1. , 20130563, published 7 July 20143692014Phil. Trans. R. Soc. B
Beverley J. Glover
Allan G. Ellis, Samuel F. Brockington, Marinus L. de Jager, Gregory Mellers, Rachel H. Walker and
Gorteria diffusadeception in
Floral trait variation and integration as a function of sexual
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Research
Cite this article: Ellis AG, Brockington SF, de
Jager ML, Mellers G, Walker RH, Glover BJ.
2014 Floral trait variation and integration
as a function of sexual deception in Gorteria
diffusa. Phil. Trans. R. Soc. B 369: 20130563.
http://dx.doi.org/10.1098/rstb.2013.0563
One contribution of 14 to a Theme Issue
‘Phenotypic integration and modularity in
plants and animals’.
Subject Areas:
taxonomy and systematics, evolution,
ecology, developmental biology
Keywords:
Gorteria, integration, insect mimicry
Authors for correspondence:
Allan G. Ellis
e-mail: agellis@sun.ac.za
Beverley J. Glover
e-mail: bjg26@cam.ac.uk
†
These authors contributed equally to this
study.
Electronic supplementary material is available
at http://dx.doi.org/10.1098/rstb.2013.0563 or
via http://rstb.royalsocietypublishing.org.
Floral trait variation and integration
as a function of sexual deception in
Gorteria diffusa
Allan G. Ellis1,†, Samuel F. Brockington2,†, Marinus L. de Jager1,†,
Gregory Mellers2, Rachel H. Walker2 and Beverley J. Glover2
1
Botany and Zoology Department, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa
2
Department of Plant Sciences, University of Cambridge, Downing St., Cambridge CB2 3EA, UK
Phenotypic integration, the coordinated covariance of suites of morphologi-
cal traits, is critical for proper functioning of organisms. Angiosperm flowers
are complex structures comprising suites of traits that function together
to achieve effective pollen transfer. Floral integration could reflect shared
genetic and developmental control of these traits, or could arise through
pollinator-imposed stabilizing correlational selection on traits. We sought to
expose mechanisms underlying floral trait integration in the sexually decep-
tive daisy, Gorteria diffusa, by testing the hypothesis that stabilizing selection
imposed by male pollinators on floral traits involved in mimicry has resulted
in tighter integration. To do this, we quantified patterns of floral trait variance
and covariance in morphologically divergent G. diffusa floral forms represent-
ing a continuum in the levels of sexual deception. We show that integration
of traits functioning in visual attraction of male pollinators increases with
pollinator deception, and is stronger than integration of non-mimicry trait
modules. Consistent patterns of within-population trait variance and covari-
ance across floral forms suggest that integration has not been built by
stabilizing correlational selection on genetically independent traits. Instead
pollinator specialization has selected for tightened integration within modules
of linked traits. Despite potentially strong constraint on morphological
evolution imposed by developmental genetic linkages between traits, we
demonstrate substantial divergence in traits across G. diffusa floral forms and
show that divergence has often occurred without altering within-population
patterns of trait correlations.
1. Introduction
Phenotypic integration refers to the coordinated variation of morphological traits
within functional modules, and is essential to the function of complex phenotypes
[1,2]. Such integration of trait modules may result from shared genetic control in
the form of pleiotropy, close genetic linkage and ontogenetic interaction [3,4].
Alternatively, trait covariation may reflect linkage disequilibrium built up by cor-
relational selection on genetically independent traits [5–7]. While long-term
selection for optimal functionality has likely promoted genetic and developmen-
tal integration [4], the extent to which these mechanisms constrain or promote
further morphological evolution by natural selection is an important question
in evolutionary biology [3,8].
Flowering plants comprise a developmental hierarchy of connected but dis-
crete functional modules [9]. The reproductive structure of flowering plants, the
flower, constitutes one such module composed of distinct units that function in
the dispersal and receipt of pollen. In animal-pollinated plant species, strong
pollinator-mediated selection pressure could favour the integration of floral
traits to better fit the animal pollinator’s morphology and behaviour [6,10].
For example, the higher levels of covariation between corolla and filament
length observed in Raphanus raphanistrum are likely due to selection imposed
by pollinator behaviour [10]. The most common pollinators on this species
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3. cannot enter the corolla tube, and so land on the petals and
insert a proboscis. The position of the anthers relative to the
corolla tube length must therefore be closely correlated: fila-
ments too short and the anthers will not contact the
pollinators, too long and pollen deposition might be inaccur-
ate. However, in addition to this phenotypic covariation,
flower modules are also subjected to genetic constraint, func-
tional restraints and developmental linkage. Consequently,
flowers, and flowering plants, have emerged as important sys-
tems in understanding the interplay of forces underlying
phenotypic integration.
Berg [11], in her classic comparisons of trait correlations
between plants with specialized and generalized pollination
systems, laid the groundwork for exploration of patterns of
floral trait integration in the context of plant pollination and
breeding systems. Berg’s work suggested that the floral traits
of plants with specific pollinators exhibit ‘correlation pleiades’
[11] or modules of integrated traits, whereas the floral traits
of wind- or self-pollinated plants are less strongly correlated.
Pollinator specificity was deemed to produce this pattern
through floral adaptation for more efficient pollen transfer
[11]. Further support for this idea has come from studies that
found floral trait integration in pollinator-dependent outcross-
ing species relative to selfing species, which are less reliant
on pollinators [12–14] and in pollinator-specialized versus
generalized species [12,15,16].
However, several studies have also demonstrated equal or
greater levels of floral integration in self-compatible versus
self-incompatible species [12–14]. Pollinator-mediated selec-
tion may therefore weaken existing developmental genetic
integration by relaxed selection or opposing selection on cor-
related traits [13,14]. Additional mechanisms must also
maintain accurate pollen transfer within self-compatible
species, contributing to floral integration independent of pol-
linator-mediated selection [12–14]. These mechanisms will
include genetic linkage and pleiotropy, which can also con-
strain response to selection for trait covariance [17–19].
More random processes, such as genetic drift, may affect pat-
terns of trait integration among populations [20], whereas
environmental variation may alter patterns of covariance
within vegetative versus reproductive units [21]. So patterns
of floral trait integration are clearly complex [22] and influ-
enced by diverse and contrasting processes, both extrinsic
and intrinsic to the plant [23].
