, 20130563, published 7 July 2014369 2014 Phil. Trans. R. Soc. B Beverley J. GloverAllan 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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ResearchCite 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

& 2014 The Author(s) Published by the Royal Society. All rights reserved.

†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 integrationas a function of sexual deception inGorteria diffusa

Allan G. Ellis1,†, Samuel F. Brockington2,†, Marinus L. de Jager1,†,Gregory Mellers2, Rachel H. Walker2 and Beverley J. Glover2

1Botany and Zoology Department, Stellenbosch University, Private Bag X1, Matieland 7602, South Africa2Department 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. IntroductionPhenotypic 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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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. capensisbehaviour, such as sleeping and feeding activities (AG Ellis

2012, unpublished data). These features of the G. diffusasystem 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.

(a)

(c)

(e) ( f )

(g) (h)(h)

(i) ( j)

(b)

(d )

Figure 1. Ten floral forms within the G. diffusa species complex showing thefull frontal image of the flower, and for each floral form, a close-up ofthe spotted floret. Floral forms with three-dimensional structures (a – g),floral forms without three-dimensional structures (h – j). Individual floralforms 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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2. Methods(a) Taxon samplingWe 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 traitsA 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 deceptionWhile 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 formsIn 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

(i)

a

b

c

e

fg

(vi)

o

p

q

(v)

rs

(iii)

h

ij

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 toreveal 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, widthof 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 corollatube; 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-dimensionalstructures, striated black indicates three-dimensional areas without papillate cells, light grey bands are reflective strips. Idealized spot types are lined up on the ‘deceptionaxis’, 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 byMegapalpus 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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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 withinfloral 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

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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 specializationand 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 formsMeasured traits differed significantly between G. diffusafloral 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 formsContrary 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 formsTraits 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 formsWhile 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

–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)

(dis

tanc

e to

thre

e-di

men

sion

al to

p, d

ista

nce

to U

V,

spot

wid

th, f

lore

t len

gth)

(spot width, distance to UV, floret length, floret width)

(edg

e sp

ot le

ngth

, dis

tanc

e to

UV

,ad

axia

l flo

ret a

ngle

, flo

ret w

idth

)

(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 bythe discriminant functions. The most important traits are listed on the axes in descending order of standardized factor coefficients.

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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.

Table 1. Coefficients of variation of measured floral traits for each floral form expressed as percentages. Letters indicate significant differences in CVs acrosstraits. 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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(e) Effects of sexual deception on trait integrationANCOVA 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. DiscussionOur 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 inGorteria 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

Tabl

e2.

Corre

cted

inte

grat

ionin

dice

s(e

xpre

ssed

aspe

rcent

age

ofm

axim

um)

for

each

ofth

etra

itm

odul

es.

95%

confi

denc

ein

terv

alsar

ein

dica

ted

inpa

rent

hese

s.Le

tters

indi

cate

signi

fican

tdi

ffere

nces

betw

een

flora

lfo

rms

inin

tegr

ation

with

intra

itco

mpa

rtmen

ts(a

sses

sed

asno

n-ov

erlap

ping

confi

denc

ein

terv

als).

Spot

traits

were

signi

fican

tlym

ore

inte

grat

edth

andi

scflo

rets

and

non-

spot

raytra

itsin

allflo

ralf

orm

sex

cept

Narie

s,So

eban

dOu

bees

.

trai

tsBu

ffels

Sprin

gCa

lOk

iep

Nieu

wKo

ma

Garie

sNa

ries

Soeb

Oube

es

disc

flore

ts6.

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)

12.9

a

(7.0

–25

.0)

rayflo

rets

non-

spot

traits

10.8

(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)

spot

traits

35.6

ab

(20.

7–54

.7)

33.4

a

(24.

5–45

.4)

30.5

a

(25.

4–38

.2)

31.1

ab

(24.

1–41

.2)

27.1

ab

(21.

3–36

.1)

20.6

abc

(17.

0–27

.6)

23.2

abc

(18.

0–32

.7)

14.4

bc

(9.7

–24

.5)

10.4

c

(6.8

–18

.8)

23.9

abc

(18.

3–34

.7)

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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 sexualdeception 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 as the 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

Tabl

e3.

