Patterns of positive selection in seven ant genomes

The evolution of ants is marked by remarkable adaptations that allowed the development of very complex social systems. To identify how ant-specific adaptations are associated with patterns of molecular evolution, we searched for signs of positive selection on amino-acid changes in proteins. We identified 24 functional categories of genes which were enriched for positively selected genes in the ant lineage. We also reanalyzed genome-wide datasets in bees and flies with the same methodology, to check whether positive selection was specific to ants or also present in other insects. Notably, genes implicated in immunity were enriched for positively selected genes in the three lineages, ruling out the hypothesis that the evolution of hygienic behaviors in social insects caused a major relaxation of selective pressure on immune genes. Our scan also indicated that genes implicated in neurogenesis and olfaction started to undergo increased positive selection before the evolution of sociality in Hymenoptera. Finally, the comparison between these three lineages allowed us to pinpoint molecular evolution patterns that were specific to the ant lineage. In particular, there was ant-specific recurrent positive selection on genes with mitochondrial functions, suggesting that mitochondrial activity was improved during the evolution of this lineage. This might have been an important step toward the evolution of extreme lifespan that is a hallmark of ants.

Hit-and-run trophallaxis of small hive beetles

Some parasites of social insects are able to exploit the exchange of food between nestmates via trophallaxis, because they are chemically disguised as nestmates. However, a few parasites succeed in trophallactic solicitation although they are attacked by workers. The underlying mechanisms are not well understood. The small hive beetle (=SHB), Aethina tumida, is such a parasite of honey bee, Apis mellifera, colonies and is able to induce trophallaxis. Here, we investigate whether SHB trophallactic solicitation is innate and affected by sex and experience. We quantified characteristics of the trophallactic solicitation in SHBs from laboratory-reared individuals that were either bee-naïve or had 5 days experience. The data clearly show that SHB trophallactic solicitation is innate and further suggest that it can be influenced by both experience and sex. Inexperienced SHB males begged more often than any of the other groups had longer breaks than their experienced counterparts and a longer soliciting duration than both experienced SHB males and females, suggesting that they start rather slowly and gain more from experience. Successful experienced females and males were not significantly different from each other in relation to successful trophallactic interactions, but had a significantly shorter soliciting duration compared to all other groups, except successful inexperienced females. Trophallactic solicitation success, feeding duration and begging duration were not significantly affected by either SHB sex or experience, supporting the notion that these behaviors are important for survival in host colonies. Overall, success seems to be governed by quality rather than quantity of interactions, thereby probably limiting both SHB energy investment and chance of injury (<1%). Trophallactic solicitation by SHBs is a singular example for an alternative strategy to exploit insect societies without requiring chemical disguise. Hit-and-run trophallaxis is an attractive test system to get an insight into trophallaxis in the social insects.

Response threshold models, stochastic learning automata and ant colony optimization-based decentralized self-coordination algorithms for heterogeneous multi-tasks distribution in multi-robot systems

In recent decades, there has been an increasing interest in systems comprised of several autonomous mobile robots, and as a result, there has been a substantial amount of development in the eld of Articial Intelligence, especially in Robotics. There are several studies in the literature by some researchers from the scientic community that focus on the creation of intelligent machines and devices capable to imitate the functions and movements of living beings. Multi-Robot Systems (MRS) can often deal with tasks that are dicult, if not impossible, to be accomplished by a single robot. In the context of MRS, one of the main challenges is the need to control, coordinate and synchronize the operation of multiple robots to perform a specic task. This requires the development of new strategies and methods which allow us to obtain the desired system behavior in a formal and concise way. This PhD thesis aims to study the coordination of multi-robot systems, in particular, addresses the problem of the distribution of heterogeneous multi-tasks. The main interest in these systems is to understand how from simple rules inspired by the division of labor in social insects, a group of robots can perform tasks in an organized and coordinated way. We are mainly interested on truly distributed or decentralized solutions in which the robots themselves, autonomously and in an individual manner, select a particular task so that all tasks are optimally distributed. In general, to perform the multi-tasks distribution among a team of robots, they have to synchronize their actions and exchange information. Under this approach we can speak of multi-tasks selection instead of multi-tasks assignment, which means, that the agents or robots select the tasks instead of being assigned a task by a central controller. The key element in these algorithms is the estimation ix of the stimuli and the adaptive update of the thresholds. This means that each robot performs this estimate locally depending on the load or the number of pending tasks to be performed. In addition, it is very interesting the evaluation of the results in function in each approach, comparing the results obtained by the introducing noise in the number of pending loads, with the purpose of simulate the robot's error in estimating the real number of pending tasks. The main contribution of this thesis can be found in the approach based on self-organization and division of labor in social insects. An experimental scenario for the coordination problem among multiple robots, the robustness of the approaches and the generation of dynamic tasks have been presented and discussed. The particular issues studied are: Threshold models: It presents the experiments conducted to test the response threshold model with the objective to analyze the system performance index, for the problem of the distribution of heterogeneous multitasks in multi-robot systems; also has been introduced additive noise in the number of pending loads and has been generated dynamic tasks over time. Learning automata methods: It describes the experiments to test the learning automata-based probabilistic algorithms. The approach was tested to evaluate the system performance index with additive noise and with dynamic tasks generation for the same problem of the distribution of heterogeneous multi-tasks in multi-robot systems. Ant colony optimization: The goal of the experiments presented is to test the ant colony optimization-based deterministic algorithms, to achieve the distribution of heterogeneous multi-tasks in multi-robot systems. In the experiments performed, the system performance index is evaluated by introducing additive noise and dynamic tasks generation over time.

