The ecology of visual pigment tuning in an Australian marsupial: the honey possum Tarsipes rostratus
1 Department of Visual Neuroscience, Division of Neuroscience, Faculty of
Medicine, Imperial College London, St Dunstan's Road, London W6 8RP,
UK
2 School of Animal Biology, University of Western Australia, Crawley, WA
6009, Australia
3 School of Biological Sciences, University of Bristol, Bristol, BS8 1UG,
UK
* Author for correspondence (e-mail: p.sumner{at}imperial.ac.uk)
Accepted 16 March 2005
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Summary |
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Key words: colour vision, ecology of vision, trichromacy, dichromacy, mammal, long wave cone, middle wave cone, optimisation
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Introduction |
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In contrast to the relatively poor colour vision of most studied mammals,
many birds, reptiles and fish have four classes of daylight-functioning
photopigment sequestered in at least as many types of retinal cone. Such
retinal complexity gives these species the potential for tetrachromatic colour
vision, which has been confirmed in some species by psychophysical experiments
(e.g. Neumeyer, 1992). It is
believed that four classes of cone photosensitive protein (opsin) existed well
before the mammals diverged from the reptiles (e.g.
Collin et al., 2003
;
Yokoyama, 2000
), and that the
placental mammals retained only the longest and shortest wavelength-sensitive
classes. Some primates, including an ancestor in the human lineage, then
re-evolved a third cone opsin by creating two subtypes of the long-wave class
(e.g. Bowmaker et al., 1991
;
Jacobs, 1993
). It was thought
that these primates were the only mammals to have more than two cone visual
pigments until Arrese et al.
(2002b
) discovered three cone
pigments in two species of Australian marsupial, the fat-tailed dunnart
Sminthopsis crassicaudata and the honey possum Tarsipes
rostratus. It is currently unknown how many other marsupial species may
have such retinal complexity and behavioural experiments have yet to
demonstrate trichromacy in any - microspectrophotometric (MSP) measurements
suggest that the quokka Setonix brachyurus and quenda (Southern brown
bandicoot, Isoodon obesulus) have three cone pigments
(Arrese et al., 2005
), while
electroretinogram, molecular and behavioural evidence suggests that the tamar
wallaby Macropus eugenii is dichromatic
(Deeb et al., 2003
;
Hemmi, 1999
;
Hemmi et al., 2000
). It is
also unknown whether the middle-wave cone pigments discovered in marsupials
are related to the middle-wave cone pigments of other vertebrates such as
fish, reptiles and birds and thus likely to have been retained from ancestral
mammals, or whether they are related to marsupial long-wave pigments and thus
mid-wavelength sensitivity is likely to have been `re-evolved' by these
marsupials in a manner analogous to the opsin duplication seen in
primates.
Presence of marsupial M cones
Middle-wave cones (M cones) seem to be absent in some marsupial species and
present in others (Arrese et al.,
2002b,
2005
;
Deeb et al., 2003
;
Hemmi, 1999
;
Hemmi et al., 2000
). Whether
the marsupial M cones have been inherited or re-invented, they are very
unlikely to have been maintained if they offered no selective advantage. Even
if there is no extra energetic cost to having more types of cone in the
retina, colour processing takes up neural resources, and more importantly,
there are visual performance costs associated with multiple receptor types.
For example, spatial acuity must be reduced, because, if only one class of
receptor is used to provide spatial information, the density of this class
must be less if there are more photoreceptor types present; but if more than
one class is used, the difference in their signals adds noise to spatial
information and there is the additional problem of chromatic aberration
(different wavelengths cannot concurrently be in focus on the retina)
(Osorio et al., 1998
;
Regan et al., 2001
). Even in
the absence of costs, genetic mutations would act in the direction of losing
visual pigments if there were no selective pressure to keep them. There are
numerous examples of species that have reduced their colour vision
capabilities. For example, in addition to the general reduction to two cone
classes in placental mammals, many species are being discovered to have
retained only one cone class. These include all whales and seals tested
(Peichl et al., 2001
), two
nocturnal primates (Jacobs et al.,
1993
,
1996
;
Wikler and Rakic, 1990
),
racoons (Jacobs and Deegan,
1992
; Peichl and Pohl,
2000
) and some rodents (summarised in
Ahnelt and Kolb, 2000
). It is
thus pertinent to attempt to discover potential advantages of trichromacy in
marsupials, and thereby attempt to identify the selective pressures acting on
the evolution of their visual system.
Tuning of marsupial L cones
Trichromacy may offer a number of advantages over dichromacy. As such,
simple comparison of trichromacy with dichromacy might not identify the
crucial tasks important to each species. Interestingly, while the marsupial M
cones so far discovered are all very similar to each other, different tunings
for the long-wave cones (L cones) have been found in even the small sample of
Australian marsupials measured to date. The L cone wavelengths of peak
sensitivity (max) are in the range 530-538 nm for four of
the six measured species - tamar wallaby Macropus eugenii, quokka
Setonix brachyurus, fat-tailed dunnart Sminthopsis
crassicaudata and stripe-faced dunnart Sminthopsis macroura
(Arrese et al., 2002b
,
2005
;
Deeb et al., 2003
;
Hemmi et al., 2000
;
Strachan et al., 2004
).