Phen

otyp

icco

rrelat

ionco

effic

ients

(Pea

rson

prod

uct-m

omen

tm

etho

d)fro

mpa

irwise

com

paris

ons

offlo

ralt

raits

(i)w

ithin

-flor

alfo

rms

(belo

wth

edi

agon

al)

and

(ii)

acro

ssflo

ralf

orm

s(a

bove

the

diag

onal

).M

ean

with

in-fl

oral-

form

corre

lation

coef

ficien

tsar

esh

own

below

the

diag

onal,

and

bold

*in

dica

tes

trait

pairs

whi

chwe

realw

ays

signi

fican

tlyco

rrelat

ed,w

hile

bold

repr

esen

tsth

ose

that

were

signi

fican

tlyco

rrelat

edin

.80

%of

flora

lfor

ms.

Corre

lation

coef

ficien

tsfro

mpa

irwise

com

paris

ons

oftra

itm

eans

acro

ssflo

ralf

orm

sar

ein

dica

ted

abov

eth

edi

agon

al,an

dbo

ld*

indi

cate

ssig

nific

ance

atp

,0.

05w

ithou

tBo

nfer

onni

adju

stmen

t.Gr

eysh

adin

gin

dica

tes

the

corre

lation

sbe

twee

nth

etra

itsw

ithin

each

ofth

eth

ree

trait

mod

ules

(left

torig

ht:n

on-sp

otray

traits

,spo

ttra

itsan

ddi

scflo

rett

raits

).3D

,thr

ee-d

imen

siona

l.

adax

ial

flore

t

angl

e

flore

t

tip angl

e

flore

t

leng

th

flore

t

wid

th

mid

spot

leng

th

edge

spot

leng

th

spot

wid

th

dist

.to

3Ded

ge

dist

.

to3D

mid

dist

.to

3Dto

p

mid

3D wid

th

dist

.to

UV

UV leng

th

UV wid

th

disc

tube

leng

th

disc

tube

wid

th

disc

peta

l

leng

th

disc

peta

l

wid

th

long

est

polle

n

pres

ente

r

adax

ialflo

reta

ngle

20.

510.

382

0.40

0.12

20.

192

0.30

0.50

0.80

0.61

0.61

0.09

0.43

20.

320.

170.

500.

150.

482

0.17

flore

ttip

angl

e2

0.04

20.

290.

88*

0.35

0.50

0.70

*0.

070.

730.

172

0.59

0.35

20.

092

0.16

20.

300.

170.

112

0.02

20.

11

flore

tlen

gth

0.04

20.

200.

160.

140.

162

0.05

20.

220.

220.

190.

562

0.02

0.16

0.30

0.73

*0.

040.

64*

0.14

20.

35

flore

twid

th0.

000.

480.

430.

390.

530.

74*

20.

140.

540.

212

0.32

0.29

20.

082

0.09

0.07

0.15

0.39

0.07

20.

32

mid

dle

spot

lengt

h0.

032

0.03

0.70

*0.

440.

90*

0.76

*0.

700.

99*

0.98

*0.

570.

90*

20.

512

0.09

0.04

20.

080.

152

0.45

0.40

edge

spot

lengt

h0.

022

0.05

0.61

*0.

400.

82*

0.71

*0.

510.

88*

0.79

*0.

340.

78*

20.

460.

220.

142

0.17

0.14

20.

590.

35

spot

wid

th0.

010.

240.

380.

74*

0.52

0.42

0.21

0.71

0.58

0.00

0.72

*2

0.60

20.

292

0.13

20.

080.

242

0.26

0.21

dista

nce

to3D

botto

mlef

t0.

012

0.05

0.54

0.30

0.70

*0.

66*

0.35

0.67

0.72

0.10

0.73

20.

082

0.30

20.

250.

442

0.07

20.

040.

57

dista

nce

to3D

botto

mm

id0.

112

0.03

0.63

*0.

390.

76*

0.64

*0.

400.

89*

1.00

*0.

560.

750.

722

0.31

0.29

0.73

0.06

0.31

20.

10

dista

nce

to3D

top

mid

0.05

20.

020.

