However, apparent adult survival estimates, which describe real survival combined with site fidelity cannot be separated from permanent emigration. Thus, heterogeneity in breeding dispersal propensities of immigrants and philopatrics can bias fitness correlates of dispersal. Differences in breeding dispersal propensities may be caused by different strategies in response to environmental cues inducing dispersal, such as reproductive success. In such cases, the reported differences between immigrants and philopatric individuals may not reflect true variation in survival. We studied whether dispersal status specific apparent adult survival is associated with reproductive success in a Temminck's stint Calidris temminckii population. We analysed two long term capture–recapture datasets characterised by low and high nest predation levels. Philopatric individuals had higher apparent adult survival than immigrants in both datasets and the difference was highlighted during the high nest predation period. By contrasting return rates between successful and unsuccessful breeders as a proxy for dispersal, we found that unsuccessful immigrants breeding for the first time dispersed more likely than successful immigrants, but such a pattern was not found among philopatric individuals. Our results support the hypothesis that immigrant and philopatric individuals have different breeding dispersal strategies following reproductive failure and that their apparent adult survival differences are at least partly explained by different breeding dispersal propensities. Our results also suggest that the recent decline of the study population reflects a multiple response to increased nest predation through decreased local recruitment and increased emigration.     

Social interactions in myxobacterial swarming

Swarming, a collective motion of many thousands of cells, produces colonies that rapidly spread over surfaces. In this paper, we introduce a cell-based model to study how interactions between neighboring cells facilitate swarming. We chose to study Myxococcus xanthus, a species of myxobacteria, because it swarms rapidly and has well-defined cell–cell interactions mediated by type IV pili and by slime trails. The aim of this paper is to test whether the cell contact interactions, which are inherent in pili-based S motility and slime-based A motility, are sufficient to explain the observed expansion of wild-type swarms. The simulations yield a constant rate of swarm expansion, which has been observed experimentally. Also, the model is able to quantify the contributions of S motility and A motility to swarming. Some pathogenic bacteria spread over infected tissue by swarming. The model described here may shed some light on their colonization process.     

Post-release dispersal in animal translocations: social attraction and the "vacuum effect"

Animal translocations are human-induced colonizations that can represent opportunities to contribute to the knowledge on the behavioral and demographic processes involved in the establishment of animal populations. Habitat selection behaviors, such as social cueing, have strong implications on dispersal and affect the establishment success of translocations. Using modeling simulations with a two-population network model (a translocated population and a remnant population), we investigated the consequences of four habitat selection strategies on post-translocation establishment probabilities in short- and long-lived species. Two dispersal strategies using social cues (conspecific attraction and habitat copying) were compared to random and quality-based strategies. We measured the sensitivity of local extinctions to dispersal strategies, life cycles, release frequencies, remnant population and release group sizes, the proportion of breeders and the connectivity between populations. Our results indicate that social behaviors can compromise establishment as a result of post-release dispersal, particularly in long-lived species. This behavioral mechanism, the "vacuum effect", arises from increased emigration in populations that are small relative to neighboring populations, reducing their rate of population growth. The vacuum effect can drive small remnant populations to extinction when a translocated group is large. In addition, the magnitude of the vacuum effect varies non-linearly with connectivity. The vacuum effect represents a novel form of the behaviorally mediated Allee effect that can cause unexpected establishment failures or population extinctions in response to social cueing. Accounting for establishment probabilities as a conditional step to the persistence of populations would improve the accuracy of predicting the fates of translocated or natural (meta)populations.     

Evidence for positive density-dependent emigration in butterfly metapopulations

A positive effect of (meta)population density on emigration has been predicted by many theoretical models and confirmed empirically in various organisms. However, in butterflies, the most popular species for dispersal studies, the evidence for its existence has so far been equivocal, with negative relationships between density and emigration being reported more frequently. We analysed dispersal in sympatric metapopulations of two Maculinea butterflies, intensively surveyed with mark–release–recapture methods for 7 years. Dispersal parameters, derived using the virtual migration model, were assessed against butterfly densities, which fluctuated strongly over the study period. Emigration was positively correlated with density, and this effect was particularly strong at densities above carrying capacity, when emigration increased up to threefold in females and twofold in males compared with the normal levels. In turn, density had little impact on other dispersal parameters analysed. Our findings provide good evidence for positive density-dependence of emigration in butterflies. Emigrating at high densities is particularly beneficial for females, because it gives them a chance to lay part of their egg-load in less crowded patches, where offspring survival is higher due to lower intraspecific competition. Even though the rise in emigration becomes considerable at densities exceeding carrying capacity, i.e. relatively infrequently, it still has serious implications for many ecological phenomena, such as species range expansions, gene flow, and metapopulation persistence. Consequently, instead of treating emigration as a fixed trait, it is worth allowing for its density-dependence in applications such as population viability analyses, genetic models or metapopulation models.     