However, the quenda (Southern brown bandicoot, Isoodon obesulus) has
a
max of 551 nm, and the honey possum Tarsipes
rostratus has the longest wave tuned L cone, with a
max at 557 nm (Arrese et
al., 2002b
). The honey possum is a unique marsupial: it is in the
diprotodont order, but it is the only species in its family/superfamily
(Strahan, 1995
). The other
measured diprotodont species are the tamar wallaby and quokka, which have L
cone
max in the range 530-538 nm. Arrese et al.
(2002b
) suggested that the
longer wavelength sensitivity of the honey possum may be correlated with the
specific requirements of its visual ecology. The honey possum has a diet
virtually unique amongst marsupials, feeding almost exclusively on nectar and
pollen, and it has numerous morphological adaptations, particularly to its
tongue, skull and gut, for this diet
(Richardson et al., 1986
).
Arrese et al. (2002b
) suggested
that the honey possum's L cones may be well tuned to enhance the
`detection of yellow and red nectar-producing flowers, particularly in a
crepuscular light environment', and/or to `assess the maturity of
flowers, which are yellow or red when ripe but green when unripe'. We set
out to test these suggestions via specific hypotheses.
We divided the honey possum's need to find food into three tasks: (1)
detecting food-rich `target' flowers amongst their natural background (foliage
or other vegetation); (2) distinguishing target flowers from flowers of
non-target species; (3) discerning the maturity (correlated with food value)
of flowers of the most important target species (see
Fig. 1). For each of these
tasks we assessed first whether the honey possum's trichromacy offered an
advantage over the dichromacy apparent in most mammals. More interestingly, we
asked whether the tuning of the honey possum's L cones provided advantages
compared with the tuning of the other marsupial's L cones, and whether any
other hypothetical tuning would be better still. To this end, we developed the
methodology of Vorobyev and Osorio
(1998) by combining it with
the analysis used by Regan et al.
(1998
) and Sumner and Mollon
(2000a
). In this way we hoped
to identify the critical visual tasks that may have provided selective
pressure for the evolution of cone spectral sensitivities in the honey possum.
Our study differs from previous studies of this kind on other animals in that
all radiance spectra were measured directly in the field, rather than
estimated from multiplying spectral reflectance with a measure of spectral
irradiance of daylight (the latter method does not, for example, take into
account light transmitted through leaves or petals; see for example,
Sumner and Mollon, 2000a
).
Since honey possums can be active at various times of day from afternoon
through dusk and evening, and then again before dawn until mid morning
(Arrese and Runham, 2002
;
Vose, 1973
), we made
measurements under different light conditions (sun, cloud, shade, dusk), and
kept these separate in the analysis.
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Materials and methods |
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Calibrating the teleradiometer involved measuring a NIST-traceable light source (Ocean Optics DH-2000-CAL) of known radiant output. The teleradiometer calibration was found to vary with both focus distance and f-number of the lens, but knowledge of these variables allowed the data recorded in the field to be corrected to absolute spectral radiance for use in subsequent analyses.
Field measurements
Field work was conducted at two sites in Western Australia, both of which
are known habitats for honey possums: Mount Lesueur National Park near Jurien,
and Whiteman Park near Perth. The former is an eroded laterite landscape of
some 27 kha, vegetated with scrub comprising a diverse flora of more than 800
species, many of which are shrubs less than 2 m high but ranging from ground
plants to trees. The latter is a metropolitan area parkland that includes some
700 ha of mixed bushland, from which the general public is largely excluded.
Spectral radiance measurements were recorded with the teleradiometer, which
was mounted on a short tripod (ca. 0.25 m high) providing a `possum's eye
view' of the surrounding vegetation. In total, some 2300 spectral radiance
measurements were made, including both general vegetation and the leaves and
flowers of over 15 identified species of plants. Measurements were made from
dawn to post-dusk and in a variety of weather conditions ranging from full
cloud to full sunlight. Time of day, weather and orientation of the
teleradiometer relative to the sun were recorded with the spectral radiance
data for inclusion in analyses. Spectral radiance data were recorded in the
field as ASCII text files that were managed and merged by category using
Microsoft Excel 2000 before being further processed using Matlab (The
Mathworks Ltd.) version 6.5.
Quantum catches
For each stimulus radiance spectrum, quantum catches were calculated for
each class of cone photoreceptors by multiplying the stimulus radiance
spectrum by the cone's spectral sensitivity (i.e. corrected spectral
absorptance) over the full range of wavelengths to which the cone would have
any sensitivity. Qi, the quantum catch for receptor
i, is thus given by:
![]() | (1) |
where denotes wavelength, S(
) is the stimulus
radiance spectrum and Ri(
) is the receptor's
spectral sensitivity. Each receptor sensitivity (effective absorptance)
function was generated using the rhodopsin visual pigment template of
Govardovskii et al. (2000
),
adjusted for self-screening (assuming a cone outersegment length of 20 µm
and a specific absorbance at the
max of 0.0065
µm-1; Arrese et al.,
2002b
) and the spectral transmission of the lens (we used data for
the placental mouse, Mus musculus, lens; R. H. Douglas, personal
communication). The
max values for honey possum cones were
taken from Arrese et al.