Although these influences have been examined in a broad
range of species and experimental systems, few, if any,
studies have specifically studied the role of pollinator-
mediated selection on the integration of traits involved in
pollinator attraction. Indeed, integration of traits involved
in pollinator attraction has been suggested to be less likely
[12], compared with the integration of floral traits involved
in promoting accurate transfer of pollen to stigmas. In part,
this is because attractive traits may not engender legitimate
pollen transfer, and in part, because the same traits can also
attract floral antagonists [24], leading to opposing selection for
trait covariance. However, an exception to this idea might be
species whose pollination is achieved through mimicry and
sexual deception. Suites of mimicry traits are so specialized
that male pollinators attempt to copulate with the female-
mimicking floral structure within the vicinity of pollen bear-
ing organs. Such precise mimetic structures may be less likely
to indiscriminately attract floral antagonists, and more likely
to be intimately associated with legitimate pollen transfer.
Stabilizing selection could therefore act on two aspects of
these complex structures: (i) the mimetic structures that attract
male insects and elicit the copulation response and (ii) the rela-
tive position of pollen-bearing structures for accurate pollen
deposition on and pick-up from copulating males. Pollination
by sexual deception is most prevalent in the Orchidaceae,
and commonly in these sexually deceptive orchids, pollinator
attraction has a significant olfactory component, including
pheromone mimicry [25,26]. However, more recently a parallel
system of sexual deception has emerged outside of the Orchi-
daceae, in Gorteria diffusa Thunb. (Asteraceae). Here, the
primary component of attraction appears to be a mimetic
suite of visual traits [27].
Gorteria diffusa is a self-incompatible annual from South
Africa comprising at least 14 closely related, but morphologi-
cally discrete, allopatric floral forms [28,29]. The system is
characterized by variation in floral colour and the complexity
and distribution of the black anthocyanin spots at the base of
the ray florets (figure 1). These spots, which are complex phe-
notypic structures, play an important role in the attraction of
the bee fly, Megapalpus capensis Wiedeman [30]. M. capensis is
the main pollinator of all forms of G. diffusa [28]. Although
both male and female flies visit and pollinate G. diffusa,
males tend to prefer more complex spots [27] and often attempt
to copulate with the spots of the most complex forms, result-
ing in increased pollen export [31]. The fly-mimicking spots
typically contain specialized, three-dimensional papillate
structures and UV reflective highlights that are important in
deception, as they attract male, but not female flies [27]. Not
all floral forms are engaged in sexual deception, however,
and some forms interact with other aspects of M. capensis
behaviour, such as sleeping and feeding activities (AG Ellis
2012, unpublished data). These features of the G. diffusa
system result in a continuum of floral morphological variation
set against a continuum in the extent of deceptive exploitation
of pollinator mating behaviours. Using these juxtaposed gradi-
ents, we sought to evaluate floral integration and patterns of
trait covariation in relation to sexual deception in G. diffusa.
We first explored the patterns of divergence of floral traits
between G. diffusa floral forms. We were particularly interested
in whether components of the insect mimicking ray floret
spots exhibit most divergence between floral forms (in relation
to other trait modules) as might be expected if selection has
favoured increasing levels of deception, or alternatively, evol-
utionary transitions between non-deceptive and deceptive
forms. We hypothesized that mating male flies impose stabiliz-
ing correlational selection on trait dimensions, which provide
optimal mimicry. The floral mimicry of females would require
the accurate relative positioning of multiple different spot traits
to achieve a convincing pseudo female fly. We tested four pre-
dictions from this hypothesis: (i) that variance of the traits
involved in insect mimicry should be lower than variance of
non-mimicry traits in sexually deceptive floral forms; (ii) that
traits associated with insect mimicry should be more strongly
integrated than other traits; (iii) that increasing levels of deceit
should be associated with tighter integration of fly-mimicking
traits and (iv) that the most sexually deceptive forms should
exhibit distinctive patterns of covariance between mimicry
trait pairs in relation to non-deceptive forms. Finally, we
explored possible genetic and developmental constraints on
morphological divergence between floral forms, by comparing
patterns of trait covariation across G. diffusa floral forms in
relation to patterns within floral forms.
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4. 2. Methods
(a) Taxon sampling
We sampled inflorescences from each of 10 floral forms of
G. diffusa: Spring, Buffels, Nieuw, Koma, Okiep, Oubees, Soeb,
Cal, Garies and Naries (figure 1). This selection spanned the
range of sexual deception present in the G. diffusa system, from
sexually deceptive forms eliciting strong copulation responses
(e.g. Spring or Buffels, figure 1a,b), to floral forms eliciting high
levels of mate-searching behaviours but no copulation (e.g. Cal,
figure 1e), to forms that only induce feeding behaviours
(e.g. Soeb, figure 1h). GPS coordinates for populations of each
floral form were as follows: Buffels (S29.987, E17.659), Cal
(S30.42, E17.936), Garies (S30.656, E18.054), Koma S29.915,
E17.462), Naries (S29.701, E17.689), Nieuw (S31.372, E18.63),
Okiep (S29.571, E17.868), Oubees (S29.917, E17.467), Soeb
(S30.072, E17.587) and Spring (S29.694, E17.884).
(b) Measurement of floral traits
A single inflorescence was collected from each of forty individuals
in each population. Each inflorescence was dissected to obtain:
(i) a bird’s eye view of an entire spotted ray floret (figure 2(i));
(ii) a lateral image of the angle of spotted ray floret insertion
(figure 2(ii)); (iii) a lateral view of a disc floret exhibiting the
maximum visible pollen presenter exertion (figure 2(vi)) and
(iv) an image exposing the length and width of the disc petal
ends (figure 2(v)). All inflorescence units were photographed at
high resolution against a scale rule using a Nikon D90 SLR
camera with a AF-S Nikkor 85 mm macrolens. Photos were
analysed in IMAGEJ 1.46r (Rasband W. http://imagej.nih.gov/ij),
and trait dimensions measured to the nearest 0.1 mm (or degree
in the case of angles) by the same person. A total of 19 traits
were measured for each inflorescence (see figure 2 for details).
Two traits were angle measurements which were square-root-
transformed prior to integration analyses. In addition, we
measured head, thorax, abdomen and wing dimensions on 23
M. capensis individuals.
Spot traits (10 traits; e–n, figure 2(i)(iii)(iv)), which are involved
in visual mimicry of female flies [27], were treated as a separate
trait module in analyses. Unlike the mimicry traits (spot traits)
which are exclusively on ray florets, traits which are not directly
involved in fly mimicry were measured across ray and disc florets.
