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First published online November 2, 2007
Journal of Experimental Biology 210, 4034-4042 (2007)
Published by The Company of Biologists 2007
doi: 10.1242/jeb.003756
Flight performance in night-flying sweat bees suffers at low light levels
1 Department of Cell and Organism Biology, Helgonavägen 3, Lund
University, S-223 62, Lund, Sweden
2 Smithsonian Tropical Research Institute, Box 0843-03092, Balboa, Ancon,
Republic of Panama
* Author for correspondence at present address: University of California, Department of Physiological Science, 621 Charles E. Young Dr. South, Box 951606, Los Angeles, CA 90095-1606, USA (e-mail: jamiet{at}physci.ucla.edu)
Accepted 5 September 2007
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Key words: nocturnal vision, flight, apposition eye, visual summation, invertebrate, arthropoda, insecta
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). To see
successfully in dim light, an insect usually requires either optical
adaptations to increase light capture, such as superposition eyes, or a
significant reduction in visually demanding behaviors, such as flight. Bees
meet neither criterion; they all have apposition eyes, and they fly using
visual navigation to forage and return to their nests. Nocturnal bees,
therefore, are understandably rare. The large neotropical sweat bees of the
genus Megalopta (Family Halictidae) are an exception. Not only do
they fly exclusively at night, but they do so at light levels dimmer than
starlight (Warrant et al.,
2004; Kelber et al.,
2006), and they have undergone an adaptive radiation with 30
described species (Moure and Hurd,
1987; Engel et al.,
1997; Wcislo et al.,
2004).
Megalopta experience such low light levels for several reasons.
First, they forage only when the sun is down: shortly before sunrise, and
shortly after sunset (Warrant et al.,
2004; Kelber et al.,
2006). Second, because the sun moves perpendicular to the horizon
near the equator, light changes more quickly at sunrise and sunset than at
higher latitudes. A mere 15 min before sunrise or after sunset, the sun is
significantly below the horizon. Third, Megalopta nests are often
found under thick canopy in the understory, which can make the forest seem dim
even during bright daylight. During active flight times, the forest at nest
sites is more than ten times dimmer than the forest edge
(Kelber et al., 2006). Taken
together, these factors produce what is, to a human observer, impenetrable
darkness.
All eusocial bees, ants and wasps are in the monophyletic lineage
Euaculeata (Grimaldi and Engel,
2005), in which nesting evolved together with nest homing
(Jander, 1997). Homing is
accomplished in part using remembered visual landmarks
(Collett et al., 2007;
Collett and Zeil, 1998;
Collett, 1992), such as by
homing in on a goal (such as minute nest entrances)
(Tinbergen, 1932) and piloting
along a familiar route (Baerends,
1941), and Megalopta likely use both these techniques.
During their brief flights from the nest, Megalopta undertake the
same visual activities as diurnal bees and other insects: they learn landmarks
around their nests using orientation flights, navigate to pollen sources, and
return to inconspicuous nest entrances
(Warrant et al., 2004). For
landing at the nest, Megalopta use visual navigation to the exclusion
of other senses such as olfaction, as they reject even their own nests located
just a few cm away, when visual landmarks indicate that another nest is
correct (Warrant et al.,
2004).
For most animals, reliable vision in this environment requires a nocturnal
eye design, which maximizes capture of scarce light, and Megalopta
has several of the required adaptations. Female Megalopta genalis
have relatively large eyes (Jander and
Jander, 2002). Also, corneal facet diameters are 1.8 times larger,
and rhabdom diameters 4–5 times larger, than those of diurnal halictids
(Greiner et al., 2004a). These
optical adaptations together make the eyes of M. genalis 27 times
more sensitive than those of their diurnal counterparts
(Greiner et al., 2004a;
Warrant et al., 2004); this is
a worthwhile improvement, but not enough to explain their visual behaviors,
such as landing at the nest entrance at night
(Warrant et al., 2004). What
Megalopta and all other bees lack is the classical nocturnal
adaptation for compound eyes: superposition optics. Superposition eyes gather
light from many facets, and superimpose it onto a single rhabdom
(Land, 1981;
Land and Nilsson, 2002). This
is the predominant eye design of nocturnal insect groups, such as moths, and
can increase light catch and sensitivity by up to several thousand-fold
(Nilsson, 1989;
Warrant and McIntyre, 1993;
Land and Nilsson, 2002).
