A. Jamie Wood

Limited interactions in flocks: relating model simulations to empirical data

The mechanism of self-organization resulting in coordinated collective motion has received wide attention from a range of scientists interested in both its technical and biological relevance. Models have been highly influential in highlighting how collective motion can be produced from purely local interactions between individuals. Typical models in this field are termed ‘metric’ because each individual only reacts to conspecifics within a fixed distance. A recent large-scale study has, however, provided evidence that interactions ruling collective behaviour occur between a fixed number of nearest neighbours (‘topological’ framework). Despite their importance in clarifying the nature of the mechanism underlying animal interactions, these findings have yet to be produced by either metric or topological models. Here, we present an original individual-based model of collective animal motion that reproduces the previous findings. Our approach bridges the current gap between previous model analysis and recent evidence, and presents a framework for further study.

The impact of social networks on animal collective motion

Many group-living animals show social preferences for relatives, familiar conspecifics or individuals of similar attributes such as size, personality or sex. How such preferences could affect the collective motion of animal groups has been rather unexplored. We present a general model of collective animal motion that includes social connections as preferential reactions between individuals. Our conceptual examples illustrate the possible impact of underlying social networks on the collective motion of animals. Our approach shows that the structure of these networks could influence: (1) the cohesion of groups; (2) the spatial position of individuals within groups; and (3) the hierarchical dynamics within such groups. We argue that the position of individuals within a social network and the social network structure of populations could have important fitness implications for individual animals. Counterintuitive results from our conceptual examples show that social structures can result in unexpected group dynamics. This sharpens our understanding of the way in which collective movement can be interpreted as a result of social interactions.

Social networks and models for collective motion in animals

The theory of collective motion and the study of animal social networks have, each individually, received much attention. Currently, most models of collective motion do not consider social network structure. The implications for considering collective motion and social networks together are likely to be important. Social networks could determine how populations move in, split up into and form separate groups (social networks affecting collective motion). Conversely, collective movement could change the structure of social networks by creating social ties that did not exist previously and maintaining existing ties (collective motion affecting social networks). Thus, there is a need to combine the two areas of research and examine the relationship between network structure and collective motion. Here, we review different modelling approaches that combine social network structures and collective motion. Although many of these models have not been developed with ecology in mind, they present a current context in which a biologically relevant theory can be developed. We argue that future models in ecology should take inspiration from empirical observations and consider different mechanisms of how social preferences could be expressed in collectively moving animal groups.

Exact Results for the Evolution of Stochastic Switching in Variable Asymmetric Environments

The ability of bacteria to spontaneously switch their expressed phenotype from an identical underlying genotype is now widely acknowledged. Mechanisms behind these switches have been shown to be evolvable. Important questions thus arise: In a fluctuating environment, under what conditions can stochastic switching evolve and how is the evolutionarily optimal switching rate related to the environmental changes? Here we derive exact analytical results for the long-term exponential population growth rate in a two-state periodically changing environment, where the environmental states vary in both their duration and in their impact on the fitness of each phenotype. Using methods from statistical physics we derive conditions under which nonswitching is evolutionarily optimal, and we furthermore demonstrate that the transition between the nonswitching and switching regimes is discontinuous (a first-order phase transition). Our general analytical method allows the evolutionary effects of asymmetries in selection pressures and environmental growth rates to be quantified. The evolutionary implications of our findings are discussed in relation to their to real-world applications in the light of recent experimental evidence.

Distinguishing social from nonsocial navigation in moving animal groups.

Many animals, such as migrating shoals of fish, navigate in groups. Knowing the mechanisms involved in animal navigation is important when it comes to explaining navigation accuracy, dispersal patterns, population and evolutionary dynamics, and consequently, the design of conservation strategies. When navigating toward a common target, animals could interact socially by sharing available information directly or indirectly, or each individual could navigate by itself and aggregations may not disperse because all animals are moving toward the same target. Here we present an analysis technique that uses individual movement trajectories to determine the extent to which individuals in navigating groups interact socially, given knowledge of their target. The basic idea of our approach is that the movement directions of individuals arise from a combination of responses to the environment and to other individuals. We estimate the relative importance of these responses, distinguishing between social and nonsocial interactions. We develop and test our method, using simulated groups, and we demonstrate its applicability to empirical data in a case study on groups of guppies moving toward shelter in a tank. Our approach is generic and can be extended to different scenarios of animal group movement.

Leading from the front? Social networks in navigating groups

In many group-living animals, leadership by only a fraction of the group members can be important for group navigation. It has been shown that subgroups of informed individuals can steer the remainder of the group without direct communication, resolving conflicts of interest through individual-to-individual interactions. We present a model for the navigation of collectively moving groups that includes preferential interactions between individuals as a way of imposing social network structures, known to be present in many species. We show that effective leadership can occur when leaders do not occupy frontal spatial positions and when navigation tendency is appropriately balanced with social position. Our model also shows that small minorities can dominate movement decisions if they have navigational knowledge combined with influential social network positions. Our findings highlight the mechanistic importance of social networks for the movement decisions of animal groups. We discuss the implications of our research for interpreting empirical observations.