Because these divergent floret types likely experience differ-
ing genetic/developmental influences, non-mimicry traits were
assigned to either a disc floret (five traits; o–s, figure 2(v)(vi))
module or a non-spot ray floret (four traits; a–d, figure 2(i)(ii))
module. These three trait modules were treated separately in
analyses. In some cases, traits could not be measured accurately
from photos (e.g. owing to herbivore or dissection damage) in
which case individuals were discarded from the dataset, result-
ing in sample sizes for trait modules ranging from 27 to 40
(mean ¼ 37) individuals across floral forms. As far as possible,
we sampled inflorescences at the same developmental stage (i.e.
pollen presenters fully exerted in the outer whorl of disc florets)
in order to reduce trait variance associated with ontogenetic vari-
ation. In both figures 1 and 2, the white circles are the UV
highlights. The black shaded areas in figure 2 are the areas of
three-dimensional papillate structure, which are present in the
darkly pigmented areas of some of the floral forms in figure 1.
(c) Quantifying the degree of sexual deception
While all G. diffusa floral forms are visited, and effectively polli-
nated, by the bombyliid fly M. capensis, they differ in the
behavioural responses they elicit from the fly. All floral forms
are visited by female and male flies feeding on nectar and
pollen rewards, and differ primarily in the extent to which they
elicit mating behaviours from male flies [31]. As we were primar-
ily interested in the potential influence of sexual mimicry on
floral trait integration, we quantified the degree of deception of
floral forms as the proportion of visits by male flies involving
mate-searching behaviour (copulation behaviour or inspection
visits). Data were extracted from Ellis & Johnson [31], who pre-
sented arrays of G. diffusa inflorescences to male flies in cages
and quantified their behavioural responses to different floral
forms. Data were available for eight of the 10 floral forms used
in this study and are presented in figure 3 (no data for the
Oubees and Koma floral forms).
(d) Assessing trait divergence between floral forms
In order to determine whether traits differ between floral forms,
we conducted a MANOVA with all traits as dependent variables
followed by ANOVAs for each trait. In addition, discriminant
function analysis (DFA) was used to determine how well the
measured traits discriminate between floral forms and which
(a)
(c)
(e) ( f )
(g) (h)(h)
(i) (j)
(b)
(d)
Figure 1. Ten floral forms within the G. diffusa species complex showing the
full frontal image of the flower, and for each floral form, a close-up of
the spotted floret. Floral forms with three-dimensional structures (a–g),
floral forms without three-dimensional structures (h–j). Individual floral
forms are as follows: (a) Buffels; (b) Spring; (c) Nieuw; (d) Koma; (e) Cal;
( f ) Okiep; (g) Garies; (h) Soeb; (i) Naries and ( j) Oubees. Further descrip-
tions of floral forms can be found in Ellis & Johnson [28].
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5. traits provide most discriminatory power. Two DFAs were con-
ducted, one on a dataset including three-dimensional structure
traits (a subset of floral forms) and the second on a dataset
excluding all three-dimensional structure traits (all floral
forms). Standardized factor coefficients were used to determine
which traits contribute most to discrimination between floral
forms on the first three axes recovered from the DFAs.
(e) Assessing trait variation and covariation within
floral forms
To explore patterns of trait variation in the different floral forms,
we firstly calculated coefficients of variation (CV) for all measured
traits, which are comparable between traits with different ranges of
values. We used a two-factor ANOVA to test for differences in trait
(i)
a
b
c
e
f
g
(vi)
o
p
q
(v)
r
s
(iii)
h
i
j
d
(ii)
k
l
m n
(iv)
Figure 2. Schematic of measured floral traits. (i) Dorsal view of the spotted floret, (ii) side view of a spotted floret, (iii) inset of the floret spot depicting measure-
ments of UV highlights (white circles), (iv) inset of the floret spot with measurements of the three-dimensional structures (black areas), (v) disc floret dissected to
reveal petal lobes, (vi) side view of intact disc floret. Measurements were as follows. In the non-spot ray floret trait compartment: a, length of spotted floret;
b, width of the spotted floret at 75% of its length; c, angle of the floret tip, d, angle of spotted floret presentation. In the spot trait compartment: e, width
of the spot, f, length of spot on midline g, length of spot on floret edge; h, distance to the bottom of the UV highlight; i, length of the UV highlight; j,
width of the UV highlight; k, distance to left-hand edge of the three-dimensional structure; l, distance to three-dimensional structure along central axis; m,
width of the three-dimensional structure; n, height of the three-dimensional structure. In the disc floret traits compartment: o, length of the disc floret corolla
tube; p, width of the disc floret corolla tube; q, length of the pollen presenter; r, length of the free disc floret petal end; s, width of the disc floret petal end.
GariesSpringBuffels Nieuw Koma Cal Okiep
80.0% 24.4%
Soeb Oubees Naries
12% 0%78.6% 62.2% 33.3%69.3% no data no data
Figure 3. Idealized spot arrangements of the different floral forms. Dark grey ovals are the spots, white circles are the highlights, black shapes are the three-dimensional
structures, striated black indicates three-dimensional areas without papillate cells, light grey bands are reflective strips. Idealized spot types are lined up on the ‘deception
axis’, i.e. floral forms to the left are more sexually deceptive than floral forms on the right. Deception was determined by percentage of mating/inspection visits by
Megapalpus capensis. Buffels n ¼ 75; Spring n ¼ 308; Nieuw n ¼ 202; Cal n ¼ 111; Okiep n ¼ 63; Garies n ¼ 45; Soeb n ¼ 17 and Naries n ¼ 9.
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6. CVs across trait modules and between floral forms, treating
measurements from individual traits as replicates. In addition,
CVs of individual traits were compared using ANOVA, treating
measurements from each floral form as independent replicates.
Finally, correlations of CVs of all traits with degree of deception
were assessed.