Causes and consequences of animal dispersal strategies: relating individual behaviour to spatial dynamics

Knowledge of the ecological and evolutionary causes of dispersal can be crucial in understanding the behaviour of spatially structured populations, and predicting how species respond to environmental change. Despite the focus of much theoretical research, simplistic assumptions regarding the dispersal process are still made. Dispersal is usually regarded as an unconditional process although in many cases fitness gains of dispersal are dependent on environmental factors and individual state. Condition-dependent dispersal strategies will often be superior to unconditional, fixed strategies. In addition, dispersal is often collapsed into a single parameter, despite it being a process composed of three interdependent stages: emigration, inter-patch movement and immigration, each of which may display different condition dependencies. Empirical studies have investigated correlates of these stages, emigration in particular, providing evidence for the prevalence of conditional dispersal strategies. Ill-defined use of the term 'dispersal', for movement across many different spatial scales, further hinders making general conclusions and relating movement correlates to consequences at the population level. Logistical difficulties preclude a detailed study of dispersal for many species, however incorporating unrealistic dispersal assumptions in spatial population models may yield inaccurate and costly predictions. Further studies are necessary to explore the importance of incorporating specific condition-dependent dispersal strategies for evolutionary and population dynamic predictions.     

Evolution of Swarm Communication in Eusocial Wasps (Hymenoptera: Vespidae)

Eusocial paper wasps, yellowjackets, and hornets (Vespidae) exhibit two modes of colony foundation, primitively eusocial independent founders and advanced eusocial swarm founders. Unlike independent founders, swarmfounding wasps require a means of social communication to coordinate the movement of colony members between nest sites. We employed a phylogeny of paper wasps, yellowjackets, and hornets to test for patterns of correlated evolution between the mode of colony foundation and the presence of sternal exocrine glands. We also reviewed data on worker actions during swarming to determine whether swarm communication behavior was dependent upon gland possession and whether communicative behavior was shared among swarm-founding species. We did not find evidence for an association of sternal glands with swarm founding. Although sternal gland presence differed among swarm-founding species, worker behavior during swarming showed little variation. Workers of nearly all swarm-founding species rub their gasters on objects along swarm routes, independently of the occurrence of sternal glands. Widespread gastral rubbing indicates the use of swarm emigration trail pheromones from a diversity of glandular sources. Transitions from independent to swarm founding have been achieved via diverse pheromonal mechanisms in the Vespidae, while worker communicative behavior is either highly conserved or convergent.     

On the evolution of specialization with a mechanistic underpinning in structured metapopulations

We analyze the evolution of specialization in resource utilization in a discrete-time metapopulation model using the adaptive dynamics approach. The local dynamics in the metapopulation are based on the Beverton-Holt model with mechanistic underpinnings. The consumer faces a trade-off in the abilities to consume two resources that are spatially heterogeneously distributed to patches that are prone to local catastrophes. We explore the factors favoring the spread of generalist or specialist strategies. Increasing fecundity or decreasing catastrophe probability favors the spread of the generalist strategy and increasing environmental heterogeneity enlarges the parameter domain where the evolutionary branching is possible. When there are no catastrophes, increasing emigration diminishes the parameter domain where the evolutionary branching may occur. Otherwise, the effect of emigration on evolutionary dynamics is non-monotonous: both small and large values of emigration probability favor the spread of the specialist strategies whereas the parameter domain where evolutionary branching may occur is largest when the emigration probability has intermediate values. We compare how different forms of spatial heterogeneity and different models of local growth affect the evolutionary dynamics. We show that even small changes in the resource dynamics may have outstanding evolutionary effects to the consumers.     

