Dynamic Polyethism and Competition for Tasks in Threshold Reinforcement Models of Social Insects

In this paper we study the dynamics of task division in threshold reinforcement models of social insect societies. Our work extends other models in order to include several factors that influence the behavior of real insect colonies. Main extensions of our model are variable demands for work, age-dependent thresholds and finite life span of the individuals. It is shown how these factors influence the degree of task specialization of the individuals in a colony. Moreover, we show that the introduction of a threshold-dependent competition process between the individuals during task selection leads to the occurrence of specialists and differentiation between individuals as an emergent phenomenon that depends on the colony size. This result can help to explain the proximate mechanisms that lead to specialization in large insect colonies. Our results have implications for the fields of multi-agent systems, robotics, and nature inspired scheduling where threshold response models are used for control and regulation tasks

Modeling the Adaptive Role of Negative Signaling in Honey Bee Intraspecific Competition

Collective decision making in the social insects often proceeds via feedback cycles based on positive signaling. Negative signals have, however, been found in a few contexts in which costs exist for paying attention to no longer useful information. Here we incorporate new research on the specificity and context of the negative stop signal into an agent based model of honey bee foraging to explore the adaptive basis of negative signaling in the dance language. Our work suggests that the stop signal, by acting as a counterbalance to the waggle dance, allows colonies to rapidly shut down attacks on other colonies. This could be a key adaptation, as the costs of attacking a colony strong enough to defend itself are significant

Spatial effects, sampling errors, and task specialization in the honey bee

Task allocation patterns should depend on the spatial distribution of work within the nest, variation in task demand, and the movement patterns of workers, however, relatively little research has focused on these topics. This study uses a spatially explicit agent based model to determine whether such factors alone can generate biases in task performance at the individual level in the honey bees, Apis mellifera. Specialization (bias in task performance) is shown to result from strong sampling error due to localized task demand, relatively slow moving workers relative to nest size, and strong spatial variation in task demand. To date, specialization has been primarily interpreted with the response threshold concept, which is focused on intrinsic (typically genotypic) differences between workers. Response threshold variation and sampling error due to spatial effects are not mutually exclusive, however, and this study suggests that both contribute to patterns of task bias at the individual level. While spatial effects are strong enough to explain some documented cases of specialization; they are relatively short term and not explanatory for long term cases of specialization. In general, this study suggests that the spatial layout of tasks and fluctuations in their demand must be explicitly controlled for in studies focused on identifying genotypic specialists

Evolution of self-organized division of labor in a response threshold model

Division of labor in social insects is determinant to their ecological success. Recent models emphasize that division of labor is an emergent property of the interactions among nestmates obeying to simple behavioral rules. However, the role of evolution in shaping these rules has been largely neglected. Here, we investigate a model that integrates the perspectives of self-organization and evolution. Our point of departure is the response threshold model, where we allow thresholds to evolve. We ask whether the thresholds will evolve to a state where division of labor emerges in a form that fits the needs of the colony. We find that division of labor can indeed evolve through the evolutionary branching of thresholds, leading to workers that differ in their tendency to take on a given task. However, the conditions under which division of labor evolves depend on the strength of selection on the two fitness components considered: amount of work performed and on worker distribution over tasks. When selection is strongest on the amount of work performed, division of labor evolves if switching tasks is costly. When selection is strongest on worker distribution, division of labor is less likely to evolve. Furthermore, we show that a biased distribution (like 3:1) of workers over tasks is not easily achievable by a threshold mechanism, even under strong selection. Contrary to expectation, multiple matings of colony foundresses impede the evolution of specialization. Overall, our model sheds light on the importance of considering the interaction between specific mechanisms and ecological requirements to better understand the evolutionary scenarios that lead to division of labor in complex systems

Dynamic Polyethism and Competition for Tasks in Threshold Reinforcement Models of Social Insects

In this paper we study the dynamics of task division in threshold reinforcement models of social insect societies. Our work extends other models in order to include several factors that influence the behavior of real insect colonies. Main extensions of our model are variable demands for work, age-dependent thresholds and finite life span of the individuals. It is shown how these factors influence the degree of task specialization of the individuals in a colony. Moreover, we show that the introduction of a threshold-dependent competition process between the individuals during task selection leads to the occurrence of specialists and differentiation between individuals as an emergent phenomenon that depends on the colony size. This result can help to explain the proximate mechanisms that lead to specialization in large insect colonies. Our results have implications for the fields of multi-agent systems, robotics, and nature inspired scheduling where threshold response models are used for control and regulation tasks