We calculated eigenvalues from principal component analyses
of measured floral traits in each of the trait modules (spot traits, non-
spot ray floret traits and disc floret traits) for all floral forms separ-
ately. We then calculated trait integration as the variance of the
eigenvalues of the trait correlation matrices [INT ¼ V (l)] [32] in
each trait module for all floral forms. To control for differences
in sample size between the floral forms investigated and bet-
ween trait modules, we subtracted the expected eigenvalue
variance under the hypothesis of random covariation of traits
[Exp(INT) ¼ (number traits 2 1)/N] from INT for each form to
obtain the corrected INT values [32,33]. These were expressed as
% of maximum INT. We used bootstrapping with 1000 repetitions
to estimate the 95% confidence intervals (CIs) for corrected INT.
Values were considered to represent significant integration if
their 95% CIs did not include zero and significance of differences
in integration between floral forms and trait compartments was
assessed by examining overlap in CIs [20].
Patterns of covariation between traits were further explored by
examining within-floral-form pairwise Pearson correlation coeffi-
cients and their significance. In addition, we examined pairwise
trait correlations across floral forms using trait means for each
floral form. These were compared with mean within-floral-form
correlations in order to identify trait combinations where diver-
gence has occurred counter to genetic/developmental constraints
(the within-floral-form covariation patterns). In these instances,
we used analysis of covariance (ANCOVA) to test whether slopes
of within-floral-form trait correlations vary between floral forms.
(f) Assessing the influence of pollinator specialization
and deception on trait integration
The influence of the degree of deception (proportion of mating/
inspection behaviours elicited from Megapalpus males) on trait
integration was investigated using ANCOVA with trait module
as the categorical predictor and degree of deception as the continu-
ous predictor. We were particularly interested in determining
whether the influence of deception on trait integration varied
between trait compartments (i.e. the interaction term in ANCO-
VAs). The influence of degree of deception on integration of
traits in each of the three trait compartments was further explored
using simple regression. All statistical analyses were conducted in
R or STATISTICA.
3. Results
(a) Trait divergence between floral forms
Measured traits differed significantly between G. diffusa
floral forms (MANOVA: all traits—F108,1211 ¼ 76.7, p , 0.001;
all traits excluding three-dimensional spot structures—
F135,2560 ¼ 51.79, p , 0.001). DFA correctly classified 100%
and 98.3% of individuals into floral forms based on the
measured traits with and without three-dimensional structure
traits, respectively. While univariate ANOVAs of all traits (elec-
tronic supplementary material, table S1) and MANOVAs
of each trait compartment suggest that all measured traits
differ significantly between at least some floral forms, standar-
dized factor coefficients from the DFAs suggest that spot
traits, and to a lesser extent non-spot ray traits, contribute
most to the discrimination between floral forms. Distance to
UV highlight, distance to three-dimensional structures and
three-dimensional width (and to a lesser extent floret length
and width and spot length and width) provide most dis-
criminatory power on the first three axes of the DFAs of all
traits including three-dimensional structures which account
for 79.9% of between-group variance (figure 4a). Floret dimen-
sions, spot dimensions, distance to UV highlight and ray floret
presentation angle had highest coefficients on the first three
discriminant functions (76.8% of between-group variance)
from the dataset excluding three-dimensional structures
(figure 4b).
(b) Variance of traits within floral forms
Contrary to our expectations, in a combined analysis across
traits, trait CVs did not differ between floral forms, but differed
significantly between trait compartments (trait compartment—
F2,165 ¼ 6.05, p , 0.01; floral form—F9,165 ¼ 0.87, p ¼ 0.56).
Furthermore, non-spot ray traits had significantly lower CVs
on average than spot or disc traits. Moreover, analysis of CV
differences between traits across floral forms (F18,158 ¼ 27.4,
p , 0.001) showed that CVs of some visually attractive traits
(UV length, UV width) were significantly higher than for
other traits (table 1). Interestingly, while the position of the
UV highlight on the spot has low CV, UV length and UV
width (both position-independent measurements) have signifi-
cantly higher variance. This indicates that the dimensions of
this visually attractive trait are unlikely to be under strong
selection in sexually deceptive floral forms. In fact, the CV
values of all measured traits were not significantly correlated
with degree of deception (all correlations not significant).
Trait CVs of measured fly traits fell within the range of CVs
of G. diffusa spot traits (fly traits—12.4–29.3%, mean ¼
19.3%; spot traits—8.7–60%, mean ¼ 16.5%).
(c) Trait covariation within floral forms
Traits in all modules were significantly integrated with the
exception of disc floret traits in the Soeb floral form (table 2).
Apart from differences in disc floret integration between the
Soeb and Oubees floral forms, integration of disc floret and
non-spot ray traits did not differ significantly between floral
forms. In contrast, integration of spot traits varied significantly
across some floral forms (table 2). In all floral forms, mimetic
spot traits were more tightly integrated than non-mimicry
traits (disc floret and non-spot ray floret traits), but in the
case of Soeb, Naries and Oubees, the trend towards tighter inte-
gration in spot traits was not significant. These patterns were
supported by consistently high (0.61–0.93) and significant
pairwise Pearson correlation coefficients between some spot
traits (spot length, UV highlight position, three-dimensional
structure position; table 3). In addition, these spot traits were
strongly correlated with ray floret length, whereas other trait
pairs exhibited weaker correlations.
(d) Trait covariation across floral forms
While the pairwise structure of trait correlations across floral
forms largely matched mean within-floral-form correlations
(table 3), there were important exceptions. The most notable
mismatches in trait covariance patterns within and between
floral forms involve correlations between the length of ray
florets and the size of the spots and their component parts
(table 3 and figure 5a). ANCOVA revealed that the slope of
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7. the relationship between floret and spot length does vary
across floral forms (interaction term: F9,357 ¼ 4.5, p , 0.001),
suggesting the potential for selection to have altered the pat-
terns of covariation between spot and ray floret dimensions.
In contrast, correlations between trait pairs determining the
relative positioning of spot components (three-dimensional
position, UV position) were consistent within and between
floral forms. The obvious exception was spot width and
three-dimensional structure width (figure 5b), which covaried
significantly within floral forms, but not across floral forms.
