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Virtual reality (VR) offers an appealing experimental framework for studying visual performances of insects under highly controlled conditions. In the case of the honeybee Apis mellifera, this possibility may fill the gap between behavioural analyses in free-flight and cellular analyses in the laboratory. Using automated, computer-controlled systems, it is possible to generate virtual stimuli or even entire environments that can be modified to test hypotheses on bee visual behaviour. The bee itself can remain tethered in place, making it possible to record neural activity while the bees is performing behavioural tasks. Recent studies have examined visual navigation and attentional processes in VR on flying or walking tethered bees, but experimental paradigms for examining visual learning and memory are only just emerging. Behavioural performances of bees under current experimental conditions are often lower in VR than in natural environments, but further improvements on current experimental protocols seem possible. Here we discuss current developments and conclude that it is essential to tailor the specifications of the VR simulation to the visual processing of honeybees to improve the success of this research endeavour.

The movement pattern of a searching animal affects how it interacts with the environment, thus playing an important role in many environmental processes. Social hymenopteran foragers make good models for studying search patterns because their only role is to search for food and bring it back to the nest or hive. Search patterns in ants and bees, the most studied social hymenopterans, consist of loops around the origin of search that expand in size as the search goes on. Different factors influence search structure, including the type and distribution of the resource that is targeted, and the kind and amount of information available for navigation. In the distributions of the lengths of search segments, bees exhibit a Levy walk pattern, which follows a power law in which occasional long segments are interspersed within many short segments, and yet longer segments are interspersed within the long segments. Such a scale-free and heavy-tailed distribution has been shown to be optimal in searching for sparse targets. Ants on the other hand show a composite Brownian search distribution, composed of two exponential distributions at different scales. We argue that such composite Brownian searches serve to approximate a Levy walk. Both Levy walks and composite Brownian searches are found in a range of other animals, including hunter–gatherer humans. These patterns may be ancient, as they have been found in fossils dating to at least 50 million years.

In a synthetic approach to studying navigational abilities in desert ants, we review recent work comparing ants living in different visual ecologies. Those living in a visually rich habitat strewn with tussocks, bushes, and trees are compared to those living in visually barren salt pans, as exemplified by the Central Australian Melophorus bagoti and the North African Cataglyphis fortis, respectively. In bare habitats the navigator must rely primarily on path integration, keeping track of the distance and direction in which it has travelled, while in visually rich habitats the navigator can rely more on guidance by the visual panorama. Consistent with these expectations, C. fortis performs better than M. bagoti on various measures of precision at path integration. In contrast, M. bagoti learned a visually based associative task better than C. fortis, the latter generally failing at the task. Both these ants, however, exhibit a similar pattern of systematic search as a 'back up' strategy when other navigational strategies fail. A newly investigated salt-pan species of Melophorus (as yet unnamed) resembles C. fortis more, and its congener M. bagoti less, in its path integration. The synthetic approach would benefit from comparing more species chosen to address evolutionary questions. This article is part of a Special Issue entitled: CO3 2013.

Scientific Reports 5: Article number: 10747; Published online: 29 May 2015; Updated: 08 July 2016 The authors neglected to cite a published thesis that investigated a related aspect of tandem running in the same study species. This additional reference is listed below as reference 1, and should appear in the text as below.

Honeybees (Apis mellifera) are regularly faced with the task of navigating back to their hives from remote food sources. They have evolved several methods to do this, including compass-directed “vector” flights and the use of landmarks. If these hive-centered mechanisms are disrupted, bees revert to searching for the hive, using an optimal Levy flight searching strategy. The same strategy is adopted when a food source at a known location ceases to be available. Here, we show that the programming for this Levy strategy does not need to be very sophisticated or clever on the bee’s part, as Levy flight patterns can be derived from the Weber–Fechner law in a bee’s odometer. Odometry errors of a different kind occur in desert ants (Cataglyphis spp., Melophorus bagoti). The searching behaviors of these ants are very similar in overall structure to that of honeybees but do not display any Levy flight characteristics. We suggest that errors in the estimation of distance can be implicitly involved in shaping the structure of systematic search behavior and should not be regarded as merely deficiencies in the odometer.

Summary Many animals - including insects - navigate visually through their environment. Solitary foraging desert ants are known to acquire visual information from the surrounding panorama and use it to navigate along habitual routes or to pinpoint a goal like the nest. Returning foragers that fail to find the nest entrance engage in searching behaviour, during which they continue to use vision. The characteristics of searching behaviour have typically been investigated in unfamiliar environments. Here we investigated in detail the nest searching behaviour of Melophorus bagoti foragers within the familiar visual environment of their nest. First, by relating search behaviour to the information content of panoramic (360°) images, we found that searches were more accurate in visually cluttered environments. Second, as observed in unfamiliar visual surrounds, searches were dynamic and gradually expanded with time, showing that nest-pinpointing is not rigidly controlled by vision. Third, contrary to searches displayed in unfamiliar environments, searches observed here could be modelled as a single exponential search strategy, which is similar to a Brownian walk, and there was no evidence of a Lévy walk. Overall, our results revealed that searching behaviour is remarkably flexible and varies according to the relevance of information provided by the surrounding visual scenery.

Terrestrial panoramic cues, path integration and search behavior are the main navigational strategies used by ants to locate food and find their way back to the nest. Searching becomes important when the other navigational cues are either not available or cannot provide sufficient information to pinpoint the goal. When searching in one-dimensional channels Melophorus bagoti ants exhibit a systematic drift in the starting-point-to-goal direction as they turn back and forth, sometimes past the goal location ( Narendra et al., 2008 ). Here we show that this drift in channels is not a stereotypical part of the search behavior in these ants. It rather depends on the conditions of training. In experiments in which the nest entrance is located not at the end but at the side of the channel, forward drift is not always part of the nest search. Experiments on food searches showed that with the food source at the end of the channel, ants performed a linear drift in the starting-point-to-food direction. With food at the side of the channel, they showed a less pronounced drift toward the food source. In this constrained environment, especially with the goal at the end of the channel, ants seem to learn a routine such as ‘run along the channel’, and mix this routine with their usual strategy of turning back and forth in search.

The Australian desert ant Melophorus bagoti often follows stereotypical routes through a cluttered landscape containing both distant panoramic views and obstacles (plants) to navigate around. We created an artificial obstacle course for the ants between a feeder and their nest. Landmarks comprised natural objects in the landscape such as logs, branches, and tussocks. Many ants travelled stereotypical routes home through the obstacle course in training, threading repeatedly the same gaps in the landmarks. Manipulations altering the relations between the landmarks and the surrounding panorama, however, affected the routes in two major ways. Both interchanging the positions of landmarks (transpositions) and displacing the entire landmark set along with the starting position of the ants (translations) (1) reduced the stereotypicality of the route, and (2) increased turns and meanders during travel. The ants might have used the entire panorama in view-based travel, or the distal panorama might prime the identification and use of landmarks en route. Despite the large data set, both options (not mutually exclusive) remain viable.