(2002b
). For most aspects of
the analysis only the relative, not the absolute, quantum catch needs to be
known. However, absolute quantum catches are needed for the estimate of
quantum noise, explained below. To estimate absolute quantum catches we
assumed a 0.0001 sr solid angle for the stimulus (corresponding to a 1
cm2 circular stimulus at a distance of 1 m), a pupil diameter of 3
mm and a 100 ms integration time (Hood and
Finkelstein, 1986
). For trichromatic honey possums we estimated
that L cones covered 10% of the retinal area
(Arrese et al., 2002a
), and the
ratio of L:M:S cones was 10:5:1 (Arrese et
al., 2002b
), whereas for a hypothetical dichromatic animal lacking
M cones, the L:S ratio and the total retinal area covered by cones remained
approximately the same, so the L cone area increased to 15% and the S cone
area to 1.5%. We also made minor adjustments for light reflected back from the
cornea (5%; Hecht et al.,
1942
), the quantum efficiency of rhodopsins (0.67;
Knowles and Dartnall, 1977
)
and the fact that the effective sampling aperture of cones is probably smaller
than their diameter (0.8; Geisler,
1989
; although how the marsupial cone oil droplets affect this is
unknown). While these chosen values are only estimates and therefore their
product may vary up to an order of magnitude, the effect of varying them is
exactly equivalent to varying intensity in the illuminant, which changes over
several orders of magnitude during the daytimes at which honey possums are
active. We have tested several illuminant conditions and have also
artificially varied the level of the illuminant in our analyses to check that
this does not affect the results and conclusions given in this paper.
Chromatic distances
From the cone quantum catches, chromatic distances between stimuli were
calculated following the technique of Vorobyev and Osorio
(Vorobyev et al., 2001;
Vorobyev and Osorio, 1998
).
This technique has the advantage that the post-receptor neural `wiring' of an
animal's visual system does not need to be known, because the model assumes
that receptor noise is the main limitation in near threshold chromatic
discriminations. The quantum catches give each stimulus a position in a colour
space whose axes are the signals from each class of cone. For a dichromat the
colour space is thus two-dimensional. Each stimulus is in fact described not
by a point but by an ellipse that represents the probability spread of the
stimulus' position given that there is noise (i.e. error) in the receptor
signals. The centre of the ellipse is given by the calculated quantum catches
of the two cone classes and the width of the ellipse in each direction is
given by an estimate of the signalling noise for each cone class (see below).
The noise-scaled chromatic distance between two stimuli is then calculated as
the distance between the centres of each ellipse in the chromatic direction,
scaled by the width of the ellipses in that direction (the achromatic signal
is not used). This calculation for a dichromat reduces to:
![]() | (2) |
where )S is the noise-scaled chromatic distance between two
stimuli;
)fL is the difference between the L cone
signals for the two stimuli, this receptor signal being the log of the cone
quantum catch, fi=lnQi
(Osorio et al., 2004
);
)fS is similarly the difference between the S cone
signals for the two stimuli; eL and eS
are the noise in the L and S cone signals, respectively (see below).
For a trichromat the colour space is three dimensional, and each stimulus
is therefore represented as an ellipsoid whose centre is given by the
calculated S, M and L cone signals, and whose extent represents the estimated
signalling noise for each of these cone classes. The ellipsoid can be
collapsed onto a two-dimensional chromatic plane, and the noise-scaled
chromatic distance between two stimuli is then calculated as the distance
between the centres of each stimulus' ellipse scaled by the width of the
ellipses in that direction (see fig. 2 in
Osorio et al., 2004). This
calculation for a trichromat reduces to Eqn 3 below (for the formal
derivation, see Vorobyev and Osorio,
1998
):
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Signalling noise
The estimate of signalling noise for each cone class had two components:
quantum noise and neural noise. Quantum noise represents the probabilistic way
in which photons are absorbed by photopigment, whereas neural noise represents
the variation in synaptic neurotransmitter release per photon absorbed. In
very low light levels when quantum catches are low, quantum noise dominates.
In higher light levels quantum noise becomes unimportant and neural noise
dominates. Quantum noise is estimated as the square root of the calculated
quantum catch, , because
the quantum catch follows a probabilistic Poisson distribution with a variance
equal to the mean (i.e. the calculated quantum catch). Receptor neural noise
is estimated as
)iQi, where
)i is the `Weber fraction' of each cone class. The increment
in intensity needed to detect a target on a background is generally a constant
proportion of the background intensity, and this proportion is known as the
Weber fraction (e.g. Wyszecki and Stiles,
1982
). The expression used for the standard deviation in signal
due to the combined effects of quantum noise and neural noise is thus:
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and the relative signalling noise in each receptor class for each stimulus:
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The combined signalling noise for stimuli A and B, whose chromatic distance
we wished to calculate, is thus:
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We estimated the relative Weber fractions for the three honey possum cones
classes as 0.05, 0.071 and 0.16 for the L, M and S cones, respectively. The
ratio of these values is given by the square roots of the relative numbers of
each cone in the retina. The absolute values have to be estimated from human
values (e.g. Wyszecki and Stiles,
1982) and the few measurements made for other species (e.g.