To bridge the gap between the tremendous light gathering ability of a
superposition eye and their own modest optical enhancements,
Megalopta may rely heavily on neural strategies. Both anatomical
(Greiner et al., 2004b;
Greiner et al., 2005) and
theoretical (Theobald et al.,
2006) evidence indicates the use of two forms of neural summation
in Megalopta optic lobes. Spatial summation, which improves visual
reliability by grouping signals from neighboring photoreceptors, and temporal
summation, which does so by increasing integration times. These strategies can
dramatically improve vision in conditions otherwise plagued by photon noise
(Laughlin, 1990;
Warrant et al., 1996;
Warrant, 1999).
However, while the primary cost of optical strategies is just the extra
size, mass and energy required by a bigger eye
(Kirschfeld, 1976;
Land, 1981;
Laughlin et al., 1998), neural
summation strategies are costly due to their degradation of visual acuity
(Warrant, 1999). Size and mass
are certainly important factors for small flying insects, but acuity is
equivalent to visual information. The only reason to trade resolution for
sensitivity is if it improves visual performance, which is the case in really
dark conditions (Snyder et al.,
1977a; Snyder et al.,
1977b). Without nocturnal optics, a sharp, fast visual system must
become blurry and slow, or face an image swamped with photon noise. This is
conceptually analogous to the problems faced by a photographer in dim light
without a large lens, who must use either grainy film or slow shutter speeds
to get a proper exposure. Both techniques sacrifice quality to obtain an image
that is otherwise impossible.
The combination of apposition eyes and nocturnal behaviors makes Megalopta the ideal candidate to exploit neural summation strategies. If they are, in fact, relying on visual summation to fly at the very darkest limits of their nocturnal activity, do they suffer from reduced acuity? Our goal was to determine whether visual summation, while lowering the light levels at which bees are able to fly, also degrades their capacity for precise flight. After foraging, the return flight to the nest culminates in an approach and landing at the nest entrance. In brighter light this is direct and accurate. We expected that nest returns would become slow and inexact in darker conditions. To assess this we measured light levels at the nest, and reconstructed three-dimensional flight paths of bees returning to the nest.
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)
and Leigh (Leigh, 1999).
Megalopta is a Neotropical genus of nocturnal and crepuscular sweat
bees (Hymenoptera: Halictidae) (Moure and
Hurd, 1987; Engel et al.,
1997). Megalopta genalis Meade-Waldo is distributed
throughout Panama and northern Colombia, and Megalopta ecuadoria
Friese is found in Panama, Colombia, Ecuador and Brazil
(Moure and Hurd, 1987).
Light measurement
To measure photometric light levels we used an International Light IL700
(International Light, Inc., Newburyport, MA, USA) photometer (detector: SHD033
#234) fitted with a lens and filter (Y #21496) to read cd
m–2. The detector was pointed at the nest site of interest,
at a distance of 5 m to avoid disturbing the bees and to include a sample of
the scene surrounding the nest. A feature of extended fields is that luminance
stays constant with distance; the drop in intensity with distance exactly
offsets the extra area included by the projected solid angle. Sampling
different directions revealed that at this site, brightness was fairly
constant with detector angle. Horizontal directions varied between 0.9 and 1.4
times the brightness pointed at the nest; upwards at the canopy was about 10
times as bright, downwards at the ground was 0.2 times as bright, and these
ratios were constant as ambient light changed. We took readings every 2 min
during videotaping for approximately 30 min before and after sunrise and
sunset. Although Megalopta are known to fly earlier in the morning
and later at night, at this site they were never observed to do so. All
readings were taken with a 1 min integration time.
Three dimensional flight paths
We included both M. genalis and the closely related M.
ecuadoria for this experiment. They were pooled because their nests
cannot be reliably distinguished in the field without damaging them and
disturbing the bees. We videotaped eight different nests from which bees
emerged to forage. Of these, three were indigenous to our site and videotaped
where they were discovered. The other five were transported to our site,
placed at the locations of old nests, and allowed to settle for at least 3
days before data were taken. Each nest site was 1–1.5 m above ground,
and was flanked by at least one hemisphere of open space. This made the nests
convenient to locate and videotape. The site was approximately 40 min hike
from the nearest buildings on BCI, chosen to minimize light pollution from
non-natural sources.