68*

0.43

0.84

*0.

73*

0.43

0.84

*0.

92*

0.49

0.78

*0.

372

0.35

0.25

0.70

0.03

0.28

0.02

3Dw

idth

20.

050.

090.

390.

520.

420.

410.

580.

340.

400.

410.

462

0.22

0.19

0.51

0.12

0.14

20.

120.

13

dista

nce

base

2UV

0.00

0.03

0.61

*0.

45*

0.78

*0.

71*

0.44

0.85

*0.

93*

0.91

*0.

442

0.49

20.

092

0.29

0.06

0.29

20.

380.

57

UVlen

gth

0.05

0.05

0.15

0.03

0.22

0.15

20.

010.

120.

150.

182

0.09

0.05

20.

050.

150.

70*

0.01

0.75

*2

0.72

*

UVw

idth

0.06

0.09

0.13

0.28

0.09

0.13

0.31

0.07

0.19

0.16

0.30

0.18

0.12

0.20

20.

260.

172

0.52

0.24

disc

flore

tlen

gth

20.

032

0.01

0.38

0.23

0.33

0.29

0.24

0.26

0.28

0.31

0.12

0.27

0.05

0.09

20.

112

0.01

0.05

20.

47

disc

flore

twid

th0.

030.

080.

010.

180.

020.

050.

132

0.04

0.02

20.

030.

080.

050.

090.

100.

090.

180.

77*

20.

42

disc

peta

llen

gth

20.

040.

000.

150.

120.

150.

190.

120.

170.

230.

220.

100.

190.

050.

050.

250.

190.

192

0.06

disc

peta

lwid

th2

0.05

0.03

0.14

0.10

0.08

0.07

0.10

20.

010.

110.

050.

040.

130.

150.

100.

220.

280.

272

0.73

*

long

este

xerti

on0.

012

0.02

0.23

0.13

0.20

0.16

0.10

0.20

0.24

0.23

0.09

0.15

0.03

0.04

0.31

20.

030.

110.

08

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5 10 15 20 250

0

2

4

6

8

10

floret length (mm)

mid

dle

spot

leng

th (

mm

)

small floret/large spotlarge floret/small spotlarge floret/large spot Spring

NieuwKoma

NariesOubeesSoebGariesOkiepCal

20 4 6 80

1

2

3

4

5

spot width (mm)

thre

e-di

men

sion

al w

idth

(m

m)

edge spot length (mm)

mid

spo

t len

gth

(mm

)

0 2 4 60

2

4

6

8

10

8

curved spotsstraight spots

0 2 4 6 80

2

4

6

8

distance to three-dimensional top (mm)

dist

ance

to U

V (

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-formcorrelations 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 significantlybetween floral forms despite shifts in the mean ratio of these traits between floral forms. (c,d) Trait pairs relevant to sexual deception (UV-three-dimensionalposition, and spot shape) which exhibit significant correlations within and between floral forms, despite clear changes between floral forms in mean ratio ofthe traits. Points are trait means for floral forms, lines are fitted linear correlations within floral forms.

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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. diffusaappears 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

non-spot traitsdisc traitsspot traits

spot traitsnon-spot traitsdisc traits

0 25 50 75 100

0

10

20

30

40

% of Megapalpus mating per inspection visits

% in

tegr

atio

n

R2 = 0.74*

R2 = 0.15 (n.s.)

R2 = 0.55*

Figure 6. The influence of degree of sexual deception ( proportion of visits byM. capensis males involving mating or inspection responses as opposed tofeeding responses) on trait integration in the three trait modules. R-squaredvalues (*p , 0.05) from simple regressions are shown. ANCOVA analysis indi-cates that degree of deception significantly influences integration whenall trait compartments are considered, and that regression slopes differsignificantly across trait compartments.

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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 evolutionaryallometry

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 1band 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. ConclusionOur study joins a body of literature that is consistent with

Berg’s [11] hypothesis that pollinator-mediated selection

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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 providingaccommodation through the field season, and Caroli de Waal forassistance in the field. The material was collected under the followingpermit obtained from the Northern Cape Conservation Board (Flora050/2/2013).

Funding statement. We thank the Royal Society for funding this workthrough 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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