Multilevel selection analysis of a microbial social trait

The study of microbial communities often leads to arguments for the evolution of cooperation due to group benefits. However, multilevel selection models caution against the uncritical assumption that group benefits will lead to the evolution of cooperation. We analyze a microbial social trait to precisely define the conditions favoring cooperation. We combine the multilevel partition of the Price equation with a laboratory model system: swarming in Pseudomonas aeruginosa. We parameterize a population dynamics model using competition experiments where we manipulate expression, and therefore the cost‐to‐benefit ratio of swarming cooperation. Our analysis shows that multilevel selection can favor costly swarming cooperation because it causes population expansion. However, due to high costs and diminishing returns constitutive cooperation can only be favored by natural selection when relatedness is high. Regulated expression of cooperative genes is a more robust strategy because it provides the benefits of swarming expansion without the high cost or the diminishing returns. Our analysis supports the key prediction that strong group selection does not necessarily mean that microbial cooperation will always emerge.     

Evolutionary dynamics of prey exploitation in a metapopulation of predators

In well-mixed populations of predators and prey, natural selection favors predators with high rates of prey consumption and population growth. When spatial structure prevents the populations from being well mixed, such predators may have a selective disadvantage because they do not make full use of the prey's growth capacity and hence produce fewer propagules. The best strategy then depends on the degree to which predators can monopolize the exploitation of local prey populations, which in turn depends on the spatial structure, the number of migrants, and, in particular, the stochastic nature of the colonization process. To analyze the evolutionary dynamics of predators in a spatially structured predator-prey system, we performed simulations with a metapopulation model that has explicit local dynamics of nonpersistent populations, keeps track of the number of emigrants entering the migration pool, assumes individuals within local populations as well as within the migration pool to be well mixed, and takes stochastic colonization into account. We investigated which of the predator's exploitation strategies are evolutionarily stable and whether these strategies minimize the overall density of prey, as is the case in Lotka-Volterra-type models of competitive exclusion. This was analyzed by pairwise invasibility plots based on short-term simulations and tested by long-term simulation experiments of competition between resident and mutant predator-types that differed in one of the following parameters: the prey-to-predator conversion efficiency, the per capita prey consumption rate, or the per capita emigration rate from local populations. In addition, we asked which of these three strategies are most likely to evolve. Our simulations showed that under selection for conversion efficiency the predator-prey system always goes globally extinct yet persists under selection for consumption or emigration rates and that the evolutionarily stable (ES) exploitation strategies do not maximize local population growth rates. The most successful exploitation strategy minimizes the overall density of prey but does not make it settle exactly at the minimum. The system did not settle at the point where the mean time to co-invasion (i.e., immigration of a second predator in a local prey population) equals the mean local interaction time (an idea borne out from studies on host exploitation strategies in host-pathogen systems) but rather where the mean time to co-invasion was larger. The ES exploitation strategies represent more prudent strategies than the ones that minimize prey density. Finally, we show that-compared to consumption-emigration is a more likely target for selection to achieve prudent exploitation and that prudent exploitation strategies can evolve only provided the prey-to-predator conversion efficiency is subject to constraints.     

Characterization of swarming motility in Citrobacter freundii

Bacterial swarming motility is a flagella-dependent translocation on the surface environment. It has received extensive attention as a population behavior involving numerous genes. Here, we report that Citrobacter freundii, an opportunistic pathogen, exhibits swarming movement on a solid medium surface with appropriate agar concentration. The swarming behavior of C. freundii was described in detail. Insertional mutagenesis with transposon Mini-Tn5 was carried out to discover genetic determinants related to the swarming of C. freundii. A number of swarming genes were identified, among which flhD, motA, motB, wzx, rfaL, rfaJ, rfbX, rfaG, rcsD, rcsC, gshB, fabF, dam, pgi, and rssB have been characterized previously in other species. In mutants related to lipopolysaccharide synthesis and RcsCDB signal system, a propensity to form poorly motile bacterial aggregates on the agar surface was observed. The aggregates hampered bacterial surface migration. In several mutants, the insertion sites were identified to be in the ORF of yqhC, yeeZ, CKO_03941, glgC, and ttrA, which have never been shown to be involved in swarming. Our results revealed several novel characteristics of swarming motility in C. freundii which are worthy of further study.