To compute flight paths, we used a pair of consumer video-cameras in `nightshot' infrared recording mode (Sony Corporation, Tokyo, Japan), which recorded at 30 frames s–1, at 720x576 pixels. Videotapes provided just over 1 h of recording time, which began approximately 30 min before sunrise or sunset, and ended 30 min after. These limits were chosen after preliminary observations indicated that, at this site, no flights usually took place outside of this time window. We placed video-cameras on tripods at right angles, each 1 m from the entrance of an identified nest and oriented horizontally, with the nest entrance centered in each frame. Cameras were leveled using a level bubble on the tripods, set perpendicular to one another with a known right angle pointed towards each simultaneously, and moved 1 m from the nest entrance (measured with a meter stick). Zoom settings were held constant and absolute lengths were calibrated each time by holding a ruler at the nest towards each camera in turn, approximately 10 min before taping began (to avoid disturbing the bees).
Megalopta monitors the light level from the nest before flying in
the morning, and artificial lights near the nest entrance can cause bees to
exit earlier than they ever do naturally
(Kelber et al., 2006). To
avoid this, for each morning recording we set up tripods on the previous
night. In the morning, cameras were set up and started in the dark. Likewise,
in the evening after recording, cameras were taken down in the dark.
We used auxiliary infrared lights to illuminate bees from below. This produced a bright image, but nightshot is always quite blurry. So although the bee's position could be measured reliably, body axis could not, and we measured only her position in these experiments.
Before each recording session, we synchronized the camera clocks to within 1 s of each other. However, at 30 frames s–1, recordings might still be tens of frames off. We used the redundant dimension, up and down, to correct this asynchrony. In other words, in a (x, y, z) coordinate scheme, one camera captured x and z motion, while the other captured y and z motion. After data were digitized, we interpolated the paths with a line that presumed each bee's jerk – the derivative of acceleration – to be constant between points. The two views were then synchronized by adding a time offset to the front camera recording that maximized the correlation between the front and side camera z motion. This adjustment was always small, never more than 0.17 s (five frames), and in over half our recordings it was less than 0.03 s (one frame).
Every video frame at this point had a complement taken at the same moment, but at a 90° angle. A point in an image represents an object in space, relative to the entrance pupil of the camera. In a single image this position is ambiguous, as it could represent any point along a line in that direction, but with two images taken from known, different locations, the three-dimensional coordinates of a point are determined by the intersection of lines projected at the two angles. This is illustrated in Fig. 1. With this set-up we could compute flight paths in a volume of space slightly larger than a 1 m cube.
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Notably, this variability was not simply the result of bright days and dim days, which varied, for example, with the phase of the moon. Rather, much of the variability was on a minute-to-minute basis, which is illustrated by several sample curves in Fig. 2 (gray lines). A seemingly bright evening sometimes became much darker than average in just a few minutes. This was largely the result of clouds, which could alter brightness in short time periods. Clouds appearing overhead had a complex effect, and could produce local dimming, for example when they blocked the moon, or brightening, for example when they reflected light from the horizon. Sometimes wind moving the canopy leaves also had a small effect.
Although mean light levels were fairly symmetrical between morning and evening, we found a curious increase in light variability after sunset, which had no counterpart in the early morning. We do not know the cause, and it may have been just a peculiarity of our sample, but one striking difference between mornings and evenings is air temperature at the ground. Since cloud formation and position is driven by temperature and humidity, and clouds probably caused most of the variation in light level at a given time of day, temperature is a good candidate to explain this variability.
Flight trajectories and duration
Our reconstructed flight paths were videotaped with simultaneous light
measurements at the site of the nest. For the month of our measurements, no
bees flew while the sun was up, with the single exception of an orientation
flight that occurred just 4 min before sunset.
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To determine whether these longer approaches were the result of smoothly edging towards the nest (such as a spiral approach), or something more erratic, we chose an arbitrary distance of 15 cm from the nest entrance, and recorded how often each bee entered and left this imaginary threshold sphere. Fig. 5E shows the distance from the nest for the sample flights as a function of time, and a horizontal threshold marker. The derivative of this distance trace is not velocity, since it is a scalar distance between the bee and its nest. For example, a bee could move quite quickly, but orbit at a constant nest distance. The final plot (Fig. 5F) shows for each flight, the number of approaches crossing this threshold, against landing duration. The number of approaches is significantly related to flight duration, supporting the notion that the longer landings are erratic.
