A hard day's night: Patterns in the diurnal and nocturnal foraging behavior of Apis dorsata across lunar cycles and seasons.

The giant honey bee Apis dorsata is unusual in being able to forage during both the day and the night. To date, the extent of this unique nocturnal foraging behavior and the environmental factors correlating with it have not been deeply investigated. We conducted the first systematic investigation into the nocturnal behavior of A. dorsata in Southern India by tracking the daily and nightly foraging activity of A. dorsata colonies in an urban environment for 8 months, over multiple seasons and lunar cycles. We found strong evidence that A. dorsata can behave in a manner that is "cathemeral" (active over the entire diel cycle) when environmental illumination is sufficient for nocturnal flight. However, workers were not always active even when the environment should have been bright enough for them to forage, suggesting that their nocturnal foraging behavior was also affected by seasonal changes in resource availability. The foraging activity observed during the day versus twilight versus night differed between seasons; notably, nocturnal activity rates were higher than diurnal activity rates during the winter. We found that at our study site A. dorsata routinely exhibits both diurnal and crepuscular activity, foraging just as intensely during the short twilight hours as during the day. The high foraging activity observed during the twilight and nighttime hours shows that A. dorsata colonies can extend their foraging beyond the daylight hours and reveals that foraging during these dimly lit hours is an integral part of their foraging ecology. This evidence of the importance of nocturnal and crepuscular foraging by A. dorsata paves the way for future studies examining the role of this species in nocturnal pollination networks, the contribution of nocturnal foraging to colony-level nutrition and energy budget, and the evolution of this unusual behavior. Future work comparing nocturnal activity in light polluted urban environments versus unpolluted natural environments is particularly encouraged to determine the generalizability of these findings.

The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities.

Evolution provides a creative fount of complex and subtle adaptations that often surprise the scientists who discover them. However, the creativity of evolution is not limited to the natural world: Artificial organisms evolving in computational environments have also elicited surprise and wonder from the researchers studying them. The process of evolution is an algorithmic process that transcends the substrate in which it occurs. Indeed, many researchers in the field of digital evolution can provide examples of how their evolving algorithms and organisms have creatively subverted their expectations or intentions, exposed unrecognized bugs in their code, produced unexpectedly adaptations, or engaged in behaviors and outcomes, uncannily convergent with ones found in nature. Such stories routinely reveal surprise and creativity by evolution in these digital worlds, but they rarely fit into the standard scientific narrative. Instead they are often treated as mere obstacles to be overcome, rather than results that warrant study in their own right. Bugs are fixed, experiments are refocused, and one-off surprises are collapsed into a single data point. The stories themselves are traded among researchers through oral tradition, but that mode of information transmission is inefficient and prone to error and outright loss. Moreover, the fact that these stories tend to be shared only among practitioners means that many natural scientists do not realize how interesting and lifelike digital organisms are and how natural their evolution can be. To our knowledge, no collection of such anecdotes has been published before. This article is the crowd-sourced product of researchers in the fields of artificial life and evolutionary computation who have provided first-hand accounts of such cases. It thus serves as a written, fact-checked collection of scientifically important and even entertaining stories. In doing so we also present here substantial evidence that the existence and importance of evolutionary surprises extends beyond the natural world, and may indeed be a universal property of all complex evolving systems.

The Evolutionary Origin of Associative Learning.

Learning is a widespread ability among animals and, like physical traits, is subject to evolution. But how did learning first arise? What selection pressures and phenotypic preconditions fostered its evolution? Neither the fossil record nor phylogenetic comparative studies provide answers to these questions. Here, we take a novel approach by studying digital organisms in environments that promote the evolution of navigation and associative learning. Starting with a nonlearning sessile ancestor, we evolve multiple populations in four different environments, each consisting of nutrient trails with various layouts. Trail nutrients cue organisms on which direction to follow, provided they evolve to acquire and use those cues. Thus, each organism is tested on how well it navigates a randomly selected trail before reproducing. We find that behavior evolves modularly and in a predictable sequence, where simpler behaviors are necessary precursors for more complex ones. Associative learning is only one of many successful behaviors to evolve, and its origin depends on the environment possessing certain information patterns that organisms can exploit. Environmental patterns that are stable across generations foster the evolution of reflexive behavior, while environmental patterns that vary across generations but remain consistent for periods within an organism's lifetime foster the evolution of learning behavior. Both types of environmental patterns are necessary, since the prior evolution of simple reflexive behaviors provides the building blocks for learning to arise. Finally, we observe that an intrinsic value system evolves alongside behavior and supports associative learning by providing reinforcement for behavior conditioning.