Dynamic Polyethism and Competition for Tasks in Threshold Reinforcement Models of Social Insects

In this paper we study the dynamics of task division in threshold reinforcement models of social insect societies. Our work extends other models in order to include several factors that influence the behavior of real insect colonies. Main extensions of our model are variable demands for work, age-dependent thresholds and finite life span of the individuals. It is shown how these factors influence the degree of task specialization of the individuals in a colony. Moreover, we show that the introduction of a threshold-dependent competition process between the individuals during task selection leads to the occurrence of specialists and differentiation between individuals as an emergent phenomenon that depends on the colony size. This result can help to explain the proximate mechanisms that lead to specialization in large insect colonies. Our results have implications for the fields of multi-agent systems, robotics, and nature inspired scheduling where threshold response models are used for control and regulation tasks

Behaviour of Foraging Bumble Bees Across Morphological and Environmental Contexts

Bumble bees as pollinators are being produced at an industrial scale and are used throughout the world to pollinate agricultural crops in glasshouses. The agricultural crops they are exposed to are often monocultural and mass-produced. The lack of floral variety they are provided with is thought to have negative effects on pollination performance and bee health, and has been suggested to influence worker drift in a glasshouse. Bumble bees are unique due to the large size differentiation among workers within a colony, which are thought to lead to consistent differences among individuals. Larger workers are more likely to be foragers, and smaller workers are more likely to perform in-nest tasks. These size differences are thought to cause differences among workers in foraging efficiency, the types of flowers they visit, and the size of their foraging ranges. Worker size also affects circadian rhythm strength, and individuals with stronger circadian rhythms are thought to anticipate potential activity cues such as sunrise. Bumble bees also show communication among foragers, but it is unknown whether they have ‘scouting’ bees that recruit inactive bees early in the day to forage. Understanding more about the behaviour of these populations and the effect environments can have on their activity is important for understanding how to aid in the conservation of these populations. Chapter 3 investigates bumble bee foragers and their activity among individuals of different sizes and within different colonies. I hypothesized (1) if bumble bees differ intrinsically from one another, then consistent differences in behaviour will be observed among foragers from the same colony and (2) if body size causes differences in anticipation of sunrise and foraging activity, then larger foragers will be seen initiating foraging earlier. To answer these questions, the nest entrance of two colonies were recorded that had access to a semi-natural floral environment in a glasshouse with tomato, cornflower and snapdragon flowers. Each bumble bee was marked with a coloured number tag to allow identification of each forager. Individuals differed from one another in foraging activity within both colonies. Additionally, larger workers initiated foraging earlier than smaller ones. The results support previous studies that show that individuals within a nest vary intrinsically from one another in foraging behaviour and show consistent differences within the same colony, as well as from other colonies. Moreover, larger bees appear to anticipate sunrise and potential food availability, suggesting the presence of strong diurnal foraging circadian rhythms, with larger bees leaving the next for the first time earlier than smaller bees. These differences among individuals could facilitate the temporal division of workers, and morphological differences could account for some of the variation seen among colonies. In chapter 4 I assessed bumble bee foraging activity across two different environments, a simple monofloral glasshouse, and an enriched polyfloral glasshouse. I hypothesised that (1) if simplified monocultures have a detrimental effect on bumble bee colonies, then decreased foraging activity will be observed in the simple environment compared to the enriched and (2) if nest switching behaviour is influenced by the availability of natural nectar sources, then lower levels of nest switching will be observed in the enriched environment. The methods of this chapter were the same as chapter 3, except that there were two glasshouses and four colonies. One glasshouse had 3 flower types including tomatoes, and the other only had tomatoes and artificial sugar syrup as a nectar source. I found that in the simple environment, bumble bees showed significantly decreased foraging activity, initiated foraging later, and spent less time out of the nest. Nest switching occurred at high rates and there was no difference among colonies or environments. These results show that bumble bee performance is affected by a monocultural glasshouse environment, and that nest switching occurs within a glasshouse independent of the environment they are exposed to. The research done in this thesis contributes to understanding bumble bee size differentiation and suggests that it may persist to separate workers temporally in activity. It shows differences among bumble bee foragers, and these foragers may differ from one another intrinsically or in thresholds to foraging tasks. It also provides insights into how monocultures and glasshouses can be affecting bumble bee colonies. This adds to literature about how monocultures may be having detrimental effects on pollinator species and reiterates the importance of providing a variety of floral resources to bees to enhance these populations