To understand the structure of these flights, we examined the changes in flight speeds as they varied with nest distance. Fig. 6A shows a box plot of speeds (both dark and light flights) as they varied with distance from the nest entrance. The median speeds near the nest (<10 cm) dropped to about a third of the speeds from farther out (>50 cm). More notable, however, was the range of speeds farther out, nearly an order of magnitude greater than the range near the nest. Put another way, the nearer the nest, the more restricted flight speed became. We then broke these motion vectors into components parallel and perpendicular to the nest axis (Fig. 6B). Most of this variation – not necessarily most of the motion – is from flight parallel to the nest axis.
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We had anticipated that bees might advance more slowly in the dark, temporally integrating visual information as they homed in on their nests. Low flight speeds would benefit any onlooker faced with an unreliable scene, or low acuity caused by spatial and temporal pooling. Nevertheless, the bees that landed in dim light did not move slowly.
Two considerations might explain why they did not. First, slow flight and
hovering are difficult skills even in bright light, but they pose special
problems at night (O'Carroll et al.,
1996). They require sensitivity to low velocity motion, which is
coded in a visual scene in high spatial frequencies and low temporal
frequencies (the velocity of any sinusoidal component of a scene is
ft/fs, the temporal divided by the
spatial frequency) (O'Carroll et al.,
1997). Diurnal hovering insects, such as dragonflies, have
unusually high acuity compound eyes. Nocturnal hovering insects, such as
hawkmoths, lose acuity to spatial pooling, and so must be sensitive to very
low temporal frequencies. All things considered, night hovering may actually
be more difficult than night nest finding. Second, it has been shown that bees
(Cartwright and Collett, 1979)
and wasps (Zeil, 1993) learn
the speed at which landmark images move across the retina as they fly towards
their goal. It is possible that, even as light levels and acuity drop, bees
cannot slow their approaches without compromising landmark recognition near
the nest.
Instead, the advancing and retreating flights noted in
Fig. 5F and
Fig. 6B offer the compelling
interpretation that each advance is a landing attempt. Megalopta land
with certainty in the bright light, but as it darkens the chance of a
successful landing the first time drops, and the average number of attempts
increases. This accounts for the variable flight time in the dark by
probability; some landings worked on the first try, others took multiple
passes. It is also consistent with visual summation; bees faced with blurry
images of their nests might often miss the landing. Finally, it is consistent
with orientation behavior in diurnal bees, where perturbations to previously
learned landmarks induce multiple approaches and retreats from a nest entrance
(Tinbergen, 1972;
Wcislo, 1992).
When navigating towards a close goal, insects continually compare their
current retinal image with memory `snapshots' of landmarks and move to reduce
discrepancies between the two (Cartwright
and Collett, 1983; Junger,
1991). Whether in the morning or evening, Megalopta
leaves and returns to the nest at different light intensities. Matching an
image remembered from a different light level could be problematic because dim
light produces a mismatch between viewed and remembered images
(Zeil et al., 2003). This
problem is minimized, however, since optimal vision in the dark favors low
frequency spatial information (Warrant,
1999), which corresponds to the highest contrasts in natural
scenes (Burton and Moorhead,
1987; Ruderman,
1994). Further, natural images are easily transformed to reduce
the effects of illumination (Sturzl and
Zeil, 2007).
Megalopta's landing attempts can be roughly compared to the familiar task of finding a light switch in the dark. We might study the wall with night vision and gradually locate the switch, or simply start groping around. Surely we use both strategies to light up the room as quickly as possible. Megalopta probably uses both strategies as well, but the attempted landings may dominate the obvious structure of the flight. Occasional quick landings in the dark may be the pay-off for taking a guess even when uncertain. One difference that favors a bee over a light switch hunter is that as a bee moves in, she gets a closer view of her target. A difference that works against a bee, in contrast, is that without feet on the ground, she can use only visual information to estimate her own motion. This could potentially lead to unintended collisions with surrounding sticks, but we didn't observe this. As noted before, the nests we videotaped had wide, open spaces around at least a hemisphere of the entrance, and bees approached from this direction for landing.
Sometimes bees failed to return during our videotaping
We restricted our analysis to flights that ended in a successful landing.