Exploring the evolution of a trade-off between vigilance and foraging in group-living organisms.

Even though grouping behaviour has been actively studied for over a century, the relative importance of the numerous proposed fitness benefits of grouping remain unclear. We use a digital model of evolving prey under simulated predation to directly explore the evolution of gregarious foraging behaviour according to one such benefit, the 'many eyes' hypothesis. According to this hypothesis, collective vigilance allows prey in large groups to detect predators more efficiently by making alarm signals or behavioural cues to each other, thereby allowing individuals within the group to spend more time foraging. Here, we find that collective vigilance is sufficient to select for gregarious foraging behaviour as long there is not a direct cost for grouping (e.g. competition for limited food resources), even when controlling for confounding factors such as the dilution effect. Furthermore, we explore the role of the genetic relatedness and reproductive strategy of the prey and find that highly related groups of prey with a semelparous reproductive strategy are the most likely to evolve gregarious foraging behaviour mediated by the benefit of vigilance. These findings, combined with earlier studies with evolving digital organisms, further sharpen our understanding of the factors favouring grouping behaviour.

Predator confusion is sufficient to evolve swarming behaviour.

Swarming behaviours in animals have been extensively studied owing to their implications for the evolution of cooperation, social cognition and predator-prey dynamics. An important goal of these studies is discerning which evolutionary pressures favour the formation of swarms. One hypothesis is that swarms arise because the presence of multiple moving prey in swarms causes confusion for attacking predators, but it remains unclear how important this selective force is. Using an evolutionary model of a predator-prey system, we show that predator confusion provides a sufficient selection pressure to evolve swarming behaviour in prey. Furthermore, we demonstrate that the evolutionary effect of predator confusion on prey could in turn exert pressure on the structure of the predator's visual field, favouring the frontally oriented, high-resolution visual systems commonly observed in predators that feed on swarming animals. Finally, we provide evidence that when prey evolve swarming in response to predator confusion, there is a change in the shape of the functional response curve describing the predator's consumption rate as prey density increases. Thus, we show that a relatively simple perceptual constraint--predator confusion--could have pervasive evolutionary effects on prey behaviour, predator sensory mechanisms and the ecological interactions between predators and prey.

A case study of the de novo evolution of a complex odometric behavior in digital organisms.

Investigating the evolution of animal behavior is difficult. The fossil record leaves few clues that would allow us to recapitulate the path that evolution took to build a complex behavior, and the large population sizes and long time scales required prevent us from re-evolving such behaviors in a laboratory setting. We present results of a study in which digital organisms-self-replicating computer programs that are subject to mutations and selection-evolved in different environments that required information about past experience for fitness-enhancing behavioral decisions. One population evolved a mechanism for step-counting, a surprisingly complex odometric behavior that was only indirectly related to enhancing fitness. We examine in detail the operation of the evolved mechanism and the evolutionary transitions that produced this striking example of a complex behavior.

Motivation and vector navigation in honey bees.

Animals that forage from a central place can keep track of their displacement relative to home through a process called "path integration." During a study of the stability of homing information over time, we noticed that honey bees held at a feeding place for several hours sometimes headed not in the homeward compass direction on their release, but in the reverse compass direction. This behavior suggested that the path integration system had been reset to a state corresponding to an outward flight to the food. Most models of insect navigation assume that it is the experience of reaching home that resets the path integration system, enabling the activation of vectors appropriate for subsequent outbound foraging trips. Here we provide evidence that this resetting can be influenced by motivational cues associated with food deprivation. The effect of food deprivation is independent of any positional cues provided by familiar landmarks or by experience in traveling toward a goal.

The biology of the dance language.

Honey bee foragers dance to communicate the spatial location of food and other resources to their nestmates. This remarkable communication system has long served as an important model system for studying mechanisms and evolution of complex behavior. I provide a broad synthesis of recent research on dance communication, concentrating on the areas that are currently the focus of active research. Specific issues considered are as follows: (a) the sensory and integrative mechanisms underlying the processing of spatial information in dance communication, (b) the role of dance communication in regulating the recruitment of workers to resources in the environment, (c) the evolution of the dance language, and (d) the adaptive fine-tuning of the dance for efficient spatial communication.