An introduction to swarm robotics

Swarm robotics is a field of multi-robotics in which large number of robots are coordinated in a distributed and decentralised way. It is based on the use of local rules, and simple robots compared to the complexity of the task to achieve, and inspired by social insects. Large number of simple robots can perform complex tasks in a more efficient way than a single robot, giving robustness and flexibility to the group. In this article, an overview of swarm robotics is given, describing its main properties and characteristics and comparing it to general multi-robotic systems. A review of different research works and experimental results, together with a discussion of the future swarm robotics in real world applications completes this work.

Variable threshold algorithm for division of labor analyzed as a dynamical system

Division of labor is a widely studied aspect of colony behavior of social insects. Division of labor models indicate how individuals distribute themselves in order to perform different tasks simultaneously. However, models that study division of labor from a dynamical system point of view cannot be found in the literature. In this paper, we define a division of labor model as a discrete-time dynamical system, in order to study the equilibrium points and their properties related to convergence and stability. By making use of this analytical model, an adaptive algorithm based on division of labor can be designed to satisfy dynamic criteria. In this way, we have designed and tested an algorithm that varies the response thresholds in order to modify the dynamic behavior of the system. This behavior modification allows the system to adapt to specific environmental and collective situations, making the algorithm a good candidate for distributed control applications. The variable threshold algorithm is based on specialization mechanisms. It is able to achieve an asymptotically stable behavior of the system in different environments and independently of the number of individuals. The algorithm has been successfully tested under several initial conditions and number of individuals.

Soldier caste-specific gene expression in the mandibular glands of Hodotermopsis japonica (Isoptera: Termopsidae)

Although “polymorphic castes” in social insects are well known as one of the most important phenomena of polyphenism, few studies of caste-specific gene expressions have been performed in social insects. To identify genes specifically expressed in the soldier caste of the Japanese damp-wood termite Hodotermopsis japonica, we employed the differential-display method using oligo(dT) and arbitrary primers, compared mRNA from the heads of mature soldiers and pseudergates (worker caste), and identified a clone (PCR product) 329 bp in length termed SOL1. Northern blot analysis showed that the SOL1 mRNA is about 1.0 kb in length and is expressed specifically in mature soldiers, but not in pseudergates, even in the presoldier induction by juvenile hormone analogue, suggesting that the product is specific for terminally differentiated soldiers. By using the method of 5′- and 3′-rapid amplification of cDNA ends, we isolated the full length of SOL1 cDNA, which contained an ORF with a putative signal peptide at the N terminus. The sequence showed no significant homology with any other known protein sequences. In situ hybridization analysis showed that SOL1 is expressed specifically in the mandibular glands. These results strongly suggest that the SOL1 gene encodes a secretory protein specifically synthesized in the mandibular glands of the soldiers. Histological observations revealed that the gland actually develops during the differentiation into the soldier caste.