However, occasionally in the evenings we observed flights that did not end
with a landing (Fig. 7). Often
a bee had not returned even 20 min after the attempt, at which point the
videotape ended. In every case bees were present the next morning, but when
and how they returned is unknown. One possibility is that they made more
attempts later in the night, although it would be no brighter before the
morning. Another possibility is that bees landed nearby and walked back, and
although this would be an inherently risky strategy in the crowded rainforest,
there is at least one example of a diurnal neotropical bee that walks to her
nest after foraging (Cameron and Whitfield,
1996). It remains uncertain how well a bee that navigates by
vision and usually approaches her nest in the air, can find her nest on foot.
Possibly olfactory cues, although not part of regular landing
(Warrant et al., 2004), come
into play in this situation (Wcislo,
1992).
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On some mornings we observed early returning bees unsuccessfully attempt to land, but they simply left and returned later. Since light levels often increased by an order of magnitude in just 10 min, a bee struggling to locate her nest might have no problems just minutes later.
In this sense, morning flights are less risky than evening flights.
Megalopta are in some sense, risk-averse bees, guarding their nests
almost full time. This is important, since unprotected nests are highly prone
to ant predation (Smith et al.,
2003). The observation that bees seem sometimes unable to return
from evening flights is not in line with this general strategy. Further, the
degradation of their flight performance in the dark is risky as well, since
swooping bats were videotaped near the nest on an almost daily basis.
Other sources of variation
Light level is only one of several factors potentially affecting the
accuracy of bee flights. In this study we pooled M. genalis and
M. ecuadoria, but M. genalis has larger eyes, which
therefore collect more light. Both species have large eyes relative to body
size, and this shows the evolutionary importance of vision for these groups
(Jander and Jander, 2002). But
absolute eye size determines how much light is collected, and thus limits
resolution and sensitivity. Even eye size variations between individuals of
the same species might matter when resolving a dark image.
As mentioned above, bees probably use memorized landmark images, or
`snapshots', on the outward and inward routes, which are of large size
objects, for example the canopy patterns, which some ants are known to use for
orientation (Hölldobler,
1980). These probably get bees close to the vicinity of the nest,
and the quality of these snapshot memories may vary from bee to bee. Bees with
better memories and better snapshots could find the nest more quickly.
The terrain itself may also provide better snapshots. An area with
conspicuous landmarks might be fundamentally more navigable than one without
features noticeable to a bee. For example, honeybee navigation utilizes visual
odometry and landmarks, but will favor landmarks in situations of ambiguity
(Vladusich et al., 2005).
Further, odometry varies with the properties of the terrain
(Tautz et al., 2004). Even if
bees began with good, recognizable nest locations, the nests are built in
detached, dead sticks, which can be moved by wind, gravity and larger animals
(biologists, for example).
Finally, many environmental and physiological issues might affect the quality of any single landing, such as wind, temperature, pollen load, energy level or bee age.
Predictions from information theory
If evolution produces eyes to maximize information capacity, then the
optimal resolution depends on both light level and image speed
(Snyder et al., 1977a;
Snyder et al., 1977b). This
means animals that often view dim or fast visual scenes need lower visual
acuity to collect more information. This study demonstrates that
Megalopta view a wide range of brightnesses and probably a wide range
of image speeds, making them prime candidates to vary their acuity with their
immediate conditions. This study measured light levels and bee speeds, but
determining image velocity on the retina requires body and head orientation,
which we could not measure (the video camera is also limited to blurry images
in the dark). Better cameras and more infrared light might allow this level of
analysis.
However, comparative behavior would also offer insight into this problem.
As noted above, visual acuity is limited by absolute eye size, meaning that
smaller bees with smaller eyes have much lower spatial resolution, no matter
what light levels and image speeds they view
(Jander and Jander, 2002).
Tellingly, smaller bees also have more erratic nest approaches
(Decelles and Laroca, 1979),
and we surmise that low acuity from small size and low acuity from dim light
vision have parallel effects on nest approaches. A direct comparison of flight
paths from nocturnal bees and small diurnal bees could test this
experimentally.
Conclusions
Megalopta have evolved into a niche rarely occupied by bees, and
thus presumably enjoy reduced predation and competition
(Wcislo et al., 2004).
However, they have moved into this niche without the most powerful optical
adaptations of their nocturnal competitors. This study shows that
Megalopta flies in light so dim that flight performance is
compromised, and suggests the benefits of a nocturnal lifestyle may have
pushed them to fly near the very limit of their visual ability.
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