Vorobyev et al., 2001
). Given
the small size of the eyes and the density of cones in the retina
(Arrese et al., 2002a
), we
chose the value of 0.05 for the L cones as a reasonable estimate (see
Vorobyev et al., 2001
), being
more than twice the value (half the sensitivity) of the human L cone system
(e.g. Wyszecki and Stiles,
1982
). For a hypothetical dichromatic animal lacking M cones, in
order that the L:S ratio and the total retinal area covered by cones remained
the same as for trichromats, the absolute numbers of L and S cones in the
model increased, giving reduced Weber fractions of 0.04 and 0.13. Since these
Weber fraction estimates are only approximate, we tested the effects of
varying these values beyond the plausible range to check that the results and
conclusions presented here were not altered in any important way.
The chromatic distances between stimuli calculated using Eqns 2 or 3 for dichromatic or trichromatic animals, respectively, were then used to assess the three foraging tasks of the honey possum: detecting target flowers in their natural background; discriminating flowers of target species from non-target species; and discerning the maturity of important target flowers. We explain these analyses with the simplest first, which is in fact the reverse order as listed above.
Discerning flower maturity
Each measured inflorescence of Banksia attenuata (see
Fig. 1) was classified as
immature if the flowers were not yet open, mature if they were open and
scented, and senescent if open but there was no scent detectable to us.
Following the procedure that Osorio et al.
(2004) applied to ripe and
unripe fruit, we found for each mature flower measurement the chromatic
distance to the most similar non-mature flower (immature or senescent), by
calculating chromatic distances to every non-mature flower measured in the
same conditions and finding the minimum. This discrimination between mature
and nearly mature or just senescent flowers represents the most difficult
colour discrimination the honey possum has to make, and one which cannot be
made on the basis of size and shape. We then simply calculated the mean and
median of these chromatic distances for all mature flower samples. First we
compared the outcome for a trichromatic honey possum with cone visual pigment
max values of 350, 505, 557 nm with the outcome for a
hypothetical dichromatic honey possum with
max of 350 and
557 nm (lacking M cones). Then, to find the optimal tuning of the L cone, we
calculated the outcome for hypothetical trichromatic honey possums with S and
M cone
max of 350, 505 nm and an L cone
max varying from 510 to 650 nm. These hypothetical L cone
spectral sensitivity functions were generated in the same way as the standard
honey possum cone sensitivities, using the rhodopsin visual pigment template
of Govardovskii et al. (2000
),
adjusted for self-screening and the spectral transmission of the lens. All of
the above was repeated separately for measurements made in five lighting
conditions: sun, cloud, early dusk (60 min to 15 min pre-sunset), sunset and
post-sunset.
Discriminating flower species
Each measured species of flower was classified as a target species or
non-target species according to the known diet of honey possums
(Turner, 1984; Wooller et al.,
1984
,
1983
). Unlike the case above,
in which we could be sure that we measured the complete range of Banksia
attenuata flower maturities, we could not measure the complete range of
target and non-target flowers species that honey possums may come across,
because some species were not in flower during the limited time of our study.
In addition, the discrimination between a target and its chromatically nearest
non-target may not be the most difficult discrimination, because sometimes two
flowers had very similar colours but were very different sizes and grew on
very different plants. Therefore, we considered that it was not appropriate to
base this analysis purely on the chromatically nearest non-target to every
target, and instead we calculated for each target the median chromatic
distance to all the non-targets. All other aspects of the analysis were the
same as for discerning flower maturity above. We did not have measurements for
the brief periods of sunset and post-sunset, nor enough measurements of
non-target species in cloud for a meaningful analysis. We did, however, have
many measurements in shade for species other than Banksia attenuata
(which being a tree among mostly shrubs is rarely in shade, see
Fig. 1).
Detecting flowers in their natural environment
For each set of measurements of target species we also took measurements of
the natural background, which was either foliage of the same species or the
vegetation of surrounding plants. The ease of detecting a target depends not
only on the difference between target and background but also on the
homogeneity of the background (e.g.
Desimone and Duncan, 1995). To
capture this, Regan et al.
(1998
,
2001
) and Sumner and Mollon
(2000a
) assessed the
visibility of fruit in foliage using signal-to-noise ratios where the `noise'
in this case was the chromatic spread of the background foliage. Here we
combine this approach with that of calculating chromatic distances using the
model of Vorobyev and Osorio
(1998
) explained above (Regan
et al. and Sumner and Mollon did not use this model, relying instead on
knowledge of the post receptor chromatic channels in primates and calculating
chromaticities analogously to MacLeod and
Boynton, 1979
). For each target the median chromatic distance to
the background measurements was divided by a measure of the chromatic spread
in the background, which was the standard deviation of the distances from that
target to each background measurement. We also included a term for receptor
noise that maintained a minimum level of overall noise in the signal-to-noise
ratio (and as mentioned above we tested the effect of varying the estimates
that contribute to this noise, and found that the conclusions presented below
were not affected). Thus signal-to-noise ratios, where the noise was a
combination of receptor noise and chromatic noise in the immediate visual
environment, were calculated for each target within a species and lighting
condition, and the mean over the targets was taken. Each target species
measured was analysed separately and our measurements also allowed analysis
for five lighting conditions (sun, shade, cloud, dusk, dawn). As above, first
we simply compared trichromacy to dichromacy, and then we varied the L cone
tuning.