A nonspecific fatty acid within the bumblebee mating plug prevents females from remating

The best mating strategy for males differs from that of females, because females gain from mating with several males (polyandry), but males gain from monopolizing the females. As a consequence, males have evolved a variety of methods, such as the transfer of inhibitory substances from their accessory glands, to ensure exclusive paternity of the female's offspring, generally with detrimental effects on female fitness. Inhibitory substances have been identified as peptides or other specific molecules. Unfortunately, in social insects male-mating traits are investigated only poorly, although male social insects might have the same fundamental influence on female-mating behavior as found in other species. A recently developed technique for the artificial insemination of bumblebee queens allowed us to investigate which chemical compound in the mating plug of male bumblebees, Bombus terrestris L., prevents females (queens) from further mating. Surprisingly, we found that the active substance is linoleic acid, a ubiquitous and rather unspecific fatty acid. Contrary to mating plugs in other insect species, the bumblebee mating plug is highly efficient and allows the males to determine queen-mating frequencies.

Common endocrine and genetic mechanisms of behavioral development in male and worker honey bees and the evolution of division of labor.

Temporal polyethism is a highly derived form of behavioral development displayed by social insects. Hormonal and genetic mechanisms regulating temporal polyethism in worker honey bees have been identified, but the evolution of these mechanisms is not well understood. We performed three experiments with male honey bees (drones) to investigate how mechanisms regulating temporal polyethism may have evolved because, relative to workers, drones display an intriguing combination of similarities and differences in behavioral development. We report that behavioral development in drones is regulated by mechanisms common to workers. In experiment 1, drones treated with the juvenile hormone (JH) analog methoprene started flying at significantly younger ages than did control drones, as is the case for workers. In experiment 2, there was an age-related increase in JH associated with the onset of drone flight, as in workers. In experiment 3, drones derived from workers with fast rates of behavioral development themselves started flying at younger ages than drones derived from workers with slower rates of behavioral development. These results suggest that endocrine and genetic mechanisms associated with temporal polyethism did not evolve strictly within the context of worker social behavior.

Division of labour within cooperatively breeding groups

Within cooperative societies, group members share in caring for offspring. Although division of labour among group members has been relatively well studied in insects, less is known about vertebrates. Most studies of avian helping focus solely on the extent to which helpers provision the offspring, however, helpers can participate in everything from nest building to predator defence. Bad provisioners may, for example, not be as 'uncooperative' as they appear. if they are good defenders. Thus, the distribution of helping tasks between group members should have important implications for our interpretation of group dynamics. Here, we compare two distinct forms of helping behaviour in the cooperatively breeding noisy miner (Manorina melanocephala): chick provisioning and mobbing nest predators. We show that the way in which individual helpers invest in these two helping behaviours varies enormously across individuals and among social groups. Good provisioners often contributed relatively little to mobbing and vice versa. Indeed, (18%) of helpers only mobbed, 22% just provisioned, whereas 60% of helpers performed both forms of helping. Across nests, provisioning was significantly negatively correlated with mobbing effort. We suggest that small differences in the costs or benefits of different aspects of helping (due to differences in age, relatedness or social status) have a big impact on the division of labour within a group. Consequently, social groups can be made up from individuals who often specialise in one helping behaviour, and/or helpers who perform a number of behaviours to differing degrees. Division of labour within social groups will, therefore, have important consequences for the maintenance of cooperatively breeding in vertebrates.

Genetics and competing strategies in a threshold model for mail processing

Multi-agent algorithms inspired by the division of labour in social insects are applied to a problem of distributed mail retrieval in which agents must visit mail producing cities and choose between mail types under certain constraints.The efficiency (i.e. the average amount of mail retrieved per time step), and the flexibility (i.e. the capability of the agents to react to changes in the environment) are investigated both in static and dynamic environments. New rules for mail selection and specialisation are introduced and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a genetic algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation. From a more theoretical point of view, in order to avoid finite size effects, most results are obtained for large population sizes. However, we do analyse the influence of population size on the performance. Furthermore, we critically analyse the causes of efficiency loss, derive the exact dynamics of the model in the large system limit under certain conditions, derive theoretical upper bounds for the efficiency, and compare these with the experimental results.

The effect of load on agent-based algorithms for distributed task allocation

Multi-agent algorithms inspired by the division of labour in social insects and by markets, are applied to a constrained problem of distributed task allocation. The efficiency (average number of tasks performed), the flexibility (ability to react to changes in the environment), and the sensitivity to load (ability to cope with differing demands) are investigated in both static and dynamic environments. A hybrid algorithm combining both approaches, is shown to exhibit improved efficiency and robustness. We employ nature inspired particle swarm optimisation to obtain optimised parameters for all algorithms in a range of representative environments. Although results are obtained for large population sizes to avoid finite size effects, the influence of population size on the performance is also analysed. From a theoretical point of view, we analyse the causes of efficiency loss, derive theoretical upper bounds for the efficiency, and compare these with the experimental results.