ANCOVA suggests that there is a consistent positive relation-
ship between these traits (continuous predictor: F1,243 ¼ 98.5,
p , 0.001) and slopes of the relationship do not vary between
floral forms (interaction term: F6,243 ¼ 0.87, p . 0.05). Thus,
divergence in the relative dimensions of these traits across
forms has occurred without changes in the within-floral-forms
relationship (i.e. the probable axis of genetic/developmental
constraint). Closer examination of other trait pairs which exhi-
bit clear divergence in mean values across floral forms, but
have consistent correlation patterns within and between
floral forms suggests that this pattern of divergence in relative
trait dimensions across floral form, with no alteration of the
within-floral-form trait covariation, is common. Examples
shown in figure 5 include divergence between forms in the
ratio of spot edge to middle spot length despite similar corre-
lation of these traits within all floral forms (figure 5c;
ANCOVA interaction term F9,356 ¼ 1.21, p . 0.05), and diver-
gence between the Spring and Okiep forms and the rest in
relative positioning of UV and three-dimensional structures
(both important for attraction of male flies) [27] on the spot
despite similar within-floral-form correlation (figure 5d;
ANCOVA interaction term F6,243 ¼ 0.72, p . 0.05). In both
these examples, major phenotypic shifts (UV highlights
inside and outside of three-dimensional structures, curved
versus flat spot edges) have occurred in opposition to
the axis of least genetic/developmental constraint (i.e. the
within-floral-form correlation), whereas additional divergence
has occurred along the constraint axis.
–15 10
–10
10
DF1 (39.9%)
DF2(24.2%)
Spring
Nieuw
Koma
Cal
Garies
Okiep
Buffels
Spring
Nieuw
Koma
Naries
Cal
Oubees
Soeb
Garies
Buffels
Okiep
–10 10
–15
5
DF1 (44.8%)
DF2(20.4%)
(distance to three-dimensional top, three-dimensional width,
distance to UV, floret width)
(distancetothree-dimensionaltop,distancetoUV,
spotwidth,floretlength)
(spot width, distance to UV, floret length, floret width)
(edgespotlength,distancetoUV,
adaxialfloretangle,floretwidth)
(a)
(b)
Figure 4. Separation of G. diffusa floral forms on the first two axes of the discriminant function analyses of all measured traits, (a) with and (b) without three-
dimensional spot traits. For both datasets, spot traits, and to a lesser extent non-spot ray traits, contribute most to the variance between floral forms explained by
the discriminant functions. The most important traits are listed on the axes in descending order of standardized factor coefficients.
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8. (e) Effects of sexual deception on trait integration
ANCOVA analysis showed that trait integration differs sig-
nificantly between trait modules (F2,18 ¼ 10.27, p ¼ 0.001)
and overall integration increases with degree of deception
(proportion of mating/inspection behaviours elicited from
M. capensis males; F1,18 ¼ 24.41, p , 0.001). Importantly, the
influence of deception on integration differs between trait
modules (homogeneity of slopes tests interaction term—
F2,18 ¼ 9.57, p ¼ 0.001). Simple regressions suggest that
integration of spots and disc florets are significantly influ-
enced by degree of deception, with spot integration being
most strongly influenced (figure 6).
4. Discussion
Our data support the hypothesis that increasing exploitation
of sexual deception for pollination increases integration of
traits involved in insect mimicry in G. diffusa. However, the
data suggest that integration does not result from the
mechanism of stabilizing correlational selection acting on
independent traits, because two predictions arising from
this mechanism were not supported: (i) that the spot (mimi-
cry) traits should have lower variance in sexually deceptive
forms and (ii) that patterns of spot trait covariation, in par-
ticular the correlation slopes, should differ between floral
forms under different selection regimes. Instead our data
support the notion that selection for effective mimicry
does not favour stable dimensions or absolute positions of
individual spot components, but rather strengthens existing
developmental integration between traits, achieving consist-
ent relative positioning of the spot components involved in
mimicry. In addition, our data suggest that divergence
between the floral forms of G. diffusa has seldom involved
uncoupling of the genetic or developmental links underlying
trait covariance, but rather involves shifts in ratios between
trait means across floral forms, i.e. we detect changes in
the intercept, but not in the slopes, of the within-floral-form
pairwise trait correlations. We develop these ideas in more
detail below.
(a) Trait divergence between floral forms in
Gorteria diffusa
Our analyses of trait divergence suggest that G. diffusa con-
tains a number of discrete, easily diagnosed, floral forms,
which differ in a range of floral traits (figure 4 and table 3).
This confirms the findings of Ellis & Johnson [28], who
described 14 floral forms in the complex. While these earlier
analyses were based primarily on discrete characters, here we
demonstrate that the same floral forms can be distinguished
through detailed measurements of the position and dimension
of floral traits across ray and disc floret trait modules. In
addition, although we have not tested it here, Ellis & Johnson
[28] showed that floral traits do not differ between greenhouse-
and field-grown plants. We assume these findings extend to
Table 1. Coefficients of variation of measured floral traits for each floral form expressed as percentages. Letters indicate significant differences in CVs across
traits. Gaps correspond to instances where trait features are absent from that floral form.
Buffels Spring Nieuw Koma Okiep Garies Cal Naries Oubees Soeb
floret presentation anglea
4.93 7.94 6.54 4.67 4.84 11.13 14.88 10.21 4.66 4.75
floret tip anglebc
15.64 20.02 15.57 20.35 14.70 16.25 8.40 17.92 17.97 15.49
floret lengthabc
13.44 11.98 11.94 11.98 13.65 10.36 9.62 7.72 13.04 8.88
floret widthabc
13.78 17.29 13.68 15.23 12.77 14.39 11.11 11.57 14.56 10.16
middle spot lengthabc
14.92 10.86 11.58 11.97 13.27 10.90 13.31 10.32 14.05 14.51
edge spot lengthabc
13.20 12.69 12.34 15.49 15.08 11.84 11.97 8.81 15.91 11.79
spot widthabc
12.97 12.51 15.41 13.85 11.71 11.18 13.95 11.47 13.11 14.24
distance to three-dimensional
bottom leftabc
14.52 11.90 13.39 13.08 16.45 14.04 15.62
distance to three-dimensional
bottom midabc
13.88 12.57 11.61 13.86 16.06 11.93
distance to three-dimensional
top midabc
14.38 10.66 10.68 11.70 15.04 11.47 12.68
three-dimensional widthb
15.69 10.71 13.23 19.31 17.15 8.66 39.33
distance base–UVabc
15.23 10.40 11.90 14.95 15.00 12.69 16.56 10.70 19.81 12.59
UV lengthd
27.14 26.57 25.14 26.94 29.35 27.03 32.44 26.29 21.40 30.18
UV widthd
34.02 26.86 27.00 27.05 18.92 23.56 59.39 22.50 33.08 31.98
disc floret lengthac
9.78 7.58 10.69 10.24 11.14 6.95 8.80 11.78 10.16 11.80
disc floret widthabc
12.06 10.33 13.13 11.93 13.24 10.31 15.98 15.48 16.20 10.55
disc petal lengthbc
13.04 15.27 13.47 17.56 11.09 14.84 16.90 17.02 17.19 12.36
disc petal widthabc
11.06 14.53 12.66 13.88 12.64 11.80 18.02 13.33 11.10 12.91
longest exertiond
22.47 27.48 40.66 31.70 30.42 25.68 44.43 22.60 31.02 36.99
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9. the traits measured here, suggesting that floral divergence
between allopatric G. diffusa floral forms is unlikely to reflect
environmentally induced plastic responses. Instead, variation
in the degree to which forms exploit mating responses of
their bee-fly pollinators (figure 3) is a likely driver of floral
divergence in the complex [27,28,31,34] although alternative
possibilities (e.g. genetic drift) cannot be completely excluded.