Evolutionary optimality in stochastic search problems

‘Optimal’ behaviour in a biological system is not simply that which maximizes a mean, or temporally and spatially averaged, fitness function. Rather, population dynamics and demographic and environmental stochasticity are fundamental evolutionary ingredients. Here, we revisit the problem of optimal foraging, where some recent studies claim that organisms should forage according to Lévy walks. We show that, in an ecological scenario dominated by uncertainty and high mortality, Lévy walks can indeed be evolutionarily favourable. However, this conclusion is dependent on the definition of efficiency and the details of the simulations. We analyse measures of efficiency that incorporate population-level characteristics, such as variance, superdiffusivity and heavy tails, and compare the results with those generated by simple maximizing of the average encounter rate. These results have implications on stochastic search problems in general, and also on computational models of evolutionary optima.

Source-sink plasmid transfer dynamics maintain gene mobility in soil bacterial communities.

Significance Bacterial adaptation through horizontal gene transfer is central to microbial evolution and, in the context of antibiotic resistance, represents a growing clinical threat. Conjugative plasmids are key mediators of genetic exchange both within and between species. Experimental studies have mostly focused on plasmid population dynamics in single-species populations, but between-species transfer could counteract purifying selection and maintain plasmids in hosts that would otherwise lose them. We show that plasmids can be lost from single-species populations, even when their genes are under selection, because beneficial genes are captured by the chromosome. In contrast, experiments and models show that, in a two-species community, between-species transfer maintains community-wide access to plasmids, promoting the spread of the ecologically and clinically important genes they carry. Horizontal gene transfer is a fundamental process in bacterial evolution that can accelerate adaptation via the sharing of genes between lineages. Conjugative plasmids are the principal genetic elements mediating the horizontal transfer of genes, both within and between bacterial species. In some species, plasmids are unstable and likely to be lost through purifying selection, but when alternative hosts are available, interspecific plasmid transfer could counteract this and maintain access to plasmid-borne genes. To investigate the evolutionary importance of alternative hosts to plasmid population dynamics in an ecologically relevant environment, we established simple soil microcosm communities comprising two species of common soil bacteria, Pseudomonas fluorescens and Pseudomonas putida, and a mercury resistance (HgR) plasmid, pQBR57, both with and without positive selection [i.e., addition of Hg(II)]. In single-species populations, plasmid stability varied between species: although pQBR57 survived both with and without positive selection in P. fluorescens, it was lost or replaced by nontransferable HgR captured to the chromosome in P. putida. A simple mathematical model suggests these differences were likely due to pQBR57’s lower intraspecific conjugation rate in P. putida. By contrast, in two-species communities, both models and experiments show that interspecific conjugation from P. fluorescens allowed pQBR57 to persist in P. putida via source–sink transfer dynamics. Moreover, the replacement of pQBR57 by nontransferable chromosomal HgR in P. putida was slowed in coculture. Interspecific transfer allows plasmid survival in host species unable to sustain the plasmid in monoculture, promoting community-wide access to the plasmid-borne accessory gene pool and thus potentiating future evolvability.

Strategy selection under predation; evolutionary analysis of the emergence of cohesive aggregations

Why do animals form groups? This question has formed the basis of numerous scientific studies over the last hundred years and still remains a controversial topic. Predation is one of the foremost candidates, yet the precise mechanism remains quantitatively elusive. Here I investigate in silico the effect of ongoing predation on groups of heterogeneous individuals behaving according to a well-documented individual based model. I examine the resultant evolutionary trajectories and describe the final selected states and their stability with reference to a qualitatively modified version of adaptive dynamics. The speed of individuals is found to dominate the selection of the final state over other parameters in the model. The relative stability of the groups and their internal configurations are discussed with reference to novel structural correlation functions that are defined and introduced. The results reveal the importance of tightly bound toroidal group structures as an intermediate state prior to the emergence of slow compact groups. The study also indicates the need to more accurately model the speed distributions in real aggregations.

Gene mobility promotes the spread of resistance in bacterial populations

Theory predicts that horizontal gene transfer (HGT) expands the selective conditions under which genes spread in bacterial populations. Whereas vertically inherited genes can only spread by positively selected clonal expansion, mobile genetic elements can drive fixation of genes by infectious HGT. We tested this using populations of Pseudomonas fluorescens and the conjugative mercury resistance (HgR) plasmid pQBR57. HGT expanded the selective conditions allowing the spread of HgR: Chromosomal HgR only increased in frequency under positive selection, whereas plasmid-encoded HgR reached fixation with or without positive selection. Tracking plasmid dynamics over time revealed that the mode of HgR inheritance varied across mercury environments. Under mercury selection, the spread of HgR was driven primarily by clonal expansion while in the absence of mercury HgR dynamics were dominated by infectious transfer. Thus, HGT is most likely to drive the spread of resistance genes in environments where resistance is useless.