Tomada de decisão individual e aprendizado em Dinoponera quadríceps (Ponerinae, Hymenoptera) forrageando em ambientes dinâmicos

When searching for food, animals often make decisions of where to go, how long to stay in a foraging area and whether or not to return to the last visited spot. These decisions can be enhanced by cognitive traits and adjusted based on previous experience. In social insects such as ants, foraging efficiency have an impact on both individual and colony level. The present study investigated, in the laboratory, the effect of distance from food, capture success and food size, and reward rate on decisions of where to forage in Dinoponera quadriceps, a ponerine ant that forage solitarily and individually make their foraging decisions. We also investigated the influence of learning on the performance of workers over successive trips searching for food by measuring the patch residence time in each foraging trip. Four scenarios were created differing in food reward rates, food size offered and distances colony-food site. Our work has shown that as a rule-of-thumb, workers of D. quadriceps return to the place where a prey item was found on the previous trip, regardless of distance, food size and reward rate. When ants did not capture preys, they were more likely to change path to search for food. However, in one of the scenarios, this decision to switch paths when unsuccessful was less evident, possibly due to the greater variation of possible outcomes ants could experience in this scenario and cognitive constraints of D. quadriceps to predict variations of food distribution. Our results also indicated a learning process of routes of exploration as well as the food site conditions for exploration. After repeated trips, foragers reduced the patch residence time in areas that they did not capture food and quickly changed of foraging area, increasing their foraging efficiency.

When is bigger better? The effects of group size on the evolution of helping behaviours.

Understanding the evolution of sociality in humans and other species requires understanding how selection on social behaviour varies with group size. However, the effects of group size are frequently obscured in the theoretical literature, which often makes assumptions that are at odds with empirical findings. In particular, mechanisms are suggested as supporting large-scale cooperation when they would in fact rapidly become ineffective with increasing group size. Here we review the literature on the evolution of helping behaviours (cooperation and altruism), and frame it using a simple synthetic model that allows us to delineate how the three main components of the selection pressure on helping must vary with increasing group size. The first component is the marginal benefit of helping to group members, which determines both direct fitness benefits to the actor and indirect fitness benefits to recipients. While this is often assumed to be independent of group size, marginal benefits are in practice likely to be maximal at intermediate group sizes for many types of collective action problems, and will eventually become very small in large groups due to the law of decreasing returns. The second component is the response of social partners on the past play of an actor, which underlies conditional behaviour under repeated social interactions. We argue that under realistic conditions on the transmission of information in a population, this response on past play decreases rapidly with increasing group size so that reciprocity alone (whether direct, indirect, or generalised) cannot sustain cooperation in very large groups. The final component is the relatedness between actor and recipient, which, according to the rules of inheritance, again decreases rapidly with increasing group size. These results explain why helping behaviours in very large social groups are limited to cases where the number of reproducing individuals is small, as in social insects, or where there are social institutions that can promote (possibly through sanctioning) large-scale cooperation, as in human societies. Finally, we discuss how individually devised institutions can foster the transition from small-scale to large-scale cooperative groups in human evolution.

Social life among the insects /

Published in the Scientific monthly, June, 1922, to February, 1923.

Assessment of prey overlap between a native (Polistes humilis) and an introduced (Vespula germanica) social wasp using morphology and phylogenetic analyses of 16S rDNA

In newly invaded communities, interspecific competition is thought to play an important role in determining the success of the invader and its impact on the native community. In southern Australia, the native Polistes humilis was the predominant social wasp prior to the arrival of the exotic Vespula germanica (Hymenoptera: Vespidae). Both species forage for similar resources (water, pulp, carbohydrate and protein prey), and concerns have arisen about potential competition between them. The aim of this study was to identify the protein foods that these wasps feed on. As many prey items are masticated by these wasps to the degree that they cannot be identified using conventional means, morphological identification was complemented by sequencing fragments of the mitochondrial 16S rRNA gene. GenBank searches using blast and phylogenetic analyses were used to identify prey items to at least order level. The results were used to construct complete prey inventories for the two species. These indicate that while P. humilis is restricted to feeding on lepidopteran larvae, V. germanica collects a variety of prey of invertebrate and vertebrate origin. Calculated values of prey overlap between the two species are used to discuss the implications of V. germanica impacting on P. humilis. Results obtained are compared to those gained by solely 'conventional' methods, and the advantages of using DNA-based taxonomy in ecological studies are emphasized.