While we show that many aspects of floral and capitulum
structure have diverged between G. diffusa floral forms, DFAs
suggest that spot traits have diverged to a greater extent than
other trait modules. This result is intuitive in that divergent
selection imposed by mate-searching flies as opposed to
feeding insects would act largely on spot traits as these are
the important component of the mimicry signal. However,
spot traits also differ across sexually deceptive forms
suggesting that multiple trait combinations function effec-
tively in fly mimicry. At this stage, it is unclear to what
extent this pattern reflects polyphyletic convergent origins
of deception, or whether it reflects subtle differences in selec-
tion pressures [35], or simply the random accumulation or
sorting of mutations in different parts of the G. diffusa range.
(b) Trait variance and covariation in relation to sexual
deception in Gorteria diffusa
In contrast to the clear divergence of trait means between floral
forms, differences in trait variance and covariation are more
subtle and complex, as is also evident in many other studies
of floral integration [16]. Berg [11] and numerous other
later studies [12,15,16] have analysed trait covariance within
and among trait modules hypothesized to differ in selection
imposed by pollinators. Using this same approach, we show
that traits involved in bee-fly mimicry (the spot trait module)
display higher levels of integration than other trait modules
(table 2) and that integration of spot traits increases with the
degree of sexual deception (figure 6).
Our analyses support the hypothesis that stabilizing selec-
tion imposed by mate-searching male flies on traits involved in
accurate fly mimicry promotes spot trait integration. However,
two lines of evidence suggest that stabilizing correlational
selection on genetically independent traits, the classic mechan-
ism suggested by Berg [11] and developed by others [10,36], is
not the likely cause of increased trait integration in sexually
deceptive forms of G. diffusa.
In the first line of evidence, we find no evidence for
decreased variance of insect mimicry traits relative to other
traits in strongly deceptive forms (table 1), nor decreased var-
iance of spot traits in deceptive versus non-deceptive forms,
which are clear expectations if stabilizing selection on individ-
ual traits is involved in generating covariance between them
[37]. This finding indicates that the dimensions or absolute pos-
itions of individual spot traits are not under stronger stabilizing
selection from mate-searching flies than other traits. However,
alternative explanations for this result include the fact that we
were unable to measure key traits such asthe height and optical
effects of papillae, which vary significantly across floral
morphs (AG Ellis 2011, personal observation) and may be
the dominant elicitors of the mating response, allowing more
visual flexibility in other traits [28]. Or we are underestimating
the degree of morphological specialization in spot traits
required for pollination through feeding responses. However,
we favour the first explanation, because integration resulting
from correlational stabilizing selection is only likely when
Table2.Correctedintegrationindices(expressedaspercentageofmaximum)foreachofthetraitmodules.95%confidenceintervalsareindicatedinparentheses.Lettersindicatesignificantdifferencesbetweenfloralformsin
integrationwithintraitcompartments(assessedasnon-overlappingconfidenceintervals).Spottraitsweresignificantlymoreintegratedthandiscfloretsandnon-spotraytraitsinallfloralformsexceptNaries,SoebandOubees.
traitsBuffelsSpringCalOkiepNieuwKomaGariesNariesSoebOubees
discflorets6.0ab
(3.1–14.3)
7.9ab
(4.1–16.8)
5.0ab
(4.2–14.7)
2.5ab
(0.8–11.3)
2.8ab
(0.7–13.7)
4.8ab
(2.5–11.5)
4.7ab
(2.8–12.4)
2.1ab
(0.2–10.8)
20.4b
(20.4–5.9)
12.9a
(7.0–25.0)
rayfloretsnon-spottraits10.8
(6.5–20.0)
12.1
(10.3–20.1)
13.4
(8.7–24.5)
7.8
(7.1–16.4)
8.2
(4.5–17.0)
7.9
(5.9–14.5)
9.4
(6.6–17.6)
9.7
(7.0–18.1)
10.1
(6.4–21.6)
5.8
(4.3–14.7)
spottraits35.6ab
(20.7–54.7)
33.4a
(24.5–45.4)
30.5a
(25.4–38.2)
31.1ab
(24.1–41.2)
27.1ab
(21.3–36.1)
20.6abc
(17.0–27.6)
23.2abc
(18.0–32.7)
14.4bc
(9.7–24.5)
10.4c
(6.8–18.8)
23.9abc
(18.3–34.7)
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10. Table3.Phenotypiccorrelationcoefficients(Pearsonproduct-momentmethod)frompairwisecomparisonsoffloraltraits(i)within-floralforms(belowthediagonal)and(ii)acrossfloralforms(abovethediagonal).Meanwithin-floral-
formcorrelationcoefficientsareshownbelowthediagonal,andbold*indicatestraitpairswhichwerealwayssignificantlycorrelated,whileboldrepresentsthosethatweresignificantlycorrelatedin.80%offloralforms.Correlation
coefficientsfrompairwisecomparisonsoftraitmeansacrossfloralformsareindicatedabovethediagonal,andbold*indicatessignificanceatp,0.05withoutBonferonniadjustment.Greyshadingindicatesthecorrelationsbetweenthe
traitswithineachofthethreetraitmodules(lefttoright:non-spotraytraits,spottraitsanddiscflorettraits).3D,three-dimensional.
adaxial
floret
angle
floret
tip
angle
floret
length
floret
width
mid
spot
length
edge
spot
length
spot
width
dist.to
3Dedge
dist.