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Results |
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L cone tuning
Fig. 2 shows the effect of
altering the L cone tuning in a trichromat. Plotted separately are the results
for detecting flowers amongst general bush background and for detecting each
species against its immediate foliage surroundings (analyses were performed
separately for each species for each lighting condition for which we had
measurements, and we averaged conditions within each species and then took the
average over species). It is clear that the L cone tuning of the honey possum
offers higher signal-to-noise ratios than the shorter wave L cone tunings of
other marsupials. However, longer wave tunings would be better still: the
optimal L cone would have a max of about 615 nm. This
pattern of results holds true for most individual species against local
foliage or subsets of bush background in different lighting conditions, not
just the overall results as plotted.
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Discriminating flower species
Presence of M cones
Chromatic distances for discriminating target flowers from non-target
flowers were calculated as explained in the Materials and methods for
trichromatic honey possums and for hypothetical dichromats lacking M cones.
For the measurements made in sun and shade, the mean chromatic distances for a
dichromat were 94% and 77% of those for a trichromat. However, at dusk (for
which we had very few measurements for non-targets) the mean chromatic
distance for a dichromat was 114% that for a trichromat. This surprising
result that chromatic distances were larger for a dichromat is possible
because distances are calculated relative to receptor noise, which becomes
smaller for a cone class when its density increases - in the modelling the M
cones were not simply deleted, they were replaced by L and S cones, reducing
the quantum noise and neural noise in these classes of cones. This reflects
the fact that having an extra dimension of colour vision is not without cost
to other aspects of vision, including any other dimension of colour vision.
The pattern of results was the same if the dichromat's L cone had
max anywhere in the range 530-557 nm. Thus there was no
clear and consistent disadvantage in being dichromatic for discriminating
between the target and non-target flower species in the honey possum's
environment. This unexpected result was produced because many of the
discriminations required lie in the yellow-white-lilac colour direction, which
is still available to a mammalian dichromat.
L cone tuning
Fig. 3 shows the effect of
changing the L cone tuning for a trichromat. Discriminability between target
and non-target flowers increases as the L cone sensitivity moves to longer
wavelengths, meaning that the tuning of the honey possum's L cone is not
optimal, but it is better than the tuning of other marsupial L cones. This
pattern of results held true whether we used just the mature flowers or all
measurements of each species, and also for subsets of the target species (e.g.
leaving out Banksia species, which are more easily discriminable by
their shape than other target flowers).
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Discerning flower maturity - Banksia attenuata
Presence of M cones
Chromatic distances between mature Banksia attenuata flowers and
the most similar immature or senescent flowers were calculated for
trichromatic honey possums and for hypothetical dichromats lacking M cones
(see Materials and methods). The means of these chromatic separations for a
dichromat, as a proportion of the trichromatic signal, were 0.31, 0.94, 0.34,
0.49 and 0.34 for the measurements made in conditions of sun, cloud,
early-dusk, sunset and post-sunset, respectively. Thus for the task of
discerning the maturity of this crucial food resource, a dichromatic honey
possum would be at a disadvantage compared to a trichromat (the pattern of
results was the same if the dichromat's L cone had max
anywhere in the range 530-557 nm).
L cone tuning
Fig. 4 shows the effect of
changing the L cone tuning for a trichromat engaged in the task of discerning
the maturity of Banksia attenuata flowers. Like the tasks tested
above, the tuning of honey possum L cones is better than the tuning of L cones
from other marsupials (except for the brief period just before sunset, when
the light is changing very rapidly and for which we have fewest measurements).
However, unlike the tasks tested above, there is no clear advantage to be
gained by incrementally shifting the honey possum's L cone sensitivity to
longer wavelengths, except in the early dusk and sunset conditions. For the
sun and cloud conditions the honey possum's spectral tuning even seems to be
locally optimal. Post-hoc analysis was used to investigate why these
results were so different from those for the previous tasks, despite the
overlap between spectral measurements and analysis. First, the pattern of
results was found not to be influenced by including or omitting from the
analysis the senescent flowers or the very immature flowers. Second, the
results were altered by omitting the immature flowers, or by
replacing them with Banksia attenuata leaves or other flower species.
Thus it is the comparison of mature and nearly mature Banksia
attenuata flowers that is crucial for the pattern of results obtained.
