Reviewer #2 (Public review):
Summary:
In a 1.5m diameter, 0.8m high circular arena bumblebees were accustomed to exit the entrance to their nest on the floor surrounded by an array of identical cylindrical landmarks and to forage in an adjacent compartment which they could reach through an exit tube in the arena wall at a height of 28cm. The movements of one group of bees were restricted to a height of 30cm, the height of the landmark array, while the other group was able to move up to heights of 80cm, thus being able to see the landmark array from above.
During one series of tests, the flights of bees returning from the foraging compartment were recorded as they tried to reach the nest entrance on the floor of the arena with the landmark array shifted to various positions away from the true nest entrance location. The results of these tests showed that the bees searched for the net entrance in the location that was defined by the landmark array.
In a second series of tests, access to the landmark array was prevented from the side, but not from top, by a transparent screen surrounding the landmark array. These tests showed that the bees of both groups rarely entered the array from above, but kept trying to enter it from the side.
The authors express surprise at this result because modelling the navigational information supplied by panoramic snapshots in this arena had indicated that the most robust information to the location of the nest entrance within the landmark array was supplied by views of the array from above, leading to the following strong conclusions:
line 51: "Snapshot models perform best with bird's eye views";<br />
line 188: "Overall, our model analysis could show that snapshot models are not able to find home with views within a cluttered environment but only with views from above it.";<br />
line 231: "Our study underscores the limitations inherent in snapshot models, revealing their inability to provide precise positional estimates within densely cluttered environments, especially when compared to the navigational abilities of bees using frog's-eye views."
Strengths:
The experimental set-up allows to record the flight behaviour of bees in great spatial and temporal detail and in principle also to reconstruct the visual information available to the bees throughout the arena.
Modelling: The revised manuscript now presents the results of modelling that includes information potentially available to the bees from the arena wall and in particular from the top edge of the arena.
As I predicted, this increases the width of rotational image difference functions and therefore provides directional guidance over a larger range of misalignments. However, the authors dismiss the modelling results based on such reconstructed views which more realistically describe the information available to the bumblebees, because (line 291ff): 'Further simulations with a rendered arena wall led to worse results because the agent was mainly led to the centre of the arena (Fig. S17, Fig. S18-21)".
What the modelling in Fig. 17 actually shows is that the agent is led more or less exactly to the 'entry points' to the arena chosen by the real bees (Fig. 4). The authors ignore this and in their rebuttal state that 'We hypothesised that the arena wall and object location created ambiguity'. The problem here is that you don't remove potential 'ambiguity' for real bees by ignoring information they are unlikely to ignore.
Behavioural analysis: The full potential of the set-up was not used to understand how the bees' navigation behaviour develops over time in this arena and what opportunities the bees have had to learn the location of the nest entrance during repeated learning flights and return flights.
Without a detailed analysis of the bees' behaviour during 'training', including learning flights and return flights, it is very hard to follow the authors' conclusions. The behaviour that is observed in the tests may be the result of the bees' extended experience shuttling between the nest and the entry to the foraging arena at 28cm height in the arena wall. For instance, it would have been important to see the return flights of bees following the learning flights shown in Fig. 17.
Basically both groups of bees (constrained to fly below the height of landmarks (F) or throughout the height of the arena (B)) had ample opportunities to learn that the nest entrance lies on the floor of the landmark array. The only reason why B-bees may not have entered the array from above when access from the side was prevented may simply be that bumblebees, because they bumble, find it hard to perform a hovering descent into the array.
The revised manuscript does not address my concerns. The rebuttal states that a detailed analysis of learning and return flights was 'outside the scope of this particular study', that their experimental design 'does not require the entire history of the bee's trajectory to be tested', that 'the entire flight history...will require...effort...conceptually' and that it would be 'difficult to test a hypothesis'.
These responses clarify the frustrating problem with this study: The authors are more concerned with testing hypotheses than with trying to understand how bumblebees learn to cope with a situation which constrains their learning choreography and confronts them with the one fundamental problem view-based homing has: repetitive scene elements.
Homing is an experience-dependent process and to understand what cues the bees used to navigate this set-up requires an analysis of the whole learning process. For instance, it may well be that the B+G+ bees initially did enter the array from above, but subsequently learnt a more efficient route into the array, by simply entering it from the side, followed by 'unguided' searching.
General: The most serious weakness of the set-up is that it is spatially and visually constrained, in particular lacking a distant visual panorama, which under natural conditions is crucial for the range over which rotational image difference functions provide navigational guidance. In addition, the array of identical landmarks is not representative of natural clutter and, because it is visually repetitive, poses unnatural problems for view-based homing algorithms. This is the reason why the functions degrade so quickly from one position to the next (Fig. 9-12) when more distant scene elements are excluded.
In conclusion, I do not feel that I have learnt anything useful from this experiment; it does suggest, however, that to fully appreciate and understand the homing abilities of insects, there is no alternative but to investigate these abilities in the natural conditions in which they have evolved. A nice start would be to build camera-based 3D models of natural bumblebee nest entrance environments and analyse whether there are any particularly unusual challenges for the visual localization of the nest entrance.