to3D
mid
dist.to
3Dtop
mid
3D
width
dist.to
UV
UV
length
UV
width
disc
tube
length
disc
tube
width
disc
petal
length
disc
petal
width
longest
pollen
presenter
adaxialfloretangle20.510.3820.400.1220.1920.300.500.800.610.610.090.4320.320.170.500.150.4820.17
florettipangle20.0420.290.88*0.350.500.70*0.070.730.1720.590.3520.0920.1620.300.170.1120.0220.11
floretlength0.0420.200.160.140.1620.0520.220.220.190.5620.020.160.300.73*0.040.64*0.1420.35
floretwidth0.000.480.430.390.530.74*20.140.540.2120.320.2920.0820.090.070.150.390.0720.32
middlespotlength0.0320.030.70*0.440.90*0.76*0.700.99*0.98*0.570.90*20.5120.090.0420.080.1520.450.40
edgespotlength0.0220.050.61*0.400.82*0.71*0.510.88*0.79*0.340.78*20.460.220.1420.170.1420.590.35
spotwidth0.010.240.380.74*0.520.420.210.710.580.000.72*20.6020.2920.1320.080.2420.260.21
distanceto3Dbottomleft0.0120.050.540.300.70*0.66*0.350.670.720.100.7320.0820.3020.250.4420.0720.040.57
distanceto3Dbottommid0.1120.030.63*0.390.76*0.64*0.400.89*1.00*0.560.750.7220.310.290.730.060.3120.10
distanceto3Dtopmid0.0520.020.68*0.430.84*0.73*0.430.84*0.92*0.490.78*0.3720.350.250.700.030.280.02
3Dwidth20.050.090.390.520.420.410.580.340.400.410.4620.220.190.510.120.1420.120.13
distancebase2UV0.000.030.61*0.45*0.78*0.71*0.440.85*0.93*0.91*0.4420.4920.0920.290.060.2920.380.57
UVlength0.050.050.150.030.220.1520.010.120.150.1820.090.0520.050.150.70*0.010.75*20.72*
UVwidth0.060.090.130.280.090.130.310.070.190.160.300.180.120.2020.260.1720.520.24
discfloretlength20.0320.010.380.230.330.290.240.260.280.310.120.270.050.0920.1120.010.0520.47
discfloretwidth0.030.080.010.180.020.050.1320.040.0220.030.080.050.090.100.090.180.77*20.42
discpetallength20.040.000.150.120.150.190.120.170.230.220.100.190.050.050.250.190.1920.06
discpetalwidth20.050.030.140.100.080.070.1020.010.110.050.040.130.150.100.220.280.2720.73*
longestexertion0.0120.020.230.130.200.160.100.200.240.230.090.150.030.040.3120.030.110.08
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11. imposed by pollinators with consistent body sizes [11], for
example, honeybees, where the brood cell determines size.
The bee-fly M. capensis, which has an endoparasitic larval
phase, exhibits substantial size variation (CVs for body dimen-
sions are similar to those of spot traits) and thus mate-searching
males are unlikely to select for specific female, and hence
spot, dimensions.
In the second line of evidence, in all floral forms, strong spot
integration results from covariation between the same suite of
traits (table 3) and pairwise within-floral-form correlations of
spot traits exhibit remarkably consistent slopes (figure 5). This
is the expectation if integration results from genetically or
developmentally determined trait covariance. The alternative
explanation, that correlational selection by pollinators is consist-
ent across all floral forms, seems less plausible given the clear
differences in pollinator behavioural interactions along the
continuum from feeding to sexually deceptive forms.
Further to previous studies that demonstrate an influence of
pollinator specialization on integration of pollen transfer traits in
animal-pollinated plants [12,15,16], our findings suggest selec-
tion for the tight integration of attraction traits in sexually
deceptive flowers. Integration of attractive spot traits in G. diffusa
appears to largely reflect genetic or developmental constraints,
as has been suggested in several other systems [17–19]. But, in
contrast to these studies, our data suggest that selection for
attraction of mate-searching male flies in sexually deceptive
forms has tightened existing genetic/developmental covariance
of the key mimicry traits. In the absence of a deep understanding
of the developmental genetic pathways underlying spot for-
mation in G. diffusa, it is impossible to suggest precise
mechanisms leading to tightened developmental genetic covari-
ance. However, it is likely to include homogenization of cell
response to intrinsic developmental signals operating across
the floret or spot module, coupled with enhanced signalling
and coordination between developmental pathways controlling
individual spot traits [38].
Remarkably, disc floret traits, which are not involved in
mimicry in G. diffusa, were also slightly more integrated in
5 10 15 20 25
0
0
2
4
6
8
10
floret length (mm)
middlespotlength(mm)
small floret/large spot
large floret/small spot
large floret/large spot Spring
Nieuw
Koma
Naries
Oubees
Soeb
Garies
Okiep
Cal
20 4 6 8
0
1
2
3
4
5
spot width (mm)
three-dimensionalwidth(mm)
edge spot length (mm)
midspotlength(mm)
0 2 4 6
0
2
4
6
8
10
8
curved spots
straight spots
0 2 4 6 8
0
2
4
6
8
distance to three-dimensional top (mm)
distancetoUV(mm)
(a) (b)
(c) (d)
Buffels
Figure 5. Patterns of covariation within and among floral forms for select trait pairs: (a) floret length versus mid spot length; (b) spot width versus three-dimen-
sional width; (c) edge spot length versus mid spot length and (d) distance to three-dimensional top versus distance to UV. In (a,b) the among-floral-form
correlations were not significant despite strong within-floral-form correlations. In (a) the slopes of the within-floral-form correlations between floret and spot dimen-
sions vary significantly between floral forms, whereas in (b) the slopes of the correlations between spot and three-dimensional width do not vary significantly
between floral forms despite shifts in the mean ratio of these traits between floral forms. (c,d) Trait pairs relevant to sexual deception (UV-three-dimensional
position, and spot shape) which exhibit significant correlations within and between floral forms, despite clear changes between floral forms in mean ratio of
the traits. Points are trait means for floral forms, lines are fitted linear correlations within floral forms.
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12. the most deceptive floral forms. This could simply be a con-
sequence of selection for tighter developmental control in the
spots if, for instance, some of the pathways of developmental
regulation are linked across disc and ray floret modules.
However, it might also be because successful exploitation of
mating flies for pollination likely requires tighter integration
of disc traits for pollen removal and deposition associated
with more constrained pollinator behaviour. This second
hypothesis is supported by the remarkable variation exhib-
ited by the exertion of the pollen presenters. Although the
higher variance of pollen presenter length may in part reflect
ontogenetic variation between the individual inflorescen-
ces sampled, it is also notable that the two most sexually
deceptive forms exhibit the highest mean length of pollen
presenters (electronic supplementary material, table S1).
Long pollen presenters could therefore be a component of
sexual deception and qualitatively often appear to be posi-
tioned in close proximity to the ray petal spots (AG Ellis
2013, personal observation).
(c) Trait divergence, covariance and evolutionary
allometry
Under the reasonable assumption that patterns of within-
floral-form phenotypic trait covariance reflect the genetic var-
iance covariance (G) matrix in G. diffusa floral forms, our data
suggest that floral integration largely reflects covariance
between key traits arising through shared genetic or develop-
mental control. Contrary to the expectation that genetic/
developmental integration should impose constraint on inde-
pendent evolutionary divergence of the traits involved, we
find in G. diffusa that the traits that covary most strongly
are also those that are most strongly differentiated between
G. diffusa floral forms (three-dimensional and UV position,
spot and floret dimensions). Comparisons of within- versus
among-floral-form trait covariation patterns (electronic sup-
plementary material, table S1; table 3 and figure 5) revealed
three main patterns of trait divergence in relation to the
axes of genetic/developmental constraint (i.e. correlation
pattern within floral forms): (i) floral form trait means have
diverged along the axis of constraint, (ii) while the correlation
patterns remain unchanged, the ratio of trait means has chan-
ged (i.e. the intercepts, but not the slopes of correlations
change across floral forms) and (iii) differences in the ratio
of trait means arise in conjunction with changes in the
slope of trait correlations.
The last pattern, involving changes in covariance patterns
within floral forms, characterizes the most notable mis-
matches in trait covariation patterns within and between
floral forms, namely correlations between the length of ray
florets and the size of the spots and their phenotypic com-
ponents (table 3 and figure 5a). It is evident that the mean
trait ratios fall roughly into three allometric configurations:
(i) small floret/large spot (sexually deceptive), (ii) large
floret/small spot and (iii) large floret/large spot (feeding
forms). Given the allopatric distribution of these floral
forms, it is not possible to rule out that some of these slope
differences are generated by different responses of similar
genotypes to differing environmental conditions [39]. How-
ever, it is likely that most are allometric differences arising
through genetic change for two reasons: (i) floral forms exhi-
biting convergent slope relationships occupy very different
abiotic environments and maintain their phenotypes in
common garden experiments [28] and (ii) different slope
relationships seem to cluster between deceptive and non-
deceptive floral forms. There is thus the potential for selection
to have acted on spot length and floret length allometry.
However, this instance of altered spot-ray length allome-
try across the sexual deception continuum seems to be the
exception. For all other spot trait pairs examined, we find diver-
gence in trait means (and often their ratios) across floral forms
despite unaltered allometric relationships between traits. This
suggests that alteration of floral trait allometries is most often
constrained by shared genetic/developmental control in
G. diffusa, but that this has not necessarily constrained indepen-
dent divergence of traits across floral forms. Under strong
genetic/developmental constraint, selection for alteration of
one trait should lead to correlated changes in linked traits
thus restricting the regions of morphospace, which populations
can occupy. Trait divergence between G. diffusa floral forms
often follows this pattern (i.e. populations occupy different
positions on a ridge in two-dimensional morphospace reflect-
ing the axis of genetic/developmental constraint—figure 5b–
d for examples). Perhaps more interesting is the fact that trait
divergence patterns which generate the clearest morphological
differences between floral forms (e.g. reversal of the relative
position of three-dimensional and UV structures—figure 1b
and f versus a,c,d,g; or flat versus curvaceous spot ends—
figure 3) involve shifts in ratios of trait means away from the
axis of genetic/developmental constraint in trait morphospace
(e.g. figure 5c,d). Given the functional implications of these trait
changes in the pollination context (e.g. exploitation of feeding
versus mating behaviour for pollination), it seems likely
that pollinator-mediated selection has driven independent
divergence of traits despite strong genetic/developmental
constraints and without altering these constraints.
5. Conclusion
Our study joins a body of literature that is consistent with
Berg’s [11] hypothesis that pollinator-mediated selection
non-spot traits
disc traits
spot traits
spot traits
non-spot traits
disc traits
0 25 50 75 100
0
10
20
30
40
% of Megapalpus mating per inspection visits
%integration
R2 =0.74*
R2 =0.15 (n.s.)
R2 =0.55*
Figure 6. The influence of degree of sexual deception (proportion of visits by
M. capensis males involving mating or inspection responses as opposed to
feeding responses) on trait integration in the three trait modules. R-squared
values (*p , 0.05) from simple regressions are shown. ANCOVA analysis indi-
cates that degree of deception significantly influences integration when
all trait compartments are considered, and that regression slopes differ
significantly across trait compartments.
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13. influences integration of suites of floral traits [12,15,16]. How-
ever, our findings contrast with previous studies in two main
ways (i) we show that pollinator specialization through
sexual deception influences integration of a suite of traits
involved in pollinator attraction, whereas previous work has
demonstrated this for traits involved in accurate transfer of
pollen between anthers and stigmas but not attraction traits
[12] and (ii) our data suggest that the influence of sexual decep-
tion on trait integration in G. diffusa does not often result from
stabilizing correlational selection on genetically/developmen-
tally independent traits, but rather reflects selection for
tighter integration of existing genetically determined covari-
ance. In addition, our data suggest that the remarkable
diversification in floral form across G. diffusa, which likely
arose through variable pollinator-mediated selection imposed
along a gradient in levels of pollinator deception associated
with exploitation of mate-searching male flies, has occurred
despite potentially strong constraints imposed by genetic/
developmental covariance between traits.
Acknowledgements. We thank South Africa National Parks for providing
accommodation through the field season, and Caroli de Waal for
assistance in the field. The material was collected under the following
permit obtained from the Northern Cape Conservation Board (Flora
050/2/2013).
Funding statement. We thank the Royal Society for funding this work
through a Joint International Project Grant to B.J.G. and A.G.E.,
and Sidney Sussex College, Cambridge for travel funding to G.M.
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