Fig. 5 plots three examples of
mature flower radiance spectra for comparison with chromatically near immature
spectra. It can be seen that the honey possum's L cone tuning is approximately
aligned with the local maxima of the immature spectra, at around 550-560 nm -
a spectral peak associated with reflectance or transmission by
chlorophyll-containing material. It can be seen that incrementally shifting
the L cone tuning to longer wavelengths would reduce the contrast between
immature and mature spectra, before increasing it again for much longer wave
pigments.
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|
Lastly the exact nature of the analysis plays a role. We followed the
method of Osorio et al.
(2004), which finds for each
target the smallest chromatic distance to any non-target (i.e. the hardest
discrimination). If the median chromatic distance to all non-targets
is used instead (which we consider less appropriate for this type of task),
this destroys the striking local optimum of tuning. This is because, as shown
in Fig. 6, each mature sample
often differs from its chromatically nearest immature sample in L:M cone
absorption ratio, and thus it is helpful to have the L cone positioned in the
spectrum where the relative radiance of the mature and immature samples is
reversed compared to the region of the spectrum where the M cone is more
sensitive. However, since both immature and mature samples are spread out in
their ratio of S cone absorption to L and M cone absorption (i.e. how flat the
spectra are; how desaturated the colour appears), then the median chromatic
distance between each mature sample and all immature samples will indicate to
a higher degree the differences in shortwave to longwave ratio. This contrast
will not be helped by positioning the L cone where the relative radiance of
the mature and immature samples is reversed. Instead it would be best to tune
the L cone to where the sum of the L and M absorption is maximally different
between samples. For the same reason, the above tasks of detecting flowers and
discriminating flower species did not produce clear local maxima of L cone
tuning around 560 nm because, even if the analysis used the nearest distractor
as used in this section, the chromatic displacement to the nearest distractor
was as often in the S cone direction as the L-M direction.
|
In sum, the results have shown that for the task of discriminating between mature and nearly mature Banksia attenuata flowers, the most important food resource in our study environment, shifting the L cone tuning to longer wavelengths would not generally be advantageous. This is because this task requires detection of changes in the L:M cone absorption ratio (yellow-green to yellow in human terms), rather than more general differences in the ratio of short to long wavelengths. It is worth noting that for a honey possum, the mature flowers produce a lower L:M ratio than the immature flowers, which is opposite to the relationship for human colour vision, emphasising the importance of not relying on human vision for judgments of what other animals see.
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Discussion |
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Our data provide possible answers to three questions. Why do honey possums
possess M cones as well as the S cones and L cones found in most other
mammals? Why are honey possum L cones tuned to longer wavelengths than other
marsupial L cones? Why are honey possum L cones not tuned to longer
wavelengths still? Before we consider these questions in turn, it is important
to note that an adaptationist approach can never definitively answer such
questions about evolutionary causes. There will always be other possible
pressures or constraints than the ones tested, or it may be that the trait in
question has not itself been selected at all, but is a `spandrel' (i.e. a
byproduct of selection for another trait;
Gould, 1997;
Gould and Lewontin, 1979
).
Furthermore, the properties of sensory systems may be a compromise between
many pressures, which may be one reason why the critical sensory tasks that
affect the fitness of an individual animal are difficult to identify, despite
sensory systems generally being considered to be subject to strong selection
pressure. It is also important to distinguish between pressures that may
operate on a trait now and the pressures that may have contributed to its
selection in the past, and even a clear demonstration of increased
reproductive fitness would identify only the former. However, an adaptationist
approach can rule out possible causes of selection if it shows that an
existing trait would offer no advantage over the possible alternatives. Thus
by identifying tasks for which honey possum vision appears adapted, and tasks
for which it is sub-optimal, we can identify or rule out candidate pressures
that may have shaped it.
Presence of M cones
It is not yet known whether the honey possum M cone pigment has been
evolved relatively recently or whether it is related to M cone pigments in
other vertebrates. If the latter is the case, it could be argued that the
existing cones in marsupials have simply been inherited from shared ancestors
with reptiles, and are no longer under any selective pressure. However, since
retinal space is limited, reducing the number of different types of cone in a
retina can produce performance benefits for tasks that rely on the remaining
receptor classes. Spatial vision will be improved either by increasing the
density of the receptors that contribute to the relevant pathway, or by making
all contributing receptors identical (see e.g.
Osorio et al., 1998;
Regan et al., 2001
).
Furthermore, certain colour discriminations can also be improved by reducing
trichromacy to dichromacy and thus increasing the number of cones in the
remaining classes. This was demonstrated in the results for discriminating
target flowers from non-targets (task 2). Additionally, in the absence of any
pressure to maintain a particular photopigment, genetic mutation would act in
the direction of making it non-operational. The presence of three cone types
in honey possums stands in contrast to the general trend of colour vision
reduction in placental mammals, where the ancestral M cones were lost from the
whole group, followed by many separate examples of S cone loss (e.g.
Ahnelt and Kolb, 2000
;
Collin et al., 2003
;
Jacobs and Deegan, 1992
;
Jacobs et al., 1993
,
1996
;
Peichl et al., 2001
;
Peichl and Pohl, 2000
;
Wikler and Rakic, 1990
;
Yokoyama, 2000
). Thus it is
likely that the compliment of cone pigments present in honey possums has been
maintained by some selective pressure. Our data show that this pressure is
unlikely to have come from the ability to discriminate between target and
non-target flower species (task 2), because, perhaps surprisingly, M cone loss
would not cause much disadvantage for this task. However, the other tasks we
tested do offer clear candidates for the selective pressure. If honey possums
became dichromatic like other mammals and tamar wallabies, they would be
disadvantaged in detecting many food-bearing flowers in their natural
environment (task 1), although interestingly they would remain able to detect
the most important food resource, Banksia attenuata. However, they
would be disadvantaged in discerning the maturity of this important resource
(task 3). Thus, although a dichromatic honey possum could detect Banksia
attenuata flowers, it would have difficulty visually ascertaining which
flowers were mature and food-bearing. The potential cost of this difficulty is
discussed below.
L cone tuning
Why are honey possum L cones tuned to longer wavelengths than other marsupial L cones?
Vertebrates have a diversity of visual pigments, ranging in
max from ca. 350 nm to ca. 630 nm, and the inter- and
intra-specific variation in visual pigment tuning has been subject to much
study. Many correlations have been noted between spectral tuning of visual
pigments and spectral irradiance of the light environment, particularly in the
case of fishes (Bowmaker et al.,
1994
; Cummings and Partridge,
2001
; Lythgoe et al.,
1994
). Other studies have focussed on critical visual tasks,
emphasising spectral radiance as the raw signal used by visual systems (e.g.
Osorio and Vorobyev, 1996
;
Partridge and Cummings, 1999
;
Regan et al., 1998
;
Sumner and Mollon, 2000a
), and
this is the approach we have taken. We have identified two tasks for which the
longer wave tuning of honey possum L cones is more advantageous than the
tuning of other marsupials: detecting flowers in their natural environment
(task 1), and discriminating between target and non-target flowers (task 2;
there was a smaller and less consistent difference between the honey possum
and other marsupial tunings for the third task of discerning the maturity of
Banksia attenuata). Thus these two tasks are therefore candidate
pressures for the longer wave tuning of honey possum L cones. The ancestral
max values of mammalian groups remain obscure, so it is
impossible to say whether the honey possum tuning or the shorter wave tuning
of other marsupials is closer to the ancestral position of marsupial L cones.
It is noteworthy though, that of the marsupial L cones so far measured, most
have
max values in the range 530-540 nm, including the two
other diprotodont species besides the honey possum (Arrese et al.,
2002b
,
2005
;
Deeb et al., 2003
;
Hemmi et al., 2000
;
Strachan et al., 2004
). In
addition, the L cones in most mammals are tuned to shorter wavelengths than in
honey possums, with
max values down to around 500 nm (e.g.
Ahnelt and Kolb, 2000
;
Jacobs, 1993
). It is unknown
whether the shorter wave tunings of other marsupials and other mammals are to
be explained by ecological pressures or by a tendency for relaxed selection to
produce drift to middle wave tuning. However, given that the known L cones of
other marsupials and most mammals are tuned to shorter wavelengths, it seems
likely that the honey possum L cone
max has been under
selective pressure either to move to, or stay at, longer wavelengths. Our data
supply two candidates for this pressure: detecting target flowers amongst
leaves or general bush, and discriminating between target and non-target
flowers.
Why are honey possum L cones not tuned to longer wavelengths still?
These two tasks, which can explain why longer wave tuning is found in honey
possums than in other marsupials and most other mammals, cannot explain why
honey possum L cones are not tuned to longer wavelengths still. The optimal
max for detecting flowers (task 1) is around 615 nm, and
the benefit for discriminating flowers (task 2) continues to rise for
max values up to 640 nm (c.f. the optimal tuning of primate
L and M cones for detecting fruit; Regan et al.,
1998
,
2001
;
Sumner and Mollon, 2000a
; and
for discerning fruit ripeness, Sumner and
Mollon, 2000b
). One reason that the L cone
max
value of honey possums has not moved from 557 nm might simply be that as long
as an animal's colour vision system is `good enough' visual pigment tuning
tends to be conservative. For example, most birds seems to have very similar
sets of visual pigments despite varied habitats and lifestyles (e.g.
Hart, 2001
). However, against
this argument lies the fact that the L cone tuning of all marsupials is not
the same, so it must have changed in some species since their common ancestor,
and among mammals, L cone
max values vary from around 500
to 565 nm (e.g. Jacobs,
1993
).
There are three basic ways in which the L cone max value
in honey possums could be shifted to longer wavelengths. First, exchanging
rhodopsin for porphyropsin, in which the same opsin protein binds a different
light absorbing molecule, causes a longwave shift (e.g.
Knowles and Dartnall, 1977
).
However, although many fish and some reptiles employ porphyropsins, they are
unknown in mammals. Moreover, even if this type of pigment was available to
marsupials, porphyropsins are known to have higher dark noise than rhodopsins
(Ala-Laurila et al., 2003
;
Donner et al., 1990
), which
might entail considerable cost for animals that forage in dim conditions as
well as daylight. The second method for producing a long-wave shift would be
to employ long-pass filters, such as the red oil droplets found in birds (e.g.
Hart, 2001
). Oil droplets are
in fact present in honey possum retinae, but they are all transparent
(Arrese et al., 2002a
),
presumably because filters must cut out some light, which would entail a cost
at low light levels. Thus the fact that honey possums are active in dim light
as well as daylight would act as a selective pressure against achieving longer
wavelength sensitivity by employing porphyropsins or by using coloured oil
droplets. Alternatively, it may be that the genetic steps needed to achieve
porphyropsins or to recolour the oil droplets are highly improbable and simply
never have occurred since honey possums diverged from other marsupial groups
(who also have transparent oil droplets). The third method of achieving a
long-wave shift in tuning would be to alter the amino acid sequence of the L
cone opsin, and here it is possible that there are molecular constraints.
However, while rhodopsins with
max values near 600 nm are
unknown, they do exist at longer wavelengths than the honey possum's 557 nm:
e.g. 565 nm in primates; 575 nm in guppies (a freshwater teleost); 565-575 nm
in many birds (e.g. Archer et al.,
1987
; Hart, 2001
;
Jacobs, 1993
). Therefore
max values for unfiltered rhodopsins may be ruled out
beyond 575 nm by unknown molecular constraints, but this would not explain why
honey possum L cones are limited to a
max value of 557 nm.
We may speculate that honey possum L cone opsins could not achieve the
long-wave shift to 565 or 575 nm because of some unknown molecular
incompatibility that is not present in primates, guppies or birds.
However, in the absence of specific evidence for molecular limits, we turn
to potential ecological pressures that might act against a long-wave shift of
the honey possum L cone tuning. Such a selective pressure is suggested by our
results for discerning the maturity of Banksia attenuata flowers: a
task for which the honey possum L cone tuning may even be close to (locally)
optimal. Is it feasible that such a specific task could override conflicting
pressures from more general tasks? In fact, because the task essentially seems
to be one of detecting the removal of chlorophyll from the flowers, it is
probably applicable much more widely than to Banksia attenuata. Any
flower whose crucial change in maturity (i.e. the availability of nectar and
pollen) is correlated with removal of chlorophyll and a change in colour, in
humans terms, from yellow-green to yellow, is likely to produce similar
results. Such flowers include, for example, several other Banksia
species not present at our field sites, but known to be important to honey
possums (Turner, 1984; Wooller
et al., 1984
,
1983
). In the habitats in
which we worked, Banksia attenuata itself is certainly the most
important source of food, being both a common plant and the one with largest
inflorescences. In addition, this visual task is likely to be the most
difficult that is required for a honey possum, since mature and nearly mature
inflorescences cannot be distinguished by shape, size or position.
Furthermore, unlike most other plant species that we measured, the presence of
immature flowers does not signal the presence of mature flowers (the example
in Fig. 1 was chosen because it
contains mature, immature and senescent inflorescences in close proximity, but
this was rarely the case). Given that Banksia attenuata are large
plants with widely separated and exposed inflorescences, confusing
inflorescences that offer food with those that do not entails a clear cost for
a small terrestrial animal in terms of time, the energetic cost of climbing
and exposure to predators. It is difficult to quantify the latter, because
predation events are rarely observed and in any case avian predator
populations may have changed in recent history. We can simply estimate the
time cost, however, which is likely to be more important than the energetic
cost of climbing for a small warm-blooded mammal that requires a lot of energy
simply to stay alive. Immature inflorescences outnumbered mature ones in our
study environments by at least 5 to 1, and the large, mature-sized, but still
immature inflorescences were about twice as common as mature food-bearing
inflorescences. If a honey possum makes a mistake of visiting just one
immature inflorescence for every mature one, foraging efficiency may be
reduced by half. A good sense of smell will go some way to reducing this cost,
but smell does not have the same ability to localise targets from a distance
as vision, even for an animal with relatively poor spatial acuity. It is
difficult to know how important Banksia attenuata may have been to
honey possums in the past, especially since the ranges of both plant and
animal are likely to have decreased in recent history. However, since there
are several other species of Banksia with similar inflorescences and
with similar properties to those described above, it is not unfeasible that
discerning the maturity of Banksia flowers is the most important
single selective pressure maintaining in honey possums both the existence of M
cones and the exact tuning of the L cones.
Conclusions
Our strongest finding is that the L cone tuning of honey possums is better
adapted than the L cones of other marsupials for the tasks of detecting
food-bearing flowers in their natural environment, and discriminating target
flowers from distractor flowers. However, since further advantage in these two
tasks would be gained by even longer wave tuning, there must be a different
factor limiting long-wave tuning shifts. This factor may be molecular, since
it is rare for unfiltered rhodopsins to have longer wave
max values than 560 nm. Alternatively, an ecological
pressure is suggested by our results for the task of discerning the maturity
of Banksia flowers. Finally, it is of note that while the presence of
M cones is generally advantageous for these tasks, there are specific examples
where it is not, emphasising the difficulty in predicting the properties of
animals' visual systems from a human visual perspective, without appropriate
modelling.
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